HIC 2018:Papers with Abstracts

Abstract. Accurate simulation of both land surface and groundwater hydrologic processes in river catchments is an important step for integrated water resources management, particularly for catchments where both surface water and groundwater resources are used conjunctively. In this paper, we present a study on a complex river catchment – the Dee River catchment in the United Kingdom using a coupled land surface model (SWAT) and groundwater model (MODFLOW) to improve the performances of both models otherwise used separately, hence serving the IWRM goals of optimizing conjunctive use of surface and groundwater. The model can also be used to evaluate the sensitivity of stream flows to changing climate, groundwater extraction, and land use alternations. Preliminary results show that the coupled model can improve river flow simulation especially baseflow simulation while significantly improving the overall water balance model simulations during periods of low flow.
Abstract. With the changing climate, the prognosis is that weather extremes such as floods, drought and EL Nino are likely to increase in frequency and intensity can expand billions of economic losses and effect human lives. NAHRIM Hydroclimate Data Analysis Accelerator (N-HyDAA), known as Malaysia Climate Change (CC) Knowledge Portal, the only CC knowledge portal in Malaysia primarily developed for providing CC and water-related data, information, knowledge and technologywhich is crucial for present and future water related bussines activities, engineering practices and environment. It has eight hydroclimate-environment modules, which amongst others are rainfall, floods, droughts and water stress condition using Big Data Analytics (BDA) technology by means of comprehensive analysis and interactive visualization tools. N-HyDAA is able to trace, detect, identify and visualise future water issues associated with the adverse impacts of climate change in Malaysia. N-HyDAA assist business entities, water operators, engineers, planners and decision-makers in designing, planning and developing water related program and risk management in combating climate change impact either mitigation or adaptation actions.
Abstract. In this study, a tool is developed to estimate streamflow at Guvenc River, Ankara by using Takagi-Sugeno
(TS) Fuzzy Rule-Based (RB) model. The model takes precipitation and runoff at time t as predictor (input)
and estimates the runoff at time t + 1. The approach used to generate the TS RB model is based on density
based clustering. Each cluster center is used to generate a fuzzy rule that represents the system behaviour.
Satisfactory results are obtained especially after including the seasonal behaviour of streamflow time series
into the model.
Abstract. In the agriculture sector, combining physically based soil water balance and simulation models with GIS tools is of a considerable interest to manage the available water amount. Indeed, this combination can enhance water supply management, optimize agricultural catchments management and study impact of management intervention from small scale (plot) to a larger one, such as irrigated district and/or region.
This work presents the case of Nebhana Dam System in the region of Kairoun (central Tunisia). The main objectives were to: (1) create a specific GIS database for the six irrigated districts of the area Ain Boumorra 1, 2 & 3, Fadhloun, Dar Jameya and Sisseb 1 based on the characteristics of cultivated crops, soils types and used irrigation systems; (2) assess spatial and temporal variation of soil water budget terms from plot and farm levels to irrigated district and regional scales; (3) map results for different time steps.
The achievement of these objectives was made possible using the WEAP-MABIA Model. Thus, daily Penman–Monteith reference evapotranspiration (ETo), effective precipitation (PE), crop water requirement (CWR) and irrigation water requirement (IWR) were estimated for the six irrigated districts and their related farms and plot using spatially distributed parameters on climate, crop, soil characteristics, irrigation system and basic irrigation management practice during the cropping season 2014/2015.
Abstract. The intensification of flood-related damages and fatalities is challenging Early Warning Systems (EWS) to always better perform in predicting flood levels allowing decision makers to take the most effective decisions for mitigating the impact of extreme events. EWS require hydrologic and hydraulic modelling that are usually affected by uncertainties that can be extremely significant in data scarce regions. This work presents the implementation and application of a Data Assimilation (DA) framework, based on the Ensemble Kalman Filter, integrating the hydraulic model FLO-2D and geospatial algorithms for data post-processing and mapping. The hydraulic model is forced by both flow gages and simulated flow data produced by a simplified GIS-based hydrologic modelling for flood wave analysis tailored for small ungauged basins. The hydraulic code is adapted to assimilate different observation data types: flow measurements taken along the channel, water level observations captured within the floodplain, such as water signs on vegetation and buildings pictures by human sensors, and inundation extents obtained by processing satellite images. This DA framework required the development of significant novelties for incorporating the 2D hydraulic model and for integrating the different types of measurements considering the heterogeneous specifications and uncertainty of the various assimilated data types. Advanced GIS algorithms are implemented for improving the real time flood mapping taking advantage of the distributed output provided by the 2D inundation model. Results show improved model performances in terms of water level simulations and reduced uncertainties. The integrated hydraulic and geospatial modelling allows to empower the water levels correction on the flood extension prediction. Additionally, the capability of using the different available observations, from satellite images to crowdsourced data, is promising for the development of a flexible and scalable flood EWS model overcoming the limitations of standard DA working generally with 1D hydraulic models and traditional sensors.
Abstract. It is an important practical concern to be able to promptly predict the effect and extent of flood and debris flow. We developed a GUI system to predict the effect and extent of flood and debris flow. The system has two features. First, the system can extract the target domain using digital elevation model (DEM) data by specifying the LAT/LON of the occurrence site. Second, a raster-based, 2D diffusion wave model was used as a numerical flow model to reduce the computational time. Although this system had difficulty in predicting the impact of micro-topography as a result of the coarse mesh data, overall it satisfactorily represented the scale and potential risk of these disasters. In addition, this system can access DEM data throughout Japan to generate exact target domains. Thus, this system can be used to efficiently predict flood and debris flows at a large number of sites.
Abstract. Soil Moisture and Ocean Salinity (SMOS) data validation has been widely performed worldwide since the product became available. However, there are few studies for Brazil. This study focused on the validation of a new version of SMOS product developed by the Institut National de la Recherche Agronomique (INRA) and Center d'Etudes Spatiales de la BIOsphère (CESBIO). One of the advantages of SMOS- INRA-CESBIO (SMOS-IC) is that the product is as independent as possible from auxiliary data. The validation was performed at 7 stations located in a semi-arid mesoregion of Pernambuco State, Northeast Brazil, for the year 2016. Bias, root mean square difference (RMSD), unbiased RMSD and the Pearson correlation coefficient (R) were computed between the SMOS-IC data and in situ measurements, considering only the ascending orbit (6 am local time). The results were consistent with those found in several studies, including error metrics. The correlation coefficient (r) ranged from 0.53 to 0.86 (mean 0.68) and the sensor was able to respond adequately to rainfall events. The results of this study are useful to demonstrate the need to continue validating soil moisture data obtained by remote sensors throughout the state, especially in more rainy locations.
Abstract. Hydrological ensembles have gained importance for prediction and forecasting in water cycle variables. In spite of this, the relevance of the individual models in the ensemble is not usually established, in terms of the ensemble structure (i.e. their members) and the performance this structure exhibits through different climatic conditions (intrannual variability, for example). This analysis accounts for the uncertainty in the structure of the models and their responses (e.g. outputs), in comparison to the observed data. In this regard, the research here described attempts to determine the incidence of the ensemble members built for each month of the year, in the prediction of daily flows, through the use of the Bayesian Model Averaging (BMA) method. Moreover, using BMA calibrated parameters as inputs, an uncertainty analysis is carried out for the calibration period, and in monthly average terms, obtaining finer uncertainty bounds. This analysis was implemented in the Sumapaz River basin, part of the Magdalena Cauca Macro- Basin (MCMB) in Colombia. Results showed differences in ensemble structures and performance according to its original performance criteria, and better results when using a monthly BMA for the uncertainty analysis.
Abstract. Irrigation water use (IWU) or withdrawal is a key component for the water management of a region since it tends to exceed the crops consumptive water use, especially in water-stressed regions where groundwater is the main source of water. Nevertheless, temporal IWU information is missing in many irrigation areas. Remote sensing (RS) data is commonly used for crop water requirements estimations in areas with lack of data, however, IWU is more complex to approach since it also depends on water use efficiency, irrigation system type, irrigation scheduling, and water availability, among others. This work explores the use of remote sensing data (TRMM, MODIS) and land surface hydrological products (GLDAS 2 and MERRA 2) to obtain insights about the space-time annual IWU patterns across croplands located within Mexico’s northeast region. Reported IWU in three irrigation districts (Don Martín, Región Lagunera and Bajo Río Bravo) was used to obtain a functional model using satellite data derived. Results suggest strong relationship between reported IWU with soil moisture content from GLDAS and the maximum annual EVI from MODIS, where a potential regression shown statistical correlations of 0.83 and 0.77, respectively.
Abstract. Sustainable use of water resources requires a modern approach for complex water systems management based on system’s modeling, as unsung operation alternatives may only be devised and tested through a model. The now available IT computing tools enable setting the traditional modelling methodologies for planning and operation of such systems in a new framework. The present work deals with the development of decision support models for optimizing the operation of complex water supply systems with multiple uses and focuses on the validation of the optimization model of the regional water supply systems managed by an Italian water utility. The software used is Aquator, a state-of-the-art commercial tool for generic water resources system simulation and operational optimization. The paper shows and comments the results of the validation of the model and uses them to draw some general principles for the validation of such kind of models: in fact, operational optimization models are conceived for the enhancement of systems management and performance. Consequently, while on the one side model output is expected to reflect the actual state of the system, on the other it can point out significant management enhancements.
Abstract. Lagrange interpolation was applied to complete maximum annual rainfall data for five weather stations in Aguascalientes, State of Mexico; in most of them there were no variations in the type of distribution function obtained; in general, an overestimation of the extrapolated data was identified for different return periods when the original records were not used.
Abstract. The ECI is a multi-hazard index which has been developed in the context of the eXtreme Climate Facilities (XCF) project lead by ARC (African Risk Capacity) with the objective of detecting the occurrence of climate extremes over the African continent. The main hazards covered by ECI are the extreme dry, wet and heat events. However, the definition of ECI allows for the integration of additional hazards in the same index. The index has been designed and widely tested across Africa. The objective of this study is to test the usability and potential application of the same index under different climate regimes that are typical of the mid-latitudes, including the Mediterranean area and northern Europe. The analysis presented in this study shows that the ECI allows an accurate detection of extreme cold/heat waves as well as events of abundant precipitation across Europe over the last decades
Abstract. Drinking water treatment works are increasingly placed under external stressors including climatic variability, land use and management, and pollution incidents. Routine high-frequency water quality monitoring is an integral part of operational control and is used to inform the treatment process and support the identification of risks. However, in order to improve decision making using the complex, time-series of water quality data that are generated (and typically archived), there must be distinction between basic sensor errors, artefacts of system design and management, and process driven patterns. This paper explores these complex data in order to support synthesis of uncleaned (or raw), high-frequency data; extracting information value from routine catchment wide monitoring. The data are presented in a form that enhances the capability and capacity to utilise existing complex data; improves understanding of complex surface water systems; and helps facilitate data driven models to investigate and forecast the dynamics between water quality determinands during hard-to-treat spate (or rainfall-runoff) events.
Abstract. Accurate flood models require large amounts of data inputs which are not always available. Recently data coming from other sources, such as crowdsourced data, have been increasingly explored in the scientific literature. However, there is no clear methodology showing where willing citizens could go for data collection. Thus, this study proposes an optimization framework to generate and prioritize pathways that citizens could take while collecting data. The proposed framework is tested on the Sontea-Fortuna area, part of the Danube Delta, where water stagnation is threatening the local ecosystems. Among the pathways generated, results analysis showed that pathways closer to the starting point were more effective.
Abstract. Surface water salinization in deltaic areas due to saline groundwater exfiltration is an important issue. Fresh water diverted from the rivers is used for flushing the canals and the ditches in coastal areas to remove the low quality saline surface water mixed with saline groundwater. Worldwide, deltaic areas are under stress due to climate change, sea level increase and decrease in fresh water availability. The current fresh water management strategies in polders to overcome the salinization problem solely depends on uncontrolled freshwater use. However, this operation will not be effective during a scarce freshwater availability scenario and has to be revised for efficient management possibilities. With the advances in real time measurement of salinity and water level measurements, using a Model Predictive Control (MPC) scheme for the operation of a polder system is gaining popularity. MPC is a powerful control tool that can handle multiple objectives, consider the constraints and the uncertainties of the system. However, a MPC scheme requires a simple and reliable internal model that will be used to calculate the optimum control actions. The internal model should be robust, should reflect the system behaviour with enough detail and should not be computationally costly. In this paper, a MPC scheme is proposed using the discretized linearized De Saint Venant (SV) and Advection-Diffusion (AD) equations as the internal model of the controller. The proposed scheme will be able to control salinity and water level at any discretization point by manipulating the flushing and outflow discharges. This is an ongoing research with tests continuing on a realistic test case.
Abstract. Water supply systems are under stress due to population increase, climate change, aging infrastructures, terrorist attacks etc. all of which have an impact on the operation of water infrastructures resulting in failures/disruptions. The aim of this research is to evaluate the structural and operational properties of water supply systems together and identify the most critical locations in water networks and evaluate the systems’ functionalities. Graph-based metrics, called the entropic degree, is used to identify the critical locations on different network structures using the flow as a weighting parameter on links. The results would assist authorities, decision-makers in strategic plans for prioritizing and rehabilitating network components, identifying vulnerable locations as well as in enhancing the resilience of future water supply systems.
Abstract. This paper presents a reformulation of the 2D second-order discontinuous Galerkin scheme (2D DG2) which is more efficient and stable for realistic simulation of hydrodynamics. This modified scheme is formulated based on a local linear solution spanned by a set of local coefficients using a newly proposed cell stencil. The results show that the reformulated second-order discontinuous Galerkin scheme performs acceptably well in predicting shock propagation. The modified scheme is designed to be conservative not only for the average coefficients but also the slope coefficients, which is necessary to ensure robustness based on the well-balanced property under the lake at rest hypothesis. Our preliminary findings reveal a great potential from adopting the proposed 2D DG2 reformulation as a basis for real-world flood modelling applications.
Abstract. Water resource managers need to implement precise and efficient water management methods particularly in the context of low flow water management. The management objectives are complex because managers must satisfy both water demands for human activities and environmental goals. More often the flow objectives are defined at specific strategic points in which hydrometric stations are based. In order to allow the manager to better understand the hydrographical network behavior, in particular for inter-basin water transfer, these strategic hydrometric stations must be reinforced by some intermediate hydrometric stations, by modeling the network behavior, and by introducing weather forecast data in order to simulate the evolution in time and space of the river. For an efficient management, it is essential that the data collected and the output of the models (the natural flow and the withdrawals) must be reliable. For this purpose, a network optimization model was developed for analyzing the consistency of the available data set (measurements and model outputs) on a hydraulic system. Herein, a reconstruction of hydrometric data using this network optimization model is applied to the Arrats watershed management.
Abstract. The main objective of this study is to propose a linked simulation-optimization approach to determine the parameters of the confined and leaky-confined aquifers from the results of the pumping tests. In the simulation part of the proposed approach, the drawdowns at the given monitoring points and times are calculated by considering Theis and Hantush approaches for confined and leaky-confined aquifers, respectively. This simulation part is then integrated with a hybrid optimization approach where global exploration feature of the harmony search (HS) and strong local search capability of the generalized reduced gradient (GRG) approach of the spreadsheet Solver add-in are mutually integrated. The performance of the proposed approach is evaluated by considering two pumping test data for the confined and leaky-confined aquifers. Identified results indicated that the hybrid HS-Solver optimization approach provides better results than those obtained by using both curve matching and stand-alone HS approaches.
Abstract. The objective of this study is to develop an artificial neural network (ANN) based solution approach to predict the weekly flows of Ergene River which is the largest river in Thrace region of Turkey. In the developed approach, precipitation – flow data relationships have been investigated in order to establish the best model structure to predict streamflow at the selected basin. The developed relationships are then evaluated using a feed forward neural network where back propagation algorithm is used to determine the associated network weights. The performance of the developed ANN based solution approach is evaluated by using the weekly precipitation and flow data collected from different monitoring sites in Ergene River basin. The model results are also compared with HEC-HMS model outputs which is calibrated using the same precipitation and flow data. Results indicate that the proposed ANN based solution approach can be effectively used to predict the weekly flows of Ergene River.
Abstract. This study proposes a semi-Lagrangian scheme for numerical simulation of advection-diffusion equation. The proposed method provides unconditional stability and highly accurate solutions even at large time steps. Another advantage of this method is that it requires a low computational time. Accuracy of the method is tested by a numerical application.
Abstract. Flood control reservoirs are widely recognized as effective structural practices in order to mitigate the flood risk in natural watersheds. Nevertheless, the flood frequency distribution in the downstream reach is strongly affected by a certain number of characteristics of the upstream flood hydrographs. When a direct statistical method is utilized, a multivariate approach should therefore be utilized to accurately assess reservoir performances. In this paper, a flood frequency distribution of the routed flow discharge is derived from a bivariate joint distribution function of peak flow discharges and flood volumes of hydrographs entering the reservoir. Such a joint distribution is constructed by using the copula approach. Reservoir performances are also exploited to categorize event severity and to estimate their bivariate return periods. The method is applied to a real-world case study (Sant’Anna reservoir, Panaro River, northern Italy), and its reliability is verified through continuous simulations. Bearing in mind the popularity that design event methods still have in practical engineering, a final evaluation of the performance assessment achievable by simulations of synthetic hydrographs derived from a flood reduction curve is finally proposed.
Abstract. While previous editions of ARR have served the engineering profession well, a number of issues have necessitated the production of a new edition. These issues include the many recent developments in knowledge about flood producing processes, the increased computational capacity and data manipulation available to engineers, and the rapidly expanding body of information about climate change. There is a need, therefore, to produce a new edition of ARR. As part of the development of this new edition, it has been necessary to review the methods used and the implications of assumptions necessary for implementation of these methods. An outcome of this review has been recognition of changes in design flood estimation since development of the digital computer and the subsequent development of hydroinformatics. This has led to recasting design flood estimation as a problem in hydroinformatics. Presented herein is the background to and a discussion of this concept.
Abstract. Meteorological data such as precipitation and temperature are important for hydrological modelling. In areas where there is sparse observational data, an alternate means for obtaining information for different impact modelling and monitoring activities is provided by reanalysis products. Evaluating their behaviour is crucial to know their uncertainties. Therefore, we evaluated two reanalyses gridded data products, viz., Coordinated Regional Climate Downscaling Experiment (CORDEX) and National Centers for Environment Predictors and GCM (General Circulation Model) predictor variables (NCEP); two station based gridded data products, viz., Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and India Meteorological Department (IMD) gridded data; one satellite based gridded data product i.e., Tropical Rainfall Measuring Mission (TRMM); and one merged data product, i.e., Global Precipitation Climatology Project (GPCP). These products were compared with IMD observed station data for 1971 to 2010 to evaluate their behaviour in terms of fitness by using statistical parameters such as NSE, CRM and R2. APHRODITE and TRMM gridded data showed overall good results for precipitation followed by IMD, GPCP, CORDEX and NCEP. APHRODITE also showed good agreement for mean temperature. CORDEX and NCEP gave a promising result for minimum and maximum temperatures with NCEP better than CORDEX.
Abstract. The many facets of river hydromorphology are of crucial importance to assess the condition of rivers. Generating new knowledge is the key in achieving the water framework objectives. Therefore, detailed bathymetric information is required for each river system to evaluate the constantly changing morphological structures and to understand hydraulic, morphodynamic and ecological processes. The technology of Airborne LiDAR Bathymetry (ALB) scanning is an innovative remote sensing method for measuring the ́underwater topography ́ of water bodies. ALB is perfectly qualified to meet the requirements at an exceptionally high resolution and sufficient accuracy. The data processing of an ALB point cloud consists of a number of specific work steps to determine the point classification (water surface, bathymetry, vegetation, ground, etc.) and to derive high-quality digital terrain models (DTM). This work shows exemplary the results of an ALB survey of the Mareit/Mareta River in South Tyrol, Italy. First, the applied analysis methodology is presented. Second, the question on the optimal bathymetric resolution for hydraulic and habitat modeling purposes is discussed.
Abstract. Real time flood forecasting can help authorities in providing reliable warnings to the public. This process is, however, non-deterministic such that uncertainty sources need to be accounted before issuing forecasts. In the FloodEvac project, we have developed a tool which takes as inputs rainfall forecasts and links a hydrological with a hydraulic model for producing flood forecasts. The tool is able to handle calibration/validation of the hydrological model (LARSIM) and produces real-time flood forecast with associated uncertainty of flood discharges and flood extents. In this case study, we focus on the linkage with the hydrological model and on the real-time discharge forecasts generated.
Abstract. Wetlands are ubiquitous topographic depressions on landscapes and form critical
elements of the mosaic of aquatic habitats. The role of wetlands in the global hydrological and biogeochemical cycles is intimately tied to their geometric characteristics. We used DEM analysis and local search algorithms to identify wetland attributes (maximum stage, surface area and storage volume) in four wetlandscapes across the United States. We then derived the exceedance cumulative density functions (cdfs) of these attributes for the identified wetlands, applied the concept of fractal dimension to investigate the variability in wetland’ shapes. Exponentially tempered Pareto distributions were fitted to DEM derived wetland attributes. In particular, the scaling exponents appear to remain constant through the progressive water-filling of the landscapes, suggesting self-similarity of wetland geometrical attributes. This tendency is also reproduced by the fractal dimension (D) of wetland shorelines, which remains constant across different water-filling levels. In addition, the variability in D is constrained within a narrow range (1 <D < 1.33) in all the four wetlandscapes. Finally, the comparison between wetlands identified by the DEM-based model are consistent
with actual data.
Abstract. In this study we investigated and quantified the effects of a number of environmental conditions on the readings of fluorescent dissolved organic matter (fDOM) and total algae probes. These currently monitor fDOM, chlorophyll-a and phycocyanin for the full depth profile of different reservoirs in South-East Queensland (Australia), but interferences and quenching affecting these parameters have led to uncertainty in the reliability of the readings. Additionally, in the case of the total algae probe, obtaining reliable estimates of algal biovolume or cell counts is challenging since the pigments content varies with species and several other environmental variables influence estimates. With regards to the fDOM, a number of experiments were performed which enabled the development of a sequential compensation model accounting for the main trivial quenching. In addition, the compensated readings were compared to other experiments’ outputs to check for correlations between readings and character/molecular weight of DOM to develop an accurate real-time model that may be useful in assisting DOM removal by coagulation. Preliminary work with the algae probe also showed potential to derive more specific information on species/abundance for better cyanobacteria management.
Abstract. Soil erosion by various agents is one of the major threats of land degradation throughout the world. Revised Universal Soil Loss Equation model integrated with remote sensing and GIS was employed to assess soil erosion in the Mago basin of Arunachal Pradesh, India for a period of ten years (2004–2013). The rainfall erosivity (R-factor) was calculated using ten years rainfall data. ASTER DEM of 30 m resolution was used to generate the LS-factor map. Soil map and soil samples were analyzed to generate soil erodibility (K) map. MODIS NDVI images were used to obtain C-factor maps. The average annual soil loss was estimated and spatial and temporal variations of annual soil erosion were analyzed. The largest portion of the snow or glacier free area was observed under slight erosion and the rest of the area under moderate to very severe erosion risk zones. The temporal variation in the area under slight soil erosion showed a decreasing trend. Increasing trends were observed over the years in areas under moderate to very severe soil erosion classes. The average soil loss by water for each year crossed permissible soil loss limit of 12 t ha-1 year-1 except for the year 2006.
Abstract. Limited hydro-meteorological and sediment data of the Brahmaputra basin is available and as a result, water resources management of the basin is a challenge. Advances in remote sensing provide opportunities to access alternative data, which can be used in characterising the basin. We present hydrological and erosion models of the basin developed using remotely sensed data. In particular a hydrological model using HEC-HMS was developed using the elevation data from the Shuttle Radar Topographic Mission (SRTM). The hydrology of the basin was simulated using rainfall data from the Tropical Rainfall Measuring Mission (TRMM). Evapotranspiration, temperature, soil and landuse were collected from remotely sensed data sources. The uncertainty in the model parameters due to the uncertainty of the downstream rating curve used in the calibration of the model was estimated. Another hydrological model using SWAT was also developed to simulate the erosion pattern in the basin. A hydraulic model of the Brahmaputra River was developed using HEC-RAS. Simulated flood maps were compared with satellite imageries. A conclusion was reached that the models are able to simulate the hydrological and hydraulic processes in the basin with reasonable accuracy. Due to the lack of data the erosion model could not be validated.
Abstract. Alexandria experienced heavy rainfall in October 2015 resulting in wide spread flooding, huge damages and seven deaths. This paper presents the analysis of the hydro- meteorological data to characterise the extremity of the event. The flood map of the city and its adjoining area prepared with LANDSAT-8 satellite images shows the extent of flooding. The analysis with the rainfall forecast from the ECMWF clearly demonstrated that the extreme event could have been predicted days ahead. It is proposed to implement Anticipatory Flood Management in Alexandria (AFMA), which will allow using the extreme rainfall forecast to start pumping out water from Lake Maryot and Airport Lake before the event starts. This will enable extra storage space to accommodate some of the flood water from subsequent rain. An analysis of the October flood showed that 50% of the flood water due to the heavy rainfall could have been stored in the lakes had the AFMA been implemented. The study shows that the existing data allows us to implement AFMA to reduce flood consequences and pave the way to critically decide upon additional mitigation infrastructure. The recommendation of this study is currently being implemented.
Abstract. The paper presents a new methodology for hydrodynamic-based flood forecast focusing on sce- nario generation and database queries to select the appropriate flood inundation map in real-time. In operational flood forecasting, discharges are forecast at specific gauges using hydrological models. The water levels are obtained from a rating curve designed for each respective gauge. Particularly for higher discharges when the flow over-spills the side banks, these curves are highly uncertain. Hy- drodynamic models are then required to produce realistic inundation maps and water levels. Hydro- dynamic models are computationally expensive and therefore not feasible for real-time forecasting. Alternatively, pre-calculated inundation maps can be stored in a database which contains a substantial number of scenarios, and used for extracting the most likely map in real-time. This study investigates the application of offline inundation forecast in the city Kulmbach in Germany.
Abstract. Water balance calculation is a well-known and adapted method to analyze district-metered areas (DMAs) of drinking water distribution system. Other application of water balance results can be training dataset for consumption forecast, monitoring and managing water loss. The vast amount of application makes it a very powerful tool, which is in contrary sensitive to the accuracy of the calculation. The uncertainty of flow metering decreases as the length of the time step decreases, however, the uncertainty of stored volume measurement in tanks increases. Investigation of the limitations of water balance calculation in regard to uncertainty is necessary to develop an analytical solution for optimal calculation time step.
Abstract. Pressure management is a widely adopted technique to decrease background leakage or to extend the lifespan of the pipe network [1]. In some cases, it is inevitable to deploy multiple pressure reducing valves to supply a particular zone. In order to supply water to the customers with optimal pressure head, the precise setting of the parallel pressure reducing valves’ (PRV) target pressure is required. Steady-state hydraulic models like EPANET has the functionality to simulate pressure loss of a pressure-reducing valve [1]. This can be simulated by adding minor-loss after the pipe, or by modifying the properties of the next link on the downstream side. Either way, the proper setting of the coefficients is essential to calibrate the hydraulic model. In this paper, two non-linear optimization methods were utilized to calibrate the hydraulic model with multiple input values.
Abstract. Water loss from water distribution systems (WDS) is an ongoing problem which poses a significant risk to water resources around the world. This paper presents a novel combined sensor placement – leak/burst localisation methodology which forms, and analyses by using sc inverse-distance weighted (IDW) interpolation, a sensitivity matrix to determine, on average, how accurately each sensor configuration localises leaks/bursts modelled at all nodes in a WDS. For a given number of sensors, the multi-objective evolutionary algorithm determines the optimal location of sensors to maximise the leak/burst localisation performance using the sc-IDW outputs in its objective function. Once the optimal sensor location is selected, the sc-IDW technique is used when new leaks/bursts occur in the WDS to determine their approximate location. A benchmark WDS was used to compare the leak/burst localisation performance against a baseline sensor placement technique. The comparison indicated that by using the sc-IDW technique for both the sensor placement and leak/burst localisation steps the leak/burst search area was reduced in size by between 9 and 26%. Reducing the leak/burst search area allows field teams to more quickly repair a leak/burst and reduce the impact that it has on water company operational efficiency and customer service.
Abstract. With the aim of refining a reliable tool for groundwater management, the ERA-Interim and ERA5 global atmospheric datasets provided by the European Centre for Medium- Range Weather Forecasts (ECMWF) are examined. Attention is focused on the analysis of the behavior of the soil moisture content. The performance of ERA-Interim and ERA5 is evaluated by considering the water table measurements at three sites in the Umbria region as well as the dynamics of water flow towards the groundwater.
Abstract. The main purpose of this study is to assess the performance of the water distribution system (WDS) of the city of Messina (Italy) under different management scenarios that can be operated by the local water utility, AMAM S.p.A. To this end, a methodology is here applied for determining sustainability indices for pressure in WDS. The sustainability indices are based upon performance criteria including reliability, resiliency and vulnerability. In particular, six different scenarios are analyzed and the results are compared in order to identify possible solutions to increase sustainability in WDS.
