Mahfuzur Rahman

The overexploitation of groundwater resources is a significant concern due to the potential risks associated with a decline in freshwater availability. Future planning and policymaking should consider long-term groundwater availability and urban expansion patterns to understand urban growth. This study aims to investigate the impact of land cover change on groundwater depletion. Further, the land surface temperature (LST) and vegetation change using Normalized Difference Vegetation Index NDVI analysis have been performed to find the spatial spread of urbanization and its impact on surface temperature in the area. For groundwater assessment, the Gravity Recovery and Climate Experiment (GRACE) data have been used, while for land cover, NDVI, and LST assessment, Landsat data have been used. The GRACE-based groundwater storage (GWS) anomaly has been correlated with Global Precipitation Measurement (GPM) data. An annual groundwater storage decline of ~7.01 mm/year was identified. Groundwater and land-cover changes were evaluated at five-year intervals from 1990 to 2025. The urban expansion from 838 to 1470 km² coverage shows the rapid expansion and its impact on vegetation and groundwater recharge in the area. The results demonstrate a rapid increase in the urban area, which affected the vegetation and increased the surface temperature in the area. Urban expansion reduced vegetation cover and infiltration, contributing to elevated land surface temperature and groundwater depletion. This study focused on integrating the groundwater impacts due to other environmental variables, i.e., temperature increase and vegetation decrease. The temporal increase in urban expansion decreases the infiltration rate, which impacts the groundwater storage and depletion, as shown by the linear trend. These findings underscore the urgent need for effective groundwater management and vegetation management policies and integrated urban planning strategies to ensure the long-term sustainability of freshwater resources.

The Wadi Al-Ahsaba watershed is an arid to semi-arid catchment situated in southwestern Saudi Arabia, characterized by intermittent surface flow, high evaporation and low rainfall, and a dam reservoir built for flood control. The work aims to assess hydrological and anthropogenic controls on surface and groundwater quality, pollution status, and human health risks using an integrated approach of hydrogeochemical analysis, multivariable statistics, and water quality and contamination indices. A total of 21 water samples (15 surface water, 6 groundwater) were analyzed for general chemistry, major ions, and trace elements. Hydrogeochemical analysis and principal component analysis (PCA) were implemented to differentiate the geogenic from anthropogenic control on water quality. The pollution status and associated risk were evaluated using water quality index (WQI), contamination degree (Cd), Hazard Quotient (HQ), and Hazard Index (HI). Results suggest limited surface–groundwater interaction, with surface water dominated by Ca–Mg–HCO₃ facies, indicating recent recharge and limited water–rock interaction, whereas groundwater exhibits mixed Ca–Mg–Cl and Ca–Na–Cl–SO₄ types, revealing longer residence time and water–rock interaction. Nitrate (9.5–109 mg/L) and TDS (522–1003 mg/L) exceeded drinking water standards in 90% and 95% of tested samples, respectively, and WQI ranged from 43 to 134, reflecting excellent to poor water. High non-carcinogenic risk from nitrate was observed, especially for infants. The study concluded that the geogenic processes (water–rock interaction, evaporation, and mineral dissolution) control the general chemistry of tested water, while anthropogenic input from wastewater and agriculture input are likely contributors to nitrate contamination. The study contributes to the understanding of arid wadi-dam systems by revealing how limited recharge, hydrological connectivity, and episodic flow control contaminant transport and persistence, underscoring the critical role of integrated hydrological analysis and land use management in safeguarding freshwater resources in arid environments.

Monsoon-dominated agricultural regions face increasing hydro-climatic stress driven by climate change, yet a critical methodological gap persists: no integrated, spatially explicit framework simultaneously links drought dynamics, crop water stress, and system-level stability under future climate projections. South Korea exemplifies this challenge, where seasonal water deficits, rising evaporative demand, and dependence on monsoon rainfall create compounding vulnerabilities for agricultural resilience. Here we develop a multi-index framework combining the Standardized Precipitation Evapotranspiration Index (SPEI), a modified Crop Water Stress Index (CWSI), and a Reliability-Resilience-Vulnerability (RRV) stability metric to quantify spatio-temporal patterns of water stress and resilience. Observations (1985-2014) were used to evaluate and bias-correct multiple CMIP6 models under SSP2-4.5 and SSP5-8.5. Continuous climate fields were interpolated, and Crop Water Zones (CWZs) were derived using a percentile-based 3 × 3 classification that combines interpolated RRV and CWSI. Results show increased precipitation variability and higher evaporative demand, intensifying seasonal water stress, particularly in summer and autumn. Differences between scenarios are modest in the near term, but both indicate expansion of high-risk CWZs. Bias correction improves agreement with observations; however, performance metrics are interpreted cautiously given methodological constraints. Spatial patterns indicate a shift from stable/resilient to more critical/high-risk conditions, revealing emerging vulnerabilities in agricultural systems. This framework provides a transferable approach for assessing climate-driven water stress and supports adaptive water management in monsoon-influenced regions.

Methane (CH₄) is a potent greenhouse gas that plays a critical role in global warming, yet its relationship with climate variables remains underexplored, particularly in Eastern Saudi Arabia, which hosts over 70% of the nation’s oil fields. This study presents the comprehensive analysis of the spatiotemporal variability of CH₄ and its climatic drivers using TROPOMI/Sentinel-5P data from 2019 to 2024. Results reveal significant annual and seasonal fluctuations, with CH₄ concentrations rising from 1892 to 1927 ppb. Seasonal patterns show peak concentrations in summer and autumn and lower values in winter and spring. Spatial trend analysis indicates an average increase of 5.09 ppb yr⁻¹ (MK-test). These variations are influenced by both anthropogenic and climatic factors. To examine the relationship between CH₄ and climate variables, a geographical model is applied, achieving an overall R² of 0.82. We found that CH₄ is negatively correlated with temperature, solar radiation, and wind speed, but positively correlated with precipitation and humidity. Specifically, the mean weighted regression coefficient between CH₄ and temperature was –3.709, suggesting a decline of 3.709 ppb yr⁻¹ for each unit increase in temperature, which is likely due to enhanced oxidative processes under the region’s high temperatures, driven by increased ozone and hydroxyl radicals (OH) that promote CH₄ degradation. The random forest model further quantifies these relationships, yielding an overall R² of 0.79 and an root mean squared error of 2.934 ppb. The feature importance analysis identifies temperature and humidity as the most influential factors, followed by solar radiation, precipitation, and wind speed. These findings provide critical insights into CH₄ dynamics in arid regions, offering valuable guidance for future research and policymaking.