基于降雨-径流长期观测的山洪响应特征分析:以美国本土两个小流域为例
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1.中山大学大气科学学院;2.①中山大学大气科学学院;3.②南方海洋科学与工程实验室;4.③马里兰大学地球系统科学多学科中心,马里兰州;5.国家气象中心;6.广东省气候中心;7.马里兰大学地理科学系,马里兰州

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Analysis of flash flood response characteristics using long-term rainfall-runoff observation:take two small watersheds in the United States as an example
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Affiliation:

1.School of Atmospheric Sciences, Sun Yat-sen University;2.1 School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082;3.2 Southern Marine Science and Engineering Laboratory, Zhuhai 519082;4.3 EarthSystem Science Interdisciplinary Center, University of Maryland, College Park 20740, MD 20742;5.National Meteorological Centre;6.Guangdong Climate Center;7.Department of Geographical Sciences, University of Maryland, College Park

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    本文以长期降雨-径流观测资料为基础,建立小流域水文单位线以有效描述山洪响应特征,并探究变化环境下的山洪响应特征是否发生改变。单位线在山洪预报中应用广泛,但在气象领域受关注较少。以两个美国小流域(USGS站点02137727-Catawba河、01572025-Swatara河)为研究对象,探讨考虑不同前期降水和致洪降水条件下单位线提取和优化方法,以及前期降水对流域单位线的影响。结果表明不同前期影响雨量下的平均单位线对降水-径流模拟总体效果较好,两个流域1985年以来共16个降雨径流事件模拟的平均纳什模型效率系数分别为0.85和0.94,平均峰值相对误差分别为9.4%和7.5%。前期影响雨量越大,则单位线峰值越高,峰现时间提前。同时考虑前期降水和致洪降水组合的单位线,能更好反映雨洪事件中山洪响应特征,模拟效果进一步提高,对提高山洪概率预报很有意义。通过分析Catawba河流域33年单位线的年际变化,发现降水增多和强降水频率增加导致流域山洪响应特征发生明显变化,单位线峰值呈现增加趋势,涨洪历时呈减少趋势,未来山洪灾害风险变大。

    Abstract:

    Using long-term rainfall-runoff data, this paper constructs the unit hydrograph (UH) to simulate flash floods in small catchments, describes the characteristics of flash flood response to precipitation in particular, and explores how the characteristics of flash flood response change under different environment. Two small catchments (USGS gauges at Catawba River and Swatara River) in the United States are investigated. When the antecedent precipitation index (API) is higher, the peak UH value is higher and the peak current time becomes earlier. The results of surface runoff simulation using average UH with different API are promising with average Nash efficiency coefficients as 0.846 and 0.940 respectively. The average relative peak errors are 9.40% and 7.47% respectively. By combining rainfall and flood-causing precipitation, the simulation results can be further improved and better represent the characteristics of flash flood response, which is very promising for real-time flash flood forecasting. The further analysis of the interannual variation of UH in the Catawba River basin indicates an intensified flash flood response with increasing peak magnitude and decreasing flood duration, corresponding well to the increase in both the accumulated precipitation amount and the frequency of heavy rainfall in the past years.

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  • 收稿日期:2020-10-10
  • 最后修改日期:2020-11-05
  • 录用日期:2020-11-11
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