Abstract
This study, for the first time, assesses the impact of critical environmental factors on groundwater using Bayesian network (BN) integrated with analytical hierarchy process (AHP) and develops a groundwater vulnerability map. The considered environmental factors are divided into the following categories: physical (rainfall, temperature (Tmax/Tmin), relative humidity (RHmax/RHmin)), water use and demand (surface water availability (SW) and number of tubewells (NTW)), agriculture and land use (total irrigated area (TIA), total cropped area (TCA), and total area sown (TAS)), and population. Results show a negative relationship of rainfall, RHmax/RHmin, and SW and a positive relationship of the remaining variables with groundwater. Elasticities demonstrate that a 1% change in SW (rainfall), major contributors, results in a decrease by 0.64% (0.55%) in groundwater in Bahawalpur (Multan). A 1% change in population (NTW), major consumers, results in an increase by 0.74% (0.70%) in depth to water table (DWT) across Jhang (Khanewal). The vulnerability map shows that high and very high vulnerability classes account for more than 50% of the total area of Punjab.