Zheng Lu; De-hui Ning; Hui-bin Yang; Hai-rui Hao; Li-min Liao; Xi-xi Lan; Cheng-zhi Hao; Xu Zhou; Juan Bai; Jin-hui Wu; Sha-sha Meng

doi:10.26599/JGSE.2026.9280091

doi: 10.26599/JGSE.2026.9280091

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出版历程
- 收稿日期: 2025-11-16
- 录用日期: 2026-04-07
- 网络出版日期: 2026-10-10
- 刊出日期: 2026-12-15

Spatiotemporal dynamics of water table depth in Southwest China (1958–2015) under complex hydrogeological settings

1.
Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
2.
School Of Resources Engineering, Yunnan Tourism College, Kunming 650221, China
3.
Department of Atmospheric Sciences, Yunnan University, Kunming 650500, China
4.
Powerchina Kunming Engineering Corporation Limited; Kunming 650051, China
5.
Hainan Provincial Ecological and Environmental Monitoring Centre, Haikou 571126, China
6.
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Beijing Normal University, Beijing 100875, China
7.
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, China Geological Survey, Beijing 100083, China
8.
China Institute of Geo-Environment Monitoring, China Geological Survey, Beijing 100081, China
9.
School of Geography, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

More Information

Corresponding author: jwu@mail.cgs.gov.cn; mengshasha@mail.bnu.edu.cn

All datasets employed in this study are publicly accessible. The water table depth dataset is derived from GLOBGM v1.0, available via the Yoda research data management service of Utrecht University (https://public.yoda.uu.nl/geo/UU01/44L775.html). Precipitation data are provided at https://doi.org/10.5281/zenodo.3114194, while evapotranspiration data are accessible through the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/RemoteSen.tpdc.272831). Geomorphology and land cover data were obtained from the Resource and Environmental Science Data Platform (https://www.resdc.cn/data.aspx?DATAID=124; https://www.resdc.cn/DOI/DOI.aspx?DOIID=54). The aridity index is available from Version 3 of the Global Aridity Index and Potential Evapotranspiration Database (https://doi.org/10.57760/sciencedb.nbsdc.00086). Karst aquifer extent data were sourced from the World Karst Aquifer Map (WHYMAP WOKAM, Version 1.0; https://www.whymap.org/whymap/EN/Maps_Data/Wokam/whymap_ed2017_map_g.html). Anthropogenic stress data are available at https://doi.org/10.6084/m9.figshare.7283087. Additional supporting datasets used for figures and charts are provided by the National Tibetan Plateau/Third Pole Environment Data Center (https://data.tpdc.ac.cn/).

摘要

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Abstract: Groundwater provides an essential buffer against hydroclimatic variability in monsoon-influenced regions, yet its long-term dynamics and interactions with human activities remain poorly constrained in complex hydrogeological settings such as Southwest China (SWC). This study integrates outputs from the high-resolution PCRaster Global Water Balance model (PCR-GLOBWB) with spatial statistics to examine temporal evolution, spatial heterogeneity, and anthropogenic influences on Water Table Depth (WTD) from 1958 to 2015. Results reveal a persistent long-term rise in groundwater levels (i.e., a decline in WTD) at a Sen's slope of –0.0285 m/y, with episodic drawdowns during drought years and only partial recovery in subsequent wet periods. Seasonal oscillations remain pronounced, with the shallowest water tables occurring in late summer and the deepest in spring, although long-term depletion suggests that natural recharge is insufficient to balance cumulative extraction. Shallow aquifers (<1 m) are closely coupled with precipitation–evapotranspiration variability, while deeper systems (>5 m) are increasingly buffered and display inverse relationships, reflecting delayed recharge processes. Spatial patterns demonstrate strong heterogeneity across climate zones, geomorphic units, land cover types, and aquifer types: Shallow groundwater is concentrated in semi-arid climates, lowland plains, and urban areas, whereas mountainous regions, undeveloped land, and discontinuous carbonate aquifers sustain deeper and more variable WTDs. Anthropogenic stress further modulates these distributions, with bivariate LISA analysis identifying High–High clusters (intensive human modification and deep water tables) in the Chengdu Plain and central Yunnan, and Low–Low clusters in sparsely populated western highlands. A groundwater protection zoning framework derived from these results highlights shallow aquifers under intensive stress as priority areas for monitoring and regulation. These findings demonstrate the coupled influence of climate and human activity on groundwater variability and provide a practical basis for regionally targeted management strategies to enhance groundwater sustainability in SWC.
- Groundwater /
- Spatiotemporal dynamics /
- Geomorphology /
- Land cover /
- Karst aquifer systems /
- Anthropogenic stress
All datasets employed in this study are publicly accessible. The water table depth dataset is derived from GLOBGM v1.0, available via the Yoda research data management service of Utrecht University (https://public.yoda.uu.nl/geo/UU01/44L775.html). Precipitation data are provided at https://doi.org/10.5281/zenodo.3114194, while evapotranspiration data are accessible through the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/RemoteSen.tpdc.272831). Geomorphology and land cover data were obtained from the Resource and Environmental Science Data Platform (https://www.resdc.cn/data.aspx?DATAID=124; https://www.resdc.cn/DOI/DOI.aspx?DOIID=54). The aridity index is available from Version 3 of the Global Aridity Index and Potential Evapotranspiration Database (https://doi.org/10.57760/sciencedb.nbsdc.00086). Karst aquifer extent data were sourced from the World Karst Aquifer Map (WHYMAP WOKAM, Version 1.0; https://www.whymap.org/whymap/EN/Maps_Data/Wokam/whymap_ed2017_map_g.html). Anthropogenic stress data are available at https://doi.org/10.6084/m9.figshare.7283087. Additional supporting datasets used for figures and charts are provided by the National Tibetan Plateau/Third Pole Environment Data Center (https://data.tpdc.ac.cn/).
注释:
1) Data availability statement:

HTML全文

Figure 1. Overview and maps of the study area, Southwest China (SWC)

Notes: (a) regional location with DEM, provincial boundaries, and river networks; (b) steady-state water table depth (WTD) based on the GLOBGM v1.0 dataset (Verkaik et al., 2024); (c) multi-year average precipitation (Peng et al., 2019); (d) climate zoning based on the aridity index (Zomer et al., 2022); (e) geomorphic units (Geomorphological Map of China); (f) karst aquifer extent (World Karst Aquifer Map, WOKAM)

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Figure 2. Schematic diagram of the overall methodology and data processing workflow

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Figure 3. Temporal variations and statistical characteristics of water table depth (WTD) in Southwest China (SWC) (1958–2015): (a) annual mean WTD time series showing a long-term decreasing trend (Sen's slope = –0.0285 m/y, indicating rising groundwater levels), (b) monthly WTD time series, (c) inter-decadal statistical characteristics of annual WTD, and (d) monthly statistical characteristics of WTD

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Figure 4. Seasonal patterns of water table depth (WTD) variations in Southwest China (1958–2015)

Notes: (a) monthly variations showing mean values with standard deviation error bars, extreme values (minimum and maximum), and median WTD across all years; (b) inter-seasonal comparison of average WTD with standard deviation error bars, highlighting differences between winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug), and autumn (Sep-Nov)

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Figure 5. Time series and correlation between depth-specific, co-located Water Table Depth (WTD) and precipitation–evapotranspiration (P–ET) anomalies for different WTD thresholds: (a) WTD < 0.1 m; (b) WTD < 1 m; (c) WTD < 5 m; (d) WTD < 10 m

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Figure 6. Water Table Depths (WTDs) across different climate classes: (a) distributions of climate zones; (b) boxplots of WTDs across different climate types

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Figure 7. Water Table Depths (WTDs) across different geomorphology types: (a) distributions of geomorphic units; (b) boxplots of WTDs across different geomorphic units

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Figure 8. Water Table Depths (WTDs) across different land cover types: (a) distributions of land cover types; (b) boxplots of WTDs over different land cover types

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Figure 9. Water Table Depths (WTDs) across different karst aquifer types: (a) distributions of karst aquifer types; (b) boxplots of WTDs over different karst aquifer types

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Figure 10. Spatial associations between steady-state Water Table Depth (WTD) and anthropogenic stress in Southwest China

Notes: (a) provincial boundary map; (b) steady-state WTD distribution; (c) anthropogenic stress; (d) local spatial correlation between WTD and anthropogenic stress; (e) bivariate LISA cluster classification; (f) statistical significance (p-values) of the LISA results. Panels (b) and (c) are reproduced here for comparison purposes

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Figure 11. Spatial distribution and statistics of groundwater protection zone for Southwest China.

