Large Scale Crop Water Footprint Evaluation Based on Remote Sensing Methods: A Case Study of Maize - Zheng Li; Shikun Sun; Jinfeng Zhao; Chong Li; Zihan Gao; Yali Yin; Yubao Wang; Pute Wu (Water Resources Research)
Abstract Agriculture is the world's largest consumer of water resources, and accurate measurement of crop water footprint (CWF) can provide a scientific basis for evaluating the water use characteristics of agricultural production and guiding water management. The measurement of regional CWF requires large amounts of ground data, and remote sensing provides an effective means to scientifically measure the CWF on a large scale. In this study, we developed an effective means to estimate regional maize CWF based on global evapotranspiration (MOD16 and Global Land Data Assimilation System (GLDAS)‐Noah) products in China. And we also calculated the CWF based on the FAO Penman‐Monteith equation (FAO‐PM) on the site scale in China. We assessed the accuracy of these methods by comparing them against eight eddy‐covariance based flux tower measurements. Links and differences behind the results of the three water footprint calculations were analyzed in terms of the basic principles and characteristics of the calculations. The results showed that the CWF had a similar distribution based on the MOD16 and GLDAS‐Noah, reflecting the influence of regional soil moisture on the CWF. Computational rationale analysis of the three quantitative methods showed that the ETc‐based method from the FAO‐PM model was similar to the MOD16‐ and GLDAS‐Noah‐based CWF in the wetter areas, two remote sensing‐based methods considered the water constraints during soil evaporation and water dissipation during dry and wet canopy conditions, and were closer to reality than the ETc‐based methods in measuring the CWF in arid and semi‐arid regions.