自然资源学报

自然资源学报 ›› 2007, Vol. 22 ›› Issue (4): 649-655.doi: 10.11849/zrzyxb.2007.04.015

• 研究方法 • 上一篇    下一篇

分布式水文模型的参数率定及敏感性分析探讨

王中根1, 夏军1,2, 刘昌明1, 欧春平1, 张永勇2   

  1. 1. 中国科学院地理科学与资源研究所, 陆地水循环及地表过程重点实验室, 北京 100101;
    2. 武汉大学水资源与水电工程科学国家重点实验室, 武汉 430072
  • 收稿日期:2006-09-25 修回日期:2007-01-15 出版日期:2007-08-25 发布日期:2007-08-25
  • 作者简介:王中根(1973-),男,河南潢川人,副研究员,博士,主要从事水文水资源方面的研究工作。
  • 基金资助:

    水资源与水电工程科学国家重点实验室(武汉大学)开发基金(2004B010);国家自然科学基金项目(40671031/40671035);GEF海河流域水资源与水环境综合管理项目(MISNo:HWCCZ5005).

Comments on Sensitivity Analysis, Calibration of Distributed Hydrological Model

WANG Zhong-gen1, XIA Jun1,2, LIU Chang-ming1, OU Chun-ping1, ZHANG Yong-yong2   

  1. 1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • Received:2006-09-25 Revised:2007-01-15 Online:2007-08-25 Published:2007-08-25

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被引次数

119 | 40

摘要： 参数率定与敏感性分析是分布式水文模型应用和发展中的难点问题,论文对当前典型的、应用比较成功的全局最优化参数率定和敏感性分析方法进行归纳和分析,包括:遗传算法(Genetic Algorithm)、SCE-UA算法(Shuffled Complex Evolution)、贝叶斯方法(Bayesian Method)、RSA方法(Regionalized Sensitivity Analysis)、GLUE方法(Generalized Likelihood Uncertainty Estimation)等等。并对计算机自动优化方法和人工参数调试方法的利弊进行讨论,展望了分布式水文模型的参数率定与敏感性分析的发展方向。

关键词: 分布式模型, 参数率定, 敏感性分析, 优化方法

Abstract: The sensitivity analysis and calibration is a key and difficult issue to the application and development of the distributed hydrological model.In this paper,several typical and effective global optimization calibration and sensitivity analysis methods are inducted,which include the flowing methods:Genetic Algorithm(GA),Shuffled Complex Evolution(SCE),Bayesian Method (BM), Regionalized Sensitivity Analysis(RSA),Generalized Likelihood Uncertainty Estimation(GLUE) and so on. The advantages and disadvantages between the computer automatic calibration and the artificial calibration are discussed, and then we prospect the future development of the sensitivity analysis and calibration of the distributed hydrological model.

Key words: distributed hydrological model, parameter calibration, sensitivity analysis, optimization method

中图分类号: 

  • P334+.92