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Table 1. Groundwater protection categories using empirically derived thresholds.

Protection zone classification	Criterion	Representativeness	Area
Special protection zones	WTD < 5 m and anthropogenic stress > 0.7	Shallow groundwater under high human pressure	–9,108.10 km² (0.67%)
Priority monitoring zones	WTD < 10 m and anthropogenic stress > 0.5	Vulnerable groundwater with moderate human impact	–35,282.03 km² (2.61%)
Long-term monitoring zones	WTD < 20 m and anthropogenic stress > 0.5	Groundwater systems requiring ongoing observation	–47,753.28 km² (3.53%)
Low-risk zones	WTD > 20 m and anthropogenic stress < 0.5	Deep groundwater with minimal human impact	–1,087,435.06 km² (80.42%)
Other areas	-	-	–172,566.57 km² (12.76%)

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参考文献(108)

Adams KH, Reager JT, Rosen P, et al. 2022. Remote sensing of groundwater: current capabilities and future directions. Water Resource Research, 58: e2022WR032219. DOI: 10.1029/2022WR032219.

Ahmad S, Shazil MS, Mahmood SA, et al. 2025. Quantifying climate change impacts on hydrological dynamics and sedimentation using GIS and SWAT + modelling. Hydrological Processes, 39: e70082. DOI: 10.1002/hyp.70082.

Akhter T, Pokhrel Y, Felfelani F, et al. 2025. Implications of lateral groundwater flow across varying spatial resolutions in global land surface modeling. Water Resource Research, 61. DOI: 10.1029/2024wr038523.

Akritas MG, Murphy SA, Lavalley MP. 1995. The theil-sen estimator with doubly censored data and applications to astronomy. Journal of the American Statistical Association, 90: 170−177. DOI: 10.1080/01621459.1995.10476499.

Allouche N, Maanan M, Gontara M, et al. 2017. A global risk approach to assessing groundwater vulnerability. Environmental Modelling & Software, 88: 168−182. DOI: 10.1016/j.envsoft.2016.11.023.

Anselin L. 1995. Local indicators of spatial association—LISA. Geographical Analysis, 27: 93−115. DOI: 10.1111/j.1538-4632.1995.tb00338.x.

Anselin L, Sridharan S, Gholston S. 2007. Using exploratory spatial data analysis to leverage social indicator databases: the discovery of interesting patterns. Social Indicators Research, 82: 287−309. DOI: 10.1007/s11205-006-9034-x.

Asoka A, Gleeson T, Wada Y, et al. 2017. Relative contribution of monsoon precipitation and pumping to changes in groundwater storage in India. Nature Geoscience, 10: 109−117. DOI: 10.1038/ngeo2869.

Berghuijs WR, Luijendijk E, Moeck C, et al. 2022. Global recharge data set indicates strengthened groundwater connection to surface fluxes. Geophysical Research Letters, 49: e2022GL099010. DOI: 10.1029/2022GL099010.

Blaschke LL, Nian D, Bathiany S, et al. 2024. Spatial correlation increase in single-sensor satellite data reveals loss of Amazon rainforest resilience. Earth's Future, 12: e2023EF004040. DOI: 10.1029/2023EF004040.

Brooks PD, Solomon DK, Kampf S, et al. 2025. Groundwater dominates snowmelt runoff and controls streamflow efficiency in the western United States. Communications Earth & Environment, 6: 341. DOI: 10.1038/s43247-025-02303-3.

Chanapathi T, Thatikonda S, Pandey VP, et al. 2019. Fuzzy-based approach for evaluating groundwater sustainability of asian cities. Sustainable Cities and Society, 44: 321−331. DOI: 10.1016/j.scs.2018.09.027.

Chávez García Silva R, Reinecke R, Copty NK, et al. 2024. Multi-decadal groundwater observations reveal surprisingly stable levels in southwestern europe. Communications Earth & Environment, 5: 387. DOI: 10.1038/s43247-024-01554-w.

Chen C, Tian Y, Zhang, YK, et al. 2019. Effects of agricultural activities on the temporal variations of streamflow: Trends and long memory. Stochastic Environmental Research and Risk Assessment, 33: 1553−1564. DOI: 10.1007/s00477-019-01714-x.

