Spatiotemporal Analysis of Groundwater Storage Changes and Its Driving Factors in the Semi-Arid Region of the Lower Chenab Canal

Groundwater depletion is among the most critical hydrological threats to sustainable agriculture and water security in semi-arid regions. This study presents a high-resolution, multi-sensor assessment of groundwater storage (GWS) dynamics across the Lower Chenab Canal (LCC) command area in Punjab, Pakistan—an intensively irrigated agro-hydrological system within the Indus Basin. We integrated downscaled GRACE/GRACE-FO-derived total water storage anomalies with CHIRPS precipitation, MODIS evapotranspiration (ET) and vegetation indices, TerraClimate soil moisture, land surface temperature (LST), land use/land cover (LULC), and population density using the Google Earth Engine (GEE) platform to reconstruct spatiotemporal GWS changes from 2002 to 2020. The results reveal a persistent and accelerating decline in groundwater levels, averaging 0.52 m yr−1, which intensified to 0.73 m yr−1 after 2014. Cumulative GWS losses exceeded 320 mm yr−1, with severe depletion (up to −3800 mm) in northern districts such as Sheikhupura, Gujranwala, and Narowal. Validation with borewell data (R2 = 0.87; NSE = 0.85) confirms the reliability of the remote sensing estimates. Statistical analysis indicates that anthropogenic drivers (population growth, urban expansion, and intensive irrigation) explain over two-thirds of the observed variability (R2 = 0.67), whereas precipitation contributes only marginally (R2 = 0.28), underscoring the dominance of human-induced stress over climatic variability. The synergistic rise in evapotranspiration, land surface temperature, and cultivation of high-water-demand crops such as rice and sugarcane has further amplified hydrological imbalance. This study establishes an operational framework for integrating satellite and ground-based observations to monitor aquifer stress at basin scale and highlights the urgent need for adaptive, data-driven groundwater governance in the Indus Basin. The approach is transferable to other data-scarce semi-arid regions facing rapid aquifer depletion, aligning with the global targets of Sustainable Development Goal 6 on water sustainability.

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Publication Details

Journal
Hydrology
Published
2025-12-11
DOI
https://doi.org/10.3390/hydrology12120330
Primary Topic
Groundwater and Watershed Analysis
Type
article
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article

Spatiotemporal Analysis of Groundwater Storage Changes and Its Driving Factors in the Semi-Arid Region of the Lower Chenab Canal

Naeem Saddique, Lubna Anjum, Rana Ammar Aslam, Shazia Shukrullah et al.
Hydrology
Groundwater and Watershed Analysis
article

Spatiotemporal Analysis of Groundwater Storage Changes and Its Driving Factors in the Semi-Arid Region of the Lower Chenab Canal

Naeem Saddique, Lubna Anjum, Rana Ammar Aslam, Shazia Shukrullah, Abid Sarwar, Miaohua Mao, Muhammad Imran Khan, Muhammad Umar Akbar, Syed Naeem Abbas, Muhammad Hassan Ali, M. I. Abdul Aleem, Umar Farooq
article en

Abstract

Groundwater depletion is among the most critical hydrological threats to sustainable agriculture and water security in semi-arid regions. This study presents a high-resolution, multi-sensor assessment of groundwater storage (GWS) dynamics across the Lower Chenab Canal (LCC) command area in Punjab, Pakistan—an intensively irrigated agro-hydrological system within the Indus Basin. We integrated downscaled GRACE/GRACE-FO-derived total water storage anomalies with CHIRPS precipitation, MODIS evapotranspiration (ET) and vegetation indices, TerraClimate soil moisture, land surface temperature (LST), land use/land cover (LULC), and population density using the Google Earth Engine (GEE) platform to reconstruct spatiotemporal GWS changes from 2002 to 2020. The results reveal a persistent and accelerating decline in groundwater levels, averaging 0.52 m yr−1, which intensified to 0.73 m yr−1 after 2014. Cumulative GWS losses exceeded 320 mm yr−1, with severe depletion (up to −3800 mm) in northern districts such as Sheikhupura, Gujranwala, and Narowal. Validation with borewell data (R2 = 0.87; NSE = 0.85) confirms the reliability of the remote sensing estimates. Statistical analysis indicates that anthropogenic drivers (population growth, urban expansion, and intensive irrigation) explain over two-thirds of the observed variability (R2 = 0.67), whereas precipitation contributes only marginally (R2 = 0.28), underscoring the dominance of human-induced stress over climatic variability. The synergistic rise in evapotranspiration, land surface temperature, and cultivation of high-water-demand crops such as rice and sugarcane has further amplified hydrological imbalance. This study establishes an operational framework for integrating satellite and ground-based observations to monitor aquifer stress at basin scale and highlights the urgent need for adaptive, data-driven groundwater governance in the Indus Basin. The approach is transferable to other data-scarce semi-arid regions facing rapid aquifer depletion, aligning with the global targets of Sustainable Development Goal 6 on water sustainability.

HydrologyVol. 12(12)
Oklahoma State University (US), Commonwealth Scientific and Industrial Research Organisation (AU), University of California, Merced (US), Yantai Institute of Coastal Zone Research (CN), University of Faisalabad (PK), University of Agriculture Faisalabad (PK)
Openalex Percentile: Top 62%
Groundwater and Watershed Analysis
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