水资源

分布式时变增益流域水循环模拟

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  • 1. 中国科学院地理科学与资源研究所,北京 100101;
    2. 武汉大学,武汉 430072;
    3. 中国科学院新疆生态与地理研究所,乌鲁木齐 830011
夏军(1954-), 男, 湖北广水人, 教授、研究员, 中科院“百人计划”入选者, 国际水文科学协会(IAHS)副主席, 主要从事水文学及水资源科学研究工作。E-mail: xiaj@igsnrr.cn

收稿日期: 2003-02-23

  修回日期: 2003-05-10

  网络出版日期: 2003-09-25

基金资助

中国科学院“百人计划”项目、知识创新工程项目(CX10G-E01-08, KZCX1-09-02);国家自然科学基金项目(50279049)

A Research on Distributed Time Variant Gain Modeling

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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Wuhan University, Wuhan 430072, China;
    3. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China

Received date: 2003-02-23

  Revised date: 2003-05-10

  Online published: 2003-09-25

Supported by

The One-Hundred Talents Program & Knowledge Innovation Project of CAS, No.CX10G-E01-08; No.KZCX1-09-02; National Natural Science Foundation of China, No. 50279049

摘要

针对分布式水文模拟的问题,结合河西走廊黑河流域实际资料条件,提出将水文循环空间数字化信息与水文系统理论相结合的分布式时变增益水循环模型 (DTVGM)。DTVGM将单元时变增益水文非线性模型(TVGM)拓广到由DEM划分的流域单元网格上建立非线性地表水产流模型,基于水量平衡方程和蓄泄方程建立土壤水产流模型,并应用运动波方法建立分级网格汇流模型。最后,以黑河干流山区流域为例应用DTVGM开展了实例研究,设计开发了模型系统。研究区域被划分为38 277个网格单元 (网格大小为500 m×500 m),在此基础上将流域划分为456级带状汇流区域。考虑到黑河干流山区的寒区特点,模型耦合了融雪径流模型。模拟结果表明,DTVGM既有分布式水文概念性模拟的特征,同时具有水文系统分析适应能力强的优点,能够在水文资料信息不完全或者有不确定性干扰条件获得比较好的分布式水文模拟效率,在黑河干流山区的应用能够较好地满足水资源管理的要求。

本文引用格式

夏军,王纲胜,吕爱锋,谈戈 . 分布式时变增益流域水循环模拟[J]. 地理学报, 2003 , 58(5) : 789 -796 . DOI: 10.11821/xb200305019

Abstract

Based on requirement of distributed hydrological modelling and considering the real conditions of the arid and semi-arid regions in China, this paper develops a Distributed Time Variant Gain Model (DTVGM) by coupling the mechanism and special digit information of water cycle with hydrologic system approach. It simulates the movement of the water in the soil-vegetation-atmosphere system, describes the relation between the cellular grids in the horizontal direction, and performs mathematical calculations of the surface water and the groundwater on the watershed cellular grids divided by DEM. DTVGM includes two components: one is runoff generation process on grid elements; the other is flow routing process based on ranked grids. At present, the runoff generation process is divided into two layers in the vertical direction: the upper layer is the surface flow; the lower layer is the subsurface flow. On the other hand, the kinematic wave models are applied to simulate the flow routing process. The article also addresses a case study on Heihe mountainous basin by applying DTVGM. The basin, with an area of 9,569.25 km2, is divided into 38,277 grid elements; and the grids are partitioned into 456 ranks for flow routing.

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