长江科学院院报

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2017 , Vol. 34 >Issue 9: 6 - 13

DOI: https://doi.org/10.11988/ckyyb.20160519

水资源与环境

基于SODA方法的HyMOD模型不确定性分析

  • 李帅 ,
  • 文小浩 ,
  • 杜涛
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  • 1.中国长江三峡集团公司 三峡枢纽建设运行管理局,湖北 宜昌 443133;
    2.华中科技大学 水电与数字化工程学院,武汉 430074;
    3.长江水利委员会 水文局,武汉 430010
李 帅(1987-),男,湖北汉川人,工程师,博士,主要从事水文预报和水库调度方面的研究与管理工作,(电话)0717-6763354(电子信箱)li_shuai@ctg.com.cn。

收稿日期: 2016-05-25

  网络出版日期: 2017-09-28

基金资助

国家重点研发计划项目(2016YFC0402306-01);国家自然科学基金项目(51539009)

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Uncertainty Assessment of HyMOD Model Using the Method ofSimultaneous Optimization and Data Assimilation

  • LI Shuai ,
  • WEN Xiao-hao ,
  • DU Tao
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  • 1.Three Gorges Construction and Operation Management Department, China Three Gorges Corporation, Yichang 443133, China;
    2.School of Hydropower and Information Engineering, Huazhong University ofScience and Technology, Wuhan 430074, China;
    3.Bureau of Hydrology, Changjiang Water ResourcesCommission, Wuhan 430010, China

Received date: 2016-05-25

  Online published: 2017-09-28

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摘要

为了改进水文建模过程中的不确定性处理,采用一种融合全局优化和数据同化(Simultaneous Optimization and Data Assimilation, SODA)的混合框架,对HyMOD模型进行了不确定性分析,并与经典SCEM-UA方法进行了比较。SODA方法具有如下特点①具备较高的参数搜索效率和寻优能力;②明确考虑包括输入、输出、参数以及模型结构在内的重要不确定性来源。SODA方法在渭河流域的实例应用结果表明与SCEM-UA方法相比,SODA方法不仅显著提高了预报精度,而且推求出了性质更为优良的预报区间。SODA方法的成功应用,有助于模型概念的改进及对水文系统功能的理解。

关键词： SODA; HyMOD模型; 水文模型不确定性; SCEM-UA; 集合卡尔曼滤波(EnKF)

本文引用格式

李帅 , 文小浩 , 杜涛 . 基于SODA方法的HyMOD模型不确定性分析[J]. 长江科学院院报, 2017 , 34(9) : 6 -13 . DOI: 10.11988/ckyyb.20160519

Abstract

To improve the treatment of uncertainty in hydrological modeling, a hybrid framework of simultaneous optimization and data assimilation (SODA) was adopt to assess the uncertainty of HyMOD model in this paper, and then was compared with the classical method of the Shuffled Complex Evolution Metropolis-UA (SCEM-UA). The strengths of the SODA can be described as follows (1) high parameter search efficiency and explorative capabilities; (2) explicit treatment of the various important sources of uncertainty (i.e., input, output, parameter and model structure uncertainties) associated with the application of hydrological models. The results of the SODA applied in the Weihe River Basin demonstrate that in comparison to the performances of SCEM-UA, the SODA could notably improve the streamflow prediction efficiency, and also could derive more accurate prediction interval. The successful application of the SODA is helpful to improving model concepts and understanding of the functioning of hydrological systems.

Key words： simultaneous optimization and data assimilation (SODA); HyMOD; hydrological modeling uncertainty; Shuffled Complex Evolution Metropolis-University of Arizona(SCEM-UA); Ensemble Kalman Filter(EnKF)

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