Noniterative Implementation of Pressure-Dependent Demands Using the Hydraulic Analysis Engine of EPANET 2

To analyze water distribution networks under pressure-deficient conditions, most of the available hydraulic simulators, including EPANET 2, must be either modified by embedding pressure-dependent demands in the governing network equations or run repeatedly with successive adjustments made to specific parameters until a sufficient hydraulic consistency is obtained. This paper presents and discusses a simple technique that implements the square root relationship between the nodal demand and the nodal pressure using EPANET 2 tools and allows a water distribution network with pressure-dependent demands to be solved in a single run of the unmodified snapshot hydraulic analysis engine of EPANET 2. In this technique, artificial strings made up of a flow control valve, a pipe with a check valve, and a reservoir are connected to the demand nodes before running the engine, and the pressure-dependent demands are determined as the flows in the strings. The resistance of the artificial pipes is chosen such that the demands are satisfied in full at a desired nodal pressure. The proposed technique shows reasonable convergence as evidenced by its testing on example networks.     

Spatial Determinants of Urban Residential Water Demand in Fortaleza,Brazil

This paper aims at estimating the residential water demand function for the city of Fortaleza, Brazil, considering the potential impact of including spatial effects in the model. The empirical evidence is a unique micro-data set obtained through a household water consumption survey carried out in 2007. We estimated three econometric models, which have as explanatory variables the average/marginal price, the difference, income, number of male and female residents and the number of bathrooms, under different spatial specifications: the Spatial Error Model (SEM), the Spatial Autoregressive model (SAR), and finally, the Spatial Autoregressive Moving Average model (SARMA). Results suggest that the SARMA model is the “best” as shown by a series of tests. Such results contradict conclusions drawn by Chang et al. (Urban Geogr 31(7):953–972, 2010), House-Peters et al. (JAWRA J Am Water Resour Assoc 46(3), 2010), and Ramachandran and Johnston (2011). This means, among other things, that not controlling spatial effects is a key specification error, underestimating the effect of almost all variables in the model. Sometimes, these differences can be as high as 24.66 % and 13.32 % for price elasticity in the Average Price and the McFadden models, respectively.     

SCS-CN Based Quantification of Potential of Rooftop Catchments and Computation of ASRC for Rainwater Harvesting

Rooftop rainwater harvesting, among other options, play a central role in addressing water security and reducing impacts on the environment. The storm or annual storm runoff coefficient (RC/ASRC) play a significant role in quantification of potential of rooftop catchments for rainwater harvesting, however, these are usually selected from generic lists available in literature. This study explores methodology/procedures based on one of the most popular and versatile hydrological model, Soil Conservation Service Curve Number (SCS-CN) (SCS 1986) and its variants, i.e., Hawkins SCS-CN (HSCS-CN) model (Hawkins et al. 2001), Michel SCS-CN (MSCS-CN) model (Michel et al. Water Resour Res 41:W02011, 2005), and Storm Water Management Model-Annual Storm Runoff Coefficient (SWMM-ASRC) (Heaney et al. 1976) and compares their performance with Central Ground Board (CGWB) (CGWB 2000) approach. It has been found that for the same amount of rainfall and same rooftop catchment area, the MSCS-CN model yields highest rooftop runoff followed by SWMM-ASRC?>?HSCS-CN?>?SCS-CN?>?CGWB. However, the SCS-CN model has close resemblance with CGWB approach followed by HSCS-CN model, SWMM-ASRC, and MSCS-CN model. ASRCs were developed using these models and it was found that MSCS-CN model has the highest value of ASRC (= 0.944) followed by SWMM-ASRC approach (=0.900), HSCS-CN model (=0.830), SCS-CN model (=0.801), and CGWB approach (=0.800). The versatility of these models lies to the fact that CN values (according to rooftop catchment characteristics) would yield rooftop runoff and therefore ASRC values based on sound hydrological perception and not just on the empiricism. The models have inherent capability to incorporate the major factors responsible for runoff production from rooftop/urban, i.e., surface characteristics, initial abstraction, and antecedent dry weather period (ADWP) for the catchments and would be better a tool for quantification rather than just using empirical runoff coefficients for the purpose.     

