Novel approach of upscaling the FAO AquaCrop model into regional scale by using distributed crop parameters derived from remote sensing data

Abstract

Distributed crop models were considered a useful tool for allocating rational water resources. However, how to upscale the crop model into the regional scale is a key issue because the associated crop parameters tend to have spatial heterogeneity according to their feedback to the environment. The remote sensing may provide a possible method for generating the spatial distribution of crop parameters, thereby improving the upscaling approach. On this basis, this study aims to achieve the spatial distribution of crop parameters and establish the distributed AquaCrop-RS model by means of remote sensing. The results showed that the distribution of two crop parameters, namely, the maximum canopy coverage CCx* and the relative biomass Brel* was significantly heterogeneous with the spatial variability coefficient of 8% and 8.5% for CCx* in 2012 and 2013, respectively, and that of 6.3% and 4.6% for Brel*. Compared with the AquaCrop-GIS model without introducing the spatial parameters, the simulation accuracy of AquaCrop-RS model was improved by 20% in regional crop water consumption and by 26–36% in regional yield. The new upscaling approach could be an effective and promising method of crop model upscaling.