Abstract. The economic value of the potential energy hidden in water resources is becoming more and more relevant for pipe design. In this work a new way to design drinking main waterlines, embedding also the potential hydroelectric production as pipeline benefit, is presented. The optimum design of a cross-flow turbine, on the basis of the available head jump and discharge is first outlined; the description of a genetic algorithm to minimize the total cost (pipeline plus machinery) minus the net benefit (hydropower production) is then presented. Finally, a comparison is carried out among the costs of a case study pipeline assuming a) no hydropower production and traditional design criteria and b) two different scenarios with different values of benefits per unit energy production. The two scenarios lead to hydropower production with constant impeller rotational velocity in one case and with variable impeller rotational velocity in the other one.
Abstract. Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, we explore in this study the potential of Bayesian Networks (BNs). A BN is created using a simple version of Temperature-Index Snowmelt Model. Next, uncertainty analysis is performed using both the BN method and Monte-Carlo (MC) simulations. The results show that BN method gives similar results to the MC method and can be used for real-time applications.
Abstract. Electric energy plays a key role in the development of modern societies. Each of the electric power generation technologies (e.g., hydroelectric, wind, solar, thermal, etc.) has some advantages and disadvantages with respect to the fundamental resource indicators, including water footprint, land footprint, carbon footprint, as well as electricity generation costs. Due to the shortage and frequent crisis associated with the above resources, optimal selection of the mix of electricity generation technologies is very important and the share of each technology in the capacity expansion of the generation system must be carefully defined. Iran is in an arid and semi-arid region, with less than one third of the average world precipitation. Moreover, the available water resources are restricted due to the water crises in the Middle-East region. In this paper, we first estimated the peak power consumption of Iran in 2024, based on the time-series data from 2004 to 2014. Then, we formulated an optimization problem to find the share of each electric power generation technology to cover the required extra generation capacity for supplying the power consumption in the target year 2024, considering the effect of the four aforementioned performance indicators. The optimization problem is solved using Genetic Algorithm. Numerical results show that in the target year, 20 GW of electricity should be added to the generation capacity. The results also show that, solar thermal and solar photovoltaic are the best electric generation technologies regarding the available resources.
Abstract. Water distribution systems play a fundamental role due to their impact on public health, food, agriculture and energy and consequently, they are identified as critical infrastructures. Integrated urban water management is affected by critical issues that may interfere with the achievement of the best management practice. The work shows a methodology for the identification of interventions priorities in a region where several water distribution systems, with different criticalities, coexist. As metric for critical issues, IWA PIs has been chosen. Multi-criteria Decision Analysis (MCDA) is applied to obtain a sorting of critical issues and thus to define the priorities in the investment planning. The aim is to provide a tool that supports the consistency check between criticalities and interventions planning. The methodology has been applied to 15 management areas within an homogeneous region in the North of Italy.
Abstract. Water distribution networks are critical infrastructures that should ensure the reliable supply of high quality potable water to its users. Numerical models of these networks are generally governed by many parameters for which the true value is unknown. This may be due to a lack of knowledge like for consumer demand or due to a lack of accessibility as for the pipe roughness. For network managers, the effect of these uncertainties on the network state is important information that supports them in the decision-making process. This effect is generally evaluated by propagating the uncertainties using the mathematical model. In the past, perturbation and stochastic collocation methods have been used for uncertainty propagation. However, these methods are limited either in the accuracy of the results or the complexity of the calculation. This paper uses an alternative spectral approach with the polynomial chaos expansion that has the potential to give comparable results to the Monte Carlo sampling through the definition of a stochastic model. This approach is applied to the model of a water distribution network in order to evaluate the influence of uncertain demands on the water age.
Abstract. Distributed hydrological simulations aid to investigate the spatio-temporal behaviour of hydrological variables. However, data to feed hydrological models are not always available mainly due to lack of gauges or high retrieval fees. In this research, two 0.25- degree daily precipitation databases from the Tropical Rainfall Measuring Mission (TRMM) were tested to simulate daily runoff in the basin of the main Upper Niger River tributary. Precipitation data are TRMM and TRMM Real Time (RT) 3B42V7. For runoff simulation, the grid-based hydrological model CEQUEAU was chosen. To estimate the evaporation in the model, temperatures were retrieved from the third-generation reanalysis ERA-Interim. From gauges and both TRMM data, monthly basin precipitation was calculated and compared to analyse the performance of TRMM to estimate rainfall. Runoff was simulated with each of these three precipitation products. In each case, the daily ERA-Interim temperatures were used. By Nash-Sutcliffe model Efficiency (NSE) and coefficient of determination (R2), model performance was evaluated through comparison of daily discharges with simulations for both calibration and validation periods. Results show correlation of TRMM by 0.95 and TRMMRT by 0.91 with gauge data. Both TRMM products combined with ERA-Interim temperature were found suitable for daily runoff modelling with NSE >0.835 and R2 >0.872.
Abstract. Most cities are facing an aging sewer infrastructure in extensive and emerging need of repair, rehabilitation or renewal. Deterioration modelling can be a valued data mining tool to tackle this issue by supporting utilities in defining strategic investment planning. This study aims to demonstrate the benefits of deterioration modelling using sewer CCTV inspection data and GIS characteristics (material, age, depth, width, traffic load, etc.) of two different cities: Braunschweig in Germany and Bogota in Colombia. A probabilistic Markov-based model has been applied to identify and exploit relationships between sewer condition and characteristics in the extensive datasets of the two cities. The quality of prediction of the model has been evaluated by analyzing the deviation between model observations and model predictions. Results show relatively low deviations (< 15%) indicating a satisfying model performance in both cities and underlining the relevance of deterioration models to simulate the condition of sewer networks and to support strategic asset management.
Abstract. In the present work, a 1D-2D-coupled model was used to perform hydraulic analysis of Gornalunga River (Sicily), in order to estimate and analyze the flood risk in correspondence of a crossing bridge. In the frame of the project “Speed up of the railway line Catania-Syracuse”, an existing bridge, crossing Gornalunga River, has to be enlarged and a configuration that mitigates the hydraulic risk on the surrounding area has to be found. At this aim, two different future configurations were considered and a flood modeling study in proximity of the railway crossing in existing and future configurations was conducted using MIKE FLOOD. Depths of flowing water through the bridge, as well as the maximum flood extent and maximum inundation depth have been evaluated for each scenario in order to identify the configuration that minimizes the hydraulic risk for the surrounding area. Finally, the effectiveness of this last solution is analyzed and discussed by comparison with the actual configuration. Simulation results demonstrate that in proximity of the railway bridge water level, as well the hazard risk of the surrounding area decrease passing from the actual configuration to the future one.
Abstract. This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.
Abstract. This study aims to evaluate the impact of the Canadian Regional Climate Model’s (CRCM) spatial resolution on summer floods simulation. Four different climate simulations issued from the fourth version of the CRCM (two driven by the Canadian General Circulation Model (CGCM) and two driven by the ERA40c reanalysis) are employed. One simulation at 45 km resolution and another one at 15km resolution for each driver were compared on a daily time-step for the 1960-1990 period. These four simulations are used as inputs for two hydrological models of varying complexity (HSAMI and MOHYSE). Each model is calibrated using three different objective functions based on the Kling-Gupta Efficiency criterion (KGE) to target floods. Two seasonal indices are used to evaluate the CRCM outputs: bias (temperature) and relative bias (precipitation). For the streamflow simulations analysis, the seasonal values of KGE and relative bias are used. The results show an impact of spatial resolution on climate model outputs, on streamflow simulation and flood indicators in the hydrological models. However, other elements such as climate model driver and domain size can influence the results, highlighting the need for further research to assess the impact of spatial resolution on summer floods.
Abstract. As part of the low countries and with one of the highest population densities worldwide, the Flemish region has experienced a long history of flooding causing tens of millions euro damage each year. In response to this, water managers invested over the past decade in flood modelling and mapping with a fluvial origin. In recent years, pluvial flooding has also occurred numerous times in Flanders, but a region-wide map describing these processes more in detail in terms of extent, depth and probability was lacking. Following a pilot-study in 2016, the VMM undertook in 2017 the VLAGG1- project to develop a region-wide, high-resolution pluvial flood map for Flanders. Via a combination of state-of-the art methodologies and web technologies, a draft flood map was presented to a broad reviewing community across Flanders, who were then able to improve it further by adding local knowledge on known flooding and more detailed data on key hydraulic structures. In a three month period, over 7000 additions were made by 370 delegates from 165 organizations that have been incorporated into, and significantly improved the quality of the final flood maps which are due to be published in 2019.
Abstract. The article is devoted to the modeling and estimation of the change in the maximum daily precipitation in the northern district of Moscow and the nearest Moscow suburbs against the background of changes in the average annual air temperatures and its average temperatures over the warm seasons. Special statistical methods used in hydrometeorology were used to assess changes. The obtained results indicate an increase in the calculated values of the hazardous precipitation and their occurrence frequency in the region during the last decades, which must be taken into account in the calculation of surface runoff for hydro- technical constructions and environmental objects. The special method of Monte-Carlo is offered for simulation of storm precipitation.
Abstract. The research is aimed on development of providing additional information to the person making decisions regarding the flood control by water reservoir with help of both short term forecast of runoff together with stochastic forecast. The study proposes an approach to managing a complex reservoir that operates in rapidly developing summer floods, but at the same time during the year, but in different years there may be both floods and droughts, for which a large supply of water is needed reservoir.
Abstract. This paper proposes the knowledge development of the crisis management taking place in the largest drinking water treatment system in Thailand, with the capacity of approximately 4,000,000 CMD. The system encountered with the flood crisis six years ago. Having drawn back to 2011, the flood crisis had massive impact on Metropolitan Waterworks Authority (MWA). For examples, many water treatment processes were disrupted, consumers were not confident on the drinking water quality, and additional operation cost of MWA was raised up about 300 million baht, etc. Therefore, it is an importance to have mitigation measures for the organization to reduce the risk by increasing the capacity of the community and cooperating with the stakeholders to cope with the risks by applying well planned and well-executed in Disaster Risk Reduction (DRR) and Crisis and Emergency Risk Communication (CERC). The result shows the development opportunities of the Metropolitan Waterworks Authority in various aspects from past experiences, and proposes the best practices in order to response with all stakeholders when risks encountered.
Abstract. Water losses have a high environmental impact in terms of natural resources depletion (water, energy, ecosystems). This work aims at developing an airborne water leak detection surveillance service to provide water utilities with adequate information on leaks in water transportation mains outside urban areas. As a first step, a series of measurement campaigns were performed with hyperspectral cameras and a thermal infrared camera for selecting the most appropriate wavelengths and combinations thereof for revealing at best high moisture areas and artificial leaks. Further measurements will be performed with thereby optimized instrumentation onboard a plane and a UAV in an operational environment.
Abstract. In the terrestrial biosphere, vegetation plays vital roles in providing food and habitats for humankind and animals. In general, vegetation activity is influenced by both climate drivers and anthropogenic drivers, and studies have tried to disentangle contributions of these multiple variables from each other. However, it remains largely unclear how climatic and anthropogenic effects work together to impact on vegetation dynamics. In this study, we analyzed the vegetation change from 1995 to 2014 in the Three-River Headwaters Region (TRHR) using Normalized Difference Vegetation Index (NDVI). We applied partial correlation analyses to discriminate the contributions of climate variables and anthropogenic variables. The result indicates that the TRHR experiences a slightly greening trend from 1995 to 2014. The primary climatic driving factor is temperature for the southeast and south parts of the TRHR, precipitation in the west part, and a combination of precipitation, temperature and cloud cover for northeast part. The interaction between precipitation and cloud cover, precipitation and grazing activity, temperature and population activity, contribute to vegetation growth. The relationship between vegetation activity and the driving factors are evolving towards the direction which vegetation favors for the past two decades.
Abstract. This paper deals with flood estimation in ungauged catchment using continuous rainfall-runoff model. The rainfall-runoff model used in this study is developed based on the ENKI hydrological framework. In this study, flood estimation in ungauged catchment is based on transfer of parameter values from nearby station. The catchment used in this study to test the suitability of the ENKI system in flood estimation of ungauged catchment is the Gaula catchment located in Norway. This catchment has three main sub-catchments where flow records are available. The ENKI system is calibrated for each sub-catchment. In order to test its suitability in flood estimation, the average of the parameter set obtained from any of the two sub-catchments is used in the remaining sub-catchments. The performance of the ENKI system in flood estimation is evaluated in terms of the Nash–Sutcliffe (NSE) model efficiency index and the model ability to simulate the daily observed Annual Maximum Series (AMS). The result of this study shows that the ENKI framework has considerable potential in flood estimation in ungauged catchments.
Abstract. The effects of urbanization on hydrology, water quality, habitats, as well as ecological and environmental compartments, represent issues of primary importance for multiple agencies at the national, regional and local levels. In the context of the SMART-GREEN project, funded by Fondazione Cariplo, a new tool called SMARTGREEN plugin is under development in a desktop GIS framework.The software will provide: 1) a user friendly interface to help analysts in the hydrologic-hydraulic modelling of urban watersheds and drainage networks through the model MOBIDIC-U, with the possibility of considering Low Impact Development (LID) solutions, 2) a set of tools to easily import information from existing databases, 3) a set of tools to check the database quality, highlight missing or incorrect data, and suggest possible fixes automatically, 4) an easy and faster way to speed up the analysis of the results. In this work, we show the main functionalities of the plugin through a basic test case. The software aims at supporting water service management companies in planning LID implementation in urban areas.
Abstract. When manually calibrating a water quality model, considerable time and attention are required to calibrate each water quality variable and model parameter. Hence, developing an automated model that allows for efficient and objective automatic calibration is highly desirable. The QUAL2Kw model calibrates the QUAL2K model automatically using a genetic algorithm (GA). As the calibration results of a GA vary strongly with the performance criteria used as the objective function in GA optimization problems, this study compares and analyzes auto-calibration results and selects the optimal criterion for each objective from among 6 performance criteria: CV(RMSE), R2, NSE, PBIAS, RSR, and SSNR. Additionally, a multi-objective auto-calibration was conducted using two kinds of performance statistics as the objective function of the GA. The auto-calibration model was applied to the Youngsan River in Korea. The TMDL was established to achieve water quality goals at specific target points. Among the 6 auto-calibration results based on a single performance criterion, NSE was the best criterion for calculating fitness through auto-calibration. When the calibration accuracies of the TMDL target points and the entire river are considered simultaneously, an objective function using multiple performance criteria, specifically CV(RMSE) and RSR, was selected as the final auto-calibration of the model.
Abstract. This study presents physical habitat simulations to investigate the impact of weir removal on the composition of fish community in a river. The study site is a 900 m long reach in the Gongneung-cheon Stream in Korea, at the middle of which the weir was located. Fish monitoring revealed that lentic fishes were dominant before the weir removal, however lotic fishes became dominant after the weir removal. The ANFIS method, a data-driven method, was used for the habitat simulation with River2D for hydraulic simulation. The distribution of highly suitable portion for each fish species were given before and after weir removal. It was shown that the physical habitat simulation successfully predicts the change in the composition of fish community after the weir removal. The simulated results were compared with those from the knowledge- based model.
Abstract. In the light of water shortages, frequently affecting many regions worldwide, domestic rainwater harvesting and greywater reuse systems represent an alternative source to provide non-potable water in buildings, reducing the water demand from mains water supply systems. This study fits this framework providing a methodology, based on a hydraulic/hydrological model developed by means of the EPA’s Storm Water Management Model, which allow optimizing the system design by giving the opportunity to the user to consider different catchments surfaces (impervious, gravel and green roofs), plant's configurations, user’s habits, water end-uses, and climate conditions. The model has used to model a residential building, located in the city of Bologna (Italy), and equipped with a hybrid greywater/rainwater system. Continuous simulations were performed with 13 years daily rainfall data, and the long-term performance of different system combinations were evaluated. The case study showed a non-potable water saving efficiency of 75.86%, which accounts by 26.71% mains water withdrawal. The final goal of this paper is those of presenting the hydrological/hydraulic model that has been used as engine of a calculator tool for sizing and planning hybrid rainwater/greywater systems.
Abstract. We present a flood risk mapping framework created in the context of the update of the Mexican flood risk atlas. This framework is based on a nation-wide GIS database of map time-series. Those maps are used as forcing for a deterministic, raster-based numerical model. For each catchment of interest, the model retrieves the data from the GIS and perform the computation on the specified area. The results are written directly in the GIS database, which facilitate their post-processing. This methodology allows 1) the generation of flood risk maps in cities located across the national territory, without too much effort in the pre and post-processing of information and 2) a very efficient process to create new flood maps for urban areas that have not been included in the original batch.
Abstract. The Porous Shallow water Equations are widely used in the context of urban flooding simulation. In these equations, the solid obstacles are implicitly taken into account by averaging the classic Shallow water Equations on a control volume containing the fluid phase and the obstacles. Numerical models for the approximate solution of these equations are usually based on the approximate calculation of the Riemann fluxes at the interface between cells. In the present paper, it is presented the exact solution of the one-dimensional Riemann problem over the dry bed, and it is shown that the solution always exists, but there are initial conditions for which it is not unique. The non-uniqueness of the Riemann problem solution opens interesting questions about which is the physically congruent wave configuration in the case of solution multiplicity.
Abstract. This paper aims to explore the suitability of compact resilience metrics for application to partitioned water distribution networks (WDNs). WDN partitioning represents a different test from the usual reliability tests performed in the scientific literature, in which the operation of the WDN is unperturbed, or marginally perturbed (e.g., by segment isolation or demand amplification). The creation of permanent district metering areas (DMAs), which is carried out through the simultaneous closure of numerous links, represents, instead, a larger and permanent perturbation that deserves special attention. In this analysis, two metrics, namely the Global Resilience Failure (GRF) and the energy efficiency indices, were compared in pressure-driven approach with WDN performance indicators. The results in a real WDN, which is partitioned in a growing number of DMAs, proved that both the GRF is more sensitive to the weaknesses arisen in the partitioning processes.
Abstract. This paper presents results about the hydrological modelling of the Cascina Scala catchment. Following a preliminary analysis that proved the Nash cascade of reservoirs superior to the Clark model in the event-based rainfall-runoff simulation for this catchment, a new analysis was carried out to compare two different parameterization approaches applicable in gauged rain events. The former is based on estimating the optimal set of model parameters in each gauged event and then obtaining the ultimate set by averaging the values obtained over the whole group of events; the latter is based on estimating the optimal set of parameters directly on the whole group of gauged events. The results of the analysis proved the better performance of the latter, which enables better representation of the hydrological response of the catchment, evaluated in terms of water discharge pattern at the outlet.
Abstract. The calibration of water distribution networks is one way to perform such procedures in hydraulic models, but several are the difficulties encountered in calibrating a real network. This work proposes the improvement of modules of the calibration method proposed by Silva (2003), where using the genetic algorithm (GA) search tool, the author calibrates a real water distribution network of a Brazilian city, adjusting parameters mainly from roughness and coefficient of leakage. The enhancement of GA is the introduction of a new decision variable, the nodal demand, which assigns demand values to nodes according to the pressure-driven demand model of Tucciarelli, Criminisi and Termini (1999). The tests of the GAs implemented are tested for this real water distribution network presented by Silva (2003). The effect of the improvement on the calibration results was significant for the network, but the need for more in-depth studies, which are of course required for the application of new algorithms in real-scale networks.
Abstract. The definition of the relationship between the leak outflow, the total head at the leak and other relevant parameters such as the pipe stiffness, the leak dimension and shape has been object of extensive studies in recent decades. The use of the Torricelli equation has been questioned, because some experimental results showed that it can yield unsatisfactory results, and other formulations have been suggested to model water leakages in water distribution networks (WDNs). To investigate the effectiveness of the formulations suggested by different authors, an experimental campaign was carried out at the Environ- mental Hydraulic Laboratory of the University of Enna (Italy) for leaks of different shape and size in polyethylene pipes.
Abstract. In this study an error propagation (EP) scheme was introduced in parallel to exponential filter computation for soil water index (SWI) estimation. A preliminarily assessment of the computed uncertainties was carried out comparing satellite-derived SWI and reference root-zone in situ measurements. The EP scheme has shown skills in detecting potentially less reliable SWI values in the study sites, as well as a better understanding of the exponential filter shortcomings. The proposed approach shows a potential for SWI evaluation, providing simultaneous estimates of time-variant uncertainty.
Abstract. Current monitoring programs in the nearshore region are necessary to allow a thorough knowledge of coastline erosion as well as diffusion and dispersion of polluting tracers. Collecting a large amount of data in widespread areas is challenging, because of technical and economic limitations, thus numerical models are often preferred to simulate the hydrodynamics and the transport of tracers in extended areas with the desired level of precision. To be accurate, models need to be calibrated and validated by high quality field measurements. Therefore, to examine current and tracer patterns in a basin, using data and numerical modelling in conjunction could be the best practice. The aim of the present work is: i) to provide some information on the typical and recurrent processes occurring in a target basin, by analyzing a set of current field data; ii) to reproduce the principal current patterns and derive information on the possible sediment transport fluxes in the basin by applying mathematical modelling. The site selected for this study is a semi enclosed coastal sea, in southern Italy. The obtained results successfully confirm the typical hydrodynamic behavior of the basin, and delineate areas which are more exposed to erosion.
Abstract. This study will explore the use of a nonlinear relationship between dew point temperature (DPT) and precipitation to apply a method to downscale global circulation models (GCMs) information. Recently, there have been attempts to characterize dew point temperature (DPT) and precipitation intensity. The DPT has shown to be an easier variable to predict, and therefore forecast or prediction on GCM could provide a more reliable estimation. DPT using Clausius-Clapeyron (CC) relationship is one of the methods. This relationship has approximated a non-linear relation into a simple slope coefficient. In a recent study in the Netherlands, DPT was processed by the Advanced Delta Change Method (ADCM) and then converted to precipitation using CC or super CC relation observing better results. In this research work this approach is compared with a non-linear (neural network) model of the relationship. The main contribution of the overall project is to explore the improvement of a better relationship description and how much this could impact in our engineering intensity duration frequency curves. The problem posed is the analysis of the implications of climate change information for civil engineering design in the Metropolitan Area of Monterrey (Santa Catarina River Basin in Mexico).
Abstract. In this paper, we present two R packages, airGR and airGRteaching, which are aimed at hydrological modeling. These two open-source packages allow for undertaking simplified simulations of surface flows on river catchments, based on lumped rainfall-runoff models that require few input data. airGR can be used for engineering, research and education purposes and is well indicated for experiments on large sample datasets. airGRteaching is an add-on to airGR and is especially dedicated to education, since one of its functionalities provides an interface on which parameters and models fluxes can be easily understood through an interactive visualization. airGRteaching also contains simplified functions that require less programming from users but do not allow for some more advanced experiments.
Abstract. A Bayesian model was proposed for daily predictions of the probability of water quality standard violation of enterococci (ENT) levels in recreational beach waters. The Bayesian model consisted of a prior distribution and a likelihood function, which were constructed using seven years of environmental and bacteriological data collected at six recreational beach sites along the U.S. Gulf coast. The likelihood function followed best a normal distribution while the prior distribution was found to be best fitted with a Nakagami distribution. Modelling results showed that the Bayesian model was capable of explaining 86.13% of recreational water quality advisories issued by the U.S. Louisiana Beach Monitoring Program with a false positive rate of 7.24% and a false negative rate of 6.23%, indicating an excellent performance of the Bayesian model. The Bayesian model, presented in this paper, is unique and novel in terms of (1) the integration of a deterministic model and a probabilistic model for the prediction of recreation beach water quality; (2) the identification of important hydrodynamic processes controlling the source and transport of bacteria in coastal beach waters; and (3) the identification of key sinks of bacteria in coastal beach waters. It was found that the tidal washing process plays the most important role in causing the violation of ENT water quality standard for coastal beach waters, followed by the wash-off process of up to four-day antecedent rainfall.
Abstract. Climate change should affect inland waterways in a close future. The study of their resilience against climate change requires an optimal resource allocation. Indeed, it is possible to analyze the global change effects on inland waterways only if the water resources allocation is optimal. In addition, the events due to climate change are not deterministic. It is obvious that it is not possible to predict precisely their occurrence time, their magnitude and their duration. Hence, it is necessary to consider uncertainties in climate projections, and more precisely uncertainty bounds on these predictions. The objective of this paper is to propose a simulation architecture of inland waterways that couples simulation software of their dynamics and an optimal water resources allocation approach under uncertainties based on Markov Decision Process. The proposed simulation architecture and the designed tools are detailed and implemented by considering some expected climatic events on a part of the inland waterways in the north of France.
Abstract. Climate change is exposing more and more frequently flood prone areas to potential casualties and damages. The capability of the flow to carry relevant quantities of sediments interacts with the presence of obstacles in flood-inundated areas and contributes to the increase the related hazard, constituting a relevant concern in the framework of risk analysis. Unfortunately, existing literature on this topic is rather scarce, especially for the features of sediment transport and the forces acting on rigid obstacles. In the paper, a recent two-phase shallow-water morphodynamical model, particularly suited to the analysis of fast geomorphic transients, is applied to the numerical simulation of the propagation of a dam-break wave over an erodible floodplain in presence of a rigid obstacle. The geometry of the test-case is inspired to a recent fixed-bed study reported in the literature, for which extensive experimental and numerical data concerning the flow field and the dynamic loading against the obstacle are available. Results of the numerical simulations contribute to highlight the effect of the obstacle on the changes in the bottom topography, along with the subsequent change on the loading condition on it.
Abstract. Smart cities are getting essential to drive economic growth, increase social prospects and improve high-quality lifestyle for citizens. To meet the goal of smart cities, Information and Communications Technology (ICT) have a key role. The application of smart solutions will allow the cities to use ICT and big data to improve infrastructure and services (i.e. network efficiency, protection from contamination, etc.). In the water sector, the integration of smart meters and sensors coupled with cloud computing and the paradigm of “divide and conquer” introduces a novel and smart management of the water network allowing an efficient online monitoring and transforming the traditional water networks into modern Smart WAter Networks (SWAN). The Ctrl+SWAN (Cloud Technologies & ReaL time monitoring+Smart WAter Network) Action Group (AG) was created within the European Innovation Partnership on Water, in order to promote innovation in the water sector by advancing existing smart solutions. The paper presents an update of a previous work on the state of the art on the best On-line Measuring Sensors (OMS) already available on the market and innovative technologies in the Research and Development (R&D) phases.
Abstract. The recent development and applications of social network theory in many fields of engineering (electricity, gas, transport, water, etc.) allows both the understanding of networks and to improve their management. Social network theory coupled to the availability of real time data and big data analysis techniques can change drastically the traditional approaches to manage civil networks. Recently, some authors are working to apply this novel approach, based on social network theory, on the water distribution networks using: a) graph partitioning algorithms to define optimal district meter areas both for water losses identification and for water network protection, b) innovative topological, energy and hydraulic indices to analyze performance; and c) GIS (Geographical Information System) to provide a more effective display of results and to improve network behavior in specific operational conditions. In this paper, a novel release 3.5 of SWANP software, that implements all these features, was tested on a real large water network in Alcalá de Henares, Spain.
Abstract. Installing an efficient monitoring and control sensor system provides the possibility to carry out main tasks on Water Distribution Networks (WDNs) management and protection. Given the WDNs complexity, efficient numerical techniques are needed to support optimal monitoring system design. Generally, it is appropriate to locate sensors at highly connected places in the WDN with water flow reaching several parts of the network. This paper introduces a general method to support water utilities on the decision making process for an efficient water system monitoring. The proposal is based on graph spectral techniques that take advantage on spectrum properties of the adjacency matrix of the water distribution network graph. It is consequently created a novel tool-set of graph spectral techniques adapted to improve the water monitoring tasks and consequently simplify further sensor placement. This is approached with no need of hydraulic simulation, as data availability is often limited or not suitable to face anomaly events changing assets and distribution performance. A real water distribution network serving a town near to Naples is used to analyze the proposed graph spectral methodology. In order to test the proposed procedure, a comparison was made with a sensor layout obtained through a bi-objective optimization, through some performance indicators. The results confirm the effectiveness of the proposed spectral procedure.
Abstract. Due to the underlying characteristics of drought, monitoring of its spatio-temporal development is difficult. Last decades, drought monitoring have been increasingly developed, however, including its spatio-temporal dynamics is still a challenge. This study proposes a method to monitor drought by tracking its spatial extent. A methodology to build drought trajectories is introduced, which is put in the framework of machine learning (ML) for drought prediction. Steps for trajectories calculation are (1) spatial areas computation, (2) centroids localization, and (3) centroids linkage. The spatio- temporal analysis performed here follows the Contiguous Drought Area (CDA) analysis. The methodology is illustrated using grid data from the Standardized Precipitation Evaporation Index (SPEI) Global Drought Monitor over India (1901-2013), as an example. Results show regions where drought with considerable coverage tend to occur, and suggest possible concurrent routes. Tracks of six of the most severe reported droughts were analysed. In all of them, areas overlap considerably over time, which suggest that drought remains in the same region for a period of time. Years with the largest drought areas were 2000 and 2002, which coincide with documented information presented. Further research is under development to setup the ML model to predict the track of drought.