Chen Z, Auler AS, Bakalowicz M, et al. 2017. The world karst aquifer mapping project: Concept, mapping procedure and map of Europe. Hydrogeology Journal, 25: 771−785. DOI: 10.1007/s10040-016-1519-3.

Condon LE, Atchley AL, Maxwell RM. 2020. Evapotranspiration depletes groundwater under warming over the contiguous United States. Nature Communications, 11: 873. DOI: 10.1038/s41467-020-14688-0.

Condon LE, Maxwell RM. 2019. Simulating the sensitivity of evapotranspiration and streamflow to large-scale groundwater depletion. Science Advances, 5: eaav4574. DOI: 10.1126/sciadv.aav4574.

Cooke ML, Simo JA, Underwood CA, et al. 2006. Mechanical stratigraphic controls on fracture patterns within carbonates and implications for groundwater flow. Sedimentary Geology, 184: 225−239. DOI: 10.1016/j.sedgeo.2005.11.004.

Curran D, Gleeson T, Huggins X. 2023. Applying a science-forward approach to groundwater regulatory design. Hydrogeology Journal, 31: 853−871. DOI: 10.1007/s10040-023-02625-6.

Cuthbert MO, Gleeson T, Moosdorf N, et al. 2019. Global patterns and dynamics of climate–groundwater interactions. Nature Climate Change, 9: 137−141. DOI: 10.1038/s41558-018-0386-4.

de Graaf IEM, Marinelli B, Liu S. 2024. Global analysis of groundwater pumping from increased river capture. Environmental Research Letters, 19: 44064. DOI: 10.1088/1748-9326/ad383d.

de Graaf IEM, Stahl K. 2022. A model comparison assessing the importance of lateral groundwater flows at the global scale. Environmental Research Letters, 17: 044020. DOI: 10.1088/1748-9326/ac50d2.

de Graaf IEM, Sutanudjaja EH, Van Beek LPH, et al. 2015. A high-resolution global-scale groundwater model. Hydrology and Earth System Sciences, 19: 823−837. DOI: 10.5194/hess-19-823-2015.

de Graaf IEM, Van Beek RLPH, Gleeson T, et al. 2017. A global-scale two-layer transient groundwater model: Development and application to groundwater depletion. Advances in Water Resources, 102: 53−67. DOI: 10.1016/j.advwatres.2017.01.011.

Fan Y, Clark M, Lawrence DM, et al. 2019. Hillslope hydrology in global change research and Earth system modeling. Water Resources Research, 55: 1737−1772. DOI: 10.1029/2018WR023903.

Fan Y, Li H, Miguez-Macho G. 2013. Global patterns of groundwater table depth. Science, 339: 940−943. DOI: 10.1126/science.1229881.

Fang Z, Bogena H, Kollet S, et al. 2015. Spatio-temporal validation of long-term 3D hydrological simulations of a forested catchment using empirical orthogonal functions and wavelet coherence analysis. Journal of Hydrology, 529: 1754−1767. DOI: 10.1016/j.jhydrol.2015.08.011.

Feng D, Gleason CJ. 2024. More flow upstream and less flow downstream: The changing form and function of global rivers. Science, 386: 1305−1311. DOI: 10.1126/science.adl5728.

Flores JA, Gleason CJ, Brown C, et al. 2025. Accelerating river discharge in high mountain asia. AGU Advances, 6: e2024AV001586. DOI: 10.1029/2024AV001586.

Ford D, Williams PD. 2007. Karst hydrogeology and geomorphology. John Wiley & Sons.

Gleeson T, Cuthbert M, Ferguson G, et al. 2020. Global groundwater sustainability, resources, and systems in the Anthropocene. Annual Review of Earth and Planetary Sciences, 48: 431−463.

Gnann S, Baldwin JW, Cuthbert MO, et al. 2025. The influence of topography on the global terrestrial water cycle. Reviews of Geophysics, 63: e2023RG000810. DOI: 10.1029/2023RG000810.

Gurdak JJ. 2017. Climate-induced pumping. Nature Geoscience, 10: 71−71. DOI: 10.1038/ngeo2885.

Habib A. 2020. Exploring the physical interpretation of long-term memory in hydrology. Stochastic Environmental Research and Risk Assessment, 34: 2083−2091. DOI: 10.1007/s00477-020-01883-0.

