Evaluating the Effectiveness of Best Management Practices Using Dynamic Modeling
Publication: Journal of Environmental Engineering
Volume 134, Issue 8
Abstract
Structural best management practices (BMPs) have become a tool for stormwater managers to achieve water quality improvement and regulatory compliance. Existing empirical evaluation of BMP performance is valuable, but has limited applicability to predict BMP performance over extended durations under a variety of storm types. This study applies a dynamic model to simulate BMP performance over a 10-year period. The BMP model used hourly output from a calibrated and validated land-use model to evaluate two BMP types: a retention facility and a flow-through swale. The model evaluated each BMP alone and in series targeting volume, total suspend solids, and total copper. Effectiveness was based on load reduction, event mean concentrations, and frequency of exceedence of relevant water quality standards. The model predicted over 60% removal of solids and copper over most conditions; however, effectiveness was reduced during large storms and wet years. Although performance was similar based on load reduction and water quality standard exceedence, the latter was most sensitive to storm size. This study demonstrates that BMP modeling can help managers understand expected BMP performance over a range of storms, time periods, and design parameters, and, perhaps more significantly, evaluate BMPs in series.
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Acknowledgments
This study was supported by funding from the Los Angeles Regional Water Quality Control Board (Contract No. 03-139-554-0) and the Southern California Coastal Water Research Project. We thank Steve Weisberg and Ken Schiff of SCCWRP, Steve Carter and John Riverson of Tetra Tech, Inc., and two anonymous reviewers for providing valuable suggestions and input on drafts of this paper.
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Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 134 • Issue 8 • August 2008
Pages: 628 - 639
Copyright
© 2008 ASCE.
History
Received: May 3, 2007
Accepted: Nov 19, 2007
Published online: Aug 1, 2008
Published in print: Aug 2008
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