Abstract. A simple scaling model known as the fractional Gaussian noise is often chosen for the description of several annual (and of larger) scale hydroclimatic processes exhibiting the Hurst phenomenon. An important characteristic of such model is the induced large statistical bias, i.e. the deviation of a statistical characteristic (e.g. variance) from its theoretical discretized value. Most studies in literature perform stochastic modelling by equating the sampling second order dependence structure with the expected value of the estimator of a stochastic model. However, this is justified only when many realizations (i.e. many time series) of a single process are available. In case where we have a single realization we should model the mode estimator of the dependence structure of the desired stochastic model instead, otherwise we may overestimate the extremeness of a realization, e.g. flood event. In this study, we show an innovative way of handling the statistical bias for an fGn process when analyzing one time series. Particularly, we conduct a thorough Monte-Carlo analysis based on the climacogram (i.e., marginal distribution of a scaled process, with focus on the second central moment of variance that is shown to be the least uncertain from the rest central moments) of an fGn process and we propose to equate the 25% quartile (and not the expected) value of the modeled climacogram with the sampling one to correctly adjust the model for bias.
Abstract. Currently, in water supply engineering, the conventional technique of disinfection by chlorination is used to kill pathogenic microorganisms in raw water. However, chlorine reacts with organic compounds in water and generates disinfection byproducts (DBPs) such as trihalomethanes (THMs), haloacetic acids (HAAs) etc. These byproducts are of carcinogenic, teratogenic and mutagenic effects, which seriously threaten human health. Hydrodynamic cavitation is a novel technique of drinking water disinfection without DBPs. Turbulence structures of cavitating flow were observed by the Particle Image Velocimetry (PIV) technique in a self-developed hydrodynamic cavitation device due to square multi- orifice plates, including effects of orifice number and orifice layout on velocity distribution, turbulence intensity and Reynolds stress, which aimed at uncovering mechanism of killing pathogenic microorganisms by hydrodynamic cavitation.
Abstract. This study presents a new statistical downscaling method called Chaotic Statistical Downscaling (CSD). The method is based on three main steps: Phase space reconstruction for different time steps, identification of deterministic chaos and a general synchronization predictive model. The Bogotá river basin was used to test the methodology. Two sources of climatic information are downscaled: the first corresponds to 47 rainfall gauges stations (1970-2016, daily) and the second is derived from the information of the global climate model MPI-ESM-MR with a resolution of 1,875° x 1,875° daily resolution. These time series were used to reconstruct the phase space using the Method of Time-Delay. The Time-Delay method allows us to find the appropriate values of the time delay and the embedding dimension to capture the dynamics of the attractor. This information was used to calculate the exponents of Lyapunov, which shows the existence of deterministic chaos. Subsequently, a predictive model is created based on the general synchronization of two dynamical systems. Finally, the results obtained are compared with other statistical downscaling models for the Bogota River basin using different measures of error which show that the proposed method is able to reproduce reliable rainfall values (RMSE=73.37).
Abstract. Accurate estimates of precipitation are needed for many applications in hydrology as rainfall is one of the most influential variables of the water cycle. The common sources of information used to estimate rainfall fields are in situ rain gauges, remote sensing information and outputs from climate models. However, each of the above- mentioned sources has its own limitations, which can be reduced by blending information from these sources, in a product that takes advantage of the strengths of each dataset. In this research we study the double smoothing merging algorithm, creating a rainfall distributed product that combines remote sensed and reanalysis data, and information from a rain gauge network. The main objective of the study is to investigate the implications of varying the rain gauge density and configuration, on the merging parameters and global performance of the blended product. The results of a daily 3-year period experiment show that, although the errors in cross validation (CV) and against an independent dataset (IV) are in general low, the performance of the blended product and also the sensitivity of the parameters are highly influenced by the rain gauge configuration and density. The bandwidth merging parameters increase as the network density is artificially reduced.
Abstract. The world's urban population growth, indiscriminate use of fertilizers and chemical poisons are actually threatening groundwater resources. The main target of this paper has been tracking of distribution of a conservative tracer in a porous media and in a laboratory-scale model, to estimate the longitudinal and transverse dispersion coefficients. In this study non-cohesive sands were used to create the porous media body in the laboratory model with a grain diameter of 1-2.5 mm. Salt (NaCl) with concentrations of 5, 7.5 and 10 g/l were used as a tracer. The results of 5g/l concentration tests are reported in this paper. An EC-meter apparatus was used to measure the EC values of the tracer to monitor its plume migration. Then the collected and recorded EC data were used to calculate the tracer concentration data in different points over time, for each test. The calculated concentration data were compared with values which were obtained from the analytical solution using Fickian second law. According to the results, for instance, in the case of 5 g/l of the tracer, the obtained values of the longitudinal and transverse coefficients are equal to 3.36e-6 and 6.58e-7 m2/s, respectively.
Abstract. Water quality modelling studies are effective tools for the prediction of the impact of water quality improvement measures. This study aims to predict the future water quality of a nutrient-sensitive river basin assuming the implementation of water quality improvement measures by setting up and executing multiple models. The rationale behind the use of multiple models is the better suitability of each model for its relevant objective. Hydrodynamics of the river are simulated using the WASP model. Following the estimation of diffuse-source nutrient loadings in the river basin with the SWAT model, water quality of the river is simulated with a multi-segment Aquatox model. All models are calibrated to one year of observed data. Models are first executed to obtain the current water quality status and then to predict the water quality for the period of 2016-2040. For the future persion, it is assumed that measures are taken to reduce point-source and diffuse-source pollutant loadings. Model results suggest that load reductions are expected to be effective and that improvement in water quality can be predicted for all water quality indicators. TKN concentrations vary between 0.11-2.13 mg/l with the highest mean concentration occurring during the months of January. TP concentrations are expected to have a higher variability (0.032-0.65 mg/l).
Abstract. The Nile River is considered one of the most complex rivers in the world because of its transboundary nature and its significance for riparian countries. Currently, the basin experiences challenges stemming from a rapid population increase and the prospect of a significant economic growth, which in turn have sparked development plans aimed at meeting the growing demand for water, energy, and food. A System Dynamics approach provides a unique framework to integrate the physical system and the socio-economic drivers with the ability to capture the interaction and feedback processes between different system components. A water resources model for the entire Nile basin using the System Dynamics approach was developed as a first step. The model results for the flows at gauge locations showed a good agreement with the historical flows measurements, which reflects the SDM ability to capture the dynamic behaviour of the river and reproduce the patterns and trends of the historical flows. A description of the model development process is presented along with simulation results at the key hydrological sites in the basin. The potential to integrate the developed model with food, energy and socio-economic drivers in the basin is provided.
Abstract. A mixed variational-Monte Carlo scheme is employed to assimilate streamflow data at multiple locations in a distributed hydrologic model for flood forecasting purposes. The goal of this work is to assess the role of the spatial distribution of the assimilation points in terms of forecasts accuracy. The area of study is Arno river basin, and the strategy of investigation is to focus on one single nearly-flood event, performing various assimilation experiments that differ only in number and location of the assimilation sites.
Abstract. Water, land, food, energy, and climate are all interconnected, comprising a coherent system (the ‘Nexus’), dominated by complexity and feedback. The interactions between these different nexus components and their responses to climate change conditions are complicated as each feedback into the other. Consequently future policies should take into account the whole Nexus, when it comes to ascertain their long term impact on the system. This paper presents the conception of a System Dynamic Model (SDM) representing the Nexus, populating it with data from various sources (including output from specific thematic models covering different Nexus components), under different climate change and socioeconomic pathway scenarios. The SDM is then converted into R scripting to be included in the Knowledge Elicitation Engine (KEE) communicating with a Serious Game (SG). Models and games are built specifically for ten Case Studies, at regional, national, continental and global level. The SG is being developed for decision making for local stakeholders to study and get acquainted to long term impacts of different policies on the Nexus. In this paper the regional Case Study of Sardinia is presented as proof of concept.
Abstract. Flood risk analysis involves simulating many scenarios from which to draw statistical information about flood extent and depth. Rapid but still sufficiently accurate models enabling flooded areas to be delimited using a DEM have been introduced in the scientific literature. These models, called Rapid Flood Spreading Models (RFSMs), are based on highly simplifying hydraulic assumptions while make large use of GIS information and elaborations. Three different RFSMs are here applied to a test case, largely characterized by flat land. The results obtained are compared with those of a two-dimensional hydraulic model confirming the possibility of preliminarily elaborating topographic GIS data to easily gain geometric information on flooded areas through geospatial analysis.
Abstract. Places with limited coverage of rainfall gauges could present the challenge of providing accurate predictions, especially in cases of urbanised areas with rapid responses to heavy rainfall events. Physically-based models can represent the physics and spatial distribution of rainfall events in urban watersheds. Data assimilation techniques have been widely used in hydraulic and hydrological models to update model states and provide a more reliable prediction. However, model updating in case of non-linear systems is considerably complex. In this study, we present an approach to update an urban model assimilating water level values. The preliminary results of this study show a significant improvement in the results of simulations when assimilating water level observation. The methodology is applied in the city of São Carlos, in Brazil, where the urban system is modelled using SWMM.
Abstract. This work presents an algorithm for real-time fault detection in the SCADA system of a modern water supply system (WSS) in an Italian Alpine Valley. By means of both hardware and analytical redundancy, the proposed algorithm compares data and isolates faults on sensors through the residual analysis. Moreover, the algorithm performs a real- time selection of the most reliable measurements for the automated control of the WSS operations. A coupled model of the hydraulic and remote-control system was developed to test the effectiveness of the proposed algorithm. Simulations showed that error detection and measurement assessment are crucial for the safe operation of the WSS.
Abstract. During the last few years, the integrated real-time control (RTC) of both the urban sewer network and the wastewater treatment plants (WWTP), has attracted increasingly attention. In order to apply integrated RTC control approach efficiently considering both the hydraulic and quality variables, models, simplified conceptual quality modelling approaches are required. This paper presents research work based on simplified water quality models in sewers, which have been developed in the European project LIFE EFFIDRAIN (Efficient Integrated Real-time Control in Urban Drainage and Wastewater Treatment Plants for Environmental Protection). The contribution of this paper is to analyze the potential factors that would influence the performance of the proposed modelling approach and consequently the corresponding integrated RTC control. A real sewer pilot the Perinot sewer network has been used as case study. Results and conclusions have been provided which would be useful for the users of these models.
Abstract. When a network works in emergency conditions, due to a pipe failure, an appropriate management of the system is necessary. These events can cause a bad service for the users, because the pressure in some nodes of the network (critical nodes) decreases and the required demand is not guaranteed. In fact, a pipe failure causes the isolation of the intervention area, modifies the circulating flow along pipes and can produce a pressure reduction in some nodes.
In network management the aim is to increase the pressure, and consequently the flow rate delivered at critical nodes in order to minimize disruptions during the time between the failure and the repair.
In this paper, a methodology based on the nodal demand control is proposed. The nodal demand control proposed is possible by using control valves and by identifying the nodes where the control should be done. The control nodes can be chosen by using sensitivity matrices or an approach based on calibration techniques. A case study shows the results obtained with both methods for the real network of Praia a Mare in the South of Italy.
Abstract. An accurate mapping of gullies is important since they are still major contributors of sediment to streams. Mapping gullies in many areas is difficult because of the presence of dense canopy, which precludes the identification through aerial photogrammetry and other traditional remote sensing methods. Moreover, the wide spatial extent of some gullies makes their identification and characterization through field surveys a very large and expensive proposition.
This work aims to develop an object-based image analysis (OBIA) to detect and map gullies based on a set of rules and morphological characteristics retrieved by very high resolution (VHR) imagery. A one-meter resolution LiDAR Digital Elevation Model (DEM) is used to derive different morphometric indexes, which are combined, by using different segmentation and classification rules, to identify gullies. The tool has been calibrated using, as reference, the perimeters of two relatively large gullies that have been measured during a field survey in the Calhoun Critical Zone Observatory (CCZO) area in the Southeastern United States.
Abstract. Assembling all the data of weather, rainfall, hydrology, engineering, water logging and other real-time information and basic information of the Beijing, the flood forecasting coupling model with hydrological and hydrodynamic method and the operation model of gate and dam are constructed. Obeying object-oriented open design concept, Beijing flood control operation system based on B/S framework is developed, using Java language and database technology, which has achieved these functions that the analysis of flood control situation, flood forecast, flood control operation, flood simulation, evaluation of regulation results and scheduling management etc. At the same time, the mobile application client is developed by using html5 technology, with the functions of flood information query, mobile patrol and dangerous case report etc. All these can provide the decision-making basis for the integrated flood control management of Beijing city.
Abstract. Reservoir management usually considers short- to medium-term operation horizons. However, climate change and other longer term societal changes pose a challenge for planning water utilization from reservoirs. The key aspect is how to incentive behaviour change towards gradual adaptation. We propose an evolutionary approach to model adaptation, considering the Water Footprint as the main criterion for driving adaptation in long-term. The approach is tested in a case in Brazil, revealing promising preliminary results.
Abstract. A correct water demand characterization is at the base of a reliable water distribution system simulation. The stochastic nature of water demand is well established and thus has to be addressed. In the present work a methodology to generate synthetic demand patterns interpolating known points by means of piecewise interpolation has been implemented in Python. Subsequently a stochastic approach has been applied to the interpolated demand patterns, which is based on a mixed probability distribution. Such approach considers the dual nature of water demand as continuous and discrete random variable, in order to contemplate both the event of it being null and not null. The needed parameters are obtainable through simple equations depending solely on the number of served users.
Abstract. This study investigates the effect of two data-driven inflow prediction methods on the performance of a proposed adaptive real-time optimum reservoir operation model. The model consists of three modules; a forecasting module, which predicts the monthly future inflows, a reservoir operation optimization module, determining monthly optimum reservoir releases up to the end of a year, and an updating module, updating the current state of the system and provides the other two modules with the latest observed information on future inflows. K-nearest neighbor (KNN) and adaptive neuro- fuzzy inference system (ANFIS) approaches are used to forecast monthly inflows to the reservoir. The results demonstrate that ANFIS outperforms the KNN approach by 25, 23, 27 and 10 percent with respect to RMSE, PWRMSE, NSCE and correlation coefficient indices, respectively. However, the objective function values of the reservoir operation optimization model associated with each of those forecast models reveal that ANFIS-based adaptive reservoir operation model is only 5% better than the KNN-based model. This observation highlights the significance role of adaptation and updating procedure in the reduction of streamflow forecast errors.
Abstract. We focus on the operation of a real centre pivot irrigation system. The system encountered problems in 2016 and did not operate for several weeks due to the low level of the Danube (its water source). In that period, water level in the Danube went below the most probable minimal level during summer, with a return period of 30 years. With a natural desire to solve the problem, the owner of the system added a new pump near the water intake. This new, double-entry vertical axis pump, coupled in series with the existing pumping station situated further downstream, added roughly 1 bar to the pressure in the system. Things went well till the end of summer 2017 when, due to a pressure surge in the pumping station (most likely at shutoff head), one of the anti- vibration joints detached suddenly from the discharge pipe, and the pumping station was entirely flooded. The performed analysis helped understand the reasons of the accident and provided solutions (including pumping operating rules and schedule for pivots that can be operated simultaneously) that will hopefully avoid reoccurrences in the future, without affecting the day to day operation of the system.
Abstract. Groundwater is one of the major sources of fresh water. Maintenance and management of this vital resource is so important especially in arid and semi-arid regions. Reliable and accurate groundwater quality assessment is essential as a basic data for any groundwater management studies. The aim of this study is to compare the accuracy of two Artificial Neural Network (ANN) and Kriging methods in predicting chlorine in groundwater. In case of ANN, we created an appropriate emulator, which minimize the prediction error by changing the parameters of the neural network, including the number of layers. The best Kriging model is also obtained by changing the variogram function, such that the Gaussian variogram has the least error in interpolation of the amount of chlorine. To evaluate the accuracy of these two methods, the mean square error (MSE) and Coefficient of determination (R2) are used. The data set consists of the amount of chlorine, in a monthly basis, measured at 112 observation wells from 1999 to 2015 in aquifer Qazvin, Iran. MSE values for ANN and Kriging are 14.8 and 15.4, respectively, which indicate that the ANN has a better performance and is more capable of predicting chlorine values in comparison with Kriging.
Abstract. Critical Infrastructures (CIs) are commonly designed, built and maintained based on rigorous standards in order to withstand the climate and weather-related pressures. However, shifts in climate characteristics may result in increases of the magnitude and frequency of potential risks, or expose specific CI to new or increased risks not previously considered. As vital components of the normal functioning of modern societies, their resilience encompasses the operational elements, their structural integrity and the capacity to maximize business output under climate stressors. In this work, we propose an integrated and participatory methodological approach to assess the risk and enhance the resilience of interconnected CIs to urban flooding under climate change. The proposed methodology has been applied to the Torbay case study in the EU-CIRCLE project that is also presented in the paper.
Abstract. In this paper, we simulate overland flows using a cell-centred finite volume (CCFV) method with three solvers – HLLC, central-upwind, and artificial viscosity schemes – and present their parallel efficiency within the framework of our in-house code called NUF- SAW2D. The parallel efficiency is investigated through four explicit time stepping schemes – the first-order Euler and the second, third, and fourth-order Runge Kutta methods. The bed slope terms are solved using a Riemann-solver-free technique and the friction terms are treated semi-implicitly for all time stepping schemes, allowing our model to simulate wet-dry problems with very low water depths on very rough beds. A second-order spatial accuracy is achieved with the Monotonic Upstream-Centred Scheme for Conservation Laws (MUSCL) linear interpolation technique. Since our code is based on an edge-based data structure, the edge-based MinMod limiter function is used to enforce the monotonicity of reconstructed variables. Our code shows accurate results and achieves a good scalability for up to 3.2 million cells or 6.4 million edges using OpenMP parallelisation technique.
Abstract. Mechanical reliability refers to the assessment of the capacity of the water distribution network (WDN) to provide a correct service to the different type of costumers under abnormal operating conditions due to a failure of a system component. It depends on the effectiveness of the isolation valve system (IVS) and on the failure probability of components. Starting from the calculation of the actual customer demands during abnormal operating conditions of the hydraulic systems due to valve shutdowns and the failure probability of the separated segments, the work develops a metric for WDN reliability assessment. The finding is that the topologic part of WDN reliability assessment, relating to the IVS, is based on the risk of disconnection. Starting from it, the works develops a special modularity index for IVS reliability assessment.
Abstract. Water losses reduction in Water Distribution Systems (WDSs) is nowadays an issue of growing importance for water companies to ensure the economic sustainability of these public services. In this context, the implementation of District Metered Areas (DMAs) and/or pressure management are considered effective tools for leakage control, particularly in large networks and in systems with deteriorated infrastructures and with high pressure.
Based in previous studies performed by the authors (Gomes et al., 2012; Gomes et al., 2015; Sousa et al., 2015), the methodology described in this paper follows the ‘water losses management international best practices’ and makes it possible to evaluate the Net Present Value (NPV) of DMAs project, as well as the benefits that can be achieved by pressure management in WDS, particularly in terms of water production reduction. Leakage assessment is performed using the analysis of the minimum night flow and the FAVAD concept, and it uses a pressure driven simulation model to predict the network hydraulic behaviour under different pressure conditions. The optimal location of DMAs entry points, pipes reinforcement/replacement and locations/settings of the Pressure Reduction Valves (PRVs) are identified by a Simulated Annealing algorithm. The potential of this methodology is illustrated through an hypothetical case study.
Abstract. Two-dimensional flood models are becoming increasing more accurate in simulating surface water flooding. Concurrently flood hazard maps have higher resolution to support flood mitigation planning. Most flood studies focus on large river flooding (~ 100-yr flood), but in urban areas, emergency access and evacuation routes are needed for frequent rainfall and flood events (< 10-yr return periods). Urban flooding is more complex than river margin flooding and requires significantly more model detail to accurate access risk and hazard for frequent storms. Urban flooding is an event characterized by its frequent repetitive and systematic impact on population and urban infrastructure. Detailed urban flood inundation is now being performed with spatially and temporally variable rainfall and infiltration, channel and street flow, hydraulic structures, surface water storm drain exchange, building loss of storage and flow obstruction, building collapse, levee/wall overtopping and collapse, groundwater flow, sediment scour/deposition and mudflows. In residential neighborhoods, shallow flooding is controlled by streets, buildings, walls and storm drain facilities. Several flood model details and their impact on shallow flooding are discussed including spatially variable storm intensities on pervious and impervious surfaces, surface water exchange with limited storm drain system capacity, and building roof runoff. Several predictive strategies are highlighted to simulate flooding from nuisance flows to major disasters.
Abstract. Regarding to importance of modeling calibration, this study will be focused on probabilistic role of different strategies in calibration and verification steps. Tank lumped conceptual model was selected as a hydrological platform to investigate the effects of each optimization strategy on model performance.
However, much considerable efforts are required to calibrate a large number of parameters in conceptual models to obtain better results. With development of artificial intelligence, three probabilistic Global Search Algorithms (GSAs) including Shuffled Complex Evolution (SCE), Genetic Algorithm (GA) and Rosenbrock Multi-Start Search (RBN) and also three Objective Functions (OFs) consisted of Nash-Sutcliffe (NSE), Root Mean Square Error (RMSE) and mean absolute error (MAE) were employed for model calibration (comparing the performance of different GSAs versus OFs). The best set of parameters, which is derived from the calibration step, will be used as prediction coefficients for the model verification stage. Performance evaluation of the simulation results was undertaken using Coefficient of Correlation (r) and Descriptive Statistics.
Results indicated that all of optimization strategies have a relative ability to retrieve optimal values of eighteen parameters of the Tank model. However, the best GSAs for daily runoff simulation are SCE (0.871) and GA (0.864), respectively, for calibration and verification phases. In case of the OFs result, NSE (0.763) and RMSE (0.834) are more performant for calibration and verification of the model. Finally, the best strategy was selected by combining the results of GSAs and OFs models. Finally, SCE*MAE (0.906) and GA*RMSE (0.868) were selected as a top series.
Abstract. Management of water uses requests to harmonize demands and needs which are getting more complex and sophisticated. During the past 3 decades, modeling systems for hydrology, hydraulics and water quality have been used as stand alone products and were used in order to produce an analysis of a current situation and to generate forecast according to different horizons. The current situation requests an integration of the modeling tools into the information systems that are now dedicated to the global management of urban environments. Energy distribution, water distribution, solid wastes collection, traffic optimization are today major issues for cities that are looking for functional Decisions Supports Systems (DSSs) that may operate in a sustainable perspective. The basic requirement of real time assessment of the situation, the modeling systems identified as main elements of analytics and used for forecasts have to integrate a common framework allowing modular approach and interoperability. The paper presents the interest for a generic operational approach that could be implemented in order to address the management of water uses in a complex urban environment and to provide real time assessment and forecasts. The proposed approach is illustrated with application on Var catchment (3,000 km2) located in the French Riviera.
Abstract. Spatial analysis of rainfall extremes benefits of scientific advances and continuous data increments, that have led to the development of various methodologies in the last decades. In the field of the hydrologic design, due to technical, socio-economic and legislative factors, the availability of new methodologies does not imply the total substitution of the old, consolidated, procedures. This suggests that the hydrologic design is often supported by the opportunity to considering and comparing the results of estimates coming from different estimation methods. In this work, a tool named MultiRain is proposed, aimed at providing harmonized regional rainfall estimates for a given point and on areal basis. The software tool is based both on a QGis plugin and on a web-based WPS (Web Processing Service) procedure. Both the interfaces allow to build in a seamless way, from multiple models, the Intensity-Duration-Frequency (IDF) curves, either relative to a point or integrated over an area. The computation has been made automatic by manipulating old procedures lacking a map-based access. The procedures adopted for ensuring homogeneous comparison between the older ones and the more recent ones are described, with reference to three different methods and to their implementation over a 25,000km2 area in the North-West of Italy.
Abstract. The objective of this paper is to explain the importance of research in wastewater transportation (sewage systems) using new technologies such as robotics systems and information and communication technologies (ICTs). ECHORD++ (European Coordination Hub for Open Robotics Development) is a very useful tool to foster this research and to meet needs and solutions. In this paper, authors explain the tool as well as the methodology to promote robotics research in urban environments, and the on-going experience will demonstrate that huge advances are made in this field.
Abstract. Land use has significant impact on the hydrologic and hydraulic processes in a catchment. This work applies a hydrodynamic based numerical model to quantitatively investigate the land use effect on the flood patterns under various rainfall and terrain conditions in an ideal V-shaped catchment and a realistic catchment, indicating the land use could considerably affect the rainfall-flood process and such effect varies with the catchment terrain, land use scenario and the rainfall events. The rainfall-flood process is less sensitive for the side slope than the channel slope. For a channel slope lower than the critical value determined as 0.035-0.040 in this work, the forest located in the middle of the catchment slope could most effectively attenuate the flood peak. When the channel slope is higher than the critical one, forest located in the downstream of the catchment could most significantly mitigate the peak discharge. Moreover, the attenuation effect becomes more obvious as the rainfall becomes heavier. The research can help more reasonably guide the land use plan related to flood risk.
Abstract. Water resources management requires the integration of many complex physical processes, as well as the interaction of many stakeholders, to ensure the sustainable use of surface and groundwater resources. Water problems to which water authorities have to face are water deficit to supply a wide and increasing demand, floods, water pollution, leaks in water distribution infrastructures, and optimization in the energy use and production. A comprehensive and detailed analysis of the availability of water resources in terms of quantity and quality, and of water demand in their variability in space and time, is indispensable. In this context, SAID (SmArt water management with Integrated Decision support systems) project addresses the development, implementation, validation and integration of the most innovative DSSs as the basis for smart water management systems in complex basins. This paper focuses on the methodology carried out to integrate multipurpose aspects involved in the management of water resources in Guadalhorce River Basin (southern Spain), as a demonstrator area. As a support in the decision making process to dam managers, the resulting integrated DSS allows to execute predictive simulations to anticipate the watershed response, considering two types of scenarios (flood and ordinary), driven by different optimization criteria.
Abstract. Effective water resource planning is an important part of long term strategy for any water company. A good water resource plan will ensure a long-term balance between supply and demand. In this paper we present a scalable, repeatable and transparent model for finding efficient demand reduction solutions given a large number of demand reducing options and small planning regions. This model is being developed for application in UK water utilities for demand side water resource planning to aid results presented to Ofwat, the UK Water regulator, as part of multi-billion-pound long term investment plans. The flexibility and granularity of the approach has been shown to offer significant cost savings while still allowing a utility company to meet customer and stakeholder targets and Ofwat regulatory requirements.
Abstract. In Mexico, the regulatory framework does not obligate water utilities to report technical, administrative or financial information, nor are they required to have a management-indicator system to help them evaluate the service that they offer. In 2005 the Mexican Water Technology Institute (IMTA) started a voluntary participation program for tracking water utility management indicators (known as PIGOO for its Spanish initials) which has permitted participants to know what their own performance and evolution is. These results, however, do not represent what users think of the potable- water service so two additional studies were carried out to analyze the quality perception users have of their water-utility company. One permits the rating of the public image of the institution, that is to say, how a user is treated upon showing up in the offices to make a complaint or to file some procedure and another that evaluates the quality perception of the service that water utilities deliver to homes. These results will contribute towards identifying improvement areas in the service to users and the rating they give in turn, can help further the development and self-sustainability of water utilities.
Abstract. Significant energy resources are used for water supply in Jing-Jin-Ji region with the rapid urbanization and economy increase. Yet the interrelations between water and energy have not received adequate attention in the country. In order to fill this gap, this paper performs a regional-level quantitative assessment of electricity consumption on water produce (including water extraction, desalination and recycled water reuse), as well as analyzed carbon dioxide emission caused by energy used in 2015. The results show that total energy consumption for water supply amounts to 255.63 million kWh of electricity, and 0.27 million ton of carbon released in water supply progress. Due to the differences in water supply structure and water use amount, the energy consumption and carbon release of water supply in Hebei province is higher than Beijing and Tianjin city. Given increasing water supply demand, the implementation of the most stringent water management system may increase the energy consumption, and the trend of future climate change is not conducive to the conservation of water resources and energy in Jing-Jin-Ji region.
Abstract. Although artificial neural networks (ANN) is widely used for real-time flood prediction model, it is pointed out that the weak point of the model is poor applicability for the inexperienced magnitude of flood. In this study, the ANN models were applied to first-grade rivers in Japan, Tokoro River catchment and Abashiri River catchment. The training data of the ANN models were all the rainfall-runoff event which exceeded the Flood Watch Water Level during the period of 1998-2015. Types of observation data were river-stage and rainfall at 1-hour pitch. The validation data was the largest flood since the river-stage observation had started. The main component of the model was the four-layer feed-forward network. As a network training method, the deep learning based on the denoising autoencoder was applied. The output of the neural network was change in river-stage in T hours at the prediction point. The input data was the upstream river-stage, hourly change in river-stage and hourly rainfall. The river- stage prediction up to 6 hours showed very good accuracy, and It was proved that it can be nicely predicted even for the past largest flood.
