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基于内部平衡误差的水文建模适配优度的调制。

Modulation of the goodness of fit in hydrological modelling based on inner balance errors.

机构信息

Department of Civil Engineering, Catholic University of Murcia (UCAM), Murcia, Spain.

Department of Geography, University of Murcia, Murcia, Spain.

出版信息

PLoS One. 2021 Nov 18;16(11):e0260117. doi: 10.1371/journal.pone.0260117. eCollection 2021.

Abstract

In hydrological modelling, a good result for the criterion of goodness of fit does not always imply that the hypothesis of mass conservation is fulfilled, and models can lose their essential physical soundness. We propose a way for detecting this anomaly by accounting the resulting water balance during model simulation and use it to modulate the obtained goodness of fit. We call this anomaly in water balance as "inner balance error of the model". To modulate the goodness of fit values, a penalty function that depends on this error is proposed. In addition, this penalty function is introduced into a multi-criteria objective function, which is also tested. This procedure was followed in modelling the Headwater of the Tagus River (Spain), applying the monthly abcd water balance model. Modulation of the goodness of fit allowed for detecting balance errors in the modelling, revealing that in the simulation of some catchments the model tends to accumulate water in, or release water from, the reservoir that simulates groundwater storage. Although the proposed multi-criteria objective function solves the inner balance error for most catchments, in some cases the error cannot be corrected, indicating that any error in the input and output data is probably related to groundwater flows.

摘要

在水文学模型中,拟合优度标准的良好结果并不总是意味着质量守恒假设得到满足,而且模型可能会失去其基本的物理合理性。我们提出了一种通过在模型模拟过程中考虑所产生的水量平衡来检测这种异常的方法,并利用它来调节所得到的拟合优度。我们将这种水量平衡中的异常称为“模型的内部平衡误差”。为了调节拟合优度值,提出了一个依赖于该误差的惩罚函数。此外,还将此惩罚函数引入到多准则目标函数中进行测试。在对塔古斯河(西班牙)上游进行建模时,采用了月度 abcd 水量平衡模型,遵循了这一程序。对拟合优度的调节可以检测到建模中的平衡误差,表明在一些流域的模拟中,模型倾向于在模拟地下水储存的水库中积累或释放水。尽管所提出的多准则目标函数解决了大多数流域的内部平衡误差,但在某些情况下,误差无法得到纠正,这表明输入和输出数据中的任何误差可能都与地下水流动有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6fb3/8601472/22b5a704c433/pone.0260117.g001.jpg

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