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作 者:苟娇娇 缪驰远 段青云 GOU Jiaojiao;MIAO Chiyuan;DUAN Qingyun(Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China;College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)
机构地区:[1]北京师范大学地理科学学部,北京100875 [2]河海大学水文水资源学院,南京210098
出 处:《地理科学进展》2022年第7期1338-1348,共11页Progress in Geography
基 金:博士后创新人才支持计划项目(BX2021045);国家自然科学基金项目(42041006);中国博士后科学基金资助项目(2021M700478)。
摘 要:水文模型是认识水文科学规律、分析水文过程及研究水文循环机理的重要科学工具。水文模型模拟结果的不确定分析是提高模型可靠性、进行有效水情预报的一个重要研究内容。参数不确定性是影响水文模型模拟结果不确定性的关键因素之一,开展模型参数不确定性及其影响因素分析对水文预报具有重要现实意义。目前的参数不确定性分析方法大致可分为3类:参数敏感性分析、参数优化以及考虑无资料流域参数值估计的参数区域化方法。论文归纳总结了近年来国内外水文模型参数不确定性分析工作的主要研究进展,分析了不同方法的优点与不足,提出了未来水文模型不确定性分析方法研究的潜在发展方向。借助多学科理论和技术方法,加强水文模型不确定性分析系统性方法的研究,是水文学科当前的迫切需求及发展趋势。Hydrological models are an important scientific tool for understanding the basic theory of hydrology disciplines, analyzing hydrological processes, and studying hydrological cycle mechanisms. The uncertainty analysis of simulation results is a prerequisite for improving the reliability of a model and for conducting an effective hydrological regime forecast. Parameter uncertainty is one of the important factors that affect the uncertainty of simulation results from hydrological models, and the analysis of model parameter uncertainty and its impact factors has important practical significance for hydrological forecasting. The current parameter uncertainty analysis methods can be roughly divided into three categories: parameter sensitivity analysis,parameter optimization, and parameter regionalization method that consider the parameter estimation in ungauged catchments. This article reviewed the current development of technique and operation status of parameter sensitivity analysis for hydrological models, as well as the advantages and disadvantages of different analysis methods. We also identified the potential development direction of future research on the method of uncertainty analysis of hydrological models, that is, to strengthen the study of the systematic method of uncertainty analysis for hydrological models with the help of multidisciplinary theories and technical methods.
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