Abstract. A decision support system for water management based on convex optimization, RTC-Tools 2, is applied for a water system containing river branches connected by weirs. The advantage of convex optimization is the ability of finding the global optimum, which makes the decision support system robust and deterministic. In this work the convex modeling of open water channels and weirs is presented. The decision support system is implemented for a river made of 12 river reaches divided by movable weirs. It is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds by controlling the weir heights. After this test the optimization can be applied to a realistic numerical model and model predictive control can be implemented.
Abstract. Change in climatic conditions worldwide has increased the frequency and severity of extreme hydrometeorological events (EHEs). Mexico is an example of this: the country has been affected by the occurrence of EHEs leading to important economic, social, and environmental losses. The objective of this investigation was to apply a Canadian Distributed Hydrological Model (DHM) to tropical conditions, and to evaluate its capacity to simulate flows in a basin in the central Gulf of Mexico. Additionally, we used this calibrated and validated DHM to predict streamflow before the occurence of an EHEs. The results of the DHM show satisfactory goodness-of-fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.41 and BIAS=-4.3), as well as its validation (NSE=0.775, RSR=0.4735 and BIAS=2.45). The DHM showed its applicability to streamflow simulation and confirmed a reliable efficiency in the modeling of thirteen EHEs (NSE=0.78 ± 0.13, RSR=0.46 ± 0.14, and PBIAS=-0.48 ± 7.5). DHM can serve as a tool to identify vulnerabilities before floods and assist in devising more rational and sustainable management of water resources.
Abstract. At the moment, it is generally accepted that global climate warming takes place. This process leads to increased precipitation in many regions, since warm air can contain more moisture and a higher temperature also accelerates the hydrological cycle, which should contribute to the increased precipitation and evaporation. Such hypothesis has to confirm for every region, since there are exceptions. Accordingly, the hypothesis checked in respect to precipitation of Moscow Meteorological station, which has observation during 135 years. It was defined, that precipitation amount of last decades is differed significantly from previous years, therefore, special method of Monte-Carlo was tested for precipitation simulation with discreteness of ten day periods according to data observations for the last 30 years, which represents more really today climatic situation. Such scenarios are needed for modeling of water reservoirs operation. The test results were enough satisfactory.
Abstract. The research is dedicated to estimation of soil moisture before storm rain flood for calculations of water erosion on the catchment. Modeling of hydrological properties of soils is used for characteristic of the soil moisture. The model based at technologies of multiple nonlinear regression, as well as the method of artificial neural networks.
Abstract. The research dedicated to modeling of flood mitigation on the river basin with help of simulation of flood control by virtual small water reservoirs located in different places of the river system. Such problem decided with help of modeling of flood hydrograph and its routing through water reservoir on the base GIS. Reducing the degree of flooding should occur due to the limited hydraulic flow capacity of the water flow by dam spillways without flood control by people. The offered model is represented on the example of concrete river basin. Results have showed relevance of the model for flood mitigation on the river basin.
Abstract. New technologies provide a new great source of information, increasing the available knowledge in many different fields, including hydrology. With this work we wish to share with the Hydroinformatics community an attempt in the direction of using the social media to increase the general understanding of the areas affected by flooding events in Italy. We have developed “Floodbook”, an online platform aimed at constituting a database for flood-damaged areas in Italy, trying to fill the knowledge gap of flood events occurring in small and ungauged basins. The platform invites citizens to contribute posting geotagged contents, photos or videos, on the social media; these contents are collected and elaborated to provide a clear, yet rigorous and comprehensive, picture of the event. Some case studies are described to show how this data collection can be used to improve flood extent assessment and flood dynamics reconstruction.
Abstract. Flooding is a phenomenon that endangers human being life and property. There are many structural and non-structural options that can be considered in order to reduce destructive effects of flooding. In this study, we propose a new methodology to enhance the performance of a real-time optimal operation model for flood mitigation in urban drainage systems. An online real-time model is developed as a simulation-optimization approach that leads to optimal operational policies based on the real-time rainfall information. Rainfall-runoff processes and hydraulic routing in the pipes are simulated by the EPA stormwater management model (SWMM) which is linked to the particle swarm optimization (PSO) algorithm, evaluating the system operation performance for assorted sets of operating policies. The initial solution in the real-time model is obtained by a long-term optimal operation model based on historical past flood events. The approach is validated by applying it to a portion of the urban drainage system in Tehran, the capital of Iran, consisting of a prototype network of pipes and detention reservoir equipped with controllable gates. Results show that the proposed strategy in introducing a reasonable initial solution to the real-time model can successfully enhance the performance of the model.
Abstract. The non-revenue water (NRW) is the water losses from unbilled authorized consumption, obvious losses and actual losses among the total amount of water supply (tap water supplied from water purification plants) in the water distribution systems. Various studies analyze data using statistical methods and identify the relationship as a method to estimate the NRW. For estimating the NRW of the water distribution systems, selected main parameters were used to this study. The main parameters were used to ANN model simulation, and compared to observed NRW data to determine the accuracy of NRW estimation. In the results, the method using artificial neural network was found to be more accurate in estimating the NRW than multiple regression analysis. In this study, the effective parameters of the NRW were determined, especially physical and operational parameters have high relationship to the NRW estimation.
Abstract. We hypothesized that groundwater flow could trigger earthquakes both in the land and in the sea due to its seasonal fluctuation following the wet season. Using 1,157 earthquake data recorded starting from 1978 to 2017 by Korea Meteorological Agency monthly earthquake energy and count of occurrence were analyzed to test the hypothesis. For the earthquakes occurred in the land a six-month earthquake active period from August to January was identified, which starts two months later from the beginning of the monsoon season (June-September). Meanwhile, for the earthquakes occurred in the sea another six-month earthquake active period from February to July, delayed by six months from that of the land, was also identified. These two-month and 8-month time lags between the active periods and the monsoon season seem to be attributable to the time required for groundwater to recharge aquifer, to propagate increased hydraulic pressure through fractures and to travel from the land to the sea. Monthly earthquake count and energy series seem to support the main shock- aftershock relation proposed by the hydroseismicity model but with longer and more variable time lags (i.e. one month for the sea and three to five months for the land) than those suggested by the hydroseismicity model. An excellent correlation of earthquake energy series which means almost perfectly synchronized activation of earthquakes between the land and the South Sea having the shortest travel path with steep slope among three seas seems to be the strong evidence supporting the hydroseismicity of earthquakes occurring in South Korea. Considering constant movement of tectonic plates which builds up intraplate stress relentlessly the cyclic burst of earthquake energy release supposed to be triggered by groundwater fluctuation seems to be playing the role of invisible hands which prevent excessive accumulation of geotectonic energy in the curst. From this point of view on- going climatic change that might bring about abnormal behavior of groundwater flow may change not only the pattern but also the magnitude of earthquakes occurring in South Korea in the future.
Abstract. China is an energy starved country that has faced a severe energy crisis for the last few decades. In response to China’s increasing dependence on non-renewable fuels, the Chinese government has discussed current and potential biomass energy resources as well as energy conversion and promotion policies. Bioethanol production has proven to be environmentally friendly and energy-efficient and is a potentially important source of renewable fuels. However, the uneven distribution of water and the implementation of the Three Red Lines water conservation policies may limit the development of bioethanol in China. From the perspective of water footprint (WF), this paper analyzes the water requirements of producing bioethanol from crop straws, and shows that water consumption in the bioethanol conversion stage is less than that in the crop growth stage; in other words, producing bioethanol from crop straws may be more water-efficient than that from grains or non-grain crop because water that would be consumed for grain growth is already being allocated to the agricultural sector. There is an abundance of crop straws of approximately 150.71 million tons that can be used for bio-ethanol production in China; if converted, 41.83 billion L ethanol would be produced annually, and an amount equal to 4 times China’s fuel ethanol production in 2014. According to a crop straws and water resource conditions, the provinces of Jilin, Shandong, Henan and Sichuan are the best for developing bioethanol from crop straws however, variations in the local availability of water resources and crop straws prevent us from drawing immediate conclusions about which crop straws would be most suitable for bioethanol production in China.
Abstract. Evolutionary algorithms have been used to optimize water systems in the literature for over three decades. However, their use for solving real-world water system problems in industry is still very limited. The work presented in this paper details the development of an interactive visualisation client for water distribution network design, which is part of a larger project to bring EAs closer to practicing engineers. The system aims at engaging engineers by actively involving them in the optimization process through the use of advanced visual analytics and novel interactive evolution techniques.
Abstract. In this work we present an application of coupled HEC RAS river model with NSGAII multi-objective optimization algorithm, for optimal operations of flood protection storage areas in the downstream part of Huai River in China. During flood, these storage areas are used for decreasing the flood water level downstream in order to protect the important, densely populated city of Bengbu. However, the same storage areas have also been used by local population, as both residential and agricultural zones, with high damage potential in case of flooding. The application investigates optimal operations of opening and closing the gates that connect the storage areas to the main river, which minimize the damage in the storage areas without compromising the protection of Bengbu. Two objectives are formulated related to: 1) downstream risk of flooding in Bengbu, and 2) damages in the storage areas. Decision variables are stage differences between the river and a given storage area, used for controlling gates operations (opening and closing). The coupling is performed in MATLAB using recently available HEC RAS API, known as HEC-RAS Controller. Initial results, obtained using flood hydrograph from the summer of 2007, indicate possible optimal operations, with selective usage of the storage areas.
Abstract. In order to accurately simulate physical phenomena, appropriate boundary conditions must be implemented. Where some information propagate along the characteristic curves as in the hyperbolic system such as shallow water equations (SWEs), open boundary conditions (OBCs) must be designed so that such an event should also be maintained even at the boundaries. In other words, OBCs of SWEs must pass information out of the domain and receive the incoming information without any numerical distortion. If OBCs do not reflect the characteristics of SWE, errors will occur and contaminate the information in the internal domain. This study compares several OBCs based on the hyperbolic characteristics of SWE and shows that OBCs derived using hyperbolic characteristic performs better in the several OBCs.
Abstract. Heavy rainfall can cause large variations in the water level of navigable waterways when a lot of urban runoff is generated on sealed surfaces and discharged into the river. Due to climate change, extreme weather events will increase in intensity and frequency demanding a better automated water level control at impounded waterways. High- resolution forecasts of catchment rainfall are intended to serve as input to a rainfall- runoff model. Based on the resulting discharge forecasts, a model predictive feed forward controller calculates the ideal water level and discharge across the barrage. The control system is completed by a PI control loop. In this way water level deviations and discharge peaks resulting from stormwater overflow events can be reduced, which enhances the safety of shipping. Regarding the uncertainties of weather predictions, the consequences of an underestimated or overestimated overflow discharge are investigated.
Abstract. A nonlinear autoregressive exogenous artificial neural network model was developed to predict turbidity response in two different trunk mains with measured flow and turbidity data. Models were initially established to prepare the data and automatically select the appropriate events for model training. Then, an autoregressive exogenous network model was developed and applied to predict turbidity responses based on past events in the time series. A per site continual data driven calculation of turbidity event risk was included as an additional input to capture the effect of temporal distance between the selected events as well as increasing the accuracy of the predictions. The calculated normalised mean square error and mean absolute error showed that the developed model combined with the data preparation and pre- processing models provides good regressions on a future event with a period of 7 to 10 hours for a multi-step ahead prediction. Furthermore, the result of the autoregressive exogenous network was compared with the output of a feed-forward network where the former significantly outperformed the latter (R value of approximately 0.97 compared to 0.66).
Abstract. This work outlines the use of wavelet bases to re-formulate a finite volume (FV) local solution of the shallow water equations (SWEs), so as to achieve mesh adaptivity via local compression and truncation of the numerical solution’s details across successive resolution scales with reference to a single threshold error set by the user. The wavelet bases naturally lead to a scalable FV formulation and how they can readily be exploited to achieve adaptive mesh-resolution selection: up-scaling and/or down- scaling by means of the local solutions’ data (i.e. both flow variables and terrain). Our results show a notable promise in using wavelets as a basis for future flood models to achieve conservative and more autonomous simulation at a wide range of length-scales.
Abstract. Having an efficient hydrometric network is important not only for successful water resources management but also for dealing with the economic cost of maintaining the network. One of the challenging tasks is to have a reliable dataset at candidate locations of additional monitoring stations. While many have applied regionalization methods, such as spatial interpolation, this study introduced a spatially distributed hydrologic model for generating data at potential locations. The determined optimal networks are compared with those from the use of spatial interpolation. The optimal networks are also evaluated using the outcome of transinformation analysis. The results showed that the optimal results using a spatially distributed model performed better than those using a spatial interpolation method.
Abstract. Using the Unity3d game engine, a Serious Game has been developed to explore different flooding scenarios under climate change in the town of Torbay in Devon, United Kingdom, and discover the resulting consequences on different critical infrastructures, aiming at enhancing their resilience. The system also sports a rather unique 3D navigable information board comprised of a virtual table populated with documents and interactive post-it notes introducing a compelling narrative.
Abstract. Using the Nvidia off-the-shelf particle based “Flex” simulation engine, we visualize the impact of rainfall over different sub-catchments on flooding in the village of Millbrook in the UK. Stakeholders are able to see what part of the catchment contributes most to which flooded area in the village. Hundreds of thousands of colored particles (balls), whose color is based on the quadrant of the catchment area, are dropped above the terrain and left to roll down while interacting with each other. The approach is similar to the ‘rolling ball’ method, which identifies natural flow pathways by rolling a ball down a digital elevation model, but uses multiple balls instead. Although the visualized results of our approach are of limited hydraulic accuracy, this type of visualization explains causality when analyzing the contribution of different portions of the terrain to the flooding from rainfall. This is possible due to colored deposits resembling well the final flood extent. Consequently, it is a useful technique for implementation in Serious Gaming, with flooding related themes, targeting in improving the understanding of stakeholders/players.
Abstract. In the hydraulic design practices, it is necessary to apply areal reduction factor to convert the point rainfall into the areal rainfall in the reference area. The fixed-area ARF (ARFf), which is commonly used, can be considered unrealistic because it is estimated through independent frequency analysis of the point rainfall and the areal rainfall. In this study, storm-centred ARF (ARFs) was estimated using radar rainfall data to reflect the spatial distribution characteristics of storm events effectively. ARFs representing the duration and the return period was extracted by 95% non-exceedance probability of the Weibull distribution to derive envelope covering all values from various storm events. ARFs has a correlation with not only the reference area but also the duration and the return period. Their relationships are defined as the scaling factors. A new ARFs equation that reflects the spatio-temporal characteristics of actual rainfall is presented.
Abstract. This study implemented the evaluation of Low Impact Development (LID) using SWMM-LID model developed by the U. S. Environmental Protection Agency (EPA), to assess the quantitative performance of LID facilities (seven type of LID facilities installed, vegetation place, plants garden pot, tree filter box, permeable pavement, infiltration ditch, rain barrel, infiltration rain-block). SWMM-LID modeling was useful to reflect the LID design into the model using the technical content representing LID facility in SWMM-LID. In the event-based result, the stormwater reduction was considerable since the reduction in average was 76.6% by the LID facilities. In the long- term result, the range of the reduction in average was 11.5~77.7% for seven types of LID facilities, and the average reduction for the total drainage area was 22.9%. The monthly reduction rate was affected by total rainfall depth and rainfall intensity.
Abstract. Where the physical and environmental characteristics of the coast and estuary change dramatically and complicatedly due to the multiple controlling sources as like as the tide, wave, river discharge, in order to collect the environmental data effectively and reliably, the locations of monitoring should be optimally determined with the standardized framework. The present study proposes a protocol to find the best monitoring location in a local bay based on a spatial and temporal optimizing method. With the simulation data from the accurately validated numerical model, the monitoring locations are designed with the constrained optimization method, which finds the optimal solution by constraining the objective function into the design space. The objective and constrained functions are determined from the objective analysis, which is combined with constrained optimization. Finally, those two functions are used to find the optimal solutions of the locations.
Abstract. This paper outlines the development of a novel, non-invasive microwave sensing system. A series of experimental investigations were undertaken to test the reliability of the sensors for determining the discharge in partially filled pipes under various hydraulic conditions.
Abstract. This paper presents a global sensitivity analysis study applied to a TELEMAC2D nu- merical flood forecast model of Gironde estuary which aims at identifying which input variables should be better described for water levels to be better simulated and forecasted. A variance sensitivity study (ANOVA) was carried out, by calculating Sobol’ indices for all numerical parameters (wind influence coefficient, Strickler friction coefficients for 4 zones) and time-dependent forcings of the model (rivers discharges and maritime boundary con- ditions). It led to the identification of parameters and forcings to which the model is most sensitive for each area of the estuary. Sobol’ indices for 2003 event show a predominance of the influence of the maritime boundary conditions and of Strickler coefficients all along the estuary. A mesh convergence study shows that the results don’t depend on the mesh. Moreover, a special focus on the eigenvalues of the tide signal correlation error function shows no predominance of one mode on the other. These first results are currently used to implement a sequential ensemble Kalman filter improving both the state of the system and the maritime boundary condition and optimizing the friction coefficients over the Gironde estuary.
Abstract. A new playful interface allowing a more intuitive understanding of real-life problems is the Serious Gaming, which combines video game and utility functions addressed to problems other than the mere entertainment. The use of Serious Gaming allows having fun while favoring the learning process related to specific technical fields. This paper presents the results of using Serious Gaming within a university classroom of 26 students to solve an engineering problem, i.e. the pipe sizing of several water distribution networks. It relates to five benchmark water distribution networks, and students were asked to find the optimal value of pipe diameters to match minimum capital cost of pipes and good average pressure. Therefore, the players/students can be seen as decision makers, from a real-life standpoint. The paper has multiple aims, such as investigating the gaming approach usefulness in consolidating/learning the main concepts of network hydraulics and bringing users closer to real-life complexity of engineering problems where different technical aspects must be considered at the same time.
Abstract. Using a reservoir is an effective solution to prevent lowland flooding and mitigate socio-economic damages. However, due to the high density of river network and the presence of reservoirs, dam safety assurance is becoming one of the most important mission in water resource management in Vietnam. Hydraulic characteristics of dam-break wave are necessary information to generate early warning plans for downstream area of reservoir. To aim this purpose, the Finite Volume Method with Godunov-type is considered to solve two-dimensional shallow water equations and develop a numerical model. In this study, the numerical model for dam-break simulation is suggested and verified through a comparison between calculated results and observed data of two reference tests. Very good agreement shows the effectiveness and accuracy of the proposed model. The Nam Chien reservoir in Vietnam has been chosen and the numerical model is applied to simulate flooding wave for the scenario of arch dam collapse. Alternative solutions are produced, such as: water depth, discharge hydrographs, arrival time, time to reach maximum water level; flooding map. The simulated result implies that this model is an indispensable tool for simulating dam-break scenarios.
Abstract. Achieving an optimised management of water supply infrastructures is a very important and challenging task, namely in urban environments. The identification and prediction of actual water consumption patterns can be exploited to improve the overall performance of water supply infrastructures. This work considers the application of pattern recognition techniques on water consumption time-series to quantify the time distribution of common consumption behaviours in urban environments. Three groups representing typical consumption patterns have been considered: one characterised by residual consumptions, which occur during the summer months of June and July, while the remaining two consist of significant consumption during the day, with differences taking place during night periods – the first group, more prevalent during warmer months, is represented by higher consumptions during the night, when compared with the second group, more representative of colder months, but showing also some expression all year round. Results also demonstrate that an automatic categorisation of urban water consumptions can be carried out along with the identification of specific time periods in which each pattern occurs.
Abstract. Water management is a complex problem that relates to human and physical variables that are very hard to predict, there is a cultural and social and human driven variables (Agricultural practices, Cities growth and others) that are hard to capture into the complex interactions of the water allocation and the hydrological system.
This research presents a new novel yet simple system that integrates information from river basin social and hydrological variables in an online system for decision support. The concept developed so far represents the Magdalena river system in Colombia, and allows to simulate and to share ideas. A communication bar includes a score of goodness provided by decision makers such that a level of agreement between actors can be achieved. Aside of this, the system is made open source such that other river basin can be set up and even other hydrological modelling systems can be plugged in.
Abstract. The objective of smart water management is to achieve water security at all levels (building, city and regional) in a sustainability and self- sufficiency manner, through the use of information technology, monitoring and control technology and the implementation of holistic system of all the processes in water cycle. It also provides the water utilties economic benefits through the reduction of non-revenue water losses through the detection of illegal connections and water theft. According to the characteristics of smart water, we proposed the following overall framework for a smart water city. In the proposed framework, there are seven main components which can be categorized into three main compartments. First is Hardware (Sensors and Sensors Adapters) which deals data acquisition, monitoring, conversion and transmission. The second component is Water Information System (Big Water Data Management and Analysis) which deals with data processing and storage. The third one is Software (Support Services and Applications), which deals with modelling and analytics, real- time monitoring and control system, decision support system and visualization and dissemination of information to stakeholders.
Abstract. The purpose of uncertainty propagation is the quantification of input data uncertainties on the output results. This involves understanding (i) how uncertainty is represented in the model structure and the input data ? (ii) how are uncertainties propagated in the model ? (iii) Which uncertainties affect mostly the model outputs ? The propagation analysis be- gins with the identification and characterization of the uncertainties of the input data. The aim of this work is to estimate the uncertainties pertaining the parameters of a 2D morphodynamic model so as to characterize the probability distribution P h(x, y, t) ≤ hcritical of the water depth h(x, y, t) over the Gironde Estuary, where hcritical is a critical threshold of the water depth h(x,y,t) that allows navigation. To handle this purpose, we propose an original approach that includes sediment parameters and bathymetry data, through the use of probabilistic methods, imprecise probability and non-linear regression. The pro- posed strategy offers flexibility to handle the variability of these data are also suitable for data-driven applications since the uncertainty quantification can also be conducted from a small set of parameters of the 2D morphodynamic model.
Abstract. This paper evaluates the effects of calibration data series length on the performance of a hydrological model in data-limited catchments where data are non-continuous and fragmental. Non-continuous calibration periods were used for more independent streamflow data for SIMHYD model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
Abstract. Rainfall monitoring networks provide fundamental input for hydrological models. Entropy, as a measure of uncertainty or information, is widely used in network evaluation or optimization. Computing entropy requires data discretization with methods like floor function, whereas the parameter selected is crucial and influential. This paper proposed an entropy based multicriterion method for evaluation of rainfall monitoring networks. Two indexes, separately account for information content and redundancy, were integrated with ideal point method. Values of the objective function were then computed to rank the stations and identify the significant ones. To find out the effect of discretization, parameter of the floor function was altered to get different schemes. A rainfall monitoring network containing 95 stations in the western Taihu Lake basin of China was analyzed as case study. Results showed that stations in the northern hilly area are more prominent in the network. Impact of the parameter in floor function is non-negligible as it determines entropy values, including its ranging scale and distribution pattern. Location of the stations rank extremely high and low also varies. As discretization process has an impact on the evaluation, it should be carefully used and sensitivity analysis is needed to avoid subjectivity and arbitrariness.
Abstract. This study performed a rationality analysis of the delay time and embedding dimension value during phase space reconstruction in hydrological series and the effect on their chaotic characteristics. Using a monthly average runoff time series from the Ayanqian station (upstream) and the Jiangqiao station (midstream) in the Nen River Basin, we reached the following regularity conclusions. 1 Based on the flood season (4 months) in the Nen River Basin, we can deduce that the correlation sequence length for the runoff is 4~5 months, i.e., the delay time =3 or 4 is a reasonable choice. 2 Learn from the predictability experiment results for the monthly rainfall time series, we know that the calculation results of the G-P algorithm for the dimension of runoff series for the Nen River Basin are reasonable, i.e., the embedding dimension is no more than seven. 3 the most suitable parameters for the phase space reconstruction and its chaotic characteristic index in the Nen River Basin are as follows: delay time = 3~4, embedding dimension = 6~7, correlation dimension = 2.90~3.00, maximum Lyapunov index = 0.24~0.32, and the forecast time is 3~4 months.
Abstract. Most of the existing drainage network models focus on capturing different flow regimes in sewer pipes. Despite being important to produce reliable results of urban flood simulation, the development of robust scheme to describe the coupled conditions at pipe-to-pipe intersections has received less research attention. In this work, the two-component pressure approach (TPA) is chosen to support pipe flow calculation due to its superior capability in simulating complicated transient flow between the free-surface and pressurized conditions in pipes. To avoid the complicated boundary conditions as required by a TPA model to approximate the junction connections, a novel strategy is proposed in this work where the flow at a junction is calculated using the 2D shallow water equations (SWEs). In junctions, irregular grids are created automatically according to the layout of connecting pipes, on which a first-order Godunov-type finite volume scheme is implemented to solve the 2D SWEs to simulate the junction flow. The 2D SWEs model is driven by the boundary conditions provided from the pipe calculations and rainfall input in necessary, which in turn creates boundary conditions for pipe calculations at the next time step. It is expected that the new approach as proposed will support large-scale drainage network modelling with higher efficiency and stability.
Abstract. Urban flood pre-warning decisions made upon urban flood modeling is crucial for human and property management in urban area. However, urbanization, changing environmental conditions and climate change are challenging urban sewer models for their adaptability. While hydraulic models are capable of making accurate flood predictions, they are less flexible and more computationally expensive compared with conceptual models, which are simpler and more efficient. In the era of exploding data availability and computing techniques, data-driven models are gaining popularity in urban flood modelling, but meanwhile suffer from data sparseness. To overcome this issue, a hybrid urban flood modeling approach is proposed in this study. It incorporates a conceptual model to account for the dominant sewer hydrological processes and a logistic regression model able to predict the probabilities of flooding on a sub-urban scale. This approach is demonstrated for a highly urbanized area in Antwerp, Belgium. After comparison with a 1D/0D hydrodynamic model, its ability is shown with promising results to make probabilistic flood predictions, regardless of rainfall types or seasonal variation. In addition, the model has higher tolerance on data input quality and is fully adaptive for real time applications.
Abstract. The rivers in Taiwan are steep, the surface runoff is rushed into ocean quickly with high speeds and large discharges. When the typhoons hit Taiwan with heavy rain, how to predict correct peak time and peak stage of rivers is the most important aim in this research. Taiwan Typhoon and Flood Research Institute will produce a rainfall forecasting every six hours for disaster warning, according to different physical parameters setting. The research site, Xiuguluan River is steepest one of Taiwan central rivers. By cross section data、land use、slope、soils and the rainfall forecasting, we can get results of each member by integrating the physically based on model HEC-HMS and WASH123D.
The research reveals that ensemble numerical modeling can predict precise peak stage of the river by analysis and correction by machine learning system TensorFlow. As for peak time forecasting, it becomes accurate by making use of the open social network information such as facebook、network news、PTT discussion to improve. Moreover, no matter peak time or peak stage, it has highly variation in members. In other words, no member is always the best of typhoons. But we can use the probability flood forecasting to predict and get the best results.
Abstract. Cyanobacteria blooms are a serious problem around the world and have caused severe ecological and social-economic damage. Data-mining models have proven effective at predicting such blooms; however, few of them can provide the spatial dynamics. Although process-based numerical models do provide a way to model, such approach often involves too many parameters to be calibrated. This study took the case of Taihu Lake and developed a model that embedded a data-mining technique into a cellular automata configuration, so as to obtain the spatial-temporal dynamics of cyanobacteria blooms. The lake was divided into polygons in accordance with the monitoring stations by using the Voronoi method. Data on flows, water quality and phytoplankton were collected from monitoring stations inside Taihu Lake. Genetic programming was applied to establish predictive formulations for the cyanobacteria population dynamics in relation to flow and water quality variables by using the collected data. The formulations accounted for local interactions between polygons as the evolution rules for the cellular automata. The results show that in this way CA models are able to predict both approximate magnitudes as well as accurate timing of cyanobacteria blooms quite well for all areas except for regions with lower cyanobacteria population. Overall the CA model shows very promising performance in capturing the spatial-temporal dynamics of algal abundance in lakes.
Abstract. Rapid urbanization has greatly increased the impermeable surface in urban area, which led to serious urban flooding and waterlogging in China. There are more than 100 cities that suffered from urban flood every year since 2006, and more than 100 million citizens are involved in China. Urban flood mitigation is one of the most important issues for both water administration and city management agency. This paper simulated the urban flooding in Xiamen Island based on a hydrodynamic model coupled with hydrological model. The datasets of underlying surfaces were input to the model, including the terrain data, building plan, land use, etc. A typical rain pattern of 50 years return event were used for flood simulation. The results show that the main inundated areas (flooded depth more than 40cm) are located in three groups: south east to the Yundang Lake, around the Hubian Reservoir, along the Exhibition Road. The other inundated areas that less than 40 cm deep are scattered in the flat regions of Xiamen Island. The main inundated areas simulated are consistent with the point survey of urban flooding, which verifies that the suggest model is reasonable and useful for urban flood prediction.
