格林-安普特降雨径流模型改进及初步应用
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P338

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国家重点研发计划(2018YFC1508101,2018YFC1508100);国家自然科学基金(51679061);中央高校基本科研业务费专项(2016B04714)


Improvement and preliminary application of Green-Ampt rainfall-runoff model
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    摘要:

    将基于土壤及降雨资料计算得出的具有物理基础的下渗能力分布曲线引入格林-安普特降雨径流模型,选择中国和美国2个半干旱流域作为研究区域,将改进后的格林-安普特模型与原模型及新安江模型进行模拟对比,研究改进后模型的应用效果及其在半干旱地区的适用性。结果表明:在2个半干旱流域,改进格林-安普特模型模拟结果均好于原始格林-安普特模型及新安江模型;增加的具有物理基础的下渗能力分布曲线能够更好地反映流域内各位置下渗能力随降雨和时间变化的特点,更加精确地计算出流域内下渗量及产流量;半干旱地区洪水多由短时强降雨引起,产流主要以超渗地面径流为主,降雨观测精度和降雨强度对模型模拟精度影响较大;改进格林-安普特降雨径流模型能够在半干旱地区洪水预报中发挥作用。

    Abstract:

    A physics-based infiltration capacity distribution curve, which was calculated using the soil and rainfall data, was introduced into the Green-Ampt rainfall-runoff model to improve its performance. The improved Green-Ampt model was compared with the traditional Green-Ampt model and the Xin’anjiang model in two semi-arid basins in China and US, and then, the performance and applicability of the improved model in semi-arid regions were evaluated. The results show that in two semi-arid basins, the improved Green-Ampt model performs better than the traditional Green-Ampt model and the Xin’anjiang model. The added physics-based infiltration capacity distribution curve effectively reflects the changing of infiltration capacity with time and rainfall for the whole basin, and the results of infiltration and runoff generation calculated by the improved infiltration curve are more accurate. The flood in semi-arid region is mainly caused by the short-term and heavy rainfall, and the runoff is dominated by the infiltrated-excess surface runoff. Rainfall observation accuracy and rainfall intensity have great influence on the simulation accuracy of hydrological models. The improved Green-Ampt rainfall-runoff model can play an important role for the flood forecasts in semi-arid regions.

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李致家,霍文博,张珂.格林-安普特降雨径流模型改进及初步应用[J].河海大学学报(自然科学版),2020,48(5):385-391.(LI Zhijia, HUO Wenbo, ZHANG Ke. Improvement and preliminary application of Green-Ampt rainfall-runoff model[J]. Journal of Hohai University (Natural Sciences),2020,48(5):385-391.(in Chinese))

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  • 在线发布日期: 2020-09-23
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