Water resources and their quality are paramount for urban development and maintaining ecological health, particularly in arid regions confronting water scarcity. This study assessed groundwater quality in water-stressed region in southern Iran using the newly developed Root Mean Square Water Quality Index (RMS-WQI) model in conjunction with a health risk assessment (HRA) to evaluate potential risks to human health. Analysis of groundwater samples revealed that approximately 99.41 % of sites met the permissible limits for pH, fluoride (F-), and nitrate (NO3-). Total dissolved solids (TDS) exceeded the recommended guidelines at nearly 63.90 % of locations. The RMS-WQI classified groundwater quality as ranging from "marginal" to "good", with scores between 43.20 and 85.33 (averaging 62.91 +/- 9.33). The Extremely Randomized Trees (ExT) algorithm demonstrated strong predictive capability for RMS-WQI, with sensitivity analysis identifying electrical conductivity (EC) and chloride (Cl-) as the most influential parameters. The HRA results indicated notable health risks from Fand NO3- exposure, particularly among children, where the hazard index (HI) exceeded the safety threshold at 57.4 % of sites. Ingestion rate (IR) was the dominant contributor to HI across all age groups. NaCl is found to be a major constituent of the regional groundwater. These findings highlight the efficacy of integrating RMS-WQI with machine learning tools for a robust assessment of groundwater quality and associated health risks in arid environments.