Exploring the optimal crop planting structure to balance water saving, food security and incomes under the spatiotemporal heterogeneity of the agricultural climate

Crop planting provided foods, generated incomes, and consumed water resources to different extents under different spatiotemporal agroclimatic conditions. For balancing three aspects, targeting the rice, maize, wheat, and sorghum planted in Liaoning during the recent two decades, we established an integrated research framework consisting of water footprint (WF) accounting, clustering analysis, and fuzzy optimization programming to quantify the temporal trends and spatial distribution of water footprints, and optimized the planting structure under the different spatiotemporal agroclimatic conditions. Results showed that the maximum water footprint differences were 4166.73 m3/t and 4790.71 m3/t in spatial distribution and temporal series, respectively. Based on precipitation, we established 12 agroclimatic scenarios according to K-Means clustering. The fuzzy optimization result indicated that the planting area percent ranges of maize, wheat, rice, and sorghum in Liaoning province were 4.96%-98.62%, 0.00%-8.55%, 0.00%-18.18%, and 0.00%-95.04%, respectively under the different spatiotemporal conditions. This study's methods and results help make targeted decisions related to grain planting structure while considering the complex spatial-temporal conditions.

Automated summary

The study aimed to quantify the temporal trends and spatial distribution of water footprints, and optimize the planting structure under different spatiotemporal agroclimatic conditions. Results showed significant differences in water footprints, helping make more targeted decisions related to grain planting structure while considering complex spatial-temporal conditions.