Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation

© 2018, National Ground Water Association.

Bibliographische Detailangaben
Veröffentlicht in:Ground water. - 1979. - 57(2019), 2 vom: 13. März, Seite 320-328
1. Verfasser: Fang, Chuanglin (VerfasserIn)
Weitere Verfasser: Sun, Siao, Jia, Shaofeng, Li, Yuanyuan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:Ground water
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a 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 
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650 4 |a Research Support, Non-U.S. Gov't 
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700 1 |a Jia, Shaofeng  |e verfasserin  |4 aut 
700 1 |a Li, Yuanyuan  |e verfasserin  |4 aut 
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