Integrated Artificial Intelligence and Numerical Modeling for Groundwater Sustainability and Reclaimed Wastewater Utilization in Abu Dhabi’s Arid Climate

Water scarcity in hyper-arid environments like Abu Dhabi necessitates innovative and data-driven approaches for sustainable groundwater management. This study proposes an integrated modeling framework that combines artificial intelligence (AI) with numerical groundwater simulation to evaluate the impact of reclaimed wastewater reuse on aquifer sustainability. Long-term datasets (۲۰۰۰–۲۰۲۳) including groundwater levels, quality parameters (TDS, NO₃⁻), climatic variables (rainfall, temperature, ET₀), and treated wastewater volumes were compiled from Abu Dhabi’s environmental agencies. Three AI models—Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Machines (SVM)—were trained to forecast groundwater behavior and contamination risks under varying climate and usage scenarios. The ANFIS model achieved the highest accuracy with RMSE = ۰.۴۸ m, R² = ۰.۹۳, and NSE = ۰.۹۲, outperforming ANN and SVM in capturing delayed recharge dynamics. Concurrently, a MODFLOW-based finite-difference model simulated aquifer response to four water reuse scenarios, ranging from zero to ۱۰۰% reclaimed wastewater integration. Scenario C (۱۰۰% reuse with reduced pumping) resulted in a ۰.۴ m average rise in groundwater level over five years and over ۳۰% reduction in nitrate concentrations, compared to a ۱.۵ m decline in the baseline. The hybrid AI–MODFLOW model enabled real-time forecasting with spatial resolution, dynamic boundary updates, and scenario optimization. This dual-model approach demonstrated superior predictive power and operational applicability, offering a scalable, replicable solution for water resource planning in arid urban environments. The study recommends institutional adoption of reclaimed water reuse, expansion of monitoring networks, and deployment of hybrid AI-numerical tools for resilient aquifer management across the Gulf region and beyond.

کلیدواژه ها:

Abu Dhabi ، Artificial Intelligence (AI) ، Groundwater Sustainability ، Wastewater Reuse ، Adaptive Neuro-Fuzzy Inference System (ANFIS) ، MODFLOW ، Machine Learning (ANN ، SVM) ، Aquifer Recharge ، Arid Region Hydrology ، Hybrid Modeling Framework.