MatSWMM - An open-source toolbox for designing real-time control of urban drainage systems

This manuscript describes the MatSWMM toolbox, an open-source Matlab, Python, and LabVIEW-based software package for the analysis and design of real-time control (RTC) strategies in urban drainage systems (UDS). MatSWMM includes control-oriented models of UDS, and the storm water management model (SWMM) of the US Environmental Protection Agency (EPA), as well as systematic-system edition functionalities. Furthermore, MatSWMM is also provided with a population-dynamics-based controller for UDS with three of the fundamental dynamics, i.e., the Smith, projection, and replicator dynamics. The simulation algorithm, and a detailed description of the features of MatSWMM are presented in this manuscript in order to illustrate the capabilities that the tool has for educational and research purposes.Peer ReviewedPostprint (author's final draft

Conceptual quality modelling and integrated control of combined urban drainage system

This paper presents the first results of conceptual quality modelling approach oriented to the integrated real-time control (RTC) strategy for urban drainage networks (UDN) and wastewater treatment plants (WWTP) developed in the European project LIFE EFFIDRAIN (Efficient Integrated Real-time Control in Urban Drainage and Wastewater Treatment Plants for Environmental Protection). Model predictive control (MPC) has been selected as a proper RTC to minimize the polluting discharge in case of raining events. The simulator SWMM5 was modified to integrate a lumped conceptual model for total suspended solids (TSS) called SWMM-TSS, which has been used as virtual reality for calibration and validation of the proposed modelling approaches in Perinot network, a real case study in Bordeaux.Peer ReviewedPostprint (author's final draft

Doing a Lot with a Little: A Diagnostic Analysis of SWMM to Simulate Hydrologic Behavior within LID Systems

Low Impact Development (LID) aims to mitigate the hydrological impacts of urbanization by promoting evapotranspiration, storing and slowing the flow of water in formerly impervious areas. Green roofs, a form of LID often utilized in highly urbanized watersheds, are widely simulated using the Storm Water Management Model (SWMM). However, methods to improve diagnostic analysis of SWMM have lagged compared to other environmental disciplines. In this study, I utilize frugal diagnostic analyses to investigate potential sources of non-linearity, uncertainty, and equifinality within SWMM applied to a particular case study, the OnCenter green roof in Syracuse, New York. My findings highlight the major sources of uncertainty in SWMM – model inputs, parameters, structural equations, and reconciling differences between simulated outputs versus observed variables – and demonstrate that more complex diagnostic analysis is necessary to fully understand the fundamental drivers of, and interactions amongst, uncertainty in the SWMM LID bioretention module. As SWMM contains many parameters and therefore multiple degrees of freedom, sensitivity analyses performed using one-at-a-time tests highlight that these analyses are only local estimates within a neighborhood of the selected parameter set. Though we could achieve strong agreements between simulated and observed runoff, SWMM was not able to replicate observed storage timeseries during simulation, suggesting that common approaches to calibrate only to periods of precipitation may misrepresent key hydrologic storages and fluxes within the model. While information gained from frugal analyses can aid in SWMM calibration, the approaches we’ve used oversimplify complex hydrological processes in an extremely non-linear model, limiting their effectiveness as diagnostic tools. The development of a more flexible model structure that allows for complex diagnostic analysis is necessary to fully understand the fundamental drivers of uncertainty in the SWMM LID bioretention module. Encouraging the co-production of knowledge through mutually beneficial dialog between researchers and practitioners presents an opportunity to accelerate SWMM model improvement

A Study of DRAINMOD-Urban For Enhanced Bioretention Cell Modeling

Bioretention has become a leading infiltration-based stormwater control measure for mitigating urban hydrology by reducing urban stormwater runoff volumes and peak flows. Despite widespread field and laboratory studies, less investigation has been directed toward effectively modeling these systems. This is critical, as modeling of bioretention systems provides an avenue for evaluating their effectiveness prior to devoting time and resources into installation. Many hydrologic models capable of simulating bioretention consist of lumped parameters and simplifications that do not fully account for fundamental hydrologic processes such as soil-water interactions. One model, DRAINMOD, has overcome many limitations of other models by incorporating the soil-water characteristic curve (SWCC) to provide better analysis of soil moisture conditions within a bioretention cell and offering better drainage configurations such as an internal water storage (IWS) zone. DRAINMOD is an agricultural drainage model that has shown promise when applied to bioretention systems but operates at a daily temporal scale which does not capture rapid changes in urban hydrology. This study begins by modifying DRAINMOD to adapt to the flashy nature of urban hydrology and bioretention systems in a new model named DRAINMOD-Urban. The performance of DRAINMOD-Urban established that it can produce output hydrographs that represent measured drainage and overflow from a bioretention system while still maintaining calibrated volumes of outflow similar to DRAINMOD. Next, DRAINMOD-Urban was compared to the LID module of the commonly used hydrologic model, the U.S. Environmental Protection Agency (EPA) Stormwater Management Model (SWMM). DRAINMOD-Urban produced better drainage hydrographs but SWMM was very accurate at predicting measured drainage (NSE=0.77-0.94) and overflow (NSE=0.67-0.81) volumes. Pedotransfer functions (PTF) were used to derive the SWCC and vi saturated hydraulic conductivity required for DRAINMOD-Urban and model performance was compared among measured and PTF-derived soil properties. This study showed that a calibrated DRAINMOD-Urban can perform equally well with a SWCC that is measured and calculated using the ROSETTA PTF. These investigations provide a better understanding of how DRAINMOD-Urban has enhanced the field of bioretention cell modeling at the site-scale

Modeling stormwater management at the city district level in response to changes in land use and low impact development

Mitigating the impact of increasing impervious surfaces on stormwater runoff by low impact development (LID) is currently being widely promoted at site and local scales. In turn, the series of distributed LID implementations may produce cumulative effects and benefit the stormwater management at larger regional scales. However, the potential of multiple LID implementations to mitigate the broad-scale impacts of urban stormwater is not yet fully understood, particularly among different design strategies to reduce directly connected impervious areas (DCIA). In this study, the hydrological responses of stormwater runoff characteristics to four different land use conversion scenarios at the city scale were explored using GIS-based Stormwater Management Model (SWMM). Model simulation results confirmed the effectiveness of LID controls; however, they also indicated that even with the most beneficial scenarios hydrological performance of developed areas was still not yet up to the pre-development level, especially with pronounced changes from pervious to impervious land

Modelling Runoff from Permeable Pavements: A Link to the Curve Number Method

Permeable Pavement (PP) models are valuable tools for studying the implementation of PPs in urban environments. However, the runoff simulated by traditional models such as the Curve Number (CN) is different from that created with PP models, as infiltration is computed differently. However, many investigations compare the runoff created by both models to extract broader conclusions without considering how the two models are related. Hence, this research explores the relation between runoff simulated by one general model, selecting the widespread CN model as a baseline, and the PP model provided in the Storm Water Management Model (SWMM). Correlation was set using the hydrograph created with the CN in a single event as a baseline and obtaining the best pavement permeability value from the PP model by calibration. The influence of storm depth, pavement slope, catchment shape, and PP type was also analysed. Calibration was conducted based on the Nash–Sutcliffe coefficient, but peak and volume performances were also studied. The results show that it is possible to link runoff hydrographs computed with the PP model to those created with the CN method, although that relation is not useful for the entire CN range. That relation is practical for CNs higher than 88 and shall be helpful for urban planners and researchers to compare several pervious/impervious scenarios in urban drainage models more robustly. One direct application is to compare the runoff computed by both models without changing the method that simulates runoff. It shall be enough to change a unique parameter that can be linked to a certain imperviousness by the CN.This research was funded by the University of the Basque Country UPV/EHU grant number US22/1

Assessment of the EPA-SWMM Software for Urban Stormwater Management Manual (MSMA) Requirement

The purposes of this project are to identify and investigate the assessment of the EPA Storm Water Management Model (EPA SWMM) for urban stormwater management in order to meet the MSMA requirement and make a comparison with manual calculation in term of the physical quantity

Use of the EPA SWMM for Continuous Simulation

Paper by Wayne C. Hube

Modelling runoff from permeable pavements: a link to the Curve Number method

[EN] Permeable Pavement (PP) models are valuable tools for studying the implementation of PPs in urban environments. However, the runoff simulated by traditional models such as the Curve Number (CN) is different from that created with PP models, as infiltration is computed differently. However, many investigations compare the runoff created by both models to extract broader conclusions without considering how the two models are related. Hence, this research explores the relation between runoff simulated by one general model, selecting the widespread CN model as a baseline, and the PP model provided in the Storm Water Management Model (SWMM). Correlation was set using the hydrograph created with the CN in a single event as a baseline and obtaining the best pavement permeability value from the PP model by calibration. The influence of storm depth, pavement slope, catchment shape, and PP type was also analysed. Calibration was conducted based on the Nash-Sutcliffe coefficient, but peak and volume performances were also studied. The results show that it is possible to link runoff hydrographs computed with the PP model to those created with the CN method, although that relation is not useful for the entire CN range. That relation is practical for CNs higher than 88 and shall be helpful for urban planners and researchers to compare several pervious/impervious scenarios in urban drainage models more robustly. One direct application is to compare the runoff computed by both models without changing the method that simulates runoff. It shall be enough to change a unique parameter that can be linked to a certain imperviousness by the CN.This research was funded by the University of the Basque Country UPV/EHU grant number US22/10.Madrazo-Uribeetxebarria, E.; Garmendia Antín, M.; Almandoz-Berrondo, J.; Andrés-Doménech, I. (2023). Modelling runoff from permeable pavements: a link to the Curve Number method. Water. 15(1). https://doi.org/10.3390/w1501016015

An Overview of Some Hydrological Models in Water Resources Engineering Systems

Researches in hydrological modelling are aimed to the understanding of the behavior of hydrologic systems in an attempt to make better predictions and to address the major challenges in water resources systems. Hydrological modelling concept is concerned with the relationship of water, climate, soil and land use. Hydrological models are classified either as: conceptual or physical, lumped or distributed, deterministic or stochastic. Hydrological models are the main tools that hydrologist use with different purposes such as water resources management, storm water management, reservoir system analysis, flood prediction, climate change assessment and among others. Many hydrological models have been developed for different purposes. The methodology for using hydrological models include: definition of the problem and specifying the objectives, studying the data available, specifying the economic and social constraints, choosing a particular class of hydrological models, selecting a particular type of model from the given class, calibrating and validating the model, evaluating the performance of the model, and finally using the model for the specified purpose. Some recently developed, frequently used, and powerful hydrological models including WEAP, SWMM, HEC-HMS, HEC-RAS, and HEC-ResSim were herein assessed taking into cognizance their applications in solving challenges in water resources engineering systems