Tuning the Monitoring of Actual Daily Evapotranspiration Merging Satellite Data Fusion and Surface Energy Balance

The estimation of actual daily evapotranspiration (ET) at field scale from satellite imagery poses a challenge for water management due to the spatio-temporal limitations of the current sensors operating in the thermal infrared. This study introduces a methodology that aims to address these issues by estimating ET and crop coefficients (Kc) once per week. Intermediate days are gap-filled, from these calibrated Kc and reference daily evapotranspiration (ETo) values. Weekly ET estimates were obtained using recent advances in Sentinel-3, Sentinel-2 and Landsat satellite data fusion as inputs in a Two Source Energy Balance (TSEB) model. This research was carried out in a semiarid region in southeastern Spain. An experiment was conducted in a drip-irrigated almond orchard between June 5 and July 25, 2023. The resulting ET was evaluated using data from an eddy-covariance tower. An overall bias of 1.0 mm•day
^-1
and a root mean square error of 1.5 mm•day
^-1
were revealed. These results underscore the feasibility of the proposed method to monitor almond crop evapotranspiration at the field scale on a daily basis while minimizing computational workload.