Stormwater Symposium

Oral

397992 - Optimizing Watershed Improvement Strategies-Comparing RSWMM and SUSTAIN

Monday, June 4
4:00 PM - 5:30 PM
Location: Mirage Room
Co-Authors: Nasrin Alamdari, Blacksburg, VA – Virginia Polytechnic Institute and State University; Joong Lee, Cincinnati, ON – Center for Urban Green Infrastructure Engineering (CUGIE Inc)

Restoring the hydrology, water quality, and aquatic habitat of urban watersheds requires selecting and sizing the most appropriate stormwater control measures (SCMs). Many stormwater master plans use a hydrologic model to assist in this effort. Models such as the Storm Water Management Model (SWMM) can simulate watershed conditions and SCM performance. In addition to performance, an assessment of cost is an essential first step in identifying the most optimal suite of SCMs. Selection, sizing, and evaluation of SCMs can quickly become computationally difficult with increasing watershed size. This has led to the development of simulation-optimization tools such as the System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN). Unfortunately, SUSTAIN models must be initially created with older versions of ESRI's ArcGIS and the Spatial Analyst extension, possibly limiting its use. The objective of this study was to develop an easy-to-use tool that works independent of ArcGIS to help identify groups of the most cost-effective SCMs in an urban watershed. An existing program known as R for Stormwater Management Model (RSWMM) was enhanced and integrated with a cost estimation spreadsheet for tallying costs of SCMs; and integrated with a metaheuristic solver to optimize life cycle costs for SCMs across an urban watershed. RSWMM functions as an executive routine that controls SWMM, and can be run as many times as needed. A case study watershed was selected, and a SWMM model of the watershed was developed. A simulation-optimization with both RSWMM was conducted, and repeated using SUSTAIN for comparison. Developing public domain tools such as these that combine hydrologic modeling, cost estimation of SCMs, and optimization would help decision makers select the most cost-effective suites of SCMs. This could potentially lower the costs of watershed restoration and allow more to be done for the same investment.

David Sample

Associate Professor
Virginia Polytechnic Institute and State University

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