Abstract. As floods could be effectively forecasted by distributed hydrological model, their study and application became the key points of flood forecasting and early warning. Based on high performance computing clusters, a parallel flood forecasting and warning platform with the characteristics of partition, classification, and complicated process coupled was established to forecast and warn flood across China, especially for flash flood in China. In addition, the platform was based on China Flash Flood Hydrological Model (CNFF-HM). It used files (not MPI), which based on a shared hierarchical storage system, to pass message to control the start and stop of simulation processes, and the rapid communication among simulation processes was realized; pre-allocation and dynamic allocation methods was together applied to manage the resource of the high performance computing clusters; the automatic switch among different time scale models was realized by simulation driven strategy based on rainfall events; the reboot framework was designed to deal with the process crash and delayed rainfall data. The effectiveness and stability of the platform has been tested by the flood events of 2017. Finally, a case of Weishui catchment in Hunan Province was shown.
Abstract. Assessing the impacts of future changes in land use on the hydrological cycle is an important issue for the proper management of water resources, since land use changes have implications on both water quantity and quality. Land use changes, in particular the expansion of urban areas, can significantly affect river flow increasing flood risk, whereas, the development of woodland areas could have positive effects on the reduction of peak flow. The present study has been carried out to assess and quantify the impact of land use changes on the water resources of a river basin located in South West England. With this aim, a hydrological model has been applied to some land use scenarios. In particular, two scenarios have been investigated: the first includes the increase of agricultural areas and the decrease of woodlands, the second includes the increase of urban areas and the decrease of woodlands. Results showed that, in the area of study, river flow would likely to be affected by future land use changes, mainly in the case of urban areas increase.
Abstract. Many models have been proposed to simulate and understand the long-term evolution of meandering rivers. These models analyze the hydraulics of the in-channel flow and the river bank movement (erosion – accretion) process in different ways, but some gap still remain, e.g. the stability of long-term simulations when width variations are accounted for. Here we proposed a physics-statistical based approach to simulate the river bank evolution, that erosion and deposition processes act independently, with a specific shear stress threshold for each of them. In addition, we link the width evolution with a parametric probability distribution (PPD) based on a mean characteristic channel width. We are thus able to obtaining stable long-term simulations with realistic and reasonable spatio-temporal distribution of the along channel width.
Abstract. Road infrastructure networks are exposed to multiple damages caused by the occurrence of floods, generally, associated to hydrometeorological extreme phenomena. This can be attributed to the lack of drainage efficiency in the current designed hydraulic infrastructure. In order to renew the current methodologies for designing and improving the performance of road drainage, we proposed an approach that allows to revise the road drainage under current and future climate scenarios. For this, digital elevation information combined with a simplified shallow water equations model were used to reproduce the transversal flows to a highway located in the state of Oaxaca, Mexico. The drainage performance for both scenarios was tested along a set of identified critical points of the highway, and in those locations where hydrological design showed to be insufficient, adaptation measures were provided. This approach proved to be scalable and useful for identifying points where road drainage redesign or adaptation were needed and, to prioritize actions that minimize direct and indirect damages on roads.
Abstract. The climate change impacts leads to the raise of air temperature, which highly affected on the snow melting process in catchment hydrological system. In catchment water resources management, it gains more interests among local managers and hydrological researchers. In this study, based on the daily discharge (2008-2014) collected at the outlet of Var catchment, which located at French Mediterranean region, two flood periods were first identified during one hydrological year. For the flood occurred at spring time, the runoff produced by snow melting from upstream of the catchment has significant contribution to the flood discharge recorded at downstream. To assess the snow melting impacts in this catchment, a distributed deterministic hydrological model (MIKE SHE) was built to simulate the complex hydrological system in Var catchment from 2011 to 2013 with limited data collection. After calibrating the model with the observed discharge, the simulation of MIKE SHE were able to represent the hydrological process in Var catchment including the snow producing and melting process. The simulation results showed that the hypothesis made for the snow melting process, which not only considered the impacts of raise air temperature but also the sunshine intensity was reasonable and suitable to be applied in French Mediterranean region. The modelling approach described in this study could be beneficial to the assessment of snow melting process in the same region or similar watershed.
Abstract. During last decade, due to intensification of urbanization, connections between human and nature become more closed. Through hydro-informatics applications, such as hydrological or hydraulic model simulations, for local water managers, their knowledge and understanding of regional hydrological characteristics can be strongly improved. Among different kinds of hydrological models, the deterministic distributed hydrological model (MIKE SHE), shows obvious advantages in integrate representing multiple hydrological processes in catchment water cycle and producing more accuracy and detail results at any places on the simulation domain. This research is in project of AquaVar, which aims to create one model-based DSS in Var catchment at French Mediterranean Region. The main objective of this study is to build one deterministic distributed hydrological model through one optimized modelling strategy, which is able to overcome to problems caused by missing data, to well represent the complicated hydrological system in Var catchment. Based on a series of hydrological assessments and model testes, under reasonable hypothesized conditions, the model of MIKE SHE was calibrated from 2008 to 2011 and validated from 2011 to 2013 with daily time interval. With high statistical performance and can well presentation of the floods occurred during simulation period, the model results is able to be applied in AquaVar DSS for real time simulation and forecasting further scenarios. Besides, the modelling strategy conceived in this research can be also applied for building deterministic distributed hydrological models in other similar area.
Abstract. We have developed a versatile Model Predictive Control (MPC) framework, which can handle real-time control of a large variety of water systems. The framework combines a fast-solvable optimisation model (a quadratic program) with evaluation and realignment by a detailed hydrological-hydrodynamic model. The flexibility of the MPC framework is highlighted by two case studies: (1) a large-scale river system with several weeks of travel time, and (2) an urban storm and wastewater system with a concentration time of about half an hour to one hour. Both case studies demonstrate a large potential for improving operations by system-wide real-time optimisation.
Abstract. In the last decades, climate change is affecting several aspects of human and natural systems worldwide. Concerning water resources, the main impacts are related to the combined effect of temperature increase and changes in availability and distribution of precipitation, which affects both quantity and quality. The Mediterranean is potentially very sensitive to climate change. In Calabria (Southern Italy) the projected reduction suggests a particular care in matching water resource availability and needs. In this paper, the province of Crotone in Calabria was analyzed as a study case. This area is characterized by a sufficient availability of resources as a whole when compared with the needs of the users, but with an unbalanced distribution through its networks. This condition requires the identification of a resource allocation optimization solution. Using a least-cost optimization model, water resource optimization solutions were identified and compared starting from a review of the existing water supply systems, taking into account both current water availability and possible future availability due to climate change.
Abstract. Severe and sudden events like flash floods are considered to be one of the most hazardous environmental disasters. Therefore, predicting the whole process of flooding is fundamental to prevent urban damages. In this context, the simulation of flash floods is an important tool to analyse the flow processes in order to find solutions to the problem. In this work, a case study of the flash flood event of 9th March 2014 in the city of El Gouna in Egypt was carried out using the Hydroinformatics Modeling System (hms), a two-dimensional (2D) shallow water model developed at the Chair of Water Resources Management and Modeling of Hydrosystems, Technische Universität Berlin. The flooding processes are simulated in great detail on unstructured grids. The aim of this work is to investigate the flow field around the settlement of the study area, when structures such as storage basins and dams are adopted as protection measures for the city. Different scenarios are analyzed to find out the most suitable one, which is able to minimize the risk during the flash flood event.
Abstract. In many parts of our planet, salinity has caused numerous problems in the production of goods, especially in arid and semi-arid areas, which account for one third of the planet's surface area. The main purpose of this article is to investigate the NaCl’s adsorption to and desorption from saturated porous media of sand. The NaCl solutions with the concentrations of 2.5, 5 and 10 g/l, and three types of soil textures with the weights of 50, 100 and 200g were used as samples of the experiments. The samples were placed in capped containers. The salinity of the solutions was measured using an EC-metre at 1, 2, 4, 7 and 24 hours from the beginning of the experiment. The results indicated that in the soils with less weight, the adsorption of sodium ions were more, and as soil weight increased, the adsorption of ions decreased, and finally the adsorption phenomenon was departed. Over time, the process of adsorption and desalination eventually stopped.
Abstract. The aim of this paper is to introduce method of the robust reservoir performance evaluation under the climate change uncertainty. Water resources adaptation on climate change, drought management strategies as well as hydrological and reservoir modeling in the climate change uncertainty have been serious issues. Newly developed lumped water balance model and reservoir simulation model will be used. Based on these tools the approach of robust reservoir storage capacity reliability assessment will be introduced. The hydrological data under climate change will be constructed using the statistical downscaling tool LARS WG. Ensemble of 29 climate scenarios will be created. The hydrology analysis and the temporal reliability of reservoir storage capacity and its robustness assessment against the climate change uncertainty will be presented on the case study of the Vir I reservoir and Svratka river basin in the Czech Republic.
Abstract. The measurement and simulation of 2D free-surface shallow flows is carried out in this work. For the experimental study a 3D-sensing device (Microsoft Kinect) is used to measure both steady and transient water surface elevation fields with different flow characteristics. This procedure provides 640x480 px resolution water surface level point clouds with a frequency ranging from 8 Hz to 30 Hz. The experimental measurements are compared with 2D finite volume simulations carried out by means of a robust and well-balanced numerical scheme able to deal with flow regime transitions and wet/dry fronts. A good agreement is found between experimental and numerical results for all the cases studied, demonstrating the capability of the RGB-D sensor to capture the water free-surface position accurately. This new experimental technique, which allows us to obtain 2D water depth fields in open- channel flows, leads to a wide range of promising capabilities in order to validate new shallow water models and to improve their accuracy and performance.
Abstract. Increased drought risk in Southern Europe is expected due to changing rainfall patterns and increasing evapotranspiration. Water availability is crucial in semi-arid Mediterranean countries, where irrigation is essential for crop production.
In this work, irrigated agriculture vulnerability of three Sardinian irrigation districts and their associated reservoirs is assessed. The simultaneous impact of climate change on water inflow to the reservoir, open surface evaporation, and water supply is evaluated and then integrated into indicators. Vulnerability Index is calculated to define future reservoir adequacy in guaranteeing irrigated crops. The analysis is conducted by comparing the baseline (1976-2005) with the future (2036-2065) climate under RCP 4.5 and 8.5. The Simulation of Evapotranspiration of Applied Water model is incorporated into a GIS platform to compute crop irrigation demand. Changes in water inflow to reservoirs and evaporation losses are estimated. Results show a decreasing resilience and increasing vulnerability of irrigated agriculture under climate change in each case study. The highest resilience is estimated in Monte Pranu and Stretta di Calamaiu reservoir while the highest vulnerability in the Cuga-Alto Temo system. Climate change may only partially affect irrigation in resilient systems, where storage capacity and water entering into the reservoir is higher than water outflow.
Abstract. Nitrous oxide (N2O), a greenhouse gas with a significant global warming potential, can be produced during the biological nutrient removal in wastewater treatment plants (WWTPs). N2O modelling under dynamic conditions is of vital importance for its mitigation. Following the activated sludge models (ASM) layout, an ASM-type model was developed considering three biological N2O production pathways for a municipal anaerobic/anoxic/aerobic (A2/O) WWTP performing chemical oxygen demand, nitrogen and phosphorus removal. Precisely, the N2O production pathways included were: nitrifier denitrification, hydroxylamine oxidation, and heterotrophic denitrification, with the first two linked to the ammonia oxidizing bacteria (AOB) activity. A stripping effectivity (SE) factor was used to mark the non-ideality of the stripping modelling. With the dissolved oxygen (DO) in the aerobic compartment ranging from 1.8 to 2.5 mg L-1, partial nitrification and high N2O production via nitrifier denitrification occurred. Therefore, low aeration strategies can effectively lead to a low overall carbon footprint only if complete nitrification is guaranteed. After suddenly increasing the influent ammonium load, the AOB had a greater growth compared to the NOB. N2O hotspot was again nitrifier denitrification. Especially under concurring partial nitrification and high stripping (i.e. combination of low DO and high SEs), the highest N2O emission factors were noted.
Abstract. Decision-making processes for integrated wastewater management plans require the support of cost accounting and management techniques. This is particularly challenging in the Kidron – Wadi an-Nar basin, whose river is currently an open sewer and plans need to account for water stress, complex topography and socio-political differences. For these reasons, plans suggesting large centralised treatment facilities are difficult to implement. A potential solution, that can partially alleviate the problem, is the use of a number of smaller decentralised treatment facilities. The question that arises is, how to optimally configure combinations of centralised and decentralised wastewater treatment plants to achieve proper sanitation coverage in the basin and a sound water reuse? This study suggests a step forward towards solving the problem using a multi-objective optimisation framework. The objective functions considered are based on a Cost-Benefit analysis and the assessment of different wastewater treatment configurations. Sets of Pareto-optimal combinations of centralised and decentralised wastewater treatment solutions have been generated and evaluated in terms of the objective functions. The evaluation and comparison of wastewater treatment configurations include the potential reuses of the treated water. This analysis is especially essential in arid regions where limited water resources require an integrated and efficient water allocation.
Abstract. A mathematical optimization procedure is presented to group multiple hydrographs into a small number of clusters for the purpose of helping to understand various runoff behaviors observed in flood events in a basin. In grouping, the hydrographs belonging to each cluster can be estimated within the specified accuracy by the corresponding parameter set. The effectiveness is demonstrated using twenty-seven hydrographs observed in nine flood events and at three water level stations in the Abe River basin in Japan. The optimization results illustrate that eight sets of parameters are necessary to estimate such hydrographs within the specified accuracy. One parameter set commonly estimates as many as seven out of twenty-seven hydrographs while some other parameter sets estimate the other hydrographs with different characteristics specific to flood events or water level stations. Most of the previous research is based on continuous optimization; however, a presenting procedure such as clustering is based on combinatorial optimization. Thus, new insight into understanding the runoff behaviors is brought by combinatorial optimization which is not often used in previous research.
Abstract. An important aspect in hydrological modelling is the accurate quantification and prediction of rainfall. In ungauged or poorly gauged basins ground data is sparse and often is complemented by rainfall satellite products, which brings additional uncertainties. The main objective of this research is to assess performance of distributed hydrological models using the remotely sensed rainfall estimates as forcings for the model. The model, based is based on the conceptual HBV-96 model and the PCRaster framework, is implemented for the Brahmaputra basin. Three different remote sensed datasets of precipitation (MSWEP, TMPA and PERSIANN-CDR) are used. Simple fusion methods are used to combine models results generate by the dataset of precipitation. The preliminary results of this study show that better model results are achieved merging the output results. Using MSWEP and TMPA as the forcing data provides satisfactory model results. On the other hand, use of PERSIANN-CDR leads to better prediction of flow peaks but overestimations of the hydrographs’ falling limbs.
Abstract. Besides climate change, human activities may introduce variability in the flow regime. Thus, investigation of the impacts of climate change and human activity on hydrology recently has become an important issue. In this paper hydrological data of six catchments in the coastal area of the Adriatic sea, in central Italy, were used to detect statistically significant trends and change points in annual rainfall and streamflow. Moreover, potential changes in precipitation-runoff relationship have been investigated and finally a quantitative evaluation of the effect of climate variability and human activities on runoff has been assessed separately, with the former individuated as the more influent.
Abstract. In this paper the results of field and numerical experiments executed in a real transmission main are presented and discussed. Pressure waves injected into the pipe are generated by means of two quite different methodologies: pump shutdown and the Portable Pressure Wave Maker (PPWM) device.
Abstract. This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Urban Drainage and Sanitation Systems (UDSSs) which was proposed in the LIFE EFFIDRAIN project. This project deals with the pollution of surface waters due to CSOs and overflows from UDSSs during wet weather. The main purpose of the proposed FTC framework is to preserve as much as possible, the performance of the MPC-based Controller in terms of operation objectives when anomalies affecting the integrated ICT elements (sensors and actuators) occurs. The performance of the FTC controller has been tested using a realistic case of study.
Abstract. This study details a procedure to derive high resolution snow cover information using low-cost autonomous cameras. Images from time lapse photography of target areas are used to obtain temporally resolved binary snow-covered area information. Various image processing steps, such as distortion correction, alignment, projection using the Digital Elevation Model (DEM), and classification using clustering are described. Several innovations, such as matching the mountain silhouette with the DEM, and application of specific filters are described to make this terrestrial remote sensing method generally applicable to derive valuable snow information.
Abstract. Recent advancements in precipitation observation technology make it possible to precisely describe the intensity and temporal-spatial distribution of heavy rainfall, which can cause severe floods and inundations. Such technologies have also increased the accuracy of flood forecasting. However, error factors in flood forecasting remain to be solved, originating in not only input data but also model structure and calibration. Thus, this study focused on convergence results of errors in parameter optimization of the PWRI Distributed Hydrological Model and the reproducibility of river discharge. The reliability of ground-gauge and C-band-radar rainfall is compared in terms of flood forecasting under the condition of the minimum error due to calibration. Although the convergence results showed that C-band radar rainfall was superior to ground gauge rainfall, both were equally effective in reproducing river discharge with a high NSE of 0.9 at a station with error assessment. On the other hand, the reproducibility of river discharge with C-band radar data was highly superior to that with ground gauge data at a station without error assessment. This indicates that grid-based high resolution rainfall data is necessary for basin-wide flood forecasting.
Abstract. It is acknowledged that spatial variations in the DSD and type of rainfall are important for an adequate rainfall estimation using operational weather radars. However, due to a lack of instrumentation, the Z-R relationship is rarely considered spatially variable. This relationship is usually applied unawarely of the scale, which is questionable since the nonlinearity of this relation could lead to undesirable discrepancies when combined with scale aggregation. This paper investigates different methods to define an adequate Z–R law relation for a study region, where a spatial variation of coefficients and rain type may be considered. For this, we utilize data from a disdrometers network and a C-band radar located in Mexico City. Coefficients of the Z-R law are obtained through: the definition of the Z-R relationship at each disdrometer and the use of three methods (dBZ, R and Do/R) for the data classification by rain type (ST, T, C). Results show that the coefficients for the Z-R law are very diverse and strongly dependent on the rain type. Regarding radar data, the evaluation indicates that the values do not correspond quantitatively to those recorded on the earth’s surface, but it can represent the variances in most of the period.
Abstract. Despite the continuous increase in water supply from desalination plants in the UAE, groundwater remains the major source of fresh water satisfying domestic and agricultural demands. Additionally, groundwater has always been considered as a strategic water source towards groundwater security in the country. Quantification of groundwater recharge is a prerequisite for efficient and sustainable groundwater resources management in arid regions. Therefore, groundwater recharge from the ephemeral Wadi beds and subsurface flow from mountainous valley beds play an important role in water management. Although, both surface and groundwater resources in UAE are scarce; the anticipated climate change impacts could make these resources even scarcer. As such, the main aim of this paper is to assess the potential impacts of future climate variability and change on groundwater recharge in the eastern region of UAE. This paper will explore rainfall characteristics in the region, their projections and their impacts on Wadi hydrology and groundwater recharge processes. Another objective of the study is to identify groundwater recharge regions to the shallow unconfined groundwater aquifer in the northeastern part of Abu-Dhabi Emirate. Outcomes of this study will help to accurately estimate current and future sustainable extraction rates, assess groundwater availability, and identify pathways and velocity of groundwater flow as crucial information for determining the best locations for artificial recharge.
Abstract. Dubai is a rapidly urbanizing emirate with land development succeeding at a fast pace. The present study aims to develop a low-cost classifier based on the spectral angle mapper (SAM) and image difference (ID) algorithms. The proposed approach was developed in order to improve Land use/ Land cover (LULC) classification maps for the purpose of monitoring and analysing LULC change during the period from 2000 to 2015 for the Emirate of Dubai. The approach starts by collecting 320 training samples from high resolution images such as QuickBird with a spatial resolution of 60 cm followed by applying a 3×3 spatial convulsion filter, majority/ minority analysis, sieving classes and clump map of the produced LULC maps. After that, the accuracy of the maps were assigned using confusion matrix. The accuracy assessment demonstrated that the targeted 2000, 2005,2010 and 2015 LULC maps have 88.125%, 89.069%, 90.122% and 96.096% accuracy, respectively. The results exhibited that the built-up areas increased by 233.72 km2 (5.81%) from 2000 to 2005 and keeps to increase even up and till the present time. The results also showed that the changes in the periods 2000-2005 and 2010-2015 confirmed that net vegetation area loses were more obvious from 2005 to 2005 than from 2010 to 2015, reducing from 47.618 km2 to 40,820 km2, respectively. This study is of great help to urban planners and decision makers.
Abstract. A large-eddy simulation over a fully submerged, rigid canopy in an open-channel flow under transitional canopy flow regime has been carried out. The simulations revealed a flow structure characterized by the emergence of coherent structures, which are very elongated in the streamwise direction occupying a large portion of the flow inside and outside the canopy. These very large structures have a strong impact on the flow inside the canopy as well.
Abstract. One dimensional (1D) shallow water models are widely used for prediction purposes to assess and help river basin administrations and public authorities in the decision-making process. However, their results can be inaccurate since the hypotheses underlying the 1D model are not satisfied during flooding events. On the other hand, two-dimensional (2D) models offer more information to follow the inundation process and the flow properties over floodplains. Despite the well- known higher computational cost of 2D models, they have gained popularity since they can be implemented under GPU cards that allow faster computations, providing more information than 1D models. In this work, two flooding events in the Ebro River (Spain) are analyzed to evaluate the performance of both 1D and 2D shallow water models.
Abstract. Due to advancements in instrumentation and communication technologies, monitoring of water infrastructure is experiencing a significant growth worldwide and water managers are increasingly deploying monitoring equipment for decision-making purposes. Hydrological events and relevant datasets including rainfall data are of a complex nature and are potentially susceptible to errors from various sources. Hence, it is essential to develop efficient methods for the quality control of the acquired data. The present work introduces an artificial neural network-based approach for real-time quality control and infilling of rain gauge data. Available rainfall measurements from neighboring rain gauges are employed to train and develop the neural network model. Trained artificial neural network model was able to validate up to about 97% of the data using 95% confidence intervals. This finding suggests that artificial neural networks can be successfully implemented for erroneous data identification/correction and reconstruction of missing data points. Given its short processing time and reportedly superior performance to traditional quality control strategies, neural network methodology can be deployed as an efficient tool for the processing and control of large sets of timeseries with complex natures including precipitation data.
Abstract. We investigate the real-time and autonomous operation of a 12 km2 urban storm water network, which has been retrofitted with sensors and control valves. Specifically, we evaluate reinforcement learning, a technique rooted in deep learning, as a system-level control methodology. The controller opens and closes valves in the system, which enhances the performance in the storm water network by coordinating the discharges amongst spatially distributed storm water assets (i.e. detention basins and wetlands). A reinforcement learning control algorithm is implemented to control the storm water network across an urban watershed. Results show that control of valves using reinforcement learning shows great potential, but extensive research still needs to be conducted to develop a fundamental understanding of control robustness. We specifically discuss the role and importance of the reward function (i.e. heuristic control objective), which guides the autonomous controller towards achieving the desired water shed scale response.
Abstract. Water distribution networks (WDNs) must be reliable infrastructures since they provide an essential service to society. Reliability assessment is a complex task and involves various aspects: mechanical, hydraulic, water quality, water safety, among others. This paper focuses on the hydraulic reliability. Hydraulic reliability is computationally hard to measure directly, therefore researchers came up with surrogate measures, like the resilience index, the modified resilience index, the flow entropy or the diameter-sensitive flow entropy, that are simple and fast to compute. But, are these surrogate measures reliable to be used in the design of WDNs?
This paper proposes a new reliability index based on the surplus flow available on each node to mitigate the effects of a pipe failure. To illustrate the applicability of this new index, a WDN example is optimally designed using a simulated annealing algorithm. Results show that the solutions based on the flow entropy or on the proposed index are more reliable than the others, and, also, the maximization of the other reliability indexes gives only a residual contribution to the global reliability (or even no contribution at all).
Abstract. Water companies all over the world regularly perform inspections of their sewer networks. The data collected this way is then analysed by human technician which is time consuming and expensive. Previous work by the authors has developed methodology that can automatically detect faults in sewer pipes using standard CCTV footage. This paper presents a methodology to automatically identify types of detected faults aiming to further improve the efficiency and accuracy (i.e. consistency) of surveys. The methodology calculates a feature descriptor for individual frames of CCTV footage, before predicting the contents using a multi-class Random Forest classifier. Demonstrated on a comprehensive library of frames extracted from real-life CCTV footage of a UK water company, the methodology correctly identified the fault type in 71% of frames. Most common fault types were included in this experiment, covering a wide range of pipe sizes and materials, including vitrified clay, PVC and brick. Overall, this preliminary work shows promise for application in industry, proving an effective tool for analysing CCTV surveys.
Abstract. In recent years, flood damage caused by flash floods in mountainous rivers has been frequently reported in Japan. In order to ensure a sufficient lead time for safe evacuation, it is necessary to predict river water levels in real time utilizing a hydrological model. In this study, we conducted flood prediction using the RRI model and rainfall forecasted for the next 6 hours in the Kagetsu River basin (136.1 km2) in July 2017, evaluated the uncertainty regarding the prediction, and illustrated the results using a box-plot. The evaluation found that the mean error of the forecasted water level was approximately - 0.3 m in the prediction for the initial 3 hours and -0.97 m at the 6th hour. Also, the study investigated the possibility of correcting water levels forecasted by clarifying an uncertainty distribution. As a result, the water level forecasted was found to be underestimated because it was predicted to rise as high as Warning Level 2, while the water level forecasted with bias correction was predicted to reach Warning Level 4. Moreover, the lead time was estimated to prolong by 2 hours. Overall, the study suggested that flood forecasting can be improved by considering the uncertainty involved in prediction.
Abstract. Flooding of coastal areas can be caused by a number of contributing factors: high river flows, high tides, storm surges or a combination thereof. This paper presents results of a numerical modelling investigation of the role of river flow in flooding of Cork City. The Cork City urban flood model was developed by dynamically linking a storm surge model of the northeast Atlantic with the multi-scale nested flood model, MSN_Flood, which uses nesting to telescope down from 90m resolution in Cork Harbour to 2m resolution in the city streets. LiDAR data was used to create the urban flood plain. The model is used to hindcast the 2009 major flood event and is shown to accurately recreate the flood levels and extents. The model is then used to investigate the contributions of river flows to flooding in the city by simulating a range of peak flow scenarios combined with spring and neap tidal conditions. It is shown that flooding is relatively minor for peak flows less than 300 m3/s, while peak flows in excess of 500 m3/s result in extensive flooding of the city centre regardless of tidal condition.
Abstract. The Kelvin-Helmholtz instability promotes the appearance of complex turbulent flow patterns which typically arise in presence of shear layers. Such condition evolves linear perturbations into complex turbulent structures that determine the mass exchange across the different jets/layers in the flow. In order to accurately predict the mass exchange across a shear layer in shallow flows over complex bathymetries, very high order numerical schemes are required. In this work, a WENO-ADER Augmented scheme, called ARL-ADER method, is used to provide accurate predictions of mass exchange processes under a variety of 2D scenarios involving turbulent shear layers. The proposed scheme is assessed in terms of numerical diffusion by means of the analysis of the numerical energy cascade. Numerical results show that the diffusivity of the scheme determines the turbulent structures produced along the shear layer. It is shown that traditional 1-st order schemes are very diffusive and would require the use of very fine meshes, which is computationally inefficient. On the other hand, the ARL- ADER scheme is able to capture the small-scale vortices and reproduce the theoretical energy cascade even in coarse meshes, while preserving the well-balanced property.
Abstract. There is no need for further augment about the performance of numerical model in representing the hydraulic flow regime. Even if the mathematics and computer science have obtained many considerable progresses, there have not been yet uptil now a numerical solution that is considered comprehensively and perfectly the fluid mechanics due to its complication. Therefore, lot of numerical schemes have been developed relied on different approaches: Advection schemes, diffusion schemes, turbulence models. Model appropriate selection is considered as a key factor to sovle successfully a real problem. With the aims of evaluating the impact of different numerical schemes, this study uses TELEMAC 3D model, a product of EDF, to simulate the hydraulic regime in river. Relying on the advection schemes and turbulence models, five scenarios are organized in TELEMAC 3D for representing the hydraulic flow in a segment of the Waal, Netherlands. The modeling result is compared with the research of Mohamed F.M Yossef and Huid J. de Vriend (2011) in aspect of horizontal velocity distribution, vertical velocity distribution, flow stage. The comparison shows that there is a significant uncertainty in using different numerical schemes for flow stage modeling. The paper is expected to provide an insight view about using the computational model for hydraulic research and to be useful for studying the dynamics of flow stage by hydrodynamics simulation.
Abstract. Artificial reservoir operation is expected to affect significantly the flood disaster. It becomes more complicatedly towards the large systems where the operation of each reservoir has to meet fully with the systematic objective. Consequently, reservoir operation optimization is considered as a key factor to control the flood disaster at downstream area. Due to energy demand, more than twenty hydropower plants have been constructed over 10,350 km2 of Vu Gia Thu Bon river catchments. The system has contributed importantly for economy development when provides annually a green electrical quantity up to 6 Terawatt-hour (TWh). Therefore, operation of system has still several limitations. It is judged to make the natural disaster increase in recent years. In order to reduce negative impacts of artificial reservoir system, four largest reservoirs are selected to simulate in this study. The simulation is carried out via Structure Control (SO) module of MIKE 11 model (DHI). The performance of operational scenario is demonstrated via the relation with the water level at two stations. The study is expected to provide an overview of the impact of artificial reservoir operation to flood disasters, as well as propose a new strategy to operate optimally the hydropower plants in Vu Gia Thu Bon catchments.
