Assessment of Intrinsic Vulnerability of Alluvial Aquifers Using an Optimized DRASTIC and Combined Vulnerability Index Approach

Abstract

Groundwater, as one of the primary sources of drinking water and irrigation in arid and semi-arid regions, is constantly threatened by pollution resulting from human activities. This study aims to evaluate groundwater vulnerability in the Lenjanat Plain, Iran by integrating multiple index-based models and addressing the limitations of conventional approaches. Specifically, the study develops a combined vulnerability index (VI) to improve spatial reliability and applies an optimized DRASTIC model (ODI) using the analytic hierarchy process (AHP) to enhance parameter weighting. To this end, the aquifer vulnerability was first assessed using three conventional models, DRASTIC, SINTACS, and SI. Then, using nitrate concentration as the dominant pollutant indicator in the study area, the correlation between the results of each model and the groundwater quality data was calculated, based on which the weight of each model in the VI combined approach was determined. Moreover, to overcome the limitations of the classical DRASTIC model, the weights of its parameters were optimized using the AHP on the basis of local hydrogeological conditions, and the ODI model was introduced. The results indicated that over 50% of the aquifer area falls within moderate to high-vulnerability zones, and the ODI model shows better agreement with the spatial distribution of nitrate compared to classical models. The results indicated that over 50% of the aquifer area falls within moderate to high-vulnerability zones, and the ODI model shows better agreement with the spatial distribution of nitrate compared to classical models. A key contribution of this study is the integration of multi-model outputs with optimized parameter weighting and validation using observed nitrate data. Therefore, the ODI model and the VI can serve as effective tools for groundwater quality management, delineation of protection zones, and control of potential contamination sources in the Lenjanat Plain, Iran.