地理科学进展

• 水文过程与环境变化 • 上一篇    下一篇

HIMS模型参数的不确定性及其影响因素

刘丽芳1, 刘昌明1,2, 王中根2, 江燕3, 张永强4, 桑燕芳2, 王虎5   

  1. 1. 北京师范大学水科学研究院,北京100875;
    2. 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;
    3. 中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京100085;
    4. 澳大利亚联邦科工组织土地与水资源研究所,堪培拉2601,澳大利亚;
    5. 中国农业机械化科学研究院,北京100083
  • 收稿日期:2012-10-01 修回日期:2013-01-01 出版日期:2013-04-25 发布日期:2013-04-25
  • 通讯作者: 王中根(1973-),男,研究员,主要从事水循环模拟和水资源管理方面研究。E-mail:wangzg@igsnrr.ac.cn E-mail:wangzg@igsnrr.ac.cn
  • 作者简介:刘丽芳(1981-),女,博士研究生,主要研究方向为水文模拟。E-mail:liulifang198160@163.com
  • 基金资助:
    国家自然科学基金项目(41271048,40971023,50809004,41201036)。

Parameter uncertainty of HIMS model and its influence factor analysis

LIU Lifang1, LIU Changming1,2, WANG Zhonggen2, JIANG Yan3, ZHANG Yongqiang4, SANG Yanfang2, WANG Hu5   

  1. 1. College ofWater Sciences, Beijing Normal University, Beijing 100875, China;
    2. Key Laboratory ofWater Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, CAS, Beijing 100085, China;
    4. CSIRO Land andWater, Canberra, ACT 2601, Australia;
    5. Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China
  • Received:2012-10-01 Revised:2013-01-01 Online:2013-04-25 Published:2013-04-25

摘要: 模型参数的不确定性及影响因素分析对无资料流域水文预报具有重要意义。本文以澳大利亚3 个流域为例,采用GLUE方法分析HIMS模型参数的不确定性,在此基础上探讨流域物理属性对参数取值的影响。研究发现:① HIMS模型9个参数的不确定性都比较大,属于敏感参数;② 降雨量、森林覆盖度和表层土壤最大有效蓄水量大的流域,土壤蓄水容量Wsm取值大;土壤饱和导水率和森林覆盖度高的流域,产流系数R、r的取值较大;温度低、森林覆盖度小的流域,实际蒸散发系数ε取值大;易透水、森林覆盖度高的流域,马斯京根汇流系数C2取值大。这些结论能为今后在无资料流域应用HIMS模型进行水文预报提供一定参考。

关键词: GLUE方法, HIMS模型, 参数不确定性分析, 流域物理属性

Abstract: Parameter uncertainty of hydrological model and its influence factor analysis have important significance in hydrological forecasting for ungauged basins. In this paper, the parameter uncertainty of HIMS model was examined by employing generalized likelihood uncertainty estimation (GLUE) method based on the simulation results of daily rainfall runoff data from the three catchments in Australia, and the influence factors of HIMS model parameters were discussed. It was found that parameters of HIMS model were all sensitivity parameters. And then the parameters distribution of HIMS model and the physical attributions in different catchments were compared. The results showed that the value of soil moisture storage capacity (Wsm) in the catchment was related to the precipitation, forest coverage and available water capacity in lay 1. As the precipitation, forest coverage and available water capacity in lay 1 rising, the value of Wsm increased. The larger values of runoff generation coefficient (R) and (r) in the catchment were due to the large soil saturated hydraulic conductivity and high forest coverage. The value of actual evapotranspiration coefficient (ε) was large in the catchment with low temperature and forest coverage. The value of Muskingum model coefficient (C2) was large when soil saturated hydraulic conductivity and forest coverage were high.

Key words: catchment physical attributions, GLUE, HIMS model, parameter uncertainty analysis