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Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models
Water ( IF 3.0 ) Pub Date : 2021-08-02 , DOI: 10.3390/w13152126
Mun-Ju Shin , Chung-Soo Kim

Rainfall–runoff models are not perfect, and the suitability of a model structure depends on catchment characteristics and data. It is important to investigate the pros and cons of a rainfall–runoff model to improve both its high- and low-flow simulation. The production and routing components of the GR4J and IHACRES models were combined to create two new models. Specifically, the GR_IH model is the combination of the production store of the GR4J model and the routing store of the IHACRES model (vice versa in the IH_GR model). The performances of the new models were compared to those of the GR4J and IHACRES models to determine components improving the performance of the two original models. The suitability of the parameters was investigated with sensitivity analysis using 40 years’ worth of spatiotemporally different data for five catchments in Australia. These five catchments consist of two wet catchments, one intermediate catchment, and two dry catchments. As a result, the effective rainfall production and routing components of the IHACRES model were most suitable for high-flow simulation of wet catchments, and the routing component improved the low-flow simulation of intermediate and one dry catchments. Both effective rainfall production and routing components of the GR4J model were suitable for low-flow simulation of one dry catchment. The routing component of the GR4J model improved the low- and high-flow simulation of wet and dry catchments, respectively, and the effective rainfall production component improved both the high- and low-flow simulations of the intermediate catchment relative to the IHACRES model. This study provides useful information for the improvement of the two models.

中文翻译:

用于调查改进 IHACRES 和 GR4J 降雨-径流模型的组件组合测试

降雨-径流模型并不完美,模型结构的适用性取决于流域特征和数据。重要的是研究降雨-径流模型的利弊,以改进其高流量和低流量模拟。GR4J 和 IHACRES 模型的生产和路由组件结合起来创建了两个新模型。具体来说,GR_IH 模型是 GR4J 模型的生产存储和 IHACRES 模型的路由存储的组合(反之在 IH_GR 模型中)。将新模型的性能与 GR4J 和 IHACRES 模型的性能进行比较,以确定提高两个原始模型性能的组件。使用澳大利亚五个流域 40 年的时空不同数据,通过敏感性分析研究了参数的适用性。这五个流域包括两个湿流域、一个中间流域和两个干流域。因此,IHACRES 模型的有效降雨生成和演算组件最适合湿流域的高流量模拟,演算组件改进了中干流域和一干流域的低流量模拟。GR4J 模型的有效降雨量和路径分量都适用于一个干流域的低流量模拟。GR4J 模型的路由组件分别改进了湿流域和干流域的低流量和高流量模拟,相对于 IHACRES 模型,有效降雨生产组件改进了中间集水区的高流量和低流量模拟。本研究为改进这两种模型提供了有用的信息。
更新日期:2021-08-03
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