Optimal Estimation of Hydrogeologic Parameters in Unconfined Aquifer Systems Using the Shuffled Ant Lion Optimization Approach

Abstract

The estimation of aquifer parameters is a critical issue in groundwater modeling. Traditionally, these parameters are determined using manual curve-matching techniques. However, the accuracy of these methods heavily relies on the modeler’s expertise, which can lead to graphical or human-induced errors. To address these challenges, a coupled simulation-optimization framework is proposed for identifying the hydrogeologic parameters of unconfined aquifer systems. In the simulation phase of the proposed framework, drawdown values at specified locations and times are simulated based on Neuman’s solution for unconfined aquifers. This simulation part is then integrated into an optimization model that employs the recently introduced SHuffled Ant Lion Optimization (SHALO) approach. The primary goal of SHALO-based optimization approach is to minimize the discrepancy between simulated and observed drawdown values to accurately estimate hydrogeologic parameters. The effectiveness of the proposed approach is assessed using a pumping test dataset from the literature. The results demonstrate that the SHALO-based simulation-optimization framework outperforms the manual curve-matching techniques in parameter estimation accuracy. © 2025 International Multidisciplinary Scientific Geoconference. All rights reserved.