Abstract. Statistical models based on the scale-invariance (or scaling) concept has increasingly become an essential tool for modeling extreme rainfall processes over a wide range of time scales. In particular, in the context of climate change these scaling models can be used to describe the linkages between the distributions of sub-daily extreme rainfalls (ERs) and the distribution of daily ERs that is commonly provided by global or regional climate simulations. Furthermore, the Generalized Logistic distribution (GLO) has been recommended in UK for modeling of extreme hydrologic variables. Therefore, the main objective of the present study is to propose a scaling GLO model for modeling ER processes over different time scales. The feasibility and accuracy of this model were assessed using ER data from a network of 21 raingages located in Ontario, Canada. Results of this assessment based on different statistical criteria have indicated the comparable performance of the proposed scaling GLO model as compared to other popular models in practice. Furthermore, an illustrative application of the proposed model for evaluating the climate change impacts on the ERs in Ontario using the available NASA downscaled regional climate simulations has demonstrated the accuracy and robustness of the GLO model.
Abstract. This paper proposes an efficient spatio-temporal statistical downscaling approach for estimating IDF relations at an ungauged site using daily rainfalls downscaled from global climate model (GCM) outputs. More specifically, the proposed approach involves two steps: (1) a spatial downscaling using scaling factors to transfer the daily downscaled GCM extreme rainfall projections at a regional scale to a given ungauged site and (2) a temporal downscaling using the scale-invariance GEV model to derive the distribution of sub-daily extreme rainfalls from downscaled daily rainfalls at the same location. The feasibility and accuracy of the proposed approach were evaluated based on the climate simulation outputs from 21 GCMs that have been downscaled by NASA to a regional 25-km scale for two different RCP 4.5 and 8.5 scenarios and the observed extreme rainfall data available from a network of 15 raingauges located in Ontario, Canada. The jackknife technique was used to represent the ungauged site conditions. Results based on different statistical criteria have indicated the feasibility and accuracy of the proposed approach.
Abstract. The revitalization of Toronto’s waterfront presents the largest urban redevelopment project currently underway in North America. With respect to planning the waterfront’s urban water systems (UWS), a number of studies considered a range of criteria in search for sustainable alternatives. However, a comprehensive assessment of the integrated source-drinking-wastewater-stormwater systems over their life cycles has not been developed. According to the main postulates of the integrated approach, hybrid water systems can offer potentially more sustainable solutions than traditional centralized systems. This paper discusses the development process of a decision support tool designed to facilitate evaluation of alternatives based on UWS metabolism concept while addressing some typical challenges of hydroinformatics. This decision-making support tool analyses and compares the sustainability performance of alternative decentralized solutions against a baseline conventional approach on a neighbourhood level. The tool uses a set of criteria, adopted by the large group of stakeholders involved in the development process, that are not typically considered in the decision-making process, such as energy savings, greenhouse gas (GHG) emissions, climate change resiliency, chemical use, and nutrient recovery.
Abstract. The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.
Abstract. A Monte Carlo-based method to analyze effectiveness and risks of integrated operation of a multi-purpose reservoir for flood management considering real-time ensemble hydrological predictions is developed in this study. Preliminary release operation, in which water stored in the reservoir is released just in advance of a flood event considering real-time hydrological predictions, is considered as an integrated reservoir operation method. A simulated generation method of ensemble hydrological predictions with a certain error structure is developed in order to generate a number of ensemble hydrological predictions for Monte Carlo simulation. A number of simulations of reservoir operation are conducted with consideration of the generated ensemble hydrological predictions to analyze the effects of preliminary release operation based on ensemble hydrological predictions. The result of the analysis can provide reservoir managers with quantitative and science-based information on expected benefits and risks to introduce operational hydrological predictions into reservoir operation from the long-term viewpoint.
Abstract. Cities and agencies worldwide are predicting complex urban flooding by simulating the exchange between the surface water and storm drain system with the FLO-2D model. The FLO-2D modeling system is now supported by the robust pre- and post-processor tools in the Quantum Graphical Information Systems (QGIS) geographic information software. The QGIS tool prepares the FLO-2D data base that includes analyzing and editing spatial information as well as exporting detailed and high-resolution flood hazard maps. This paper outlines the resources and modeling tools available to engineers in an open source and free cross platform geographic information tool that supports the viewing, creation and editing of the spatial and tabular data as well as graphical and mapping output. This paper discusses the features of this unique, free, efficient and comprehensive data processing tool. A case study for the application of the QGIS tool for a FLO-2D urban project is presented.
Abstract. Recently, heavy rain by typhoon increases risk of disaster everywhere in Japan. There has been considerable interest to improve the flood control function of dams by prior releasing because an action plan was enacted to fully use the existing hydraulic structures to prevent flood disasters. Carrying out prior releasing has a risk in terms of water supply purpose, in other words, it may cause artificial drought. Therefore, it should be taken into consideration that releasing larger amount of water than rain gives water shortage. In the present study, we suggested the method of dam operation based on rainfall forecast including prior releasing considering the risk in terms of water supply purpose. Concretely, first, we investigated that it could estimate the accuracy of forecasted accumulated rainfall based on Global Spectral Model (GSM) by adding the information of spreads calculated by Weekly Ensemble Prediction System (WEPS) in the Yodo river basin. Second, accumulated rainfall based on GSM errors using gamma distribution was analyzed. Third, the method of dam operation based on rainfall forecast including prior releasing was applied to past examples and the effect was verified. As a result, peak discharge in Hirakata point was reduced than normal operation in case of rainfall prediction was accurate.
Abstract. This paper evaluates a robust Model Predictive Controller (MPC) based on Sliding Modes (SMPC) for the downstream level control in irrigation canal pools. Its features are compared with the conventional Generalized Predictive Controller (GPC), regarding set point tracking (water level) and output disturbances (offtake discharges). Simulation results suggest feasibility of applying SMPC for gate manipulation, with suitable command signals and robustness.
Abstract. Multi-step ahead streamflow forecasting is of practical interest. We examine the error evolution in multi-step ahead forecasting by conducting six simulation experiments. Within each of these experiments we compare the error evolution patterns created by 16 forecasting methods, when the latter are applied to 2 000 time series. Our findings suggest that the error evolution can differ significantly from the one forecasting method to the other and that some forecasting methods are more useful than others. However, the errors computed at each time step of a forecast horizon for a specific single-case study strongly depend on the case examined and can be either small or large, regardless of the used forecasting method and the time step of interest. This fact is illustrated with a comparative case study using 92 monthly time series of streamflow.
Abstract. In this paper, a System Dynamics (SD) computer simulation model was developed to assess the effects of developing and providing an alternate water source on the management of a water supply system and customer satisfaction. A water supply service satisfaction index was also developed to estimate the level of overall customer satisfaction on water supply service. Data from the Busan water supply authority and the Korea Development Institute regarding the Nakdong riverbank filtration development were utilized for the construction of the model. Major managerial indicators of the system under study were analyzed by the simulations of the model that incorporates the development of the alternate water source for Busan. The developed SD model and the water service index may be further utilized as a tool that can assess the extent and timing of an additional service improvement project.
Abstract. Wastewater treatment facilities of the Ave River basin (located in NW Portugal) are especially vulnerable to infiltration since they present considerable extensions of sewers installed in streams and rivers and collect wastewaters from longstanding sewer networks of five municipalities. The operational management of this complex system involves decision variables such as the selection of the treatment plant where collected wastewater will be treated, with implications for pumped volumes and consequent energy consumption. Aiming to reduce these inflows and increase the management performance of TRATAVE, the company responsible for operating the system, a monitoring network that includes the entire drainage network and treatment facilities operated by the company was designed and implemented. Several flow measurement devices were installed at strategic locations within the sewer network and integrated with a SCADA system responsible for its operation. All measured data was organized in databases. This monitoring platform will support the implementation of a decision support system (DSS) based on a hydrological model of the basin, a hydrodynamic model of the river network and the sewer network. The DSS is being implemented using the Delft-FEWS platform, integrating monitoring data and models. The DSS conceptual framework and the first results of the estimated infiltration volumes are presented.
Abstract. In this study, the calibration of the rain-flow conceptual model UFGModel1.1 is carried out, and the uncertainties in the predictions of flow rates associated with the parameter set estimates are evaluated by the Generalized Likelihood Uncertainty Estimation (GLUE) and Differential Evolution Adaptive Metropolis (DREAM). The water catchment area of the Botafogo Stream, located in the city of Goiânia, Brazil, was selected as experimental for the development of the study, in which a more distributed spatial discretisation degree (thirteen planes and six channels) was adopted for this basin. The results showed that the various parameter sets were considered optimal, allowing high modelling efficiency, despite the loss of the quality of the simulations and uncertainty increase when using the GLUE.
Abstract. This research evaluated two main sources of impact on the results of the ocean regional circulation model (ORCMs) during downscaling and nesting the results from the ocean global circulation model (OGCMs). Representative two sources should be the spatial resolution difference between driving and driven data, and the frequency for up- dating LBCs. The Big-Brother method investigated the effect of them on the results of the ORCMs separately. The results showed that the lateral boundary conditions (LBCs) potentially degraded the results of ORCMs. The errors developed at the boundaries propagate slowly into the center of the nested domain as time passes. The simulation results of the ORCMs significantly depend not only on spatial resolution but also on the frequency for updating the lateral boundary conditions. The ratio resolution of spatial resolution between driving data and driven model can be up to 3 and the updating frequency of the LBCs can be up to every 6 hours per day.
Abstract. In recent years, the evaluation of water quality in distribution systems has generated enormous interest in the scientific community due to the increasing concentration of population in urban areas and frequent issues connected with supply water quality. Following the wave of bioterrorism subsequent the events of September 11th 2001, a need can be foreseen to seek adequate preventive measures to deal with contamination in water distribution systems that may be related to the accidental contamination and deliberate injection of toxic agents of any origin in the distribution networks. Therefore, it is very important to create a sensor system that detects contamination events in real time, while maintaining the reliability and efficiency of the measurements, limiting the cost of the instrumentation. A reliable monitoring system, for this kind of problems, cannot be deployed without realistic modelling support. The current state-of-the-art in water distribution systems analysis usually adopt a simplified approach to water quality modelling, neglecting dispersion and diffusion and considering simplified reaction kinetics. Even if such simplifications are commonly acceptable in fully turbulent flows, they may take to relevant errors in transition flows with low velocity thus taking to unreliable interpretation of the contamination in complex networks. The present paper aims to compare different modelling approaches to the evaluation of contaminant dispersion in two distribution networks: one laboratory network in which contamination experiments were carried out in a controlled environment (Enna, Italy) and a full-scale real distribution network (Zandvoort, Netherlands).
Abstract. VEAS is the largest WWTP in Norway, where inflow is collected through a combined sewer system, i.e., storm water runoff is combined in a common conduit with wastewater from homes, businesses, and industry and delivered to the plant. From a process perspective this already high degree of variability is further compounded by return flows from the plant itself. The VEAS plant is fully located in cavern and is operated 24/7. Cavern location requires low footprint and consequently high surface load. The VEAS process features a “single-shot” sedimentation and has a record-low water retention time of 3 hours. This highly efficient configuration is sensitive to variation in the inflow water parameters and internal plant recirculation flows, 25 measured parameters have been identified as impacting the effectiveness of the sedimentation process. Due to the high non-linearity of the parameters influence, even extensive use of classic non-linear statistical analysis has failed to clearly identify the main performance drivers of the process.
In this paper we investigate the use of Kernel-based and Neural methods for the learning of the optimal control parameters in the context of industrial plants. The main objective is to define an automatic way to identify and tune the most relevant parameters of the plant (e.g., dosage of chemicals, sump level setting) to minimize the final water turbidity. The adopted machine learning framework enables the automatic analysis of the evolution of the plant behavior over time, i.e. exploits sensors readings stored for a long time period (one year), to develop a predictive model of the future behavior of the system.
Abstract. The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real- time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.
Abstract. The construction of harbor defense structures changes the natural sedimentary fluxes that contribute to feed the coastal drift in the adjacent beaches, in many harbors of the world located at river mouths. This paper presents a numerical modelling work, based on the Delft3D software, to study morphodynamics at the river Lima estuary, Portugal. This model was implemented recurring to a hydroinformatic environment that was constructed at University of Minho along the last two decades. Considering specific hydrodynamic conditions and typical characteristics of the estuarine sediments, the capacity of hypothetical structures to improve transport of sediments to the coast was assessed: (i) a submerged transverse non-erodible dam and (ii) an emerged groin linked to the left embankment located at the upstream section of the harbor. The implemented hydroinformatic environment presents capacities to simulate the complex morphodynamic behavior of river mouths. The preliminary results reveals that the proposed structures can have a positive impact throughout dredging works facilitation by transferring depositional areas during flood events to a location near the coast inside the harbor. Ongoing field acquisition data will be essential to validate depositional patterns under different river discharges and wave conditions.
Abstract. Hydrological and hydrodynamic models are valuable tools for understanding complex river hydrodynamics behavior during flood events. These tools have been applied to develop a detailed study of the flood event occurred between 9 and 11 January 2016 in the river Mondego basin, causing severe floods at Coimbra city (Portugal). The study included the characterization of the operational discharge schemes of three upstream dams with direct influence on flow rates in the river basin, and the runoff flows from contributing catchments. A detailed analysis on hydrodynamic water levels at the flooded areas influenced by the operation of a downstream dam and the local river morphodynamics was performed. Hydroinformatic tools were applied in different scenarios allowing the characterization and identification of the key factors responsible for the flood event and contributing to emphasize the need to comply with the established rules for the discharges at the upstream dams during flood events.
Abstract. Recently, it has been demonstrated that it is possible to relate water levels of a reservoir with its dam displacements. Water levels were determined via remote sensing, while dam displacements were measured via Global Navigation Satellite System (GNSS). Results have shown that displacements and water levels are correlated.
Water levels at the Magazzolo reservoir in southern Italy were firstly retrieved using two remote sensing approaches: by visual matching between the reservoir shoreline and contour lines, and by evaluating the surface extent via unsupervised classification to estimate the water levels with an area/depth relation. Dam displacements were measured using GPS receivers on the dam and a permanent station from a GNSS Continuously Operating Reference Stations (CORS) network, about 30 kilometers away.
Subsequently, two other remote sensing approaches were tested to detect reservoir levels; the first based on shape similarity indices, while the second on the evaluation of the average distance between a reservoir shoreline and contour levels. First results were extracted from a Landsat 8 optical image acquired during a clear sky day. Within this work, algorithms for water level retrieval have been tested and validated under different conditions over a more consistent satellite dataset including Sentinel-1A Synthetic Aperture Radar (SAR) images acquired from October 2014 to September 2015. The dataset is also used to analyses dam displacements via Interferometric SAR (InSAR), to be compared with the effects of water level fluctuations on the dam. First results suggest that it is possible to correlate dam displacements and water levels derived by the same dataset. However, it is shown that displacements also depend on meteorological forcing.
Abstract. Dams cause a sediment transport trapping phenomenon and the effects can be the reduction of reservoirs operations, the decreasing of the storage, a channel erosion of the downstream watercourse and habitats pauperization. A possible method used to preserve the reservoir volume and the sediment continuity downstream the dam is to operate sediment flushing. In this work, the sediment flushing phenomena and its impact on morphology and ecology is investigated. In particular two possible flushing strategies are proposed. The two strategies differ for the flow rate, sediment concentration and event duration. The results are obtained using an original CFD model developed at the University of Trento. The CFD model has the possibility to simulate the erosion and deposition phenomena and to calculate the severity of the ill effects (SEV parameter) for juvenile and adult Salmonids. The results showed that the two strategies have very different effects on morphology and habitat. The strategy that involve lower flow rate and concentration with higher event duration, seems to minimize the deposition phenomena and the effects on the habitat.
Abstract. This study investigated the impact of fluvial flooding on bridges. A high-resolution flood model is coupled with damage and transport modelling, to assess structural vulnerability and critical functionality of bridges subjected to flooding. The study involves integrated investigation of riverine bridges, devises a systematic methodology and practical implementation in computer-based decision support tools. The research draws on the principles of a risk-based approach to assess the hydrodynamic effects of floods at bridges, and moves these forward by advancing a deep analysis over the whole UK territory. This research will fill the gap of current guidance for design and assessment of bridges relevance within the overall transport system, highly inadequate for evaluating these risks in light of the increasing external pressures.
Abstract. This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.
Abstract. The pressure sensors positioning is a crucial step for leakages detection. The optimal positioning of monitoring sensors, or simply sampling design, has been previously addressed with respect to several purposes. The proposed methodology aims to select the pressure monitoring nodes for leakages detection by coupling the water distribution network hydraulic simulation model with the identifiability analysis. The nodes selection is done among those which are more sensitive with respect to different leakages positions and uncorrelated from each other to avoid redundant information. The parameter uncertainty effect on the results is also investigated. The method is applied to the benchmark network Apulian.
Abstract. The study of the relationship between extreme rainfall events and surface temperature represents an important issue in hydrology and meteorology and it could be of capital importance for evaluating the effect of global warming on future precipitation. Various approaches have been tested across different parts of the world, and, in many cases, it has been observed an intensification of precipitation with increasing temperature consistently with the thermodynamic Clausius-Clapeyron relation (CC-rate of 6-7% °C-1), according to which a warmer atmosphere is capable of holding more moisture. Nevertheless, in different locations, the scaling rate between temperature and extreme precipitation has resulted significantly different with respect to the CC-rate, in some cases sensibly higher (super-CC) and in other relevantly lower (sub-CC). In this work, an analysis of the scaling relationship between sub-daily extreme rainfall events and surface temperature is carried out, using data from a large number of rain and temperature gauges across Sicily (Italy). Results highlight the relevant importance of some modeling choices and, particularly, of rainfall duration, for this type of analysis in semi-arid region. An overall sub-CC scaling rate has been detected for most part of the region.
Abstract. A recovery of ancient records of the Como Lake water levels at the Fortilizio in Lecco hydrometric station enabled the reconstruction of a time series of daily water level and runoff from the Como Lake spanning the 1845-2014 period. In parallel, the monthly areal precipitation at the Adda river catchment scale was estimated for the same 170 years- long period. This time series, which is one of the longest available for Italian riverbasins will support analyses of the reasons of changes in the runoff regime in response to climatic and anthropogenic changes. A comparison of the two series applying the Mann- Kendall, Spearman and Theil-Sen trend tests, shows a decline, in the long term, of runoff and a more significant one of precipitation. Because some changes in the operation at the outlet of the Como Lake occurred after 1946 and also in the storage capacity of the upstream reservoirs the time series was splitted in two periods, before and after 1946. The results of the statistical tests for both precipitation and runoff in three time periods are consistent, but only for the time series of annual runoff the decline is statistically significant with 5% significance level. To analyse if changes occurred at different time scales the wavelet transform was applied to the daily runoff series. Finally the Fourier power spectrum of the the daily runoff data shows a signal of higher energy corresponding to a period between 11 and 13 years, close to the sunspots cycle period, and its significance is under investigation.
Abstract. This paper shows potential application of mechanical reliability analysis in WDNetXL in a risk-based asset management applied to a distribution network in Norway. Evaluation of hydraulic importance of the network's pipe segments, based on quantification of pressure deficiency and unsupplied customer demand during simulated service interruptions, allows risk assessment on individual pipe level with the inclusion of statistical information about break rate of the pipe. From risk assessment of individual pipe, a priority ranking for pipe rehabilitation can then be developed. Such an approach should benefit the rehabilitation planning by highlighting criticality of a specific pipe and its impact on the service of the network. This approach can also be extended to evaluate the risk reduction reached once the rehabilitation plan is executed.
Abstract. Droughts are among the weather-related disasters, which affects most people around the world. Its large spatial extent and slowly, creeping onset, makes it difficult to define its start and end. Indeed, monitoring and early warning systems for drought hazards are recognized as critical activities of risk governance. Nevertheless, in many regions of the world, the scarcity of direct observations of climatological and hydrological variables, hinder an adequate follow-up and investigation of this phenomenon. This paper introduces a novel framework to generate drought hazard maps and time series, at national and regional levels, based on univariate and multivariate standardized drought indices. Notably, we utilize freely and globally available, gridded datasets of hydrological variables derived from remote sensing and data assimilation systems (e.g., rainfall, soil moisture, streamflow), which are verified against in situ measurements. A good performance of the framework is documented through the comparison of results against observed drought events in Mexico. This paves the road towards its use in other regions of the world, where data scarcity is an issue for drought monitoring activities.
Abstract. Numerical model is generally to simulate hydrodynamic parameters such as surface currents. However, it has limits such as difficulty in definition of initial and boundary conditions. As remote sensing such as satellite and radars advances and is applied in practice. Data assimilation technique has becoming a promising means to improve modeling performance through taking advantages of available observations. In this paper, surface currents hourly monitored by a radar system were assimilated into a 3D numerical model to improve modeling performance using a sequential data assimilation algorithm. Results indicated that application proposed data assimilation approach not only improved hindcasting of surface flow fields, but also improved its forecasting.
Abstract. Water losses are a major concern for water companies, mostly due to their economical, technical, social and environmental negative impacts.
Unreported leaks are a major cause of water losses in water distribution networks (WDNs) and they are difficult to locate, particularly in plastic pipes, large diameters and low pressure conditions. The location of these leaks is very time consuming and requires specialized human resources, using sophisticated and costly acoustic equipment.
The use of modelling and optimization tools, supported by flow and pressure measurements, is showing to be a challenging alternative to the traditional procedure. This paper presents the application of the methodology proposed in Ribeiro L. S., 2012; Ribeiro L. S., 2015; Sousa, 2015 to a real WDN, highlighting the major difficulties faced when dealing with real world conditions, namely gathering and checking data, and building and calibrating the water distribution model.
The results obtained in this case study show that this approach is very promising, encouraging future applications and developments.
Abstract. This paper presents a study aimed at improving the event detection capabilities of the existing, threshold-based detection system at a selected Water Treatment Works operated by United Utilities. The study shows that improvements can be achieved by using optimised threshold and persistence values identified by performing a sensitivity type analysis. The main findings from this study show that, although an overall increase in the true detection rate and decrease in the number of false alarms can be achieved, the high number of false alarms remains an issue. To address this problem a new event detection system based on suitable relations across multiple signals will be developed as part of future work.
Abstract. The evapotranspiration consists of counting all the water on the surface of the earth lost to the atmosphere, through evaporation and transpiration. The evapotranspiration can be estimated from evaporimeters and lysimeters (direct methods) and empirical and semi-empirical models (indirect methods). Some models have been developed for semi- arid regions such as the Blaney-Criddle and the Hargreaves-Samani, and other models for temperate climates, such as the Thornthwaite model. The Penman-Monteith model, recommended by the UN-FAO, is the most accurate estimating method for evapotranspiration. A determination of evapotranspiration is essential for irrigation management, to plan system and develop irrigation schedules. The present work aims to develop a tool for mobile devices to estimate evapotranspiration through models, with the help of a GPS receiver, and that allows the comparison of the different models with the FAO standard estimation method. The app is available on Google Play at https://play.google.com/store/apps/details?id=com.thunkable.android.diogo_borbar.Eva poCalc.
Abstract. DEMs are important data required in watershed-based hydrological and water quality modeling since they are employed to derive critical characteristics of watershed through a watershed delineation process. This study aims to analyze the uncertainties associated with DEM sources in watershed modeling and compare them to DEM resolution-originated uncertainties. Toward this end, six different scenarios, involving 3 DEMs of 30-m resolution and 3 DEMs of 90-m resolution from NED, ASTER and SRTM sources, were developed using HSPF model for an agricultural watershed in Iowa, USA. The HSPF model was run for each scenario to produce simulated flow and loads of sediment, nitrate, and phosphorus. Results suggested that the level of uncertainty involved in the DEM sources was considerably (up to twofold) greater than those originated from decreasing DEM resolution. The finding is important to the proper selection of DEM data source and thereby to the reduction of uncertainties involved in watershed-based hydrological and water quality modelling.
Abstract. Combined Sewer Overflows (CSOs) are a major source of pollution, spilling untreated wastewater directly into water bodies and/or the environment. If spills can be predicted in advance then interventions are available for mitigation. This paper presents Evolutionary Artificial Neural Network (EANN) models designed to predict water level in a CSO chamber up to 6 hours ahead using inputs of past CSO level, radar rainfall and rainfall forecast data. An evolutionary strategy algorithm is used to automatically select the optimal ANN input structure and parameters, allowing the ANN models to be constructed specifically for different CSO locations and forecast horizons. The methodology has been tested on a real world case study CSO and the EANN models were found to be superior to ANN models constructed using the trial and error method. This methodology can be easily applied to any CSO in a sewer network without substantial human input. It is envisioned that the EANN models could be beneficially used by water utilities for near real-time modelling of the water level in multiple CSOs and the generation of alerts for upcoming spills events.
Abstract. By combining and integrating different areas of knowledge (Urban Planning, GIS, Remote Sensing, Cellular Automata, Climatology, etc.) with the cities traditional infrastructures using new digital technologies, it is possible to generate more efficient urban systems. Therefore, it can support new forms of water governance. This study aims to reproduce environmental and water management scenarios using Geographic Information Systems (GIS) and cellular automata as a methodological approach for spatial patterns simulations of urban growth (dynamic scenarios). Water consumption simulations plus floods modelling and environmental comfort simulations were integrated into the same SDSS (Spatial Decision Support Systems) environment as a GIS. To support the analysis, Dinamica EGO and Storm Water Management Model were chosen as modelling platforms. The simulations used the future land use trends (dynamic modelling) and legal aspects to evaluate the mitigation of floods with low impact development techniques (LID). Results indicated good runoff reductions with the integration of stormwater and dynamic modelling. This research expects to support interdisciplinary approach for urban planning teams making the water issues and urban planning issues closer and essential for the resilience of present and future cities.
Abstract. Green roofs (GRs) have become a popular sustainable drainage system (SuDS) technology in urban areas. As many countries and regions experience political encouragement and substitution schemes in implementing GRs, there is a need for reliant models that can support designing purposes. The stormwater management model’s (SWMM) Low Impact Development Green Roof (LID-GR) control is used to simulate the hydrological detention performance of two GRs, GR1 and GR2, with different drainage properties located in Oslo, Norway. This study uses event-based data to replicate GR runoff. Accordingly, four event-models were calibrated using the Shuffled Complex Evolution algorithm with the Nash-Sutcliffe criteria (NSE) as the objective function. Eight events were used for model validation. Simulation results revealed that SWMM’s LID module can capture response of the GRs even though the adequacy varies among events. During calibration two GR1 (0.55 and 0.72) and three GR2 (0.73, 0.88 and 0.51) event-models yielded NSE>0.5. However, only parameter sets of two GR2 event-models yielded NSE>0.5 when applied to the validation events. Parameter sensitivity analysis exhibited significant correlation between conductivity slope and maximum precipitation intensity. The study shows potential of SWMM as a design tool if supplemented with a calibration algorithm and some adjustments to the LID module.
Abstract. In Coimbra city, Portugal, the riverbanks have suffered several floods events in the past, due to its hydrological regime, the low slope and consequent lack of capacity of the Mondego River in its final 30 km. The construction of several dams in the upstream part of the river catchment has improved the use of the hydraulic capacity of the river system and reduced the number and intensity of flooding events in Coimbra. Nevertheless, intense rainfall events combined with inadequate procedures of the dam operation rules and lack of monitoring of sediments dynamics can still originate inundation in Coimbra such as those registered between 9th and 11th of January 2016. This work presents modelling scenarios demonstrating the influence of the sediment accumulation into the riverbed and its effect on the water levels. It also presents the influence that piers from a new bridge can have into the river flow dynamics.
Abstract. The selection of suitable wastewater treatment solutions is a complex problem that requires the careful consideration of many factors. With water at a premium and water consumption increasing, India is facing a challenging time ahead, requiring effective water treatment solutions. The Wastewater Decision Support Optimizer (WiSDOM) presented here is a user-friendly software package designed to aid in the formulation and configuration of wastewater systems in developing countries such as India. WiSDOM employees advanced multi-objective optimization and decision analysis techniques to identify optimal wastewater treatment options. It has been demonstrated that WiSDOM can adapt to a wide array of scenarios, considering a range of contributing factors (technical, environmental, economic and social), enabling stakeholders to make more informed decisions. The tool was applied to three different scenarios to test its functionalities and assess treatment technologies potential for different contexts. Initial results suggest that it is possible to automatically generate feasible distinct treatment strategies for user-defined contexts/constraints.
