We calibrate a storm-event distributed hydrologic model to a watershed, in which runoff is significantly affected by reservoir storage and release, using a multi-objective genetic algorithm (NSGA-II). This paper addresses the following questions: What forms of the objective (fitness) function used in the optimization model will result in a better calibration? How does the error in reservoir release caused by neglected human interference or the imprecise storage–release function affect the calibration? Reservoir release is studied as a specific (and popular) form of human interference. Two procedures for handling reservoir releases are tested and compared: (1) treating reservoir releases to be solely determined by the hydraulic structure (predefined storage or stage-discharge relations) as if perfect, a procedure usually adopted in watershed model calibration; or (2) adding reservoir releases that are determined by the storage–discharge relation to an error term. The error term encompasses a time-variant human interference and a discharge function error, and is determined through an optimization-based calibration procedure. It is found that the calibration procedure with consideration of human interference not only results in a better match of modeled and observed hydrograph, but also more reasonable model parameters in terms of their spatial distribution and the robustness of the parameter values.
Calibrating a watershed simulation model involving human interference: an application of multi-objective genetic algorithms
Mohamad I. Hejazi, Ximing Cai, Deva K. Borah; Calibrating a watershed simulation model involving human interference: an application of multi-objective genetic algorithms. Journal of Hydroinformatics 1 January 2008; 10 (1): 97–111. doi: https://doi.org/10.2166/hydro.2008.010
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