Estimation of root-zone soil moisture using crop water stress index (CWSI) in agricultural fields

Due to the limited availability of Root-Zone Soil Moisture (RZSM) information at regional scale, this paper explores use thermal infrared remote sensing estimate RZSM in agricultural fields. This study presents Crop Water Stress Index (CWSI) derived from data used as an indicator root zone soil moisture. Theoretical limits were calculated using canopy and air temperature difference, which is related vapor pressure deficit. An empirical model was developed continuous remotely sensed optical, with meteorological collected a wheat site, Dookie experimental farm, Victoria, Australia during 2012 2013. Linear exponential models predicting CWSI constructed compared two different cropping seasons. Cross-validation results demonstrate that linear predicted error 3.9% 5.3% 2013 The proposed method applied another root-zone moisture dataset 2002–04 seasons corn field site Optimizing Production Inputs for Economic Environmental Enhancement (OPE3) USA. Validation showed produces reasonable estimates, except high rainfall distribution even though crop types calibration validation sites different. efficacy estimations demonstrated OPE3 dataset. potential limitation sparse vegetation initial growth stages negative values due dominant surface. Overall, support role theoretical water stress index estimations.