Sustainable exploitation of water resources in the framework of water-energy-food nexus in climate change conditions using new multi-objective optimization algorithm MOGWO-3D

Climate change exerts significant pressure on environmental and socio-economic systems, with water resources being among the most affected. Water, energy, and food form three interdependent pillars within the agricultural sector. Each of these pillars is influenced by climatic variability, and each also contributes to it. Because these components interact in complex ways, their management cannot be separated. So, achieving long-term sustainability requires integrated strategies that consider these interactions. In the Kermanshah Plain, the absence of such an integrated approach has resulted in the unsustainable use of natural resources and growing system instability. System instability denotes the vulnerability of enviroment to disruptions in WEF resourced availability. This research introduces a comprehensive framework for conjunctive surface–groundwater management under climate change conditions using the water-energy-food (WEF) nexus concept. Guided by projections from the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC6), the framework simulates future changes in temperature and precipitation. It evaluates the resulting impacts on water availability and develops adaptive strategies for sustainable resource management. A coupled WEAP–MODFLOW model was used to dynamically simulate surface–groundwater interactions across the Kermanshah Plain. Based on these simulations, a multi-objective optimization model was developed using the three-dimensional Multi-Objective Gray Wolf Optimizer (MOGWO-3D). The optimization considered WEF interdependencies and sought the most efficient cropping pattern and resource allocation under projected climate scenarios. System performance was then assessed by comparing the optimized configuration with a reference SSP8.5Hy scenario. The WEF index analysis identified tomatoes, sugar beets, and potatoes as the most influential crops, with correlation coefficients of 0.70, 0.58, and 0.55, respectively. Implementation of the Optimized SSP8.5 Hybrid (Optimized SSP8.5Hy) scenario improved the reliability of meeting agricultural and water demands to 78.4–77.7 %, representing an increase of approximately 19–19.8 % compared with the baseline scenario. Moreover, the simulated groundwater decline was reduced by 9.5 m, indicating a 22 % improvement in subsurface resource stability. Overall, the optimization scenario demonstrated superior performance in maintaining reservoir storage levels, stabilizing groundwater, and sustaining water supply reliability across both dry and wet periods. In addition, the approach mitigated environmental risks associated with agricultural activities, including soil degradation, nutrient runoff, and greenhouse gas emissions. These findings confirm that the proposed simulation–optimization framework provides a robust basis for sustainable water management and agricultural resilience under changing climatic conditions.