A Contribution to the Study of the Phenomenon of Horizontal Infiltration

In this work an attempt is made to compare experimental soil moisture profiles for a horizontal infiltration experiment (Poulovassilis, Water Resour Res 13:369?C374, 1977) with calculated profiles. These calculated profiles are obtained variously through the use of the computation code of HYDRUS 1D and through the semi-analytical solution of the appropriate diffusion equation when the soil water diffusivity is obtained directly from the experimental data. The necessary input data for using HYDRUS 1D are obtained in three different ways: First, the experimental data of the main wetting branch of the moisture retention curve (MRC) coupled with Ks (the hydraulic conductivity at saturation) are used. Second the predicted, according to the Parlange model (Parlange, Water Resour Res 12:224?C228, 1976) main wetting branch of the MRC, when experimental data points of the main drying branch of the MRC are used. Third the predicted, according to the Mualem model (Mualem, Water Resour Res 13:773?C780, 1977) main wetting branch of the MRC, again when experimental data points of the main drying branch of the MRC, are used. In the previous three cases predicting appropriate hydraulic conductivity K(??) relationship is obtained through the model of Mualem (Water Resour Res 12:513?C522, 1976). The comparison of the above soil moisture profiles leads to the following: The numerically calculated profiles are moving faster than the experimental ones. Calculated profiles exhibit a Green?CAmpt-like shape. Differences among the experimental and calculated profiles are more pronounced in larger ??-values. Closer to the experimental profiles are those obtained semi-analytically. From the cumulative infiltration versus square-root of time curves, it is evident that the HYDRUS 1D results are compatible with the requirements imposed by the Boltzmann transformation.     

Estimation of Mean Annual Flood in Indian Catchments Using Backpropagation Neural Network and M5 Model Tree

This paper explored the potential of Backpropagation Neural Network (BNN) and M5 model tree based regression approach to estimate the mean annual flood. Data used in this study were taken from an earlier study by Swamee et al. (J Water Resour Plan Manage 121:403–407, 1995) for 93 Indian catchments spread over the entire country. The relationship proposed by Swamee et al. (J Water Resour Plan Manage 121:403–407, 1995) was compared with the predictive accuracy of a BNN and M5 model tree approach. The data were analyzed using a tenfold cross-validation. Comparison of the results showed that predictions with the backpropagation neural network fell within a scatter line of ±30% with a correlation coefficient of 0.975. Furthermore, predictions with the M5 model tree fell well within a scatter line of ±15% with a correlation coefficient as high as 0.994. The results also showed that predicted values with neural network and M5 model tree were within about 1.25 times the actual values. However, the predicted values obtained using the Swamee et al. (J Water Resour Plan Manage 121:403–407, 1995) approach fell much beyond the scatter line of ±50% and the predicted mean annual flood values were sometimes as high as eight times the actual values. The correlation coefficient with this approach was 0.897. The results from this study suggest that backpropagation neural network and M5 model tree-based modeling approaches are superior in accuracy to the model proposed by Swamee et al. (J Water Resour Plan Manage 121:403–407, 1995). This study also suggests that M5 model trees, being analogous to piecewise linear functions, have certain advantages over neural networks as they offer more insight into the generated model, are acceptable to decision makers and are very efficient in training, and always converge.     

Development of a Rainfall-Recharge Relationship for a Fractured Basaltic Aquifer in Central India

Groundwater being an important component of the hydrological cycle, estimation of its annual replenishment is essential to evolve a plan for optimum utilization. Groundwater balance approach, which is used extensively for the quantification of recharge and discharge components has been adopted for the rainfall-recharge estimation. Various inflow and outflow components have been identified and estimated for Sagar block in Sagar district of Madhya Pradesh, which faces acute water scarcity and continuous decline in groundwater levels. The computed recharge from rainfall varies between 122.45 and 183.71 MCM. The computed rainfall-recharge is compared with the Chaturvedi (1973), Kumar and Seethapathi (2002), Krishna (1987), and U.P. Irrigation Research Institute models. Models have also been developed to estimate rainfall-recharge for varying ranges of the annual rainfall and have been compared with the existing models. The relative error in estimation of rainfall-recharge from proposed models varies between 0.03 and 9.24%. The overall scenario is net decline in groundwater storage to an extent of ?31.31 MCM over a period of 16 years from 1985–1986 to 2000–2001. The trend analysis by Kendall’s rank correlation test, regression test for linear trend and Mann–Kendall test also clearly suggests falling trends in groundwater storage at 5% significant level, thereby demonstrating over-exploitation of the groundwater aquifer. This has subsequently led to progressive decline in groundwater table in the study area. Efforts should be initiated to tap the surface water by creating storages at suitable sites and artificial recharge practices should be encouraged after identifying suitable recharge zones. Conjunctive use of the surface and groundwater along with water conservation practices and groundwater management measures should be taken up to arrest the progressive decline in groundwater levels and over-exploitation of groundwater aquifer.     

