Understanding the Food‐Energy‐Water Nexus in Mixed Irrigation Regimes Using a Regional Hydroeconomic Optimization Modeling Framework

Understanding the nexus between food, energy, and water systems (FEW) is critical for basins with intensive agricultural water use as they face significant challenges under changing climate and regional development. We investigate the food, energy, and water nexus through a regional hydroeconomic optimization (RHEO) modeling framework. The crop production in RHEO is estimated through a hierarchical regression model developed using a biophysical model, AquaCropOS, forced with daily climatic inputs. Incorporating the hierarchical model within the RHEO also reduces the computation time by enabling parallel programming within the AquaCropOS and facilitates mixed irrigation—rainfed, fully irrigated and deficit irrigation—strategies. To demonstrate the RHEO framework, we considered a groundwater‐dominated basin, South Flint River Basin, Georgia, for developing mixed irrigation strategies over 31 years. Our analyses show that optimal deficit irrigation is economically better than full irrigation, which increases the groundwater pumping cost. Thus, considering deficit irrigation in a groundwater‐dominated basin reduces the water, carbon, and energy footprints, thereby reducing FEW vulnerability. The RHEO also could be employed for analyzing FEW nexus under potential climate change and future regional development scenarios. Key Points A new regional hydroeconomic optimization modeling framework is proposed for mixed irrigation regimes using AquaCropOS Optimal deficit irrigation strategy is economically better than full irrigation by reducing the cost and energy for groundwater pumping Crop simulation module and optimization module are linked using Bayesian Hierarchical Model to reduce computation time