黄土高原典型流域LCM模型集总、半分布和分布式构建对比分析  

Comparison of LCM hydrological models with lumped, semi-distributed and distributed building structures in typical watershed of Yellow River Basin

作　　者：张亦弛[1] 刘昌明[2,3] 杨胜天[1] 刘晓燕[4] 蔡明勇[1] 董国涛[5] 罗娅[1,6] 

机构地区：[1]北京师范大学地理学与遥感科学学院,北京100875 [2]北京师范大学水科学研究院,北京100875 [3]中国科学院陆地水循环与地表过程重点实验室,北京100101 [4]黄河水利委员会,郑州450003 [5]黄河水利科学研究院,郑州450003 [6]贵州师范大学地理与环境科学学院,贵阳550001

出　　处：《地理学报》2014年第1期90-99,共10页Acta Geographica Sinica

基　　金：国家"十二五"科技支撑计划课题(2012BAB02B00);水利部公益项目(201101037);中央高校基本科研业务费专项~~

摘　　要：暴雨中心的空间分布是影响小流域暴雨洪水过程模拟精度的关键要素。不同模型构建方式对降雨空间异质性的响应差异很大,选择恰当的水文模型构建方式对提高模型计算效率,减少降雨空间异质性对模型的影响从而提高预测精度具有重要意义。为此,本文基于刘昌明提出的适用于黄土高原超渗产流机制的LCM(Liu Changming Model)模型,分别构建了集总式、半分布式和全分布式的暴雨—径流模型,旨在比较分析不同模型构建方式对于降雨空间异质性的响应及其对模拟精度和计算效率的影响。结果表明:分布式构建模拟精度最高,纳什效率系数达到0.81,相关系数达到0.82;集总式构建计算时间最短;相比较而言,半分布式构建方法纳什效率系数达到0.78,主峰值模拟精度分别达到76.1%和65.8%。总体上,全分布式构建方法模拟精度最高,集总式计算耗时最短效率最高,半分布式在保持较高模拟精度的同时也具有较高的计算效率。The distribution of rainstorm center is critical factor influencing the simulation accuracy of rainstorm runoff process. There are significant differences among the varying discretization responding to rainfall heterogeneities, thus it is important to improve simulation efficiency and accuracy by selecting appropriate discretization methods for reducing the influence of rainfall heterogeneity. For this, the LCM model which deduced from the unsaturated infiltration theory in Loess Plateau by Liu Changming was modeled in three ways： lumped, semi-distributed and distributed. The simulation results indicate that： the NSE with distributed method arrives at 0.81 and correlation coefficient attains 0.82 which shows the best fitness to gauge data. Comparatively, NSE of semi-distributed method arrives at 0.78, while the fitness to main peak of outlet stream-flow reaches 76.1% and 65.8%. Generally, distributed method shows the highest simulation accuracy, lumped method owns the highest calculation efficiency, and semi-distributed method indicates high simulation accuracy, and high calculation efficiency at the same time. So, spatial discretization of modeling is helpful to reduce the influence of rainfall heterogeneity and to improve simulation accuracy of LCM model, but it will consume more time. Thus, it is appropriate to select suitable spatial discretization methods according to the application requirements.

关 键 词：LCM模型 降雨空间异质性 黄河流域 孤山川 暴雨洪水 分布式构建 

分 类 号：P333[天文地球—水文科学]