• Sorted by Date • Sorted by Last Name of First Author •
Yan, Feng, Zhang, Yuwen, Wang, Xinpeng, Xu, Zheng, Liang, Yuebing, Wang, Zongchao, Wang, Jiaxin, Chen, Yaheng, and Zhu, Zhenzhou, 2025. Characteristics of spatial and temporal non-stationarity of groundwater storage in different basins of China and its driving mechanisms. Journal of Hydrology, 655:132882, doi:10.1016/j.jhydrol.2025.132882.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025JHyd..65532882Y, author = {{Yan}, Feng and {Zhang}, Yuwen and {Wang}, Xinpeng and {Xu}, Zheng and {Liang}, Yuebing and {Wang}, Zongchao and {Wang}, Jiaxin and {Chen}, Yaheng and {Zhu}, Zhenzhou}, title = "{Characteristics of spatial and temporal non-stationarity of groundwater storage in different basins of China and its driving mechanisms}", journal = {Journal of Hydrology}, keywords = {GWSA, (Groundwater Storage Anomaly): Groundwater storage anomaly, indicating the amount of change in groundwater storage in millimetres (mm), TWSA, (Terrestrial Water Storage Anomaly): Terrestrial water storage anomaly, which indicates the amount of change in terrestrial water storage in millimetres (mm), SM, (Soil Moisture): The sum of soil water content data for 4 layers, including soil water content from 0 to 10 cm, from 10 to 40 cm, from 40 to 100 cm, and from 100 to 200 cm, in millimetres (mm), SWE, (Snow Water Equivalent): Snow Water Equivalent (SWE), which expresses the depth of water equivalent to the melting of snow in millimetres (mm), Pre, (Precipitation): Precipitation, which indicates the total amount of precipitation over a period of time, ET, (Evapotranspiration): Evapotranspiration, which indicates the total amount of water transpired by vegetation and evaporated from the soil, Tem, (Temperature): Temperature, which indicates air temperature in degrees Celsius ({\textdegree}C), LST, (Land Surface Temperature): Surface temperature, which indicates the temperature of the earth's surface in degrees centigrade ({\textdegree}C), X1-X18, Representing different drivers including TemperatureãAnnual cumulative precipitationãLand surface temperatureãElevationãEvaporationãPopulation densityãLight intensity at nightãGDP densityãGrain productionãGDP of primary sectorãGDP of the secondary sectorãGDP of the tertiary sectorã0-100 cm soil porosityã100-200 cm soil porosityãSand content of 0{\textendash}100 cm soilãClay content of 0{\textendash}100 cm soilãChalk content of 0{\textendash}100 cm soilãLand use type, GWSA, Spatio-temporal non-stationarity, Residual analysis, Optimal parameter geoprobe, China}, year = 2025, month = jul, volume = {655}, eid = {132882}, pages = {132882}, abstract = "{GWSA is a key resource for maintaining human survival and ecological balance, and changes in its reserves have far-reaching implications for regional socio-economic sustainable development. The continuous decline of GWSA in China over the past 20 years has become a serious challenge, especially in regions such as the Haihe River Basin. In order to reveal the characteristics of spatial and temporal instability of GWSA in different basins in China and its driving mechanism, and to achieve the sustainable use and protection of water resources, this study uses GRACE and GLDAS satellite remote sensing data, combines the methods of Sen Trend + MK test, Hurst index, cross- wavelet, residual analysis and parameter optimal geodetic detector to investigate the pattern of spatial and temporal distribution of GWSA in nine major basins of China and its influencing factors. The results show that: (1) between 2002 and 2022, China's GWSA will decrease by an average of 2.10 mm/year, with the largest annual decrease rate in the Haihe River Basin (â13.13 mm/a) and the largest increase rate in the Southeast Basin (2.13 mm/a); spatially, 70 \% of the region showed a decreasing trend, with severe losses in the central and northeastern parts of China and small increases in the southern and western parts of the country. It is predicted that half of China's regional GWSA will continue to decline in the future. (2) Monthly GWSA in different watersheds all showed a high correlation with monthly precipitation and evapotranspiration, and the ratio of potentially increasing area to decreasing area was 2:3. The anthropogenic improvement of GWSA accounted for 61.72 \% of the increasing area and 50.13 \% of the decreasing area, which was an important driver of the spatial and temporal changes of GWSA.(3) The results of the Optimal Parametric Geodetector (OPGD) showed that GWSA in the Haihe River Basin was significantly affected by the GDP of the three industries, the grain output and the annual cumulative precipitation (q > 0.5), and the bilinear enhancement effect of the annual cumulative precipitation was the strongest with the GDP of the tertiary industry, the GDP of the secondary industry, the GDP of the primary industry, and the grain output, respectively, with q = 0.8427, 0.8006, 0.7819, and 0.7563, and the higher content of soil sand volume is not conducive to the increase of GWSA, and moderate soil porosity and soil sand content are conducive to groundwater storage. The conclusions of the article provide an important reference for the scientific management of regional GWSA and policy formulation, especially in identifying and addressing the challenges of groundwater storage reduction by providing data support and research examples.}", doi = {10.1016/j.jhydrol.2025.132882}, adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..65532882Y}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }
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