Using the Meteorological Information for the Regional Rainfall Frequency Analysis: An Application to Sicily

Regional frequency analysis is a useful tool for accurate estimation of precipitation quantiles than at-site frequency analysis, especially in the case of regions with a short rainfall time series. The use of meteorological information, combined with rainfall data analysis, could improve the selection of homogeneous regions. Starting from 1958, 198 meteorological configurations, related to extreme events, have been identified throughout the national territory of Italy. The reanalyzed meteorological data of the 40 Year Re-analysis Archive (ERA-40) of the European Centre for Medium-Range Weather Forecast (ECMWF) have been analyzed to identify homogeneous regions with respect to the Convective Available Potential Energy (CAPE), the Q vector Divergence (QD) and the Vertically Integrated Moisture Flux (VIMF). The latter index appears to be the better candidate for finding regional homogeneity inside areas where high frequency values of CAPE or QD are present. The paper presents an application based on the delimitation of homogeneous regions using climatic indexes for the island of Sicily. By applying the proposed methodology, seven homogeneous areas over Sicily were found. The consistency of the final results has been validated by using a coupled approach based on the Valuation of Floods in Italy procedure (VAPI) and on the heterogeneity test of Hosking and Wallis (Water Resour Res 29:271–281, 1993, 1997).     

Modelling Water Distribution Systems with Deficient Pressure: An Improved Iterative Methodology

In the last three decades, many researchers have proposed different models for water distribution network (WDN) hydraulic analysis by head-driven analysis (HDA). By considering a pressure-discharge relationship (PDR), head-driven analysis (HDA) can avoid deviation caused by traditional demand-driven analysis (DDA) under abnormal conditions. Generally, there are three types of HDA models: 1) models achieved by embedding a PDR into DDA, 2) models using EPANET structures such as emitter or tank to take place of PDR, 3) models aiming at modifying nodal outflows to satisfy PDR based on EPANET. Among these models, modifying nodal outflows is flexible to simulate network with different PDRs and specify parameters related to PDR. Most of the models use iterative algorithms to solve HDA problems; however, present ways to ensure convergence of models are still inadequate. The purpose of this paper is to present a new way to meet the iterative convergence when modifying nodal outflows based on PDR and leakage. This new methodology has been incorporated into the hydraulic network solver EPANET and is formalized algorithmically as EPANET-IMNO. Then two typical networks are used to test EPANET-IMNO, and the results demonstrate that EPANET-IMNO can converge well and applied successfully both in static simulation and extended period simulation. Different pressure deficiency conditions are tested to further confirm the flexibility and the convergence of EPANET-IMNO. Furthermore, quality analysis results back that pressure reduction can be a practical way in contamination accident response.     

Parameter Identification for a Slug Test in a Well with Finite-Thickness Skin Using Extended Kalman Filter

Yeh and Chen (J Hydro 342(3?C4):283-294, 2007) integrated a slug test solution for a well having a finite-thickness skin with the simulated annealing (SA) to determine the hydraulic parameters of the skin zone and formation zone. Some results obtained in positive-skin scenarios are however not accurate if compared with the target values of the parameters. This study first employs the sensitivity and correlation analyses to quantify the relationship between two normalized sensitivities and analyze the resulting errors in parameter estimates. It is found that the inaccuracy in parameter estimates can be attributed to following two problems: (1) the normalized sensitivities of the skin thickness and hydraulic conductivity are highly correlated and (2) the SA algorithm is very sensitive to round-off error in well-water-level (WWL) data. A parameter identification approach is thus developed based on the extended Kalman filter (EKF) coupled with the solution used by Yeh and Chen (J Hydro 342(3?C4):283-294, 2007) to determine the parameters in six positive-skin scenarios where the parameters were not accurately determined before. We show that previous two problems can be overcome by the proposed approach because it is designed to account for uncertainties of measurements. Moreover, the EKF can save 99.8% and 99.9% computing time when compared with the results using the SA in analyzing 20 WWL data and 47 WWL data, respectively.     

