PySWMM: The Python Interface to Stormwater Management Model (SWMM).

Bryant Mcdonnell,Michael Tryby,Katherine Ratliff,Jennifer Wu,Abhiram Mullapudi

doi:10.21105/joss.02292

Abstract

Stormwater management seeks to reduce runoff from rain or melted snow and improve water quality. Where it can absorb into soil, runoff is filtered and returns to streams, rivers, and aquifers, but in developed areas, precipitation often cannot soak into the ground because impervious surfaces (e.g., pavement, buildings), and already saturated soils can create excess runoff. This water, which can contain pollutants, then runs across urban surfaces and into storm drains, drainage ditches, and sewer systems. Stormwater runoff can cause flooding, erosion, infrastructure and habitat damage, and contamination (including combined and sanitary sewer overflows). In urban and developed areas, effective stormwater management that routes and detains stormwater helps to mitigate these impacts and improve water quality.

Highlights

Stormwater management seeks to reduce runoff from rain or melted snow and improve water quality
The U.S Environmental Protection Agency’s (EPA) Stormwater Management Model (SWMM) is a dynamic rainfall-runoff model that has been used for decades to conduct single event or long-term hydrologic, hydraulic, and water quality simulations
The EPA distribution of SWMM does not, allow the modeler to interact with the SWMM model during simulation time nor access all of the simulated values and results

Summary

Introduction

Stormwater management seeks to reduce runoff from rain or melted snow and improve water quality. In urban and developed areas, effective stormwater management that routes and detains stormwater helps to mitigate these impacts and improve water quality. The U.S Environmental Protection Agency’s (EPA) Stormwater Management Model (SWMM) is a dynamic rainfall-runoff model that has been used for decades to conduct single event or long-term hydrologic, hydraulic, and water quality simulations.

Results

Conclusion