Optimization of Agricultural Systems Under Water-Energy-Food Nexus: A Framework for the Urmia Lake Basin

Abstract

The Urmia Lake Basin (ULB) in northwest Iran faces critical water management challenges significantly impacting agricultural sustainability and regional water–food security. This study presents a novel framework employing multi-objective linear programming to optimize crop selection and resource allocation strategies, addressing critical trade-offs inherent within the water–energy–food (WEF) nexus. Central to this framework is the Water–Energy–Food Nexus Index (WEFNI), which integrates seven pivotal productivity indicators: water consumption indicator (WCI), energy consumption (EC), water mass productivity (WMP), energy mass productivity (EMP), economic water productivity (EWP), and economic energy productivity (EPE). The analysis leverages 22 years of agricultural data (1995–2016) for the primary crops (wheat, barley, sugar beet, alfalfa, corn, and fruits) cultivated within the basin. Three distinct optimization scenarios are assessed: maximizing combined WEF productivity and economic returns (Sc1); maximizing WEF productivity with minimized water consumption (Sc2); maximizing economic returns under stringent water use limitations (Sc3). Results consistently identify corn as the superior crop in terms of water–energy efficiency, whereas sugar beet demonstrated the lowest overall performance. This robust optimization approach elucidates critical trade-offs, providing actionable insights for policymakers managing similar water-stressed regions, although specific regional calibrations are necessary.