Multi-Objective Calibration of SWMM for Improved Simulation of the Hydrologic Regime
This chapter presents a multi-objective calibration of the Storm Water Management Model (SWMM) using the Non-dominated Sorting Genetic Algorithm (NSGA-II) developed by Deb et al. (2001). The effects of model calibration on the representation of various hydrologic characteristics with ecologic and geomorphic relevance are studied. Results indicate that there are modeling conflicts between low flows, medium to bank-full flows, and high flows. As a consequence, calibration improvements of minimum water quality maintenance flows, decreases the agreement between computed and observed flows above bankfull elevations. The presence of these trade-offs should be acknowledged in model-based watershed management strategies in order to minimize the uncertainty bias towards certain characteristics of the flow regime. Results show the effects of such trade-offs in the model accuracy to represent different hydrologic quantities, such as mean monthly flows, peak monthly flow, minimum monthly flows, and flow durations and exceedance volumes for different flow ranges and months.
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