AUTOMATIC CALIBRATION OF A DISTRIBUTED CATCHMENT MODEL
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dc.contributor.author | Eckhardt K. | |
dc.contributor.author | Arnold J.G. | |
dc.date.accessioned | 2021-03-11T07:47:44Z | |
dc.date.available | 2021-03-11T07:47:44Z | |
dc.date.issued | 2001 | |
dc.identifier | https://www.elibrary.ru/item.asp?id=771515 | |
dc.identifier.citation | Journal of Hydrology, 2001, 251, 1-2, 103-109 | |
dc.identifier.issn | 0022-1694 | |
dc.identifier.uri | https://repository.geologyscience.ru/handle/123456789/26615 | |
dc.description.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. | |
dc.subject | DISTRIBUTED MODELS | |
dc.subject | CALIBRATION | |
dc.subject | PARAMETER ESTIMATION | |
dc.subject | SWAT | |
dc.subject | SCE-UA | |
dc.title | AUTOMATIC CALIBRATION OF A DISTRIBUTED CATCHMENT MODEL | |
dc.type | Статья |
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