A fully coupled crop-water-energy balance model based on satellite data for maize and tomato crops yield estimates: The FEST-EWB-SAFY model

Agricultural crop management requires extensive and comprehensive tools that allow for a full knowledge of the crops' status and growth dynamic. This study aims at estimating crop yield for maize and tomato crops over large areas at field scale. For this purpose, we developed a fully coupled model based on a parameter-saving crop growth model (Simple Algorithm For Yield estimates (SAFY)) with a water-energy balance model (Flash-flood Event-based Spatially-distributed rainfall-runoff Transformation-Energy Water Balance model (FEST-EWB)) with a double exchange of leaf area index (LAI) and soil moisture (SM) information. Both models are driven by remote sensing data and are calibrated independently from in situ measurements. Satellite LAI data are used to calibrate the crop growth model parameters, while the energy-water balance parameters are calibrated against satellite land surface temperature (LST) data. Multiple satellite data are used either at high spatial resolution (Sentinel 2 and LANDSAT 7 and 8) and at low-resolution (MODIS). Two Italian case studies are selected to test the model accuracy: the Chiese Irrigation Consortium (Northern Italy), mainly devoted to maize crop cultivation, and the Capitanata Irrigation Consortium (Southern Italy), where tomatoes are largely diffused. At local scale, LAI is reproduced for tomatoes with a mean RMSE of 0.92 and yield with a RMSE of 1.2 ton ha(-1); while for maize, a RMSE of 1 is found for LAI and a RMSE of 1.5 ton ha(-1) for yield. Results show an overall correspondence of daily soil moisture and evapotranspiration estimates with a RMSE in between 0.11 and 0.15 and of 1.3-3 mm, respectively. At the regional scale, LAI estimates show a RMSE around 1.1 for both case studies, while a RMSE of 13.4 ton ha(-1) is obtained for tomato yield and of 1.4 ton ha-1 for maize.