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USE OF A GENETIC ALGORITHM AND MULTI-OBJECTIVE PROGRAMMING FOR CALIBRATION OF A HYDROLOGIC MODEL

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Transactions of the ASAE. 41(3): 615-619. (doi: 10.13031/2013.17229) @1998
Authors:   C. C. Balascio, D. J. Palmeri, H. Gao
Keywords:   Hydrologic models, Calibration, Genetic algorithm, Multi-objective programming, SWMM

A genetic algorithm was used to calibrate the RUNOFF component of the EPA storm-water management model, SWMM. A multi-objective function was developed which attached user-specified weights to error terms for estimates of peak flow rate, runoff volume, and time of peak. The genetic algorithm proved to be a valuable tool for isolating the neighborhood of the optimal parameter set. A conventional calibration scheme was used whereby the model was first fitted to a low intensity storm which produced runoff from impervious areas only. After parameters for the impervious cover were found, a larger storm was used to determine the variables for pervious land use. The calibrated model was used to simulate two additional storms with good accuracy.

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