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首页> 外文期刊>Hydrological Processes >Investigating the use of spatial discretization of hydrological processes in conceptual rainfall runoff modelling: a case study for the meso-scale
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Investigating the use of spatial discretization of hydrological processes in conceptual rainfall runoff modelling: a case study for the meso-scale

机译:在概念性降雨径流模拟中研究水文过程空间离散化的使用:中尺度的案例研究

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摘要

In this study a simple modelling approach was applied to identify the need for spatial complexity in representing hydrological processes and their variability over different scales. A data set of 18 basins was used, ranging between 8 and 4011 km~2 in area, located in the Nahe basin (Germany), with daily discharge values for over 30 years. Two different parsimoniously structured models were applied in lumped as well as in spatially distributed according to two distribution classifications: (1) a simple classification based on the lithology expressed in three permeability types and (2) a more complex classification based on seven dominating runoff production processes. The objective of the study was to compare the performances of the models on a local and on a regional scale as well as between the models with a view to identifying the accuracy in Capturing the spatial variability of the rainfall-runoff relationships. It was shown that the presence of a specific basin characteristic or process of the distribution classification was not related with higher model performance; only a larger basin size promoted higher model performance. The results of this study also indicated that the permeability generally contained more useful information on the spatial heterogeneity of the hydrological behaviour of the natural system than did a more detailed classification on dominating runoff generation processes. Although model performance was slightly lower for the model that used permeability as a distribution classification, consistency in its parameter values was found, which was lacking with the more complex distribution classification. The latter distribution classification had a higher flexibility to optimize towards the variability of the runoff, which resulted in higher performance, however, process representation was applied inconsistently.
机译:在这项研究中,采用了一种简单的建模方法来确定表示水文过程及其在不同尺度上的变异性所需的空间复杂性。在纳河盆地(德国)使用了18个盆地的数据集,面积在8到4011 km〜2之间,日排放值超过30年。根据两个分布类别,在集总和空间分布中应用了两个不同的简约结构模型:(1)基于以三种渗透率类型表示的岩性的简单分类,以及(2)基于七种主要径流产生的更复杂的分类流程。该研究的目的是比较模型在局部和区域尺度以及模型之间的性能,以期确定捕获降雨-径流关系的空间变异性的准确性。结果表明,特定盆地特征或分布分类过程的存在与较高的模型性能无关;只有更大的水盆尺寸才能促进更高的模型性能。这项研究的结果还表明,与对主导径流产生过程进行更详细的分类相比,渗透率通常包含更多有关自然系统水文行为空间异质性的有用信息。尽管使用渗透率作为分布分类的模型的模型性能略低,但发现其参数值具有一致性,而更复杂的分布分类则缺乏。后者的分配类别具有更大的灵活性,可以针对径流的可变性进行优化,从而获得更高的性能,但是,流程表示法的应用却不一致。

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