Spatial optimization of cropping pattern in the upper-middle reaches of the Heihe River basin, Northwest China

Agriculture has by far the largest water footprint of human activities. Improving the water productivity of crop production is key to enhancing both water and food security. Irrigation is a significant pressure on water resources in the arid region of Northwest China. Here, we examine optimizing the regional cropping distribution within the Heihe River basin for achieving the dual goals of improving productivity and reducing irrigation water demand. The Soil and Water Assessment Tool (SWAT) and a cellular automata model are employed to model the processes of cropping pattern changes. The optimization takes the maximum of crop water productivity (CWP), the maximum economic water productivity (EWP) and the maximum nutrient water productivity (NWP) as the objective function. The model optimizes the spatial distribution of six crops including corn, spring wheat, spring barley, spring canola-Polish, alfalfa and upland cotton. Results show that under the premise of considering food security, the maximization of water productivity for CWP, EWP, and NWP, leads to the reduction of corn planting area and the eastward shift of corn planting region. A significant decrease in the proportion of wheat planting occurs in the objective of EWP maximization, while the planting proportion of barley and canola increased significantly. All three optimization objectives yield cropping distributions that reduce the irrigation water demand of cultivated land and improve the water productivity of the basin, among which maximizing CWP scenario has the greatest water-saving intensity. Furthermore, from the perspective of ecosystem services, the cropping distribution of maximizing EWP is more reasonable for the basin. Different cropping change scenarios provide effective references for decision makers to make a reasonable cropping distribution in the region.