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Automatic calibration of a conceptual rainfall-runoff model using multiple objectives

机译:使用多个目标自动校准概念性降雨-径流模型

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Formulation of an automatic calibration strategy for the MIKE 11/NAM rainfall-runoff model is outlined. The calibration scheme includes optimisation of multiple objectives that measure different aspects of the hydrograph: (1) overall water balance, (2) overall shape of the hydrograph, (3) peak flows, and (4) low flows. An automatic optimisation procedure based on the shuffled complex evolution algorithm is introduced for solving the multi-objective calibration problem. A test example is presented that illustrates the principles and implications of using multiple objectives in model calibration. Significant trade-offs between the different objectives are observed in this case and no single unique set of parameter values is able to optimise all objectives simultaneously. Instead, the solution to the calibration problem is given as a set of Pareto optimal solutions, which from a multi-objective viewpoint are equivalent. A large variability is observed in the Pareto optimal parameter sets, resulting in a large range of "equally good" simulated hydrographs. From the set of Pareto optimal solutions, one can draw a single solution according to priorities of the different objectives for the specific model application being considered. A balanced aggregated objective function is proposed, which provides a compromise solution that puts equal weights to the different objectives. (C) 2000 Elsevier Science B.V. All rights reserved. [References: 31]
机译:概述了针对MIKE 11 / NAM降雨径流模型的自动校准策略的制定。校准方案包括多个目标的优化,这些目标可测量水文图的不同方面:(1)总水量平衡,(2)水文图的总体形状,(3)峰值流量,(4)低流量。介绍了一种基于混洗复杂演化算法的自动优化程序,以解决多目标校准问题。给出了一个测试示例,该示例说明了在模型校准中使用多个目标的原理和含义。在这种情况下,观察到了不同目标之间的重大权衡,并且没有任何一组唯一的参数值能够同时优化所有目标。取而代之的是,将校准问题的解决方案作为一组Pareto最优解给出,从多目标角度来看,这是等效的。在帕累托最优参数集中观察到较大的可变性,从而产生了大范围的“相等良好”的模拟水位图。从一组帕累托最优解中,可以根据所考虑的特定模型应用程序根据不同目标的优先级得出单个解决方案。提出了一个平衡的聚合目标函数,它提供了一个折衷的解决方案,可以对不同的目标赋予相等的权重。 (C)2000 Elsevier Science B.V.保留所有权利。 [参考:31]

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