Estimating daily actual evapotranspiration using gap-filled satellite retrievals

Abstract

Abstract Appropriate determination of actual evapotranspiration (ETa) is crucial to improve crop water productivity and optimizing water resource consumption. Satellite data enables us to calculate ETa for a large spatial extent with higher granularity, but the temporal frequency of non-commercial satellite data is often a limitation. This research proposes a method that combines crop coefficients with satellite data to fill temporal data gaps and calculate ETa on a daily basis. The study was conducted on sugarcane crops in the Amirkabir Agro-industries area in the southern part of Khuzestan Province, southwestern Iran. First, Landsat-8 data with the 8- day temporal resolution is acquired to estimