作 者：Guo, YiHuang, ShengzhiHuang, QiangLeng, GuoyongFang, WeiWang, LuWang, Hao
作者机构：State Key Laboratory of Eco-Hydraulic in Northwest Arid Region of ChinaXi'an University of Technology Xi'an710048 ChinaKey Laboratory of Water Cycle and Related Land Surface ProcessesInstitute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 ChinaEnvironmental Change InstituteUniversity of Oxford OxfordUKOX1 3QY United KingdomChina Institute of Water Resources and Hydropower ResearchState Key Lab Simulat & Regulat Water Cycle River Beijing100038 China
出 版 物：《Science of the Total Environment》
年 卷 期：2020年第712卷
基 金：The authors are grateful to the financial support by the National Natural Science Foundation of China (grant number 51709221 )the National Key Research and Development Program of China (grant number 2017YFC0405900 )the Key laboratory research projects of Department of EducationShaanxi Province (grant number 17JS104 )and the Planning Project of Science and Technology of Water Resources of Shaanxi (grant numbers 2017slkj-19 ).
主 题：DroughtBayesian networksGroundwaterProbabilityConditional probabilitiesGroundwater supplyHydrological droughtsMeteorological droughtModelbased OPCPropagation timeUnderlying surfaceWei river
摘 要：What the extent of meteorological drought could trigger the corresponding hydrological drought with different levels? This question is an important topic in the field of drought propagation, which however has not been resolved. Therefore, a novel model based on a Bayesian network was proposed to address this issue in this study. In this model, the drought pooling and excluding methods were applied to eliminate minor drought events. A drought matching approach based on drought propagation time was proposed to achieve the one by one matching between different types of drought. Moreover, based on the matched drought events and the copula-based conditional probability model, the drought propagation thresholds of meteorological drought for triggering hydrological drought at various levels were determined. In addition, the interval conditional probability was calculated to further explore the sensitivity of hydrological drought response to different meteorological drought conditions. Furthermore, the propagation ratio was proposed to characterize the differences of drought propagation threshold among various regions. The Wei River Basin was selected as a case study. Results indicated that the results of drought propagation threshold were reliable and accurate. The increase of interval conditional probability showed a typical S-curve, which can intuitively obtain the probability of hydrological drought occurrence at different levels under specific meteorological drought condition, so as to effectively guide drought preparedness and mitigation. The propagation ratio can describe the overall resistance of the basin to meteorological drought, and it mainly depended on the meteorological and underlying surface conditions as well as groundwater supply. © 2018 Elsevier B.V.