A multiobjective simulation-optimization tool for assisting in urban watershed restoration planning. (10th March 2019)

• Record Type: Journal Article
• Authors: Alamdari, Nasrin; Sample, David J.
• Is Part Of: Journal of cleaner production. Volume 213(2019)
• Page Start: 251
• Page End: 261
• Publication Date: 2019-03-10
• Subjects: Watershed restoration -- Cost-effectiveness -- Total maximum daily load (TMDL) -- Storm water management model (SWMM) -- Watershed model -- Multiobjective optimization; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.12.108
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Significant efforts are being made to restore urban watersheds. Stormwater control measures (SCMs) reduce runoff and provide water quality treatment, and are the predominate means of achieving restoration objectives. Determining an effective implementation strategy for these measures often requires a simulation model. The Storm Water Management Model (SWMM) is a hydrologic-hydraulic and water quality model specifically developed for use in urban watersheds. We enhanced an existing external control program for SWMM by adding automated calibration for user-selected events, sensitivity analysis capability, and a multiobjective cost-optimization feature using a well-known evolutionary solver, the Non-dominated sorting genetic algorithm (NSGA-II). The enhanced program, RSWMM-Cost, was then applied to a previously developed SWMM model of the Difficult Run watershed of Fairfax County, Virginia. Calibration and verification were performed using the program. Sensitivity analysis was conducted by varying SCM attributes as a function of performance metrics. Cost-optimization was conducted on a 123.4 ha headwater subcatchment of the watershed using generalized cost relationships and constraints based upon SCM design guidance and water quality requirements. A cost-effectiveness curve was generated, consisting of sets of SCMs that either are optimal or nearly so. Thus, RSWMM-Cost can assist decision makers identify watershed management strategies that meet water quality goals. Highlights: Urban watershed management is often facilitated with models like SWMM. We enhanced an existing tool (RSWMM) used for SWMM automation. RSWMM-Cost can identify the best control strategies for watershed restoration. We demonstrate RSWMM-Cost by using it to meet required reductions in pollutants. RSWMM-Cost can also calibrate to multiple events, and perform sensitivity analysis.