Enhancing the pollutant modeling capabilities of EPA-SWMM using PySWMM and StormReactor

Abhiram Mullapudi, Brooke Mason, Jia Xin (Jennifer) Wu, Constantine Karos, Branko Kerkez, Caleb Buahin and Bryant McDonnell


This talk introduces a novel approach for extending the pollutant modeling capabilities of EPA-SWMM. Pollutants stemming from the urbanization of catchment areas are deteriorating the quality of receiving water bodies. Developing solutions for curtailing these pollutants requires modeling tools that can represent the complex pollutant interactions in stormwater control measures (e.g., Green Infrastructure). Though EPA-SWMM can model pollutant generation, treatment, and routing, its ability is limited to a set of specific scenarios such as percentage removal and first-order decay kinetics. We address this limitation by adopting a modular modeling paradigm; we decouple the water quality module from the EPA-SWMM’s simulation engine and use a Python-based model for simulating pollutant dynamics. We still rely on the EPA-SWMM’s powerful simulation engine for modeling hydrology, hydraulics, and pollutant routing. Furthermore, this modeling paradigm enables us to retain the existing capabilities of EPA-SWMM and enhance them when and where it is needed. This presentation demonstrates how modelers can use PySWMM, a Python package for interacting with EPA-SWMM’s simulation engine from Python, to develop customized water quality models ranging from exponential-decay models to partial differential equation-based models. We also introduce StormReactor, a Python package that provides users with predefined water quality models that they can use in any EPA-SWMM model with a few lines of Python code. Finally, we illustrate the use of these two packages in a diverse set of real-world inspired examples. Through this presentation, we aspire to provide the attendees with the tools to integrate any water quality modeling method with EPA-SWMM and comprehensively model pollutant dynamics in stormwater systems.

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