The Brazilian Water Resources Management Policy: Fifteen Years of Success and Challenges

As a result of the increasing global awareness about the importance of water, many developed and developing countries have reviewed their water resources management policies and laws. In Brazil, Law 9,433, enacted in (1997), establishes the National Water Resources Policy (NWRP) and the National Water Resource Management System (NWRMS), introducing a new integrated approach to water resources management through the application of planning and economic instruments. At the institutional level, this brought many changes. A new institutional framework was established with the creation of river basin committees and water agencies. Almost 15 years after the Law took effect, these changes are still being implemented, and some adjustments have been necessary. In light of the Brazilian NWRP, this paper presents and analyzes the legal and institutional reform that has been taking place in Brazil’s water resources sector since 1997. An initial analysis shows that today, the implementation process still faces many challenges, hindering the effective consolidation of the instruments set out by Law 9,433/1997. The paper concludes that although Brazil’s model is generally in line with international trends, and despite the major progress that has been made to date, in some hydrographic regions the instruments conceived in the country’s model are still in the incipient stage of implementation, indicating that greater efforts are necessary, some of which are suggested in this article.     

Assessment of Environmental Flow Requirements by Entropy-Based Multi-Criteria Decision

Environmental flow methodologies based on hydrological indices have increasingly evolved, because they play an important role in a riverine ecosystem management. Moreover, human activities, such as dams, in many basins have altered their natural hydrologic processes and they also change habitat for aquatic and riparian species. Decision making by echo-managers considering these multi-variables has been subjective. Therefore, to provide eco-managers with guidelines, an eco-index with entropy related to the probability density function (pdf) and Ordered Weighted Averaging (OWA) operator is been suggested in this study. The index was applied to Geum River in South Korea with 33 Indicators of Hydrologic Alteration (IHA) by Richter et al. (1998) through IHA software (TNC 2009). The objective of this paper is to outline an entropy-based hydrologic alteration assessment of biologically relevant flow regimes using gauged flow data. On the Geum River, dams have affected river flow measured at four stations and the eco-index suggests that more attention needs to be paid to the tributaries between Gongju and Gyuam stations. Echo-Index with maximum entropy and OWA operator reflects the effect of every parameter and helps with determination considering multi variables. In future more temporal and spatial information needs to be examined for ecosystem alteration.     

A Comparison Between Conventional and M5 Model Tree Methods for Converting Pan Evaporation to Reference Evapotranspiration for Semi-Arid Region

In this study, the performance of M5 model tree and conventional method for converting pan evaporation data (E_p) to reference evapotranspiration (ET₀) were assessed in semi-arid regions. Conventional method uses pan coefficient (K_p) as a factor to convert E_p to ET₀. Two common K_p equations for pans with dry fetch (Allen et al. 1998; Abdel-Wahed and Snyder in J Irrig Drain Eng 134(4):425–429, 2008) were considered for the comparison. The values of ET₀ derived using these three methods were compared to those estimated using the reference FAO Penmane Monteith (FAO-PM) method under semi-arid conditions of the Khuzestan plain (Southwest Iran). The results showed that the M5 model is the best one to estimate ET₀ over test sites (0.5 mm d^?1 of root mean square error (RMSE) and 0.98 of coefficient of determination (R ²). Conversely, the performance of the two K_p equations was poor.     

Regional Frequency Analysis of Extreme Rainfalls in the West Coast of Peninsular Malaysia using Partial L-Moments

This study was to reinstate the development of regional frequency analysis using L-moments approach. The Partial L-moments (PL-moments) method was employed and a new relationship for homogeneity analysis is developed. For this study, the PL-moments for generalized logistic (GLO), generalized pareto (GPA) and generalized value (GEV) distributions were derived based on the formula defined by Wang (Water Resour Res 32:1767?C1771, 1996). The three distributions are used to develop the regional frequency analysis procedures. As a case of study, the Selangor catchment that consists of 30 sites which located on the west coast of Peninsular Malaysia has chosen as sample. Based on L-moment and PL-moment ratio diagrams as well as Z-test statistics, the GEV and GLO were identified as the best distributions to represent the statistical properties of extreme rainfalls in Selangor. Monte Carlo simulation shows that the method of PL-moments would outperform L-moments method for estimation of large returns period event.     

