A Bayesian Method for Water Resources Vulnerability Assessment: A Case Study of the Zhangjiakou Region, North China

被引:5
|
作者
Wang, Xuan [1 ,2 ]
Ma, Fangbing [1 ,3 ]
Li, Chunhui [1 ,2 ]
Zhu, Jie [1 ,2 ]
机构
[1] Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, Sch Environm, Minist Educ, Key Lab Water & Sediment Sci, Beijing 100875, Peoples R China
[3] Shidu Town Peoples Govt, Beijing 102411, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
GROUNDWATER; AQUIFER; SYSTEM; RISK; DISTRIBUTIONS; CATCHMENT; MODEL; AREA;
D O I
10.1155/2015/120873
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Water resources vulnerability (WRV) assessment is an important basis for maintaining water resources security in a basin. In this paper, considering the complexity of the water resources system and the uncertainty of the assessment information, a method based on the Bayesian theory was developed for performing WRV assessments while using the constructed indicator system. This systemincludes four subsystems, the hydrological subsystem, the socioeconomic subsystem, the ecoenvironmental subsystem and the hydraulic engineering subsystem. The WRV degree for each subsystem and the integrated water resources system were assessed. Finally, the assessment results and the characteristics of the Bayesian method were compared with those of the grey relational analysis method and the parametric-system method. The results showed the following. (1) The WRV of the integrated water resources system of the entire Zhangjiakou region was very high; Zhangjiakou City and Xuanhua County have tendencies to belong to Extreme WRV, with probabilities of 26.8% and 25%, respectively, while the other seven administrative counties have tendencies to belong to High WRV, with probabilities ranging from 24.6% to 27%. (2) Compared with the parametric-system method and the grey relational analysis method, the Bayesian method is simple and can effectively address the uncertainty issues with the reliable WRV assessment results.
引用
收藏
页数:16
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