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Simulation of Combined Best Management Practices and Low Impact Development for Sustainable Stormwater Management 1
Author(s) -
Damodaram Chandana,
Giacomoni Marcio H.,
Prakash Khedun C.,
Holmes Hillary,
Ryan Andrea,
Saour William,
Zechman Emily M.
Publication year - 2010
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2010.00462.x
Subject(s) - low impact development , surface runoff , stormwater , flood control , environmental science , rainwater harvesting , flood mitigation , flood myth , watershed , green infrastructure , hydrology (agriculture) , bioretention , water resource management , stormwater management , environmental planning , computer science , engineering , geography , geotechnical engineering , archaeology , machine learning , biology , ecology
Damodaram, Chandana, Marcio H. Giacomoni, C. Prakash Khedun, Hillary Holmes, Andrea Ryan, William Saour, and Emily M. Zechman, 2010. Simulation of Combined Best Management Practices and Low Impact Development for Sustainable Stormwater Management. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/j.1752‐1688.2010.00462.x Abstract: Urbanization causes increased stormwater runoff volumes, leading to erosion, flooding, and the degradation of instream ecosystem health. Although Best Management Practices (BMPs) are used widely as a means for controlling flood runoff events, Low Impact Development (LID) options have been proposed as an alternative approach to better mimic the natural flow regime by using decentralized designs to control stormwater runoff at the source, rather than at a centralized location in the watershed. For highly urbanized areas, LID practices such as rainwater harvesting, green roofs, and permeable pavements can be used to retrofit existing infrastructure and reduce runoff volumes and peak flows. This paper describes a modeling approach to incorporate these LID practices in an existing hydrologic model to estimate the effects of LID choices on streamflow. The modeling approach has been applied to a watershed located on the campus of Texas A&M University in College Station, Texas, to predict the stormwater reductions resulting from retrofitting existing infrastructure with LID technologies. Results demonstrate that use of these LID practices yield significant stormwater control for small events and less control for flood events. A combined BMP‐LID approach is tested for runoff control for both flood and frequent rainfall events.