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RCCC-WBM模型区域适用性及参数敏感性分析 被引量:2

Regional Suitability and Parameter Sensitivity Analysis of RCCC-WBM
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摘要 天然径流量的模拟计算是区域水资源评价的关键,以中国不同气候区的6个典型流域为例,评估RCCC-WBM月尺度水文模型对天然径流过程的模拟能力,并分析其参数的敏感性。结果表明:RCCC-WBM模型对不同气候区典型流域的天然径流过程都具有较好的模拟效果,Nash-Sutcliffe效率系数均在0.80以上,径流量相对误差较小,满足径流模拟的精度要求,区域适用性较好。南方流域冬季气温较高,降雪积雪较少,导致融雪径流汇流系数对模拟结果的影响微乎其微;在6个典型流域中地表径流汇流系数对模型精度具有显著的影响;土壤蓄水容量通过决定土壤含水的上限值间接地影响着水源的划分与计算,对模型径流模拟至关重要。 Simulation of natural runoff plays a key role in regional water resources assessment.Taking the typical watersheds in different climatic regions of China as an example,the RCCC-WBM,a monthly hydrological model,was used to simulate the runoff process in the natural stage,and the sensitivity of its parameters was analyzed.The results show that the WBM has fairly good performance in 6 typical basin and the Nash-Sutcliffe efficiency coefficient is above 0.80,the relative error of runoff is also small.The surface runoff coefficient has a significant impact on the model accuracy,while in southern basins the influence of the snowmelt runoff coefficient on the simulation results is negligible due to small proportion of snowfall and higher temperature in winter,and the surface runoff coefficient has a significant impact on the model performance;the soil water storage capacity indirectly affects the runoff component partitioning and calculation by determining the upper limit of soil moisture,to which the sensitivities of typical watersheds is inconsistent.
作者 管晓祥 刘悦 张成凤 杨晓甜 金君良 王国庆 GUAN Xiaoxiang;LIU Yue;ZHANG Chengfeng;YANG Xiaotian;JIN Junliang;WANG Guoqing(College of Hydrology and Water Resource,Hohai University,Nanjing 210098,China;Research Center for Climate Change,MWR,Nanjing 210029,China;State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,NHRI,Nanjing 210029,China)
出处 《水文》 CSCD 北大核心 2020年第2期55-61,共7页 Journal of China Hydrology
基金 国家重点研发计划项目(2017YFC0404403,2016YFA0601501) 国家自然科学基金项目(51779144,51679144,51879164,41401024,41371063) 中国工程院重大咨询项目(2015-ZD-07)。
关键词 典型流域 水量平衡模型 参数敏感性 typical watershed water balance model parameter sensitivity
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