Modifiers and Amplifiers of High and low Flows on the Ping River in Northern Thailand (1921–2009): The Roles of Climatic Events and Anthropogenic Activity

We analyse an 89-year streamflow record (1921?C2009) from the Upper Ping River in northern Thailand to determine if anomalous flows have increased over time (Trenberth, Clim Res 47:123?C138, 1999; Trenberth, Clim Chang 42:327?C339, 2011). We also relate the temporal behavior of high and low flows to climatic phenomena and anthropogenic activities. Peak flows have not increased significantly since 1921. However, minimum flows showed a very significant downward trend over the study period (???=?0.01). Annual and wet season discharge show significant downward trends (???=?0.05). All flow variables appear to be more variable now than 90?years ago especially annual peak flows. Both annual peak and minimum flows are correlated with annual and wet season rainfall totals. Minimum flow is also sensitive to the length of the monsoon season and number of rainy days in the previous monsoon season. Peak flow activity is driven predominantly by climate phenomena, such as tropical storm activity and monsoon anomalies, but the relationship between peak flows and ENSO phenomena is unclear. In general, annual discharge variables did not correspond unequivocally with El Nin? or La Nin? events. Minimum flows show a major decline from the mid-1950s in line with major anthropogenic changes in the catchment. The plausible intensification of the hydrological cycle that may accompany global warming is of concern because of the potential to affect tropical storm activity and monsoon anomalies, phenomena that are linked with very high flows in this river system. The obvious effect of human activities such as reservoir management on low flows calls for careful management to prevent droughts in the future.     

City Blueprints: Baseline Assessments of Sustainable Water Management in 11 Cities of the Future

The necessity of Urban Water Cycle Services (UWCS) adapting to future stresses calls for changes that take sustainability into account. Megatrends (e.g. population growth, water scarcity, pollution and climate change) pose urgent water challenges in cities. In a previous paper, a set of indicators, i.e., the City Blueprint has been developed to assess the sustainability of UWCS (Van Leeuwen et al., Wat Resour Manage 26:2177–2197, 2012). In this paper this approach has been applied in 9 cities and regions in Europe (Amsterdam, Algarve, Athens, Bucharest, Hamburg, Reggio Emilia, Rotterdam, Oslo and Cities of Scotland) and in 2 African cities in Angola (Kilamba Kiaxi) and Tanzania (Dar es Salaam). The assessments showed that cities vary considerably with regard to the sustainability of the UWCS. This is also captured in the Blue City Index (BCI), the arithmetic mean of 24 indicators comprising the City Blueprint (Van Leeuwen et al., Wat Resour Manage 26:2177–2197, 2012). Theoretically, the BCI has a minimum score of 0 and a maximum score of 10. The actual BCIs in the 11 cities studied varied from 3.31 (Kilamba Kiaxi) to 7.72 (Hamburg). The BCI was positively correlated with the Gross Domestic Product (GDP) per person, the ambitions of the local authorities regarding the sustainability of the UWCS, the voluntary participation index (VPI) and all governance indicators according to the World Bank. The study demonstrated that the variability in sustainability among the UWCS of cities offers great opportunities for short-term and long-term improvements, provided that cities share their best practices.     

Method for Extended Period Simulation of Water Distribution Networks with Pressure Driven Demands

This paper proposes a non-iterative method to perform the simulation of water distribution systems with pressure driven demands using EPANET2 without the need to use its programmer’s toolkit. The method works for single period simulation (snapshot) and for extended period simulation (EPS) as well. It is based on the addition of a flow control valve (FCV), a throttle control valve (TCV), a check valve (CV) and a reservoir to each demand node in the network, in addition to a list of simple controls to modify the setting of the FCV and TCV in each time step. The main advantages of this approach are: 1. the source code of EPANET2 is not modified, 2. the toolkit functions are not needed for the simulation and they remain available for further uses, 3. the extended period simulation (EPS) is performed by EPANET2 and it carries tank levels, demand variation and other time-changing variables internally. The performance of the method is tested in two benchmark networks and a real size network with pumps, tanks and a 24 h demand pattern. The results show that the method computed the pressures and outflows accurately and that the computational time required is not significantly higher than a demand driven execution in most cases.     

Discussion of “Assessments of Impacts of Climate Change and Human Activities on Runoff with SWAT for the Huifa River Basin, Northeast China” by Aijing Zhang; Chi Zhang; Guobin Fu; Bende Wang; Zhenxin Bao; and Hongxing Zheng

Zhang et al. (Water Resour Manag doi:10.1007/s11269-012-0182-2, 2012) studied the impacts of climate change and human activities on the runoff for the Huifa River basin. They employed a soil and water assessment tool (SWAT), which was calibrated for the baseline period 1956–1964, and then used to reconstruct the natural runoff for the climate change period 1965–2000. Results showed that both climate change and human activities decrease the observed runoff. Climate change impacts on annual runoff were ?37.7, ?59.5, +36.9, and ?45.2 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively, compared with the baseline period 1956–1964. Human activities decreased runoff and caused a relatively larger magnitude impact than those of climate change after 1985. Human activities decreased the annual runoff by ?32.9, ?46.8, ?67.8, and ?54.9 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively. Human activities further decreased runoff in wet years due to regulation and storage of water projects.     

Use of Gene-Expression Programming to Estimate Manning’s Roughness Coefficient for High Gradient Streams

Manning’s roughness coefficient (n) has been widely used in the estimation of flood discharges or depths of flow in natural channels. Therefore, the selection of appropriate Manning’s n values is of paramount importance for hydraulic engineers and hydrologists and requires considerable experience, although extensive guidelines are available. Generally, the largest source of error in post-flood estimates (termed indirect measurements) is due to estimates of Manning’s n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for estimating n values. The objective of this study was to develop a soft computing model in the estimation of the Manning’s n values using 75 discharge measurements on 21 high gradient streams in Colorado, USA. The data are from high gradient (S?>?0.002 m/m), cobble- and boulder-bed streams for within bank flows. This study presents Gene-Expression Programming (GEP), an extension of Genetic Programming (GP), as an improved approach to estimate Manning’s roughness coefficient for high gradient streams. This study uses field data and assessed the potential of gene-expression programming (GEP) to estimate Manning’s n values. GEP is a search technique that automatically simplifies genetic programs during an evolutionary processes (or evolves) to obtain the most robust computer program (e.g., simplify mathematical expressions, decision trees, polynomial constructs, and logical expressions). Field measurements collected by Jarrett (J Hydraulic Eng ASCE 110: 1519–1539, 1984) were used to train the GEP network and evolve programs. The developed network and evolved programs were validated by using observations that were not involved in training. GEP and ANN-RBF (artificial neural network-radial basis function) models were found to be substantially more effective (e.g., R² for testing/validation of GEP and RBF-ANN is 0.745 and 0.65, respectively) than Jarrett’s (J Hydraulic Eng ASCE 110: 1519–1539, 1984) equation (R² for testing/validation equals 0.58) in predicting the Manning’s n.     

A Numerical Model of the Wave that Overtopped the Vajont Dam in 1963

The Vajont landslide took place in northern Italy on October 9th 1963 and caused a huge impulse wave to travel along the artificial reservoir and overtop the dam, flooding and devastating a considerable area along the Piave riverbed. In this event about 1900 people died, 1700 of them in the Piave Valley alone. The water depth of the wave in some points exceeded 50 m. Although the phenomenon is clearly tridimensional, the application of a pure 3D hydraulic numerical model to this wide and natural territory is very complicated. Recently, the authors have presented a numerical model of the impulse wave that wasted the Vajont basin as a consequence of the landslide Bosa and Petti (Environ Model Softw 26:406–418, 2011). In this paper, a 2DH numerical model has been applied to study the effects of the overtopping wave in the Piave Valley, in order to verify if the simplifications assumed by a 2DH model still make it possible to describe the evolution of the wave in the proper manner.     

HydroGen: an Artificial Water Distribution Network Generator

Many (metaheuristic) techniques for water distribution network (WDN) design optimisation already have been developed. Despite of the aforementioned scientific attention, only few, high-quality benchmark networks are available for algorithm testing, which, in turn, hinders profound algorithm testing, sensitivity analysis and comparison of the developed techniques. This absence of high-quality benchmark networks motivated us to develop a tool to algorithmically generate close-to-reality virtual WDNs. The tool, called HydroGen, can generate WDNs of arbitrary size and varying characteristics in EPANET or GraphML format. The generated WDNs are compared to (and shown to closely resemble) real WDNs in an analysis based on graph-theoretical indices. HydroGen is used to generate an extensive library of realistic test networks on which (metaheuristic) methods for the optimisation of WDN design can be tested, allowing researchers in this area to run sensitivity analyses and to draw conclusions on the robustness and performance of their methods.