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Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China

文献类型：期刊论文

作者Gou, Jiaojiao2; Miao, Chiyuan2; Duan, Qingyun2; Tang, Qiuhong3; Di, Zhenhua2; Liao, Weihong4; Wu, Jingwen2; Zhou, Rui1
刊名WATER RESOURCES RESEARCH
出版日期2020
卷号56期号:1页码:19
ISSN号0043-1397
DOI10.1029/2019WR025968
通讯作者Miao, Chiyuan(miaocy@vip.sina.com)
英文摘要Model parameter calibration is a fundamentally important stage that must be completed before applying a model to address practical problems. In this study, we describe an automatic calibration framework that combines sensitivity analysis (SA) and an adaptive surrogate modeling-based optimization (ASMO) algorithm. We use this framework to calibrate catchment-specific sensitive parameters for streamflow simulation in the variable infiltration capacity (VIC) model with a 0.25 degrees spatial resolution over 10 major river basins of China from 1960 to 1979. We found that three parameters-the infiltration parameter (B) and two of the soil depth parameters (D-1, D-2)-are highly sensitive in most basins, while other parameter sensitivities are strongly related to the dynamic environment of the basin. Compared with directly calibrating the seven parameters recommended for the default calibration procedure, our framework not only reduced the computing time by two thirds through opting out of insensitive parameters (type I error) but also improved the Nash-Sutcliffe model efficiency coefficient (NSE) for optimized results when it identified a missing sensitive parameter (type II error) in the case study river basins. Results show that the SA-based ASMO framework is an effective and efficient model-optimization technique for matching simulated streamflow with observations across China. The NSE for monthly streamflow ranged from 0.75 to 0.97 and from 0.71 to 0.97 during the validation and calibration periods, respectively. The calibrated parameters can be applied directly in streamflow simulations across China, and the proposed calibration framework holds important implications for relevant simulation studies in other regions.
WOS关键词CLIMATE-CHANGE ; GLOBAL SENSITIVITY ; WATER-RESOURCES ; LAND MODEL ; RIVER ; OPTIMIZATION ; RUNOFF ; IDENTIFICATION ; UNCERTAINTY ; PROJECTIONS
资助项目National Natural Science Foundation of China[41622101] ; National Natural Science Foundation of China[41730645] ; National Natural Science Foundation of China[41877155] ; State Key Laboratory of Earth Surface Processes and Resource Ecology
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
语种英语
WOS记录号WOS:000520132500041
出版者AMER GEOPHYSICAL UNION
资助机构National Natural Science Foundation of China ; State Key Laboratory of Earth Surface Processes and Resource Ecology
源URL[http://ir.igsnrr.ac.cn/handle/311030/133044]  
专题中国科学院地理科学与资源研究所
通讯作者Miao, Chiyuan
作者单位1.China Three Gorges Int Corp, Beijing, Peoples R China
2.Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China
4.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Gou, Jiaojiao,Miao, Chiyuan,Duan, Qingyun,et al. Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China[J]. WATER RESOURCES RESEARCH,2020,56(1):19.
APA Gou, Jiaojiao.,Miao, Chiyuan.,Duan, Qingyun.,Tang, Qiuhong.,Di, Zhenhua.,...&Zhou, Rui.(2020).Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China.WATER RESOURCES RESEARCH,56(1),19.
MLA Gou, Jiaojiao,et al."Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China".WATER RESOURCES RESEARCH 56.1(2020):19.

入库方式： OAI收割

来源：地理科学与资源研究所

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