适用于不同水文气象区的统一径流生成方案

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

潮湿地区和半干旱地区的径流生成通常分别以饱和-溢出机制和渗透-溢出机制为主。但在半湿润地区,这两种机制可以同时存在。因此,我们提出了一种统一的径流生成方案来表示单一径流生成过程和混合径流生成过程,使其适用于不同的水文气象条件。在网格单元尺度上,将新安江模型的饱和-过量径流生成方案与改进的霍顿入渗方案相结合。将网格-新安江(GXAJ)的原始径流生成方案替换为集成方案,我们开发了一种新的分布式水文模型,称为网格-新安江-渗透-过量(GXAJ-IE)模型。我们在四个流域对 GXAJ-IE 模型进行了测试,并与两个采用单一径流生成机制的基准模型进行了比较。结果表明,GXAJ-IE 模型在再现半湿润流域不同降雨条件下的洪水水文图方面具有更高的灵活性和鲁棒性,在湿润和半干旱地区与基准模型的性能相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A unified runoff generation scheme for applicability across different hydrometeorological zones

Runoff generation in humid and semi-arid regions are usually dominated by saturation-excess mechanism and infiltration-excess mechanism, respectively. However, both mechanisms can co-exist in semi-humid regions. Therefore, we proposed a unified runoff generation scheme to represent the single and mixed runoff generation processes, making it applicable for different hydrometeorological conditions. The saturation-excess runoff generation scheme of the Xin'anjiang model was integrated with a modified Horton infiltration scheme at the grid cell scale. By substituting the original runoff generation scheme of the grid-Xin'anjiang (GXAJ) with the integrated scheme, we developed a new distributed hydrological model called grid-Xin'anjiang-infiltration-excess (GXAJ-IE) model. GXAJ-IE was tested in four watersheds and compared with two benchmark models with single runoff generation mechanism. The results indicate that GXAJ-IE model has higher flexibility and robustness in reproducing flood hydrographs under different rainfall conditions in semi-humid watersheds and has comparable performances with the benchmark models in humid and semi-arid regions.

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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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