A Suitable Tool for Sustainable Groundwater Management

Artificial recharge is used to increase the availability of groundwater storage and reduce saltwater intrusion in coastal aquifers, where pumping and droughts have severely impaired groundwater quality. The implementation of optimal recharge methods requires knowledge of physical, chemical, and biological phenomena involving water and wastewater filtration in the subsoil, together with engineering aspects related to plant design and maintenance operations. This study uses a novel Decision Support System (DSS), which includes soil aquifer treatment (SAT) evaluation, to design an artificial recharge plant. The DSS helps users make strategic decisions on selecting the most appropriate recharge methods and water treatment technologies at specific sites. This will enable the recovery of safe water using managed aquifer recharge (MAR) practices, and result in reduced recharge costs. The DSS was built using an artificial intelligence technique and knowledge-based technology, related to both quantitative and qualitative aspects of water supply for artificial recharge. The DSS software was implemented using rules based on the cumulative experience of wastewater treatment plant engineers and groundwater modeling. Appropriate model flow simulations were performed in porous and fractured coastal aquifers to evaluate the suitability of this technique for enhancing the integrated water resources management approach. Results obtained from the AQUASTRESS integrated project and DRINKADRIA IPA CBC suggest the most effective strategies for wastewater treatments prior to recharge at specific sites.