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Advanced Calibration Methodology for Hydrologic Rainfall - Runoff Simulation Models

机译:水文降雨的先进校准方法 - 径流模拟模型

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Stochastic estimation techniques are presented which are capable of improving hydrologic conceptual rainfall-runoff model calibrations by accounting for streamflow measurement uncertainties (and other, additive, errors). Specifically, the auto-correlated and the heteroscedastic (changing variance) error cases are considered. The methods are shown to perform well in simulation studies, and application of the techniques to the calibration of the U.S. National Weather Services soil moisture accounting model showed superiority of the new procedures over the commonly-used simple least squares criterion. The procedures were compared under different data conditions and starting parameter values. Results indicate important phenomena needing study and accountability.

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