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自然环境恶劣、站点稀少、观测困难是干旱区水文系统研究面临的基本问题。特殊的自然地理条件给水文过程带来了极大的复杂性和不确定性,也阻碍了干旱区水文过程和机理研究的发展。选取塔里木河源区开都河流域为研究区,采用分布式水文模型MIKESHE模拟大尺度资料稀缺地区水文过程,将流域内气象、水文站点数据与遥感数据相结合,利用气象、土壤类型、土地利用和地表覆盖、数字高程(DEM)和降雨等资料,模拟流域水文过程;在出山口径流数据的基础上对模型进行率定和验证;分析了模型中的不确定性的来源,探讨模型优化方法。结果表明,MIKESHE模型能在水文、气象站点稀少,土壤及水文地质数据缺乏的条件下,模拟开都河流域的日径流过程,但精度仍有待提高;通过分析识别出了隐含于模型结构、输入及参数等3个方面的8种不确定性来源。
The harsh natural environment, sparsely populated sites and observation difficulties are the basic problems facing the research of arid hydrological system. The special physical and geographical conditions have brought tremendous complexity and uncertainty to the hydrological process and hindered the development of hydrological processes and mechanisms in arid areas. Taking the Kaidu River basin in the Heyuan area of Tarim as the study area, the distributed hydrological model MIKESHE is used to simulate the hydrological processes in the large-scale data-scarce areas. The meteorological and hydrological stations in the basin are combined with the remote sensing data, and the meteorological and soil types, land use and Surface coverage, digital elevation (DEM) and rainfall data to simulate the hydrological process in the river basin. The model is calibrated and validated on the basis of runoff data from the outfall. The source of the uncertainty in the model is analyzed and the model optimization method is discussed. The results show that the MIKESHE model can simulate the daily runoff of the Kaidu River basin under the conditions of scarce hydrological and meteorological stations and lack of soil and hydrogeological data, but the precision still needs to be improved. By analyzing and identifying the implied model structure, Input and parameters of the three aspects of the 8 sources of uncertainty.