Quantifying the impact of climate change and urbanization on groundwater resources using geospatial modeling

Abstract

Urbanization poses a significant threat to environmental sustainability, particularly in Pakistan, where uncontrolled urban growth and water mismanagement have exacerbated water scarcity and climate variability. This study investigates the spatiotemporal impacts of urbanization and climate change on groundwater in Lahore District, Pakistan. various parameters were considered to execute the study including land use/land cover (LULC), rainfall, Land Surface Temperature (LST), ground wells and population data using advanced techniques such as Random Forest machine learning algorithm, Climate Hazards Group Infrared Precipitation, and geographically weighted regression (GWR) analysis. Our findings reveal that urbanization has severely impacted the water table in the north, northwest, and southwest areas. There is a significant negative negative correlation (−0.333) between the quantity of groundwater level (GWL) and the annual average LST whereas, the p-value (0.75) is also showing highly significant relation of GWL and LST in the study area. Whereas a positive association (0.666) exist (p-value 0.333 moderately significant) between yearly GWL and the mean precipitation. This research provides crucial insights for policymakers to understand the effects of urbanization and climate change on groundwater and develop strategies to mitigate adverse impacts in the study area.