<p>Effective water resource management in the Lower Thamirabarani sub-basin is essential due to increasing water demand, pollution, and climate change-induced flood risks. The mixing of treated wastewater with reservoir water has led to deterioration in water quality, including eutrophication, highlighting the need for strategic separation and management. This study integrates Geographic Information Systems (GIS) and machine learning techniques to identify optimal sites for dams and wastewater treatment plants, addressing challenges related to water storage, groundwater recharge, and flood mitigation. A multi-criteria approach incorporating hydrological, geological, and water quality assessments was employed to evaluate potential dam sites. Sixteen suitable locations were identified based on topography, flow accumulation, and soil properties, with six sites strategically placed along the river for efficient freshwater storage and groundwater recharge. Additionally, 12 wastewater treatment plants were proposed to collect and treat wastewater before release, reducing contamination risks. Areas such as Melamunnirpallam, Manimoorthispuram, and Muthulangurichi were found suitable for dam construction, while Mehanmmudayarkulam and Pattamadai were identified as optimal for wastewater treatment facilities. This study provides an innovative framework for integrating advanced spatial analysis and machine learning models in water resource planning. The findings support evidence-based decision-making for sustainable water management, helping mitigate flood risks and improve water quality. The proposed approach serves as a model for similar regions facing water security challenges, promoting environmental sustainability and efficient resource utilization in rapidly urbanizing watersheds.</p>