Abstract. Recently in Hungary, drought affects the Drava floodplain more severely than floods. The channelization of the Drava River changed the water budget of the Cún- Szaporca oxbow lakes in the floodplain. The paper presents a 3-D groundwater model for this oxbow of the Drava floodplain to gain a better understanding of the water budget of the whole system under the normal situation and for different lake replenishment scenarios. The model is developed using the finite difference code MODFLOW-2005 and calibrated with a mean error of -0.03 m, and mean absolute error of 0.08 m. Two scenarios for the replenishment of lake were analyzed. Water level is planned to be raised by 0.5 m and 1 m, for the first and second scenario, respectively. As a consequence, an increase of seepage from the lake was found. Around 65 % of the seepage recharges the groundwater system. Such a rise in groundwater table improves the sustainability of the aquifer and serves agricultural and environmental purposes. Additionally, they show the importance of the model for decision makers to select the right future management decisions.
Abstract. In the last decades, the growth of mini- and micro-industry in urban areas has produced an increase in the frequency of xenobiotic polluting discharges in drainage systems. Such pollutants are usually characterized by low removal efficiencies in urban wastewater treatment plants and they may have an acute or cumulative impact on environment. In order to facilitate early detection and efficient containment of the illicit intrusions, the present work aims to develop a decision-support approach for positioning the water quality sensors. It is mainly based on the use of a decision-making support of the BDN type (Bayesian Decision Network), specifically looking soluble conservative pollutants, such as metals. In the application and result section the methodology is tested on two sewer systems, with increasing complexity: a literature scheme from the SWMM manual and a real combined sewer.
Abstract. Advances in shallow-water modeling and high performance computing, combined with the increasing availability of fine scale geospatial data, now makes it possible to simulate flooding at spatial and temporal scales comparable to how people experience flooding. This poses enormous opportunities to improve the targeted communication of flood risks and accelerate adoption of vulnerability reduction measures. Here we present collaborative shallow-water modeling of flood hazards with end users, which results in hazard maps tailored to local decision-making needs and poised to reduce flood vulnerability within at risk communities.
Abstract. The aging process in water distribution system is one of the main drivers for the reduction of performances in water distribution systems. Furthermore, this conditions usually imply an increase in the maintenance costs that the water utilities have to sustain. In this situation it is required to undertake programmatic strategies in order to guarantee the highest benefit for both the final users and the water companies. An optimal rehabilitation strategy has been proposed in order to take into account the regulatory schemes that have to be abided at the national level, in the water industry.
Abstract. The Brazilian semi-arid region presents a highly variable rainfall regime in space and time. Although the mechanisms of rainfall have been well described and numerically modelled, reliable forecasts for more than six months in advance cannot be produced yet, as well as projections of climate change in the long term. This paper contributes to the understanding of the variability examining a more than 100-year time series of a rainfall gauge in this region, using three techniques: wavelet analysis, Mann- Kendall and Sen tests. The techniques allow the description of the patterns of variability of rainfall and suggest that there is not still a clear evidence of climate change.
Abstract. Coastal zones face severe weaknesses and high-risk situations due to coastal threats like erosion and storms and due to an increasing intensive occupation. Tropical storms events can contribute to the occurrence of these situations, by causing storm surges with high water levels and, consequently, episodes of waves overtopping and coastal flooding. This work aims to describe a methodology to estimate the storm surge occurrences in the Portuguese coastal zone, recurring to historical tropical storms data that occurred in the vicinity of Portugal and to numerical modeling of its characteristics. Delft3D software together with DelfDashboard tools were applied for the numerical modelling. An automatic generation procedure of storms was implemented based on the few available historical storms data characteristics. Obtained results allows to characterize storm surges along the Portuguese coast, identifying the most vulnerable areas and, consequently contributing for its proper planning and management.
Abstract. Safely managed sanitation services, monitored by the United Nations 2030 Agenda for Sustainable Development, require data on treatment of excreta from sanitation systems. This data is not readily available for the majority of United Nations member states and has led to estimates being established mostly for those countries where conventional sewer-based sanitation systems are prevalent. Presented in this article is a decentralized portable treatment unit for the safe treatment of excreta and sludges from non-sewered sanitation systems. Data from daily operations is generated from a variety of sensors, each collecting approximately ten data points per minute. Innovative cloud- based methods and data science tools are implemented to collect, store and analyze data. A software platform was developed that offers real-time reporting and alerts to operators and supervisors, allows for remote operation and control, and provides a multi tier architecture that enables user interaction through a mobile or web interface. Key Performance Indicators and results from long-term analytics are presented to quantify the effectiveness of the treatment process and provide relevant information to improve daily operations.
Abstract. Inland waterways are large, complex systems composed of interconnected navigation reaches dedicated mainly to navigation. These reaches are generally characterized by negligible bottom slopes and large time delays. The latter requires ensuring the coordination of the current control actions and their delayed effects in the network. Centralized control strategies are often impractical to implement due to the size of the system. To overcome this issue, a distributed Model Predictive Control (MPC) approach is proposed. The system partitioning is based on a reordering of the optimality conditions matrix, and the control actions are coordinated by means of the Optimality Condition Decomposition (OCD) methodology. The case study is inspired by a real inland waterways system and shows the performance of the approach.
Abstract. Long term changes in pollutant loadings and water quality of the Yongdam Lake due to climate changes were estimated by using a basin model and a surface water quality model in series. Two Representative Concentration Pathways scenarios, RCP4.5 and RCP8.5, that stabilize radiative force at 4.5 W/m2 (significant reduction) and 8.5 W/m2 (current trend), respectively, were applied and their impacts were predicted. The SWAT model was selected in the basin to predict flow rates and loadings of major pollutants to the lake. Then, the CE-QUAL-W2 model was used to estimate water levels and water concentrations in the study lake. Both models were applied for 6 years from 2010 to 2015 and the latter three years were used for calibrations discarding the first three year warming up periods’ results. Using the both models, future flow rate and water concentration were estimated for 80 years from 2016 to 2095. The RCP8.5 scenario application results shows future flow rate and water quality concentrations will be increased in flood seasons and decreased in dry seasons. This result indicates that drought and flood will become more serious and also their effects on water quality will become more serious in the future. The RCP4.5 scenario showed greater increase in flow rates and TSS and TP concentrations than RCP8.5 scenarios despite the significant reduction in green house gas. This may be caused by increased air temperature followed by increased evapotranspiration that led surface runoff reduction in the basin area of the RCP8.5. This study suggests that dependent on characteristics of local climate change effect, impacts on the environmental may be different. Also, temporal distributions of precipitation pattern during simulation period and also in a year must be investigated thoroughly as simple arithmetic averages may not reflect detailed phenomena appropriately.
Abstract. In this study, a depth-averaged two-dimensional hydrodynamic model and scalar transport model were used to analyze the characteristics of both velocity field and concentration field of the complex flow in meandering channels. The two-dimensional shallow water model used in this study adopted the dispersion stress method in order to induce the effect of secondary flow which is normally omitted in the depth averaging process of the shallow water equation. A new vertical profile equation for the secondary flow was applied to the momentum equations by adopting the dispersion stress method. Comparisons with the experimental results of the large meandering channels of the River Experiment Center of KICT show that the computed values of the water surface profile and velocity magnitude were in good agreement with the observed data. The results of the 2D advection-dispersion model show that the longitudinal dispersion is much larger than theoretical results by Elder (1959) in meandering channels.
Abstract. In this study, an enhanced ANN model was developed to analyze the water quality variation at the river confluence by incorporating the resilient propagation algorithm to increase the model accuracy. An ensemble modeling with stratified sampling method was also developed in order to reduce the influence of the input data and model parameters on the prediction of river water quality. The water quality parameters such as pH, electric conductivity (EC), DO and chlorophyll-a, were predicted using proposed ANN model in the large river which is affected by pollutant inputs from the tributary river. The results of model simulation showed that the pollutant input from the tributary affected the water quality of the mainstream. The model prediction using water quality data of the tributary river as the input data in addition to the mainstream data produced better results than the simulation using mainstream data only, especially for EC and DO, R2 value was improved by 30.9% and 20.6%, respectively.
Abstract. Using Shanshan County as the research focus, this study investigates drinking water safety in northwestern China and proposes measures for improving the efficiency of clean water projects targeting drinking water quality in the region. As new technologies such as the Internet and the Internet of things gain wider usage, urban and rural safe drinking water projects should focus on equipping projects, modularizing the equipment, improving project management using internetization, and developing intellectualization for increased Internet dependence. This study proposes modularization of the equipment for clean water projects for centralized and decentralized water supply programs. For management of such projects, this research proposes internetization in project management as well as intellectualization of construction, including establishment of management facilities, automation of water plant operations, intelligent control of clean water operations, and online intelligent water monitoring. This study integrates various information resources and investigates the implementation of intellectualized management of water treatment facilities through scientific advances and evaluates the potential of these approaches for increasing the quality of public service.
Abstract. Present study examines the applications of different trend detection methodologies for investigation of trend in long-term rainfall over Lower Tapi basin, India using daily gridded rainfall data for the period 1901 – 2013 at 0.25  0.25 resolution. The trends in rainfall indices, viz. total annual rainfall (TAR), annual maximum rainfall (AMR) and average annual rainfall intensity (AAI) have been detected using non-parametric and graphical methods. The results show increasing trends in TAR across all the 9 grids in the study region, with significant increasing trend over Grids-8 and 9. Further, AMR exhibited increasing trend over 7 out of 9 grids, with significant increasing trend over Grid-8 (ZMMK = 2.478;  = 0.356 mm/year) and Grid-9 (ZMMK = 2.278;  = 0.257 mm/year). The Innovative Trend Analysis plots reveal overall increasing trend in AMR across all the grids. The AAI exhibited significant increasing trend over 5 grids including Grids-8 and 9. The Grids 8 and 9 encompass the urban areas of the Surat city, located in the Lower Tapi basin. The urbanization in the Surat city and proximity to the Arabian Sea areas may be the possible reasons for significant increase in the extreme rainfall and rainfall intensity over Grids-8 and 9.
Abstract. This paper presents the Risk Informed Decision-making Framework and software tool we developed that formally account for flood risk and uncertainty in reservoir operations. The framework and the software tool are intended for practical use by reservoir operations planners to manage flooding events. We present a robust and comprehensive approach that accounts for a multitude of flood risks and their impacts, and that enables its users to identify those alternative reservoir operating plans that formally adopt a state-of-the-art risk informed decision-making framework. Solidly grounded in and closely follows a well-structured planning process, the framework augments existing planning processes and information flows that incorporates specific techniques and methods from probabilistic risk analysis (PRA) and Multi-criteria Decision Analysis techniques (MCDA). Seven major hydropower companies and agencies in North America and Europe sponsored the development of the framework and the decision support tool. We present the results of a case study to illustrate the framework and the software system. We show that numerous advantages can be achieved using such tools over currently used approaches and that in the case of risky and high-impact processes, such as in the management of potentially high-consequence facilities such as storage reservoirs, management by a human operator is essential.
Abstract. In order to optimize and downsize pipeline diameter to prepare for water demand decrease in the future, we conducted validation to apply the Hazen-Williams formula to existing pipeline. We focused on the flow velocity coefficient (hereafter referred to as, “C”) and validated it through a pipeline network simulation and field experiments. As a result, the present value for C that is uniformly adopted in Japan should be modified for existing pipeline. Furthermore, variance in C due to the differences between the inner linings of pipeline was verified. We evaluated the effectiveness of downsizing of pipeline diameter with the result of this study, and we confirmed that this study contributes to optimizing and downsizing pipeline diameter.
Abstract. The calibration of models applied to water distribution network systems is fundamental, as this improves the computational algorithms constructed from mathematical models. In this work from a hypothetical network, three proposed calibration algorithms were tested, (a) in terms of roughness of the model; (b) in terms of roughness and random demand and (c) in terms of random roughness and pressure directed demand. The results show few differences for the three algorithms tested, the first and third results are almost identical and slightly different from the second. However, these are basis for application in real networks, where surely the more complex algorithms can produce advantages.
Abstract. Performance of networked systems greatly depends on their topologic or connectivity structure. Nowadays, the analysis of the relevant features influencing the emerging behavior of networked systems is possible because of the increasing computational power and availability of information. Complex Network Theory classifies the connectivity structures of real systems using the nodal degree, the average path length, the clustering coefficient and the probability of connection. However, networked city infrastructures, e.g. water distribution networks (WDNs), are constrained by the spatial characteristics of the environment where they are laid. Therefore, networked infrastructures are classified as spatial networks and the classification of their connectivity structure requires a modification of the classic framework. To this purpose, the paper proposes a classification of WDNs using the neighbourhood nodal degree instead of the classic degree, the network size instead of the probability of connection and the classic average path length. The research will show that the clustering coefficient is not useful to describe the behavior of these constrained systems.
Abstract. Complex Network Theory (CNT) studies theoretical and physical systems as networks, considering their features deriving from the internal connectivity between elements defined as vertex and links. In order to quantify the importance of these elements in real networked systems, researches proposed several centrality metrics.
The use of CNT centrality metrics for analysis, planning and management of infrastructure networks (streets, water systems, etc.), for example in terms of reliability and vulnerability, is today a relevant issue also considering their influences in socio- economics and environmental matters. From CNT standpoint, water distribution networks (WDNs) are infrastructure networks that can be analyzed considering some peculiar features deriving from their spatial characteristics.
The paper focuses on CNT centrality metrics and proposes novel hydraulic centrality metrics useful for understanding the WDNs behavior. Furthermore, the study is intended to evaluate the feasibility of coupling hydraulic and topologic centrality metrics based on links, in order to obtain information that are more useful from the hydraulic point of view. This way, centrality metrics of the CNT become a complementary tool to hydraulic modelling for WDNs analysis and management.
Abstract. Along the German and Luxembourgian part of the Moselle River, eleven distributed local water level and discharge controllers ensure safe navigation by guaranteeing a water level within a specified tolerance and by reducing variations in the river discharge. The current control scheme is based on gain scheduled PI control with a feed forward disturbance compensation element. Both were parametrized using a 1D Saint- Venant model. Due to advancements in control strategies and processing power, the current scheme will be upgraded by adding a model predictive feed forward component (MPFFC) which improves local control and links the isolated local controllers to coordinate their efforts. The authors want to report on this process from an operator’s point of view and share their insights from the ongoing testing procedure prior to actual service. A prototype implementation was deployed on the target hardware and linked to the data acquisition system to verify real time operation. The logged results are then verified using a simulation model.
Abstract. A very large volume of climatic and agricultural data is captured and recorded by on-farm monitoring devices that is uploaded to various different data service providers. It is consistently difficult for land managers to discover, access, understand and use the data due to its disparate nature, limited access to it and multiple proprietary formats used. The Soil Sensing project is developing tools and technologies to help improve the ability to discover, access, understand, and use time-series farm-scale data across disparate data providers. This is achieved by the development and deployment of loosely-coupled web services in the form of a Data Streams Integrator system (DSI), which implements a combined brokered and federated data supply chain pattern. The DSI is composed of the Data Brokering Layer, the Observations and Measurements translation layer, the Sensor Observation Service interface and a metadata registry and repository.
Abstract. Water companies in England and Wales use a range of decision making methods (DMMs) for water resources planning. The aim of this paper is to provide a critical review of the DMMs employed by water companies in relation to their 2014 Water Resources Management Plan (WRMP) submissions; as compared with those used for the current round of draft 2019 WRMP submissions. Most companies use a similar suite of models to assess their supply-demand situation. For previous submissions, target headroom approach was the preferred method for representing the uncertainty in water resources planning. For the recent round of draft WRMP submissions, some companies have decided to investigate more advanced DMMs, and to choose risk-based methods in order to select their preferred investment scenarios. Bristol Water, Severn Trent Water, Southern Water and Thames Water have still chosen the Economics of Balancing Supply Demand (EBSD) method for selecting their optimal investment programmes; but Thames Water have decided to progress to simulation methods (Multi Criteria Search) for optimal investment selection where zones with more complex supply demand problems are concerned. Only Thames Water decided to use a multiple linear regression model for household consumption forecast, the remaining companies used micro-component analysis for this purpose.
Abstract. As with many industries, digital disruption will play a major role in shaping agriculture over the coming years as decisions become increasingly data driven. A significant proportion of this data will come from on-farm sensors that are becoming easier to source and deploy. While access to sensors is becoming increasingly cost effective, accessing and integrating the data they provide is still a major issue for many, due to the use of different standards for describing and sharing the data. The Soil sensing - new technology for tracking soil water availability, managing risk and improving management decisions project has developed a distributed system that addresses the technical challenge of federating disparate data sources through the use of a software mediation layer and a semantically enabled metadata harvest, search and discovery tool. These web services, the O&M Translator and the Data Brokering Layer, allow a unified and federated view of the data, enabling integrated search and discovery and provide access through a SOS compliant API, delivering the data to client using the O&M data model and a TimeseriesML representation. The resulting Data Stream Integrator is already being tested in applications such as SoilWaterApp.
Abstract. The adaptation of urban water systems to climate change is a complex management challenge. Especially urban drainage systems and their adaptation to growing climate change dynamics, like increasing variations in terms of intensity and frequency of heavy rainfall events, calls for novel adaptation approaches. Growing data availability opens the chance to find suitable cost-effective solutions to tackle climate change risks. In the Damsgård area in Bergen, combined sewer overflows discharge in the fjord during extreme rainfall events. Within the European project BINGO, an evaluation of alternative ways to reduce this environmental pressure is being conducted, using extensive climate, economic and spatial data. The analysis is going to compare different combinations of green infrastructure from the field of water sensitive urban design, like green roofs, ditches and swales. These combinations are furthermore compared with an innovative approach: using the slope of roads as emergency flood water ways.
Abstract. Combined urban drainage system (CUDS) collect both wastewater and raining water through sewer networks to wastewater treatment plants (WWTP) before releasing to the environment. During storm weather, rain and wastewater can overload the capacity of the CUDS and/or the WWTPs, producing combined sewer overflows (CSO). In order to improve the management efficiency of CUDS, advanced real-time control (RTC) of detention and diversion infrastructures in the sewer systems has been proven to contribute to reducing the CSO volumes. This work considers the integrated RTC of sewer network and WWTPs based on model predictive control (MPC) and taking into account the water quality as well as quantity, with the objective of minimizing the environmental impact of CSO on receiving waters. The control approach is validated using a real pilot Badalona sewer network in Spain. The first results, discussion and conclusions are also provided.
Abstract. The purpose of this study is to examine the uncertainty of a combined artificial neural network (ANN), kriging and fuzzy logic methodology, which can be used for spatial and temporal simulation of hydraulic head in an aquifer. This methodology was applied in the past, while the verification of the model was performed by implementing it in a new study area, in Miami – Dade County, FL, USA. The percentile methodology was applied as a first approach in order to define the ANN uncertainty. As a second approach, the uncertainty of the ANN training is tested through a Monte Carlo procedure. The model was executed 300 times using different training set and initial random values each time. The training results constituted a sensitivity analysis of the ANN training to the kriging part of the algorithm. The training and testing error intervals for the ANNs and the kriging prediction intervals calculated through this procedure can be considered narrow compared to the complexity of the study area. For the third and final approach used in this work, the uncertainty of kriging parameter was calculated through the Bayesian kriging methodology. The results derived can prove that the simulation algorithm can provide consistent and accurate results.
Abstract. Sewage discharges through marine outfalls are an important source of nutrients to marine waters, which cause undesired impact such as eutrophication. However, few authors have evaluated the contribution of wastewater disposal to nutrient concentration in coastal waters. We estimated how wastewater treatment plant (WWTP) discharges alter ammonium concentrations in coastal waters of the Western Mediterranean Sea. Data obtained from the literature and from the local government was used to formulate a 1D mathematical model which predicts ammonium concentrations along coastal waters with current direct discharges. The estimations were validated by comparing them to measured data and a significant agreement was found (R2=0.91). Then, the simulation of a scenario with no anthropogenic direct discharges was carried out to determine how much of the excess ammonium is due to sewage inputs. The study concludes that marine outfalls are the main driver of ammonium pollution in the studied area. Near-natural conditions could be obtained by implementing tertiary treatment to reduce nitrogen in WWTP discharges. Further research should focus on the consequences of ammonium pollution for ecosystems to efficiently evaluate the ecological status of coastal waters under the Water Framework Directive and to prioritize those coastal areas in greater need of nitrogen- removing tertiary treatment.
Abstract. In the present work a 1-D numerical model is applied to simulate the evolution of scouring process and the variation of the bed shear stress during transients. By the help of the model and by using experimental data collected in a straight flume, the paper also investigates how the presence of flexible vegetation on the bed could limit the evolution of the erosion process.
Abstract. Debris flow velocity is an important factor which influences the impact forces and runup. Due to the complexity of the phenomenon, it is difficult to define predictive methodologies. The present work reports some results of an experimental run conducted in order to investigate the velocity and sediment concentration distributions. A modified Bagnold’s approach to calculate the vertical distribution of flow velocity is presented.
Abstract. Hydrological prediction needs high-resolution and accurate rainfall information, which can be provided by mesoscale Numerical Weather Prediction (NWP) models. However, the predicted rainfall is not always satisfactory for hydrological use. The assimilation of Doppler radar observations is found to be an effective method through correcting the initial and lateral boundary conditions of the NWP model. The aim of this study is to explore an efficient way of Doppler radar data assimilation from different height layers for mesoscale numerical rainfall prediction. The Weather Research and Forecasting (WRF) model is applied to the Zijingguan catchment located in semi-humid and semi-arid area of Northern China. Three-dimensional variational data assimilation (3-DVar) technique is adopted to assimilate the Doppler radar data. Radar reflectivity and radial velocity are assimilated separately and jointly. Each type of radar data are divided into seven data sets according to the observation heights: (1) <500m; (2) <1000m; (3) <2000m; (4) 500~1000m; (5) 1000~2000m; (6) >2000m; (7) all heights. Results show that the assimilation of radar reflectivity leads to better results than radial velocity. The accuracy of the predicted rainfall deteriorates as the rise of the observation height of the assimilated radar data. Conclusions of this study provide a reference for efficient utilisation of the Doppler radar data in numerical rainfall prediction for hydrological use.
Abstract. The use of transients as a diagnostic tool in pressurized pipe networks requires reliable and efficient numerical models. The traditional models derived in the frequency domain as solutions to the linearized water hammer equations, namely the impulse response and the transfer matrix methods, are efficient in the simulation but are not suited for complex arbitrarily configured networks. An alternative frequency domain formulation is the Network Admittance Matrix Method (NAMM), where the equations are reorganized into a matrix form using graph-theoretic concepts. In this paper the similitude between steady-state Global Gradient Approach (GGA) and the unsteady- state and NAMM formulation are explored. The resulting improvements on the efficiency of the models are tested on two case studies.
Abstract. A study of average flow in open channel with baffle blocks distributed uniformly has been considered by using channel with varied slopes. In this article, experimental and modelling studies were introduced when the correlation between the water depth and baffle block size is significant. The objective of the work is to give the rudimentary relations between discharge and water level in the channels. When the water depth is large, the effect of bottom channel friction on the flow is relatively small. This paper also gives applications of the software ‘Telemac-2D’ to simulate the flow under different conditions.
Abstract. Water demand characterization when this assumes minimum values, if not null ones, is of fundamental importance for the hydraulic network management analysis. In fact, when this water demand condition occurs – usually during the night time – maximum pressures are on network pipes and at the same time tank levels increase and treatment plants are supplied with the minimum flow. The study of the null water demand are furthermore of great interest for leakages analysis in water complex systems. In this paper a study of the probability of null residential demand is provided by referring to different case studies in which the number of users ranges between 500-1250. In order to be able of implementing this study in a water distribution modeling, relationships for the daily null water demand characterization in function of the users supplied and the interval time discretization are also proposed.
Abstract. This paper presents a multi Graphic Processing Unit (GPU) implementation of a 2D shallow water equations solver which is able to exploit the computational power of modern HPC clusters equipped with several GPUs on different nodes. The domain has been discretized by means of a Block Uniform Quadtree (BUQ) grid which allows to efficiently introduce variable resolution in a GPU-accelerated finite value code. In the present work the BUQ grid is decomposed into different partitions, and each partition is assigned to a dedicated GPU. Communications between different partitions are then handled by means of a Message Passing Interface (MPI) protocol. Computations and communications have been overlapped to reduce the overheads of the multi-GPU implementation. The strong scalability test shows an efficiency dropdown better than linear in the number of GPUs adopted by the simulation, and the weak scalability test shows that network overheads caused by border communication are completely maskable by GPU calculations.
Abstract. Water supply and sanitation infrastructures are essential for our welfare, but vulnerable to several attack types facilitated by the ever-changing landscapes of the digital world. A cyber-attack on critical infrastructures could for example evolve along these threat vectors: chemical/biological contamination, physical or communications disruption between the network and the supervisory SCADA. Although conceptual and technological solutions to security and resilience are available, further work is required to bring them together in a risk management framework, strengthen the capacities of water utilities to systematically protect their systems, determine gaps in security technologies and improve risk management approaches. In particular, robust adaptable/flexible solutions for prevention, detection and mitigation of consequences in case of failure due to physical and cyber threats, their combination and cascading effects (from attacks to other critical infrastructure, i.e. energy) are still missing. There is (i) an urgent need to efficiently tackle cyber-physical security threats, (ii) an existing risk management gap in utilities’ practices and (iii) an un-tapped technology market potential for strategic, tactical and operational protection solutions for water infrastructure: how the H2020 STOP-IT project aims to bridge these gaps is presented in this paper.
Abstract. The short-term, optimal management of storage reservoirs is challenging due to multiple objectives, i.e. hydropower, water supply or flood mitigation, and inherent uncertainties of forecasts for inflow and water demand. Model Predictive Control (MPC) provides an online solution for this management problem by combining a process model, forecasts and the formulation of objectives in an objective function and its solution by an optimization algorithm. This anticipatory management has many advantages, but may suffer from forecast uncertainty. In practice, there are several sources of forecast uncertainty, which can jeopardize control decisions. In this study, hindcast experiments integrating deterministic and probabilistic streamflows in a closed-loop mode of MPC are tested to mimic a real-time flood mitigation case. Probabilistic inflow forecasts in combination with multi-stage stochastic optimization model are used with tree-based reduction techniques. According to the results, tree-based MPC proposes less spillway discharges during a real-time control of a major flood case by incorporating longer the forecast horizon and consideration of forecast uncertainty in the decision process. On the other hand, energy generation is compared with deterministic method, and the results are promising to be used without compromising the energy production.
Abstract. Many Dutch sewer networks are combined sewer systems, they carry both storm water and foul water. They consist of multiple sub-networks, linked by pumps into a tree structure with the Waste Water Treatment Plant as its root. Within sub-networks sewage transport is by gravity driven flow. Usually the original design assumed local control. Later changes, additions and extensions sometimes reduced the effectiveness of the original design. In these cases central control can improve the performance of the system without costly new construction. We apply two algorithms from graph theory, one is based on stable flows in time, the other on quickest evacuation flows. Results on local control are included to provide a lower bound on performance. A linear programming problem based of a perfect forecast of the whole event provides an upper bound on performance.
Abstract. Numerical tools for the optimization of several aspects of drinking water distribution networks have been around for some time now and are widely discussed in the scientific literature. However, their successful practical application remains a challenge, especially when combining multiple objectives and operational boundary conditions. In this contribution, we describe a number of optimization cases, including the optimization approaches applied. We discuss the technical and practical challenges that are faced when applying numerical optimization techniques to real world problems of water utilities.
Abstract. This paper presents a conceptual web decision support systems (DSS) for assessment of a tropical Andean micro-watershed. A combination of pressure-state-response (PSR) indicators and logic fuzzy were used. Three indices were defined: climate change (ICC), quality water (IQW) and soil degradation (ISD). Each index is a combination of qualitative and quantitative indicators. Fuzzy functions were defined to generate operability in each index. Trapezoidal, triangular and singleton functions were defined. The inputs are the indicators value in each zones of the watershed: high zone, medium zone and low zone. Outputs of WebDSS are the value of each index. The Web DSS was applied in an Andean watershed named “El Chocho”, in Colombia. The results indicate the high degradation level in the watershed, evidenced by the indices values. This study indicates the possibility of building and applying a DSS to support management decision process in Andean micro- watersheds.
Abstract. Solution of the nonlinear system of equations describing the network hydraulics problem can be formulated in several different manners, yielding various methods of solution. The most popular formulation is probably the Global Gradient Algorithm (GGA). Loop-flow formulation is another method revisited by number of researchers in recent years. Loop-flow method has the smaller system matrix to solve, which is a benefit over the GGA’s matrix, coming from the fact that real networks typically have far less loops than nodes. However, need for cumbersome pre-processing to identify network loops and sparsity of solution matrix, which is highly dependent of implemented loop identification algorithm, remain key drawbacks of existing loop-flow methods. In addition, systematic testing on the real life networks of different topologies and complexities is still somewhat lacking in the literature. In this paper, new loop-flow type method based on the novel TRIangulation BAsed Loop identification algorithm (TRIBAL) coupled with efficient implementation of loop-flow based hydraulic solver (ΔQ) is presented. Performance of the new TRIBAL ΔQ method based solver is tested through the comparison with the reference GGA solver. Preliminary results show that significant calculation speedups can be achieved with proposed method, maintaining prediction accuracy and convergence of the reference solver.