Hao H, Zhang J, Illman WA, et al. 2025. Insight into karst hydrological processes in the frequency domain: Critical frequency, phase difference, causality, and machine learning model. Journal of Hydrology, 663: 134150. DOI: 10.1016/j.jhydrol.2025.134150.

Hartmann J, Moosdorf N. 2012. The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochemistry, Geophysics, Geosystems, 13: 2012GC004370. DOI: 10.1029/2012GC004370.

Herbert C, Döll P. 2025. Assessing groundwater drought hazard in groundwater depletion regions: recommendations for large-scale drought early warning systems. Water Resources Research, 61: DOI: 10.1029/2024wr038684.

Hu T, Peng J, Qiu S, et al. 2024. Social-ecological heterogeneity drove contrasting tree cover restoration in south China karst. Communications Earth & Environment, 5: 484. DOI: 10.1038/s43247-024-01641-y.

Hu Z, Chai L, Crow WT, et al. 2022. Applying a wavelet transform technique to optimize general fitting models for SM analysis: A case study in downscaling over the Qinghai–Tibet Plateau. Remote Sensing, 14: 3063. DOI: 10.3390/rs14133063.

Huang P, Wang G, Guo L, et al. 2023. Most global gauging stations present biased estimations of total catchment discharge. Geophysical Research Letters, 50: e2023GL104253. DOI: 10.1029/2023GL104253.

Huang Z, Yeh PJF, Pan Y, et al. 2019. Detection of large-scale groundwater storage variability over the karstic regions in southwest China. Journal of Hydrology, 569: 409−422. DOI: 10.1016/j.jhydrol.2018.11.071.

Huggins X, Gleeson T, Famiglietti JS, et al. 2025. A review of open data for studying global groundwater in social–ecological systems. Environmental Research Letters, 20: 93002. DOI: 10.1088/1748-9326/adf127.

Jalili S, Hamidi SA, Ghanbari RN. 2016. Climate variability and anthropogenic effects on lake urmia water level fluctuations, northwestern iran. Hydrological Sciences Journal, 61(10): 1759−1769. DOI: 10.1080/02626667.2015.1036757.

Jasechko S, Seybold H, Perrone D, et al. 2024. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature, 625: 715−721. DOI: 10.1038/s41586-023-06879-8.

Jiang Y, Zhang C, Yuan D, et al. 2008. Impact of land use change on groundwater quality in a typical karst watershed of southwest China: A case study of the xiaojiang watershed, yunnan province. Hydrogeology Journal, 16: 727−735. DOI: 10.1007/s10040-007-0259-9.

Kennedy CM, Oakleaf JR, Theobald DM, et al. 2019. Managing the middle: A shift in conservation priorities based on the global human modification gradient. Global Change Biology, 25: 811−826. DOI: 10.1111/gcb.14549.

Khadam IM, Kaluarachchi JJ. 2003. Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water. Environmental Impact Assessment Review, 23: 683−721. DOI: 10.1016/S0195-9255(03)00117-3.

Kuang X, Liu J, Scanlon BR, et al. 2024. The changing nature of groundwater in the global water cycle. Science, 383: eadf0630. DOI: 10.1126/science.adf0630.

LaFleur RG. 1999. Geomorphic aspects of groundwater flow. Hydrogeology Journal, 7: 78−93. DOI: 10.1007/s100400050181.

Leijnse M, Bierkens FPM, Gommans HM, et al. 2024. Key drivers and pressures of global water scarcity hotspots. Environmental Research Letters, 19: 54035. DOI: 10.1088/1748-9326/ad3c54.

Li P, Tian R, Xue C, et al. 2017. Progress, opportunities, and key fields for groundwater quality research under the impacts of human activities in China with a special focus on western China. Environmental Science and Pollution Research, 24: 13224−13234. DOI: 10.1007/s11356-017-8753-7.

Li Y, Wang S, Peng T, et al. 2023. Hydrological characteristics and available water storage of typical karst soil in SW china under different soil–rock structures. Geoderma, 438: 116633. DOI: 10.1016/j.geoderma.2023.116633.

Liu K, Li X, Long X. 2021. Trends in groundwater changes driven by precipitation and anthropogenic activities on the southeast side of the hu line. Environmental Research Letters, 16: 94032. DOI: 10.1088/1748-9326/ac1ed8.

