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首页> 外文期刊>Journal of Hydroinformatics >Calibrating a watershed simulation model involving human interference: an application of multi-objective genetic algorithms
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Calibrating a watershed simulation model involving human interference: an application of multi-objective genetic algorithms

机译：校准涉及人为干扰的分水岭模拟模型：多目标遗传算法的应用

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摘要

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.
机译：我们使用多目标遗传算法（NSGA-II）将暴雨事件分布式水文模型校准到流域，其中径流受水库存储和释放的影响很大。本文解决了以下问题：优化模型中使用的目标（适应性）函数的哪些形式将导致更好的校准？被忽略的人为干扰或不精确的存储释放功能导致的储层释放误差如何影响校准？储层释放被研究为人类干扰的一种特定（和流行）形式。测试并比较了两种处理油藏释放的程序：（1）将油藏释放完全由水力结构确定（预定义的存储或水位-流量关系）视为完美，这是流域模型校准中通常采用的一种程序；或（2）将由储-排关系确定的储层释放量与误差项相加。误差项包括随时间变化的人为干扰和放电功能误差，并通过基于优化的校准过程确定。已经发现，考虑到人为干扰的校准程序不仅可以使建模和观测的水文图更好地匹配，而且在其空间分布和参数值的鲁棒性方面还可以使模型参数更合理。

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