Groundwater risks driven by population growth and industrialization in metropolitan cities have become a worldwide problem. Faisalabad is Pakistan’s third largest city with a population of more than 2 million and is renowned for its diverse industries. Many factories in the area dump their untreated effluent into nearby drainage systems, having a direct negative effect on the marine ecosystem. This research focuses on the Madhuana drain and Khurrianwala industrial region of Faisalabad to investigate groundwater quality status. Sixty water samples from groundwater bore wells and open wells were obtained, and all these samples were subjected to lab experiments for physical and chemical analysis. Sixteen physiochemical parameters, namely, electrical conductivity (EC), pH, total dissolved solids (TDS), total suspended solids (TSS), turbidity, carbonate, Ca²⁺, Fe, HCO₃⁻, Cl⁻, Mg²⁺, SO₂⁴⁻, As, Cr, Cu, and Mn, were examined. To provide a comprehensive picture of water quality from a human perspective, we calculated the water quality index (WQI) by integrating 16 physiochemical criteria. The results revealed that a larger proportion had poor drinking quality due to direct releases of toxins by industries. It was observed that 87% of the water samples showed an unsuitable status of groundwater for drinking purposes in terms of pH, EC, Fe, Mn, Cu, and Cr. The results of this study could be used to build and construct wastewater treatment plant facilities for the Madhuana drain, reducing pollution loads on the drain and river, as well as contaminant seepage rates into groundwater. The research’s resulting maps will help policymakers to manage groundwater supplies more efficiently for sustainable development.

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.