Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products

Abstract

Agriculture is required to produce more food while reduce water consumption at the same time. To improve the irrigation water use efficiency in agricultural production, this study proposed a fuzzy multiobjective optimal modeling approach based on Moderate-resolution Imaging Spectroradiometer (MODIS) global evapotranspiration products for optimizing spatial water footprint of crop planting. This study attempts to accurately estimate the spatial crop water footprint based on remote sensing information, and effectively plan crop planting structure considering conflicting targets, spatial water footprint, and limited irrigation water resources under fuzzy uncertainty. To test its feasibility, the proposed approach is employed to a typical semi-arid region in Northwest China. Three performance evaluation indicators, including synthetic degree (SD), sustainability index (SI), and approximation degree of ideal objective value (AD), are applied for measuring model performance and try to give a more comprehensive picture of agricultural land use strategies. Results show that (1) the remote sensing data can effectively improve the accuracy of water footprint estimation, and identify crop planting advantage distribution in spatial; (2) the planting area of crops with high evapotranspiration should be increased in irrigation districts near the upstream with high precipitation, which can improve economic benefit, increase utilization rate of green water, and fairness of allocation; (3) through optimization, the average total, blue, and gray water footprint among IDs are drop while green water utilization rates is raised comparing with status quo (2014); (4) Water scarcity will not only damage the coordinated development degree of economy, society and environment, but also hurt the regional sustainable development ability and the realization of development objectives. The proposed optimal modeling framework can help optimize the spatial water footprint of crop planting and improve irrigation water use efficiency, which can be applied to similar regions that suffer from water scarcity.