Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation
文献类型:期刊论文
作者 | Fang, Chuanglin1![]() ![]() ![]() |
刊名 | GROUNDWATER
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出版日期 | 2019-03-01 |
卷号 | 57期号:2页码:320-328 |
ISSN号 | 0017-467X |
DOI | 10.1111/gwat.12800 |
通讯作者 | Sun, Siao(suns@igsnrr.ac.cn) |
英文摘要 | Assessment of historical evolution of groundwater levels is essential for understanding the anthropogenic impact on groundwater exploitation and developing response policies. In this study, regional groundwater level trend was addressed based on the regional Kendall test with correlated spatial data. With a limited number of data at one location, an exponential relation was proposed to be used to approximate covariances of a variable as a function of distances between locations. The effectiveness of the method was demonstrated using synthetic data experiments. The regional Kendall method was applied to assess evolution of groundwater levels and their annual decline rates in Beijing, Tianjin, and Hebei in China based on county-level data in 1959, 1984, 2005, and 2013. Results indicated that a continuing declining regional trend was shown in groundwater levels, revealing generally higher groundwater recharge rates than withdrawal rates in the study region. The annual groundwater decline rates presented a firstly increasing then decreasing regional trend, which is consistent with the environmental Kuznets curve. The earlier accelerating groundwater decline rate was attributed to supply-driven water resources management, whereas the reversed trend in accelerating groundwater decline rate in the latter period was due to many measures implemented to relieve local water stresses. |
WOS关键词 | ENVIRONMENTAL KUZNETS CURVE ; WATER FOOTPRINT ; UNITED-STATES ; QUALITY ; IMPACT ; RIVERS ; FLOWS |
资助项目 | National Natural Science Foundation of China (NSFC)[41590842] ; National Natural Science Foundation of China (NSFC)[41601167] |
WOS研究方向 | Geology ; Water Resources |
语种 | 英语 |
WOS记录号 | WOS:000460666100014 |
出版者 | WILEY |
资助机构 | National Natural Science Foundation of China (NSFC) |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/49169] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Sun, Siao |
作者单位 | 1.Chinese Acad Sci, Key Lab Reg Sustainable Dev Modeling, Inst Geog Sci & Nat Resource Res, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resource Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Fang, Chuanglin,Sun, Siao,Jia, Shaofeng,et al. Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation[J]. GROUNDWATER,2019,57(2):320-328. |
APA | Fang, Chuanglin,Sun, Siao,Jia, Shaofeng,&Li, Yuanyuan.(2019).Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation.GROUNDWATER,57(2),320-328. |
MLA | Fang, Chuanglin,et al."Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation".GROUNDWATER 57.2(2019):320-328. |
入库方式: OAI收割
来源:地理科学与资源研究所
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