Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2001
Publication Date: N/A
Citation: N/A Interpretive Summary: Hydrologic models are being used by government agencies and consultants to determine the input of proposed land management scenarios on water quality. In this study, an automated calibration technique was linked to a hydrologic model. This allows model users to automate the tedious and often confusing task of calibration. The autocalibration technique also removes subjectivity and gives users confidence in the calibration results.
Technical Abstract: Parameters of hydrologic models often are not exactly known and therefore have to be determined by calibration. A manual calibration depends on the subjective assessment of the modeler and can be very time-consuming though. Methods of automatic calibration can improve these shortcomings. Yet, the high number of parameters in distributed models makes special demands on the optimization. In this paper a strategy of imposing constraints on the parameters to limit the number of independently calibrated values is outlined. Subsequently, an automatic calibration of the version SWAT-G of the model SWAT (Soil and Water Assessment Tool) with a stochastic global optimization algorithm, the Shuffled Complex Evolution algorithm, is presented for a mesoscale catchment.