A Novel Approach to the Optimization of the Spatial Distribution of the Multiple Crop Pattern on a River Basin Scale

Nowadays, with the ongoing advancement of social economy and water demands, the value of water resources has increased, and the crop pattern management, in terms of water consumptions and economic benefits has become significantly important. To achieve an optimal crop pattern on a river basin scale, a spatiotemporal agro-hydrologic simulation model, SWAT (Soil and Water Assessment Tool), was coupled to the multi-objective particle swarm optimization algorithm in a simulation-optimization (S-O) framework. The SWAT model of the Seymareh River Basin (SRB), in terms of hydrological and agronomic measures, was calibrated and validated from year 2003 to 2016. Two problems concerning determinations of I) crop area and II) crop type and area, were defined by focusing on increased economic benefit and decreased water consumption, which were constrained to available land and water resources. In Problem I, the crop types were predefined as the current situation in each sub-basin and in Problem II, the crop types were variable. The results indicated that in Problem I, the most water-efficient and economic solutions of Pareto front led to 51.94% and 39.7% lower water consumption, and 23% and 25.69% economic enhancement, respectively, compared to the current crop pattern scenario. In addition, in Problem II, the economic measure in the most water-efficient and economic alternatives increased by 35.7% and 38.7%, and the water saving measure was increased by 68% and 44%, respectively, compared to the existing crop pattern scenario. In this regard, the developed S-O framework would function as an efficient decision-making tool, particularly for river basin scale studies.