Abstract. The Magdalena-Cauca macro-basin (MCMB) in Colombia, by its tropical location, annually experiences the effects of movement of the Intertropical Convergence Zone, and it is highly affected by interannual macro-climatic phenomena, such as El Niño– Southern Oscillation (ENSO). With the aim of increasing the use of global reanalysis and remote sensing data for supporting water management decisions at the watershed scale and within the framework of the eartH2Observe research project, the aridity index (AI) was calculated with three different data sources. Precipitation products and AI results were compared with their corresponding in-situ national official data. The comparison shows high correlations between the AI derived from observed data and AI obtained from the reanalysis, with Pearson correlation coefficients above 0.8 for two of the products investigated. This shows the importance of using global reanalysis data in water availability studies on a regional scale for the MCMB and the potential of this information in others macrobasins in Colombia including the Orinoquia and Amazon regions, where in-situ data is scarce.
Abstract. The generation of synthetic series is important for simulations of the behavior in the long term of a reservoir or systems of them. The Svanidze method is easy to use to generate periodic time series for a selected period of time (monthly, fortnightly, weekly). Compared with other methods (eg PAR, PARMA) this method does not require a normal distribution assumption for the series. In this work the Svanidze method was applied to obtain synthetic series of the daily inflow volume to the Las Cruces hydroelectric project, located in the state of Nayarit, Mexico; with this method we achieve the objective of reproducing the behavior of the historical series at least in its first moment (the mean). In addition, similar correlation coefficient are observed from one day to the next with respect to what happened historically.
Abstract. Accurate flood propagation and inundation models are crucial in flood risk assessments. For fast flowing rivers such as the Magdalena River (Colombia) with high vulnerability and exposure rates is even more essential. Indeed, floods in Magdalena River account for 90% of the damages and 70% of the causalities in Colombia. River cross-sectional information (i.e. their number and spacing) must be optimally selected to properly capture river’s hydraulic behaviour. Optimization is a powerful tool for doing such selection often necessary to increase the efficiency of field works and decrease model simulation time. A methodology based on the entropy concept provides interesting results in agreement with those proposed in literature. The optimization method proposes the use of two concepts belonging to information theory: the joint entropy and total correlation. Total correlation quantifies the redundancy of cross-sections; joint entropy provides their information content. This approach is applied to a reach of the Magdalena River. This study analyses the interrelation between the location of the optimal set of cross-sections and the hydraulic behaviour of the Middle-Magdalena River. Further work considers the evaluation of model performance with the optimized cross-sections, where no negative impacts on the reliability of flood profiles with respect to the original model are expected.
Abstract. Water treatments are progressively increasing their importance nowadays due to the gradual deterioration of water quality as a consequence of the environmental pollution and of industrial processes. Among these treatments, filtration still represents a major solution. In this work some results of a laboratory experimental analysis of the hydraulic performances of commercial cartridges for water treatment with filtration are presented in comparison with the results obtained by numerical simulations of the same physical model performed through the EPANET software. Specifically, the performance of filter cartridges is evaluated in terms of the head losses that they produce in the hydraulic systems in which they are introduced. These losses can be particularly undesirable for low-pressure plants, where they can inhibit the normal operation of the installed apparatus. Head losses also increase significantly with a prolonged use over time, due to the clogging particles retained on the outer surface and inside the cartridge, with a consequent reduction in the filtration capacity which generates the necessity to replace the cartridge itself. The comparison between numerical and experimental results showed a good agreement. The analysis of the data permitted to highlight several features of the filtration process in these commercial cartridges and draw up different remarks for their design and production.
Abstract. Coastal zone protection is a very crucial issue in order to defend populations and infrastructures as well as to environment conservation. Adequate tools must be tested and implemented for supporting engineering solutions to face this challenge. In this study, 1DH and 2DH models were applied to simulate wave hydrodynamics at Ofir beach, NW Portugal. For this purpose, COULWAVE (1DH) and BOUSS-2D (2DH) models were implemented considering both the presence of a detached breakwater and natural conditions aiming the study of the impact of these structures on the significant wave height and the wave energy. A comparison of the performance of the two models was also developed. The methodology adopted in this research work, where a generalised methodology of models applications was used, allows its replication to other coastal stretches being this application dependent on local environmental conditions.
Abstract. Over the past decade the research surrounding the occurrence, source, fate and removal of emerging pollutants has been increasing. The aim of this study was to create an add-on program which analyses the removal of emerging pollutants, to an existing decision support tool (WiSDOM). The tool was also used to evaluate the performance of each optimal solution in terms of removal of conventional pollutants using Multi Objective Genetic Algorithms and Multi Criteria Decision Analysis. Information was collated regarding minimum and maximum concentrations of emerging pollutants for surface water, groundwater, untreated wastewater, drinking water and treated wastewater. This information was used to populate an Excel Spreadsheet Program (ESP) which analysed the removal efficiencies of 13 different emerging pollutants for 42 wastewater treatment unit processes. The ESP is incorporated into the WiSDOM tool to allow the tool to calculate the removal of emerging pollutants. Three main scenarios were created to test the application of the tool and ESP. Scenario 1 focussed on the removal of emerging pollutants from from areas effected by tourism at different scales. Scenario 2 looked at the treatment suited for the removal of emerging pollutants from different socio- economic regions. Lastly, Scenario 3 looked at removing emerging pollutants from hospital and industrial wastewater. The scenarios were focused on wastewater treatment in India and investigated the removal of 13 emerging pollutants commonly found in India.
Abstract. The Climate change is judged to impact seriously to human society. Hence, assessing the variation of climatic factors in this process is indispensable to mitigate its negative impacts. Quang Nam Da Nang area covered 3 large river catchments (Vu Gia Thu Bon, Tam Ky, Cu De) is predicted to be affected violently by the change of climate, especially on water resources security, as well in hydrological disasters. With the aim of evaluating the consequences of climate change, the study utilizes a semi distributed hydrological model (SWAT model) to simulate the stream flow variation in Quang Nam Da Nang area. The model is constructed with specific catchment characteristics. It is calibrated and validated over a period of 38 years from 1979 to 2016 with the impressive coefficients (NASH reachs to 0.87, R reachs to 0.94). The data about climate change is supplied by Vietnamese Ministry of Natural Ressources and Environments.
Abstract. Groundwater is a fundamental component in the water balance of any watershed. It affects considerably on flow regime, especially on base flow. However, it is not easy to survey this component, notably towards the lack of data catchment and developping countries. This study is to present a new approach to overcome the limitation in simulating the ground water. By using the deterministic distributed hydrological model, the study is hope to provide basic information about ground water for a catchment in Vietnam coastal central region, Cu De river catchment. The modelling is realized for an area of 425.2 km2 in period of 2006 – 2010. The results are analyzed in many aspects such as: groundwater spatial distribution, groundwater flow process, groundwater storage, and groundwater recharged volume.
Abstract. Climate change is a complex problem and becoming the leading challenge for humankind in the 21st century. It will affect almost aspects of human well-being. Therefore, assessing climate change impacts on water resources and proposed solutions to respond to climate change is urgent and necessary. This study applied the SWAT model (Soil and Water Assessment Tool) and GIS (Geographic Information System) technique to simulate water flows due to the impact of climate change. The models were applied for Kon – Ha Thanh river catchment, located in Vietnam where is considered as one of the countries most affected by climate change. The SWAT model is calibrated and validated well using daily flow data with the Nash-Sutcliffe and correlation coefficients are 0.77 and 0.88, respectively. Two scenarios from Vietnamese government (RCP 4.5 and RCP 8.5) are used to analyze the variation of stream flow in three periods: 2016- 2035, 2045-2065, and 2080-2100. The results show that the flow in Kon – Ha Thanh rivers will vary complicatedly and severely under the impact of climate change. This flow may increase roughly 150.8% in flood season and reduce around 11.8% in dry season. Furthermore, the study also demonstrates that there are the changes in the flood dynamics as well as the hydrological shift of this region. This study presents an operational approach to integrate the results from the impacts of climate change to flood protection measures that would be useful in sustainable planning and devising resilience strategies.
Abstract. Water, energy and food are basic needs crucial to human survival but also pervade many aspects of human development. Systemically, they are vastly interdependent. A system dynamics model comprises five modules, namely water, food, energy, demographic, and human development, is being constructed. The aim is to evaluate the dynamics behaviour of water, energy and food systems and their linkages to human development at national scale. The model was simulated on annual basis from the year 1990 to 2015. It was then tested against national historical data of Indonesia. Analysis of error using mean-square error, root mean square percent error, and Theil inequality statistics were performed to test model behaviour. Preliminary results show that most of the variables such as total population, income per capita, human development index, and sectoral water demands have root mean square percent error below 10% that indicate the model produces similar behaviour pattern to the actual system. As part of the future work, once the model is fully constructed, it will be applied to assess the impact of a range of policy scenarios and implications on the water, energy and food sectors and on human development in Indonesia.
Abstract. Multi-objective evolutionary algorithms (MOEAs) are well known for their ability to optimise the water distribution network design problem. However, their complex nature often restricts their use to algorithm experts. A method is proposed for visualising algorithm performance that will enable an engineer to compare different optimisers and select the best optimisation approach. Results show that the convergence and preservation of diversity can be shown in a simple visualisation that does not rely on in-depth MOEA experience.
Abstract. It is well known that water distribution networks can be optimised by evolutionary algorithms. However, while such optimisation can result in mathematically optimal solutions, the ability of the algorithm to generate novelty can often lead to solutions that are not practical for implementation. This work describes a distributed optimisation platform that will enable the inclusion of a human decision maker in the optimisation process. The architecture of the platform is described, and examples of its execution on benchmark problems is described, using an automated client that interacts with the platform in lieu of a human decision maker.
Abstract. 3D numerical computations are performed to simulate the shallow water flow through an array of non-submerged cylinders occupying a circular area in the middle of the domain. A hydrodynamic model capable of capturing the free surface positions is developed with the SST (shear strain transport) k-ω turbulence closure. The model is first verified and validated against experimental data available in the literature. It is demonstrated that the present model can predict both the average velocity and turbulence structure well. In addition, both cylinder-scale flow as well as patch-scale flow can be well reproduced. The velocity field and distribution of bed stress are then analyzed to study the flow patterns and sediment deposition with different solid volume fractions and water depths.
Abstract. Water security is a global challenge, and intelligent water network is an important way for some countries and companies to solve regional water problems. Intelligent water network is a comprehensive and systematic water management platform, with river and lake water connected as a physical basis, through the introduction and adoption of new frontier information technology aids and advanced water management concepts to achieve water cycle and its associated process system and efficient Control as the goal. This paper studies the framework of intelligent water network, and presents three main elements of water physical network, water information network and water dispatching network, and discusses the case in Beijing.
Abstract. The fully 2D dynamic shallow water equations have been widely applied for numerical simulation of overland flow in the recent years. However, most of the existing friction term discretisation schemes do not recover the correct asymptotic flow behaviour as water depths becomes small. In this model, the shallow water equations were discretized by the framework of the Godunov-type finite volume scheme. The hydrostatic reconstruction is applied to reconstruct non-negative water depths at wet- dry interfaces. Numerical fluxes are computed with a HLLC solver. The novel aspects of the model include the slope source term treatment. Specific treatment of friction source terms has been proposed to discretize the friction terms to recover the correct asymptotic behaviour of SWEs when the water depth becomes small. The accuracy and robustness of the proposed model are verified by comparing with analytical solutions. The results demonstrate that the proposed method treating friction source term is a relatively more accurate, efficient, straightforward and universal one for evaluating overland flow problems.
Abstract. Ground-based rain-gauge stations are the most direct sources of precipitation data. The evaluation of rain-gauge network is essential and important for water management. One of the most popular methods for design of hydrometric network including rain- gauge network is information theory. Entropy concepts from information theory has been widely adopted and applied in rain-gauge network design. In this paper, spatial- temporal evaluation of rain-gauge network located in Shanghai, China will be performed based on entropy theory. The transinformation-distance (T-D) spatial model is applied under three different sampling frequencies. Weekly precipitation data fits the T-D model best. In addition, the representative network is evaluated to be suitable according to the result.
Abstract. Numerical model is an indispensable tool for understanding oceanographic phenomena and resolving associated physical processes. However, model error cannot be avoided due to limitations such as underlying assumption, insufficient information of bathymetry or boundary condition and so on. Data assimilation technique thus becomes an effective and essential tool to improve prediction accuracy. Updating of output is an efficient way to correct the model, but it is often carried out locally at specific locations in the model domain where measurement is available. In this study, instead of correcting output of numerical model locally, we propose to combine local correction and input correction to update open boundary of numerical model. The open boundary condition is corrected through spatial interpolation algorithm based on nearby observation in the hindcast period. Then the local forecast at measured location is distributed using the same interpolation scheme to update the boundary in the forecast period. Such boundary correction not only explores the variation in the future time step from the input updating but also allows the backbone physics embedded in numerical model to resolve the hydrodynamics in the entire computational domain.
Abstract. Based on sample entropy, we investigated spatial distribution and dynamic change of runoff series complexity with the long-term daily runoff series of main stem in the Yangtze River. The results showed that, complexity of the runoff series show an obvious spatial difference, and an increasing trend from upstream to downstream in the Yangtze River. There are negative relationship between average of runoff sliding window and the corresponding sample entropy, and their peak-to-valley value shows the well corresponding relationships. Complexity of the runoff series at Yichang and Datong stations show a continuous increasing trend, while that of Hankou station an increasing trend after 2000. It could provide scientific reference for understanding of runoff series dynamic evolution in the Yangtze River.
Abstract. In China, recently, quite a few water allocation projects have built its information systems. However, the design criteria of information systems are usually chaotic, and sometimes it is various degrees of over-developed. This paper consider that a design specification of information systems for water allocation projects must be issued soon. Depend on the current situation of information system design, some suggestion was proposed in this paper to discuss how to draft a design specification for water allocation project information system. The design specification will regulate the developing of information systems, save water resources, and finally improve the management level of water allocation projects.
Abstract. Detailed 1D/2D models have become standard practice for urban flood modelling. However, many applications require computationally fast simulation models. Due to their prolonged calculation times, these 1D/2D models are unsuited for such applications. This research compares three modelling approaches with different levels of complexity and simulation times: (1) a highly detailed 1D/2D model, (2) a 1D/1D model with two different flood cone parameterizations, and (3) a newly developed surrogate dual drainage model. The three approaches are tested and compared on a Belgian case study. Results show that the surrogate dual drainage model can emulate the results of highly detailed models with calculation time reductions in the order of magnitude of 105.
Abstract. The legislative norms for treated wastewater diffuse in terms of nitrogen (N) and phosphorus (P) concentrations are becoming increasingly stringent in the EU region. Compliance with the consent values compelled the water authorities to implement moving bed biofilters (MBFs) for tertiary stage effluent polishing. However, on-site and field surveys reveal that numerous MBF units suffer from non-optimal operational conditions, logistical challenges and irregular monitoring. This makes meeting the N-P criterion quite a challenging and expensive affair. It is therefore important to optimize their day-to-day operations, facilitate access to reliable and real-time status updates, and troubleshoot the failures. In this direction, an "internet-of-things", radio frequency ID (RFID) and cloud based monitoring and control tool, Sand-Cycle, was successfully developed, tested and implemented to monitor MBFs. The current study presents full- scale application of the developed remote control and mote technology at two wastewater treatment works. Sand-Cycle illustrated real-time dashboards indicating performance grading factors viz. in-situ average sand circulation rate, active bed volume and filter homogeneity. This presented clear instructions for detected malfunctions and enabled the operators to optimize the MBF output with limited effort. Further technical and technological advancements of such IoT based setups can actively assist in tackling long-term sustainability and wastewater management issues.
Abstract. A depth-averaged random walk scheme is applied to investigate the process of solute transport, including advection, diffusions and reaction. Firstly, the model is used to solve an instantaneous release problem in a uniform flow, for which analytical solutions exist. Its performance is examined by comparing numerical predictions with analytical solutions. The advantage of the random walk model includes high accuracy and small numerical diffusion. Extensive parametric studies are carried out to investigate the sensitivity of the predictions to the number of particles. The result reveals that the particle number influences the accuracy of the model significantly. Finally, the model is applied to track a pollutant cloud in the Thames Estuary, where the domain geometry and bed elevation are complex. The present model is free of fictitious oscillations close to sharp concentration gradients and displays encouraging efficiency and accuracy in solving the solute transport problems in a natural aquatic environment.
Abstract. Accurate forecasts of demand are essential for water utilities in order to manage, plan, and optimize the operation of their network. This work aims to develop a new method for short- term water demand forecasting by utilizing a new data-driven approach based on Random Forests, as well as consumption recordings, household, and socio-economic characteristics, and weather data. Initial results, obtained on real-life consumption data from the UK, demonstrate the potential of this method and show the importance of disaggregating consumption when attempting to determine the influence of weather on water demand. In this study, adding weather input to the model achieved improved forecasting accuracy, especially for the aggregation of properties with medium occupancy and affluent residents during summer months.
Abstract. Flooding is one of the most common types of natural hazards. The current practice of large-scale fluvial flood modelling relies on the use of hydrological models to predict upstream discharge hydrograph to drive inundation modelling at downstream. However, the oversimplified representation of both catchment topographies and hydraulics make hydrological models heavily rely on model parameterisation and calibration. This makes the modelling strategy unsuitable for prediction of extreme events featured with highly transient hydraulic processes, for which high-quality hydrological data is commonly missing to support model parameterisation and calibration. In this paper, the High-Performance Integrated hydrodynamic Modelling System (HiPIMS) has been adapted and applied to the whole 2500 km2 Eden catchment in the UK to reproduce the flood event caused by Storm Desmond in December, 2015. Without necessity of intensive calibration and using hydrographs as boundary conditions, satisfactory results have been obtained for both inundation extent and water level time series in channels, in comparison with observations. Accelerated by multiple modern graphic processing units (GPUs), the model runs more than 20 times faster than real time for the simulation of the whole catchment at 20m resolution. The results successfully demonstrate HiPIMS as a promising tool for real-time flood forecasting and flood risk assessment.
Abstract. The design and development of Flood Forecasting and Regulation System (FFRS) is an important part of non-structural measures for flood mitigation, and Browser/Server (B/S) system based on WEB technology is one of the main directions of the system development. The framework of FFRS based on B/S system is introduced in this paper, which includes four levels, i.e. the database level, application support platform level, the application level and the user level. The framework can provide several functions, such as flood situation analysis, flood forecasting, flood regulation and system management, which has been used for the FFRS development of Poyanghu Lake Basin in China as technical support for decision making of local flood control. Currently, the system covers almost 102 flood forecast points and 37 reservoirs, for which flood forecasts and regulations are accessible online. This work would also be demonstration for other locations.
Abstract. Storm surge and tsunami may induce violent shallow flows and carry dense debris, causing tremendous damage to human lives, buildings and structures. This work presents a series of laboratory experiments to investigate the debris movement in the extreme flows. Subsequently, a new modeling tool featured with a finite volume shock-capturing hydrodynamic model fully coupled with a discrete element model is introduced. A new coupling method totally depending on the hydrodynamic characteristics is proposed to simulate the complex debris-enriched floods induced by tsunamis or storm surges. The experimental measurements are used to validate the reliability of the coupled model. The numerical results agree satisfactorily with the experimental measurements, demonstrating the model’s capability in simulating the complex fluid-debris interactions induced by violent shallow flows.
Abstract. In this paper, the methodology of hydrological big-data standardization is discussed upon analyzing on the characteristics of hydrological data. Three main standards of hydrological data in China are considered in the standardization, which are respectively "Structure and identifier for real-time hydrological information database", "standard for structure and identifier in fundamental hydrological database" and "Structure and identifier for water quality database". Solutions on data pre-processing, data indexing and highly efficient data reading and writing are also introduced. The mass storage capacity and high speed computing capability of Hadoop are utilized for designing and implementing hydrological big-data sharing platform. Then a prototype of the hydrological big-data sharing platform is introduced in this article. Accordingly, the platform can be the technical support for information sharing and space integration between water conservancy industries and other industries, as well as the interdisciplinary sustainable development.
Abstract. The ECI is a multi-hazard index which has been developed in the context of the eXtreme Climate Facilities (XCF) project lead by ARC (African Risk Capacity) with the objective of detecting the occurrence of climate extremes over the African continent. The main hazards covered by ECI are the extreme dry, wet and heat events. However, the definition of ECI allows for the integration of additional hazards in the same index. The index has been designed and widely tested across Africa. The objective of this study is to test the usability and potential application of the same index under different climate regimes that are typical of the mid-latitudes, including the Mediterranean area and northern Europe. The analysis presented in this study shows that the ECI allows an accurate detection of extreme cold/heat waves as well as events of abundant precipitation across Europe over the last decades
Abstract. The water energy nexus– energy used for water – has received increasing attention in a changing world. With rapidly growing population and economic growth in urban areas, the demand of energy and water resources may subsequently rise. Since supply different water resources (such as transferred water and reclaimed water) requires different amount of energy, the city should perform a quantitative assessment of water energy nexus, and work out how to allocate various water resources to reduce urban energy consumption. Taking Jinan city as an example, this paper analyzes the advantages and disadvantages of using various types of water resources, predictions of the future trends in water use, and estimates unit electricity requirements for the supply of fresh water and the treatment of wastewater, and briefly depict the water energy nexus in the urban water resources allocation, and try to find a water resource - energy balance for the urban water allocation. This work would help to explore the water energy nexus for urban water resources management, and to optimize the allocation of water resources.
Abstract. A comprehensive understanding of water demand and its availability is essential for decision-makers to manage their resources and understand related risks effectively. Historical data play a crucial role in developing an integrated plan for management of water distribution system. The key is to provide high-resolution temporal-scale of demand data in urban areas. In the literature, many studies on water demand forecasting are available; most of them were focused on monthly-scales. Since monitoring of time series is a prolonged and costly procedure, the popularity of disaggregation methods is a most recent desirable trend. The objective of this research is to transfer low-resolution into high-resolution temporal scale using random cascade disaggregation and non-linear deterministic methods. This study defines a new technique to apply previously proposed random cascade method to disaggregate continuous data of the city of Peachland. The accuracy of the results is more than 90%. It represents a satisfactory application of the models. The proposed approach helps operators to have access to daily demand without acquiring high-resolution temporal scale values. Although the disaggregated values may not be precisely equal with observed values, it offers a practical solution for the low equipped WDS and leads to lesser number of drinking water-related problems.
Abstract. We present a method for partitioning Water Distribution Networks (WDNs) into District Metered Areas (DMAs) by using a spectral graph partitioning algorithm. The effectiveness of DMA design was tested for selected edge weights and multiple numbers of established DMAs. The presented method includes a novel graph theoretic approach to determine and evaluate only relevant combinations of DMA connection. It was tested on a real-life case study for which several different solutions were generated and evaluated against their hydraulic performance. The optimal solution, i.e. design of DMAs, was selected regarding the quality of partition and the cost of WDN segmentation, since hydraulic adequacy was met for all cases where partitioning resulted in connected subgraphs.
Abstract. A new numerical model for simulating overland flows has been developed using Godunov scheme based on the two-dimensional fully dynamic shallow water equations (SWEs). There are a number of frequently and partially submerged cells due to steep slopes, coarse meshes and small depth when simulating the surface runoff propagation, which are different from the original hydraulic applications such as flooding. In order to provide an accurate numerical solution for overland flows, the model in this work uses the Roe’s approximate Riemann solver for the calculation of fluxes on the triangulated unstructured grid based on the flow sheet regime, and the bottom slope terms are calculated directly by applying the Green’s theorem. To control the global stability of the model, the semi-implicit discretization method is adopted to deal with the highly nonlinear friction terms. The new model provides more comprehensive calculation capabilities, which are proved by several case studies, and the numerical results match well with analytical solutions, experimental data or results computed by other numerical models.
Abstract. National Flash Flood Disasters Investigation and Assessment project is the largest non-engineering projects in water conservancy industry in China, and also the largest scale of general census on disasters’ background in flood management and mitigation fields. Through general census, on-site investigation, field measurement, hydrological analysis and calculation, the spatial distribution, human settlement, underground situations, social and economic impacts, hazard zoning, warning indicators of flash flood disasters were collected, the storm flood characters in mountainous areas were analyzed, the flood control ability of selected villages were assessed, the critical rainfall index of these villages were obtained, and the hazard zones were finally identified, all of which provided a strong information support for flash flood early-warning and forecast and residential safety transfer. This paper systematically introduced the key technical focuses, made a general review on the data and information collected, and discussed the spatial distribution pattern of these elements. Based on these survey data, the characteristics of flash flood disaster prevention areas, the human settlement features and storm flood spatial distribution situation were further analyzed. In the end of this paper, future application and analysis on diversified utilization of national flash flood disasters investigation and assessment results were proposed.
Abstract. Complex transport mechanism and interaction between fluid and sediment make the mathematical and numerical modeling of sediment transport very challenging. Different types of models can lead to different results. This paper investigates a non-equilibrium sediment transport model based on the total load. In this type of model, it is assumed that a bed slide will occur if the bed slope reaches a critical angle. This is enabled by means of a slope failure operator. Existing slope failure operators usually suffer from the high computational cost and may fail at wet/dry interfaces. The main contribution of this work is the development of a novel slope failure operator for the total load transport model, based on a modified mass balance approach. The proposed approach is verified in three test cases, involving bank failure, dyke overtopping and a two-dimensional bank failure. It is shown that the proposed approach yields good agreement with analytical results and measurement data.
Abstract. A framework of predictions in ungauged basins (PUBs, taking Paniai lakes watershed, Indonesia as an example) for hydropower exploration is developed. In this framework, remote sensing technology and similar watershed method are used to collect necessary meteorological and topographical data for runoff simulation. Besides, a modified physical based distributed hydrological model is developed to consider the characteristics (regulation capacity of the lakes) of the watershed. Finally, considering the modeling purpose, annual average runoff index is used to assess the modeling results. In the case study (Paniai lakes watershed), TRMM precipitation, HWSD soil type, and AVHRR landcover data, combined with meteorological data from two similar watersheds, are collected to drive the modified hydrological model. According to the model results, the simulated potential evapotranspiration capacities and annual average runoff coefficients are consistent between the two cases (modeling with meteorological data of the two similar watersheds), and the simulated annual average runoff coefficients of the two cases are basically consistent with the observed annual average runoff coefficient of another similar watershed located in Indonesia.
Abstract. This study analyzed the combined effects of climate change and land use changes in the Yellow River Basin over the last 45 years. Based on the China Land-use Data for Hundred Years dataset (CLDH), East Asia daily precipitation data, and 6-h NCEP/NCAR reanalysis data, the Coupled Land Surface and Hydrology Model System (CLHMS) was applied to simulate the water cycle processes in the Yellow River under changing conditions from 1962 to 2006. During the study period, the evaporation, infiltration, and surface runoff in the Yellow River Basin all showed a decreasing trend. Comparative tests indicated that climate change was a major factor impacting water cycle variations.
Abstract. Hydromorphology is one of the key components of ecological integrity of a waterbody according to European Union Water Framework Directive (WFD). Therefore, hydromorphological quality assessment plays a significant role in evaluating the status of aquatic life. The aim of this study is to assess hydromorphological characteristics of Sakarya Watershed where hydromorphological alteration and anthropogenic pressures are significant. Morphological conditions of the streams, river continuity and hydrological regime are evaluated. In this study, hydrological foundation of the assessment is established using a hydrologic model, Water Evaluation and Planning Model (WEAP). Moreover, Geographic Information System (GIS) and Remote Sensing (RS) tools in addition to field surveys are used in the spatial and temporal evaluation of the hydromorphological characteristics in the study area. It is believed that the outcomes of this study will aid decision makers to develop sustainable management alternatives to improve ecological integrity in Sakarya Watershed.
Abstract. The integral porosity shallow water model (IP) is a modified form of the depth-averaged shallow water flow model, which utilizes porosities to account for unresolved sub-grid-scale topography such as buildings to enable fast urban flooding simulations. Existing research has repeatedly pointed out that the IP model is inherently oversensitive to the mesh de- sign. This paper presents a detailed grid convergence study of the IP model for simulating a laboratory experiment on the interaction between a dam-break wave and an obstacle in a channel, which is featured by the highly complex non-hydrostatic flow with a backwards- propagating hydraulic jump. We compare three different mesh refinement techniques with up to six levels of refinement: (1) uniform, (2) manual, (3) locally coarsened. For this investigated case, the modeling error due to the shallow water assumptions is more sig- nificant than that due to the porosity treatment. Neither a conventional shallow water model, nor the integral porosity model is able to predict the measured data well owning to non-hydrostatic flow conditions and a backwards propagating hydraulic jump. We show that the integral porosity model results converge to the conventional shallow water model results at locations that are not affected by these non-hydrostatic flow conditions. We conclude that, when the obstacle density is low, high-frequency oscillations may appear in the domain owing to Ka ́rma ́n vortex shedding. These cannot be captured accurately by the integral porosity shallow water model, unless high resolutions similar to those in the conventional shallow water models are used. However, the benefit of the porosity model is lost by using high resolutions.