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The development of rainfall/runoff models involves extensive computation and the availability of different coexisting platforms, including numerical flow models and GIS for their physiographical characterization. In this paper we present a data-driven approach which avoids the use of GIS, but is based on a combination of Principal Component Analysis (PCA) and an Adaptive Neuro Fuzzy Inference System (ANFIS) to produce a simple and effective output flow prediction based on previous rainfall/runoff data in the catchment. The emphasis of the paper is on how to set-up an efficient data structure that produces a good output flow estimation. The PCA approach is compared to the Thiessen polygons method, requiring GIS, and we demonstrate that the former can produce a better ANFIS model, with less algorithmic complexity and improved accuracy. The combined PCA + ANFIS procedure is applied to two minor river basins in Tuscany, Italy, to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Abstract: Landscape metrics are used in a wide range of environmental studies such as land use change and land degradation studies, soil erosion and run-off predictions, management of hunting communities, and strategic planning for environmental management, to name just a few. Due to their utility for a variety of applications, there are many indices and software packages that have been designed to provide calculations and analysis of landscape structure patterns in categorical maps. With the purpose of making a comparison between the most used tools (Fragstats, V-Late, PA4…), this paper examines their advantages and disadvantages in order to create a list of common features that need to be incorporated into this type of software. An Application Programming Interface (API) is produced without limitations on data input, that is capable of calculating vector or raster metrics and is extensible. This API should make it possible not only to build third party applications easily, but also make it possible to add new metrics and research into new paradigms related to traditional landscape metrics. Land-metrics DIY (Do It Yourself) is the library presented in this paper. It can calculate almost 40 landscape metrics from geometry provided by an ESRI Shapefile. [Copyright &y& Elsevier]

Abstract: The Representative Elementary Watershed (REW) approach for modeling the hydrologic response of watersheds is based on the discretization of a catchment into hydrologically sensitive control volumes. Global balance laws for mass, momentum (and energy) are formulated for the volumes. An implementation of the approach requires closing unknown REW-scale mass fluxes and forces exchanged across the REW-internal control volume boundaries and between REWs. In the present paper we focus exclusively on the horizontal groundwater flow, while neglecting other hydrological processes such as surface runoff, subsurface stormflow and surface-groundwater interaction. Here we describe a simplified groundwater modeling approach, which is based on the parsimonious estimation of mass fluxes exchanged laterally between REWs. The procedure employs principles of mass and energy conservation as stated by the Kirchhoff laws. The problem is reduced to the solution of a coupled system of linear equations in terms of inter-REW groundwater fluxes and a dimensionless ratio Θ between the local saturated zone depths ys and spatial length scales Λ over which piezometric head gaps are dissipated. The equation system is solved by successive approximation, as suggested by the Cross method, which is used in engineering practice for resolving resistor networks under steady state conditions. The procedure converges rapidly for complex network configurations. It is shown that for given boundary fluxes imposed at the watershed edges, mass fluxes exchanged in-between REWs can be calculated in an unique and consistent fashion. The paper briefly reviews the essential governing equations, introduces the formulation of the problem in terms of the Kirchoff laws and shows the numerical solution of the network. Simulation results for an application to the Hesbaye groundwater system in Belgium are presented. [Copyright &y& Elsevier]

This paper presents a case study in assessment of erosion hotspots in an Andean watershed. To do this, we made use of an interface called Geospatial Modelling of Soil Erosion (GEMSE): a tool that integrates Geographical Information Systems (GIS) with the Water Erosion Prediction Project (WEPP) model. Its advantages are: (i) it is independent of any special GIS software used to create maps and to visualize the results; (ii) the results can be used to produce response surfaces relating outputs (e.g. soil loss, runoff) with simple inputs (e.g. climate, soils, topography); (iii) the scale, resolution and area covered by the different layers can be different among them, which facilitates the use of different sources of information. The objective of this paper is to show GEMSE''s performance in a specific case study of soil erosion in La Encañada watershed (Peru) where the hillslope version of WEPP has been previously validated. Resulting runoff and soil loss maps show the spatial distribution of these processes. Though these maps do not give the total runoff and soil loss at the watershed level, they can be used to identify hotspots that will aid decision makers to make recommendations and plan actions for soil and water conservation. [Copyright &y& Elsevier]

Abstract: This paper investigates the model sensitivities to input parameter values in a Biophysical Toolbox for integrated catchment assessment and management of land and water resources. The toolbox was developed for application in the highland regions of northern Thailand. It incorporates the IHACRES rainfall-runoff model, a crop model (CATCHCROP), and an erosion model (a Universal Soil Loss Equation [USLE], modified for application to northern Thailand). In developing the individual models in the Biophysical Toolbox, emphasis was placed on limiting model complexity. The toolbox was developed and tested using data from the Mae Chaem catchment in northern Thailand. Due to the short duration and sparse distribution of the available data, the complexity of the model structure is constrained to consider only the key processes of interest. Despite the relative simplicity of the individual models, linkages between the models encompassed in the Biophysical Toolbox increase the complexity of the modelling system. This paper explores sensitivities in the Biophysical Toolbox to the parameters of CATCHCROP as this component has the greatest potential for propagating errors though the Toolbox. A simple sensitivity analysis was undertaken, whereby parameter values were perturbed to ascertain the effect of these perturbations on output indicators. The hydrologic component showed strong non-linearity to the infiltration parameters of the CATCHCROP model, although this did not greatly impact estimates of total annual discharge. Additionally, a number of CATCHCROP parameters did not greatly impact some output indicators of the toolbox. While the CATCHCROP model is relatively parsimonious when compared with many crop models, there are still 19 model parameters that must be determined from the field or prescribed from the literature. There is potential for the model to be further simplified although more extensive model testing is required to ensure that such simplifications would not adversely impact on the utility of the toolbox. [Copyright &y& Elsevier]

In this paper, an optimization framework for complex environmental management problems involving multiple stakeholders is developed and illustrated. In the framework, problems are represented as a series of smaller, interconnected optimization problems, reflecting individual stakeholders’ interests. The framework uses interactive visual analytics to explore and analyse optimization results, and the concept of Best Alternatives to a Negotiated Agreement (BATNAs) and an approach to reframe visualizations to encourage stakeholder negotiation. To demonstrate the utility of the framework, it is applied to a realistic case study involving multiple stakeholder groups funding different stormwater best management practices (BMPs) for a catchment management plan for a region of a large city in Australia. The problem features a total of sixteen objectives for four stakeholders. The results indicate that the proposed framework enables the identification of solutions that provide optimal trade-offs between many objectives and provides an effective and efficient means of assisting stakeholders with identifying acceptable solutions. [ABSTRACT FROM AUTHOR]

Integrated environmental modeling (IEM) provides a systematic way to couple models for integrated analysis. Coupled models in IEM often exchange data at runtime for time-step based executions. It is a challenge to track which raw observations or intermediate data exchanged at runtime contribute to individual model outputs. Time-step level provenance is needed to audit the trail of model execution or perform diagnosis in case of anomalies. This paper introduces a method to support provenance awareness in IEM. It suggests that individual models should expose necessary interfaces for provenance capturing in IEM environments. The provenance is represented using the W3C PROV model for interoperability. Fine-grained provenance is inferred based on coarse-grained provenance and temporal characteristics of computations of numerical time marching models. The approach is implemented in OpenMI-compliant models. A case study of model provenance tracking and inference on the watershed runoff simulation scenario illustrates the applicability of the approach. [ABSTRACT FROM AUTHOR]

Due to inherent bias the climate model simulated precipitation and temperature cannot be used to drive a hydrological model without pre-processing – statistical downscaling. This often consists of reducing the bias in the climate model simulations (bias correction) and/or transformation of the observed data in order to match the projected changes (delta change). The validation of the statistical downscaling methods is typically limited to the scale for which the transformation was calibrated and the driving variables (precipitation and temperature) of the hydrological model. The paper introduces an R package ”musica” which provides ready to use tools for routine validation of statistical downscaling methods at multiple time scales as well as several advanced methods for statistical downscaling. The musica package is used to validate simulated runoff. It is shown that using conventional methods for downscaling of precipitation and temperature often leads to substantial biases in simulated runoff at all time scales. [ABSTRACT FROM AUTHOR]

The effectiveness of genetic programming (GP) in rainfall-runoff modelling has been recognized in recent studies. However, it may produce misleading estimations if autoregressive relationship between runoff and its antecedent values is not carefully considered. Meanwhile, GP evolves alternative models of different accuracy and complexity, where selecting a parsimonious model from such alternatives needs extra attention. To cope with these problems, this paper proposes a new hybrid model that integrates moving average filtering with multigene GP and uses Pareto-front plot to optimize the evolved models through an interactive complexity-efficiency trade-off. The model was applied to develop single- and multi-day-ahead rainfall-runoff models and compared to stand-alone GP, multigene GP, and multilayer perceptron as the benchmarks. The results indicated that the new model provides substantial improvements relative to the benchmarks, with prediction errors 25–60% lower and timing accuracy 80–760% higher. Moreover, it is explicit and parsimonious, motivating to be used in practice. [ABSTRACT FROM AUTHOR]

The application of a model to different study areas often requires that the model be modified to conform to specific characteristics, but this can be challenging due to the poor readability and reusability of the legacy codes. Component-based programming supported by a modelling framework provides a generic means to develop and modify models. This paper describes the development of a distributed hydrological model using a component-based modelling framework, which is implemented as a set of functional components that are integrated at runtime. The model was applied to runoff simulation in a large scale and data scarce alpine basin, and was further improved by incorporating a simple empirical soil freezing-thawing component. The results show that the componentised model reproduced the daily and monthly flow hydrograph with ‘good’ accuracy. The framework is shown to be flexible enough for model development and model modification. [ABSTRACT FROM AUTHOR]

Conceptual rainfall runoff models are used extensively in practice, as they provide a good balance between transparency and computational and data requirements. However, the degree to which they are able to represent underlying physical processes is poorly understood. This is because the performance of such models is generally assessed based on their ability to match total streamflow, rather than component processes. In this paper, the ability of the Australian Water Balance Model (AWBM) to represent baseflow and quickflow is assessed for 66 synthetic catchments with different physical characteristics and hydrological inputs under seven calibration regimes utilising a shuffled complex evolution (SCE) algorithm. The “observed” total-, base- and quick-flow hydrographs for these catchments are generated using HydroGeoSphere. The results indicate that while AWBM is generally able to match total streamflow well, the same does not apply to baseflow and quickflow, suggesting that these processes are not represented well by AWBM. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, sensitivity analysis (SA) has been used to assess model sensitivities to input parameter values in a water quality model. The water quality model incorporates a rainfall-runoff sub-model and a sediment load estimation sub-model, and is calibrated against hydrologic and water quality data from the Moruya River catchment in southeast Australia. The tested methods, One-at-A-Time (OAT), Morris Method (MM) and Regional SA (RSA) are found to be complementary, and help to characterise the behaviour of the water quality model. The most important parameters are plant stress threshold (f), coefficient of evapotranspiration (e), catchment moisture threshold (d), in decreasing order, indicating that sediment and nutrient loads are more sensitive to parameters that affect the magnitude of flows than those (v s , τ q , τ s ) that control the timing and shape of the peak in a time series. But this application shows a need to be flexible in the use of different SA techniques. RSA is more appropriate for complex models where system nonlinearities and parameter interactions are more likely to be important. The RSA suggests that f and v s have strong interactions in the influence on nitrogen estimation. This study is also valuable for future uncertainty analysis, by separating the source of uncertainty of model parameters from the uncertainty in the model inputs. [Copyright &y& Elsevier]

Abstract: River streamflow is closely related to the surface runoff over a river basin. It is a quantity which can be measured with relatively high accuracy. In regional hydrologic models, surface runoff is usually calculated as the residuum of the surface water balance equation and is one of the most uncertain model outputs, especially for mountainous areas. In this paper, we propose a simple method within the framework of a regional hydrologic modelling system (RHMS), which integrates a hydrologic model and a land surface model, to constrain the estimates of surface runoff through progressive assimilation of observed streamflow data based on the channel flow equation. The proposed method is applied to a sub-basin of the Huaihe River Basin in East China, and numerical experiments are carried out to test the effectiveness of successively (from upstream to downstream) assimilating the streamflow data collected at three hydrological stations to RHMS. It is found that with the assimilation, the timing and magnitudes of the modelled flood peaks are much improved and the correction of surface runoff is substantial. The numerical results demonstrate the usefulness of the new method in improving the RHMS runoff-streamflow simulation as well as providing better initial conditions (e.g. channel water heights) for flood forecasting. [Copyright &y& Elsevier]

Abstract: This study presents a new algorithm, called the Weighted Adaptive Stormwater Infrastructure (WASI) algorithm, to calculate weighted flow-accumulation of surface runoff by considering man-made stormwater infrastructure that modifies natural drainage flow paths across the landscape. The WASI algorithm incorporates ancillary data sets required to determine the depth of effective rainfall (i.e., rate of precipitation plus subsurface return flow, rate of evapotranspiration plus infiltration, duration of rainfall, depth of initial absorption to ground) and a priori information on surface and underground stormwater infrastructure into grid-based hydrologic analysis using a DEM. Using new software, named the WASI surface runoff calculator (implemented as part of this study), the WASI algorithm can be applied to urban and suburban areas where both surface and underground stormwater infrastructure is installed. This paper describes the concept and details of the WASI algorithm, as well as its applications to synthetic and real-world data sets which revealed that the new software can provide more accurate hydrologic information than other commercial GIS software such as IDRISI and ArcGIS. [Copyright &y& Elsevier]

Abstract: Reference crop evapotranspiration (ETo) estimation is of importance in irrigation water management for the calculation of crop water requirements and its scheduling, in rainfall-runoff modeling and in numerous other water resources studies. Due to its importance, several direct and indirect methods have been employed to determine the reference crop evapotranspiration but success has been limited because the direct measurement methods lack in precision and accuracy due to scale issues and other problems, while some of the more accurate indirect methods, e.g. the Penman–Monteith benchmark model, are extremely non-linear and require weather input data that are not routinely monitored. In such situations, artificial intelligence (AI), neural computing techniques that are able to accurately map complex, non-linear input-output relationships offer a useful alternative. This paper has used the Kohonen Self-Organizing Map (SOM), unsupervised artificial neural networks, to develop prediction models for the ETo. This was achieved by using the powerful clustering capability of the SOM to analyze the multi-dimensional data array comprising the estimated ETo (based on the FAO Penman–Monteith model) and different subsets of climatic variables known to affect it. The findings indicate that the SOM-based ETo estimates, even when forced with fewer input data variables, were in good agreement with those obtained using the conventional FAO Penman–Monteith formulation employing the full complement of weather data. Further comparisons were carried out between the SOM model estimates of the ETo and those based on the use of feed-forward back propagation supervised artificial neural networks and the results showed that the SOM estimates were superior. Finally, the SOM-based estimates were also found to be significantly superior to those estimated using established empirical ETo methods recommended in the literature for situations where the full complement of input weather needed to drive the Penman–Monteith model are unavailable. This offers significant potential for more accurate estimation of the ETo in data scarce regions of the world. [Copyright &y& Elsevier]

Abstract: Stormwater models are important tools in the design and management of urban drainage systems. Understanding the sources of uncertainty in these models and their consequences on the model outputs is essential so that subsequent decisions are based on reliable information. Model calibration and sensitivity analysis of such models are critical to evaluate model performance. The aim of this paper is to present the performance and parameter sensitivity of stormwater models with different levels of complexities, using the formal Bayesian approach. The rather complex MUSIC and simple KAREN models were compared in terms of predicting catchment runoff, while an empirical regression model was compared to a process-based build-up/wash-off model for stormwater pollutant prediction. A large dataset was collected at five catchments of different land-uses in Melbourne, Australia. In general, results suggested that, once calibrated, the rainfall/runoff models performed similarly and were both able to reproduce the measured data. It was found that the effective impervious fraction is the most important parameter in both models while both were insensitive to dry weather related parameters. The tested water quality models poorly represented the observed data, and both resulted in high levels of parameter uncertainty. [Copyright &y& Elsevier]

Abstract: Environmental modeling frameworks support scientific model development by providing model developers with domain specific software libraries which are used to aid model implementation. This paper presents an investigation on the framework invasiveness of environmental modeling frameworks. Invasiveness, similar to object-oriented coupling, is defined as the quantity of dependencies between model code and a modeling framework. We investigated relationships between invasiveness and the quality of modeling code, and also the utility of using a lightweight framework design approach in an environmental modeling framework. Five metrics to measure framework invasiveness were proposed and applied to measure dependencies between model and framework code of several implementations of Thornthwaite and the Precipitation-Runoff Modeling System (PRMS), two well-known hydrological models. Framework invasiveness measures were compared with existing common software metrics including size (lines of code), cyclomatic complexity, and object-oriented coupling. Models with lower framework invasiveness tended to be smaller, less complex, and have less coupling. In addition, the lightweight framework implementations of the Thornthwaite and PRMS models were less invasive than the traditional framework model implementations. Our results show that model implementations with higher degrees of framework invasiveness also had structural characteristics which previously have been shown to predict poor maintainability, a non-functional code quality attribute of concern. We conclude that using a framework with a lightweight framework design shows promise in helping to improve the quality of model code and that the lightweight framework design approach merits further attention by environmental modeling framework developers. [Copyright &y& Elsevier]

Abstract: Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. <10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results. [Copyright &y& Elsevier]

Abstract: Erosive runoff is a recurring problem and is a source of sometimes deadly muddy floods in the Pays de Caux (France). The risk results from a conjunction of natural factors and human activity. Efficient actions against runoff in agricultural watersheds are well known. However they are still difficult to implement as they require co-operation between stakeholders. Local actors thus need tools to help them understand the collective consequences of their individual decisions and help to initiate a process of negotiation between them. We decided to use a participatory approach called companion modelling (ComMod), and, in close collaboration with one of the first group of local stakeholders, to create a role-playing game (RPG) to facilitate negotiations on the future management of erosive runoff. This paper describes and discusses the development of the RPG and its use with other groups of local stakeholders within the framework of two game sessions organized by two different watershed management committees. During the joint construction step, stakeholders shared their viewpoints about the environment, agents, rules, and how to model runoff in preparation for the creation of the RPG. During the RPG sessions, two groups of eight players, including farmers, mayors and watershed advisors, were confronted with disastrous runoff in a fictive agricultural watershed. Results showed that they managed to reduce runoff by 20–50% by engaging a dialogue about grass strips, storage ponds and management of the intercrop period. However, further progress is still needed to better control runoff through the implementation of better agricultural practices because, during the RPG sessions, the watershed advisors did not encourage farmers to do so. Because of the complexity of management problems, results of jointly constructing the game and the RPG sessions showed that modelling and simulation can be a very useful way of accompanying the collective learning process. This new way of working was welcomed by the participants who expressed their interest in organizing further RPG sessions. [Copyright &y& Elsevier]

This paper introduces a simple two-layer soil water balance model developed to Bridge Event And Continuous Hydrological (BEACH) modelling. BEACH is a spatially distributed daily basis hydrological model formulated to predict the initial condition of soil moisture for event-based soil erosion and rainfall–runoff models. The latter models usually require the spatially distributed values of antecedent soil moisture content and other input parameters at the onset of an event. BEACH uses daily meteorological records, soil physical properties, basic crop characteristics and topographical data. The basic processes incorporated in the model are precipitation, infiltration, transpiration, evaporation, lateral flow, vertical flow and plant growth. The principal advantage of this model lies in its ability to provide timely information on the spatially distributed soil moisture content over a given area without the need for repeated field visits. The application of this model to the CATSOP experimental catchment showed that it has the capability to estimate soil moisture content with acceptable accuracy. The root mean squared error of the predicted soil moisture content for 6 monitored locations within the catchment ranged from 0.011 to 0.065cm3 cm−3. The predicted daily discharge at the outlet of the study area agreed well with the observed data. The coefficient of determination and Nash–Sutcliffe efficiency of the predicted discharge were 0.824 and 0.786, respectively. BEACH has been developed within freely available GIS and programming language, PCRaster. It is a useful teaching tool for learning about distributed water balance modelling and land use scenario analysis. [Copyright &y& Elsevier]

Abstract: This paper introduces a fuzzy rule-based model to estimate runoff in a tropical watershed using the Soil Conservation Service Curve Number model. The data used were collected within a tropical watershed covered by Atlantic forest and pasture and involved map compilation, ASTER multispectral data processing and fieldwork. The computer models were developed using the PCRaster Environmental Modeling Language. Fuzzy theory allowed the mathematical modeling in zones of imprecision and/or uncertainties as fuzzy theory considers the transition zones among geo-objects. The evaluation of runoff derived from fuzzy and boolean methods demonstrated that the former provided calculated runoff closer to the measured runoff in the watershed, confirming the suitability of the fuzzy theory in modeling natural phenomena. [Copyright &y& Elsevier]

Abstract: This paper aims to present a rainfall-runoff model that was recently released into the public domain via the World Wide Web. The model, AFFDEF, is spatially distributed (grid based) and performs continuous time simulations of river flows at any time step and at any location in the catchment. It does not, however, account for snowmelt. Conceptual and physically based schemes are employed for simulating the rainfall–runoff transformation. AFFDEF''s main strength is its computational efficiency, which allows the model to perform long simulation runs (e.g. thousands of years at hourly time step). Furthermore, AFFDEF does not require extensive information in terms of historical hydrological data or geomorphology of the contributing area. It may, therefore, represent a powerful tool for performing hydrological simulation studies. The model code, written in FORTRAN programming language, provides a user friendly and ready to use tool that runs on personal computers, as well as UNIX systems. We believe that AFFDEF may represent an easy model to use and attractive instrument for hydrological applications where long simulation runs of river flows are needed at different locations of the catchment. Of particular interest is the possibility to generate river flows data in ungauged cross-sections of the watershed. [Copyright &y& Elsevier]

Nodal network approaches are a common framework for considering water allocation in river basins. In this type of model framework, a river basin is represented as a series of nodes, where nodes generally represent key points of extraction or instream use. When considering water allocation, agricultural production and other water use decisions generally interact with the stream system in two ways: they can affect the generation of runoff and thus the volume of water reaching the stream; or, they may involve direct extraction or use of water once it has reached the stream. Models are generally required to consider the influence of these decisions on flows and downstream water availability, as well as the influence of flows on the productive, passive use and environmental values of water. This paper provides a generalised conceptual framework for considering these types of interactions and their representation in integrated water allocation models. Applications of this framework to three very different case studies are outlined. [Copyright &y& Elsevier]

Storm Water Management Model (SWMM), a hydrodynamic rainfall-runoff and urban drainage simulation model, is widely applied in planning, analysis, and design. It is worth mentioning that the hydrological and hydrodynamic simulation functions of SWMM can also provide decision support for real-time urban stormwater management. However, it remains challenging to directly apply traditional SWMM to real-time urban stormwater management based on web technology. Here we designed and implemented a web service framework based on SWMM (WEB-SWMM), which can provide real-time computing services for urban water management. To test the functionality, efficiency, and stability of the WEB-SWMM, WEB-SWMM was applied to an urban area in China. Test results show that WEB-SWMM could provide real-time computing services stably, quickly, and accurately. In general, the implementation of WEB-SWMM enables traditional SWMM to be quickly and efficiently applied in real-time urban stormwater management. What is more, the web-based hydrological model framework proposed in this paper also applicable to most existing hydrological models. • The real-time simulation of SWMM is implemented. • WEB-SWMM can provide real-time computing services for urban stormwater management. • WEB-SWMM can provide web services and exchange data with other applications. • The core four tasks and four modules guarantee the regular running of WEB-SWMM. • The framework can be installed and deployed across platforms. [ABSTRACT FROM AUTHOR]