Over-extraction of underground freshwater is a critical environmental challenge worldwide. This paper presents a model of three interconnected hub units designed to balance reducing freshwater extraction and minimizing the operational costs of hubs that supply electricity, heat, and water. The study employs the downside risk constraint technique to address financial risks arising from various uncertainties. The model incorporates stochastic optimization to capture the uncertainty in demand and market prices. The total obtained results, which comprise the extraction level of underground freshwater, operation cost, and risk level, are prioritized via the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) approach. The first and the last prioritized solutions are named the best and the worst cases and compared. According to the results, with a slight rise in the operation cost, the risk level and the extracted water from water wells can be reduced to near- zero, which is beneficial from an environmental perspective. The proposed Mixed-Integer Nonlinear Programming (MINLP) model is implemented and solved using the DICOPT solver in GAMS.