Liu Y, Lu C, Qiu B, et al. 2024. Spatiotemporally non-stationary evolution of groundwater levels in poyang lake basin driven by meteorological and hydrological factors. Science of the Total Environment, 950: 175244. DOI: 10.1016/j.scitotenv.2024.175244.

Long D, Xu Y, Cui YJ, et al. 2025. Unprecedented large-scale aquifer recovery through human intervention. Nature Communications, 16: 7296. DOI: 10.1038/s41467-025-62719-5.

Lu Z, Chai L, Liu S, et al. 2017. Estimating time series soil moisture by applying recurrent nonlinear autoregressive neural networks to passive microwave data over the Heihe River Basin, China. Remote Sensing, 9: 574. DOI: 10.3390/rs9060574.

Lu Z, He Y, Peng S, et al. 2023. Comprehensive evaluation of multisource soil moisture products in a managed agricultural region: An integrated hydrologic modeling approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16: 1−17. DOI: 10.1109/JSTARS.2023.3289649.

Lu Z, Peng S, Wu T, et al. 2025a. Effects of irrigation and canal networks on groundwater–land surface interactions in the middle heihe river basin, china. Journal of Hydrology: Regional Studies, 60: 102532. DOI: 10.1016/j.ejrh.2025.102532.

Lu Z, Shen C, Zhan C, et al. 2025b. Quantifying multifactorial drivers of groundwater–climate interactions in an arid basin based on remote sensing data. Remote Sensing, 17: 2472. DOI: 10.3390/rs17142472.

Lu Z, Wei J, Yang X. 2024. Effects of hydraulic conductivity on simulating groundwater–land surface interactions over a typical endorheic river basin. Journal of Hydrology, 638: 131542. DOI: 10.1016/j.jhydrol.2024.131542.

Lu Z, Wu T, Lei J, et al. 2025c. Assessing a high-resolution integrated hydrologic model (ParFlow-CLM-HRB) in an endorheic basin of China. Journal of Hydrology, 661: 133579. DOI: 10.1016/j.jhydrol.2025.133579.

Lu Z, Yang X. 2024. Effects of microtopography on patterns and dynamics of groundwater–surface water interactions. Advances in Water Resources, 188: 104704. DOI: 10.1016/j.advwatres.2024.104704.

MacAllister DJ, Krishan G, Basharat M, et al. 2022. A century of groundwater accumulation in Pakistan and northwest India. Nature Geoscience, 15: 390−396. DOI: 10.1038/s41561-022-00926-1.

Maina FZ, Getirana A, Kumar SV, et al. 2024. Irrigation-driven groundwater depletion in the ganges-brahmaputra basin decreases the streamflow in the bay of bengal. Communications Earth & Environment, 5: 169. DOI: 10.1038/s43247-024-01348-0.

Mao H, Wang G, Liao F, et al. 2024. Spatiotemporal variation of groundwater nitrate concentration controlled by groundwater flow in a large basin: evidence from multi-isotopes (¹⁵N, ¹¹B, ¹⁸O, and ²H). Water Resources Research, 60: e2023WR035299. DOI: 10.1029/2023WR035299.

Maxwell RM, Condon LE. 2016. Connections between groundwater flow and transpiration partitioning. Science, 353: 377−380. DOI: 10.1126/science.aaf7891.

Maxwell RM, Condon LE, Kollet SJ, et al. 2016. The imprint of climate and geology on the residence times of groundwater. Geophysical Research Letters, 43: 701−708. DOI: 10.1002/2015GL066916.

Medici G, Smeraglia L, Torabi A, et al. 2021. Review of modeling approaches to groundwater flow in deformed carbonate aquifers. Groundwater, 59: 334−351. DOI: 10.1111/gwat.13069.

Mehboob MS, Kim Y. 2024. Impact of climate change on the hydrological projections over a western himalayan river basin and the associated uncertainties. Journal of Hydrology, 628: 130460. DOI: 10.1016/j.jhydrol.2023.130460.

Meles MB, Bradford S, Casillas-Trasvina A, et al. 2024. Uncovering the gaps in managed aquifer recharge for sustainable groundwater management: A focus on hillslopes and mountains. Journal of Hydrology, 639: 131615. DOI: 10.1016/j.jhydrol.2024.131615.

Moeck C, Grech-Cumbo N, Podgorski J, et al. 2020. A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships. Science of the Total Environment, 717: 137042. DOI: 10.1016/j.scitotenv.2020.137042.

National Research Council, Division on Earth and Life Studies, Commission on Geosciences, Environment and Resources, Committee for Assessing Ground Water Vulnerability. 1993. Ground water vulnerability assessment: Predicting relative contamination potential under conditions of uncertainty. National Academies Press. DOI: 10.17226/2050.

Niazi H, Wild TB, Turner SWD, et al. 2024. Global peak water limit of future groundwater withdrawals. Nature Sustainability, 7: 413−422. DOI: 10.1038/s41893-024-01306-w.

Ord JK, Getis A. 1995. Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27: 286−306. DOI: 10.1111/j.1538-4632.1995.tb00912.x.

Peng S, Ding Y, Liu W, et al. 2019. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 11: 1931−1946. DOI: 10.5194/essd-11-1931-2019.

Reinecke R, Gnann S, Stein L, et al. 2024. Uncertainty in model estimates of global groundwater depth. Environmental Research Letters, 19: 114066. DOI: 10.1088/1748-9326/ad8587.

Rodell M, Reager JT. 2023. Water cycle science enabled by the GRACE and GRACE-FO satellite missions. Nature Water, 1: 47−59. DOI: 10.1038/s44221-022-00005-0.

Scanlon BR, Fakhreddine S, Rateb A, et al. 2023. Global water resources and the role of groundwater in a resilient water future. Nature Reviews Earth & Environment, 4: 87−101. DOI: 10.1038/s43017-022-00378-6.

Sen PK. 1968. Estimates of the regression coefficient based on kendall's tau. Journal of the American Statistical Association, 63: 1379−1389.

Shen X, Niu L, Jia X, et al. 2025. Disentangling ecological restoration's impact on terrestrial water storage. Geophysical Research Letters, 52: e2024GL111669. DOI: 10.1029/2024GL111669.

Shi P, Tang H, Qu S, et al. 2024. Drought propagation in karst and non-karst regions in southwest China compared on a daily scale. Journal of Hydrology: Regional Studies, 51: 101628. DOI: 10.1016/j.ejrh.2023.101628.

Shu X, Xu L, Yang M, et al. 2023. Spatial distribution characteristics and migration of microplastics in surface water, groundwater and sediment in karst areas: the case of yulong river in guilin, southwest China. Science of the Total Environment, 868: 161578. DOI: 10.1016/j.scitotenv.2023.161578.

Siirila-Woodburn ER, Dennedy-Frank PJ, Rhoades A, et al. 2023. The role of atmospheric rivers on groundwater: Lessons learned from an extreme wet year. Water Resources Research, 59: e2022WR033061. DOI: 10.1029/2022WR033061.

Stevanović Z. 2015. Characterization of karst aquifer, in: Karst Aquifers—Characterization and Engineering. Springer, 47–125.

Stewart RD, Flury M, Ajami H, et al. 2025. Emerging issues and research opportunities in vadose zone processes. Vadose Zone Journal, 24: e70030. DOI: 10.1002/vzj2.70030.

Taghavi N, Niven RK, Paull DJ, et al. 2022. Groundwater vulnerability assessment: A review including new statistical and hybrid methods. Science of the Total Environment, 822: 153486. DOI: 10.1016/j.scitotenv.2022.153486.

Tanguy M, Chevuturi A, Marchant BP, et al. 2023. How will climate change affect the spatial coherence of streamflow and groundwater droughts in Great Britain? Environmental Research Letters, 18: 064048. DOI: 10.1088/1748-9326/acd655.

Taylor RG, Scanlon B, Döll P, et al. 2013. Ground water and climate change. Nature Climate Change, 3: 322−329. DOI: 10.1038/nclimate1744.

Theobald DM, Oakleaf JR, Moncrieff G, et al. 2025. Global extent and change in human modification of terrestrial ecosystems from 1990 to 2022. Scientific Data, 12(1): 606. DOI: 10.1038/s41597-025-04892-2.

Tian L, Hu L, Wang D, et al. 2024. Site-scale groundwater pollution risk assessment using surrogate models and statistical analysis. Journal of Contaminant Hydrology, 261: 104288. DOI: 10.1016/j.jconhyd.2023.104288.

van Beek LPH, Wada Y, Bierkens MF. 2011. Global monthly water stress: 1. Water balance and water availability. Water Resources Research, 47(7): W07517. DOI: 10.1029/2010WR009791.

van Jaarsveld B, Wanders N, Sutanudjaja EH, et al. 2025. A first attempt to model global hydrology at hyper-resolution. Earth System Dynamics, 16: 29−54. DOI: 10.5194/esd-16-29-2025.

Verkaik J, Sutanudjaja EH, Oude Essink GHP, et al. 2024. GLOBGM v1.0: A parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model. Geoscientific Model Development, 17: 275−300. DOI: 10.5194/gmd-17-275-2024.

Wada Y, Van Beek LPH, Van Kempen CM, et al. 2010. Global depletion of groundwater resources. Geophysical Research Letters, 37: 2010GL044571. DOI: 10.1029/2010GL044571.

Wang L, Chen W, Haung G, et al. 2024. Characteristics of super drought in southwest China and the associated compounding effect of multiscalar anomalies. Science China Earth Sciences, 67: 2084−2102. DOI: 10.1007/s11430-023-1341-4.

Wang LH, Jia B, Yuan X, et al. 2024. The slowdown of increasing groundwater storage in response to climate warming in the Tibetan Plateau. npj Climate and Atmospheric Science, 7: 286. DOI: 10.1038/s41612-024-00840-w.

Wang Z, Chen W, Piao J, et al. 2025. Synergistic effects of high atmospheric and soil dryness on record-breaking decreases in vegetation productivity over southwest China in 2023. npj Climate and Atmospheric Science, 8: 6. DOI: 10.1038/s41612-025-00895-3.

Wu H, Fang S, Yu L, et al. 2023. Limited co-benefits of protected areas in southwest China under current climate change and human modification. Journal of Environmental Management, 330: 117190. DOI: 10.1016/j.jenvman.2022.117190.

Xing X, Wang P, Wang X, et al. 2024. Dams alter the control pattern of watershed land use to riverine nutrient distribution: Comparison of three major rivers under different hydropower development levels in southwestern China. Water Research, 260: 121951. DOI: 10.1016/j.watres.2024.121951.

Xu S, Dverstorp B, Guerfi R, et al. 2023. Development of a model for radionuclide transport in streams for biosphere assessment purpose. Journal of Environmental Radioactivity, 264: 107188. DOI: 10.1016/j.jenvrad.2023.107188.

Yang C, Zhang YK, Liang X. 2018. Analysis of temporal variation and scaling of hydrological variables based on a numerical model of the sagehen creek watershed. Stochastic Environmental Research and Risk Assessment, 32: 357−368. DOI: 10.1007/s00477-017-1421-0.

Yin Z, Xu Y, Zhu X, et al. 2021. Variations of groundwater storage in different basins of China over recent decades. Journal of Hydrology, 598: 126282. DOI: 10.1016/j.jhydrol.2021.126282.

Zhai Y, Zhao X, Teng Y, et al. 2017. Groundwater nitrate pollution and human health risk assessment by using HHRA model in an agricultural area, NE china. Ecotoxicology and Environmental Safety, 137: 130−142. DOI: 10.1016/j.ecoenv.2016.11.010.

Zhang W, Zhao J, Zhang Z, et al. 2023. The economy–employment–environmental health transfer and embedded inequities of China's capital metropolitan area: A mixed-methods study. The Lancet Planetary Health, 7: e912−e924. DOI: 10.1016/S2542-5196(23)00218-8.

Zheng C, Jia L, Hu G. 2022. Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations. Journal of Hydrology, 613: 128444. DOI: 10.1016/j.jhydrol.2022.128444.

Zhong Y, Tian B, Kim H, et al. 2025. Over 60% precipitation transformed into terrestrial water storage in global river basins from 2002 to 2021. Communications Earth & Environment, 6: 53. DOI: 10.1038/s43247-024-01967-7.

Zhou S, Yu B, Lintner BR, et al. 2023. Projected increase in global runoff dominated by land surface changes. Nature Climate Change, 13: 442−449. DOI: 10.1038/s41558-023-01659-8.

Zomer RJ, Xu J, Trabucco A. 2022. Version 3 of the global aridity index and potential evapotranspiration database. Scientific Data, 9: 409. DOI: 10.1038/s41597-022-01493-1.

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