Evaluation of the EPA SWMM Model to Simulate Low Impact Development Features in an Urban Stormwater Environment

Date of Award

Summer 2014

Document Type


Degree Name

Master of Science (MS)


Civil & Environmental Engineering


Environmental Engineering

Committee Director

Xixi wang

Committee Member

Jaewan Yoon

Committee Member

Mujde Erten-Unal

Call Number for Print

Special Collections LD4331.E542 C365 2014


This research thesis explores the use of the Environmental Protection Agency's (EPA) Stormwater Water Management Model (SWMM) to model an urban watershed with a developed stormwater management system and test the SWMM model's ability to simulate Low Impact Development (LID) features by proposing typical LID features that can be retrofitted to the developed study area. The SWMM model is established with an existing survey of the study area's stormwater management system, and due to the lack of field data for the study area, the model developed in this research thesis is calibrated with the consideration of a published stormwater model developed by a different stormwater modeling software. The development of other factors included in the SWMM model are from existing data available for the study area, or local or regional values when available. When site specific or regional data is not available for the study area, a Literature Review develops values to be implemented as a substitution to the measured values. Two alternatives, existing conditions and a proposal including LID features, are tested in the SWMM model for the study area. The results compare the difference in the simulated outputs for the two models in terms of changes in runoff, outflow from the system, and pollutant loading. Due to the Chesapeake Bay Total Maximum Daily Load (TMDL) limit established for the region of the study area, the pollutants of Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) are applied to the model as an event mean concentration (EMC) for the initial pollutant loading to the system. A discussion of the results of the two alternatives, the ability of the SWMM to model different functions of LID features, and recommendations for future research is included in the concluding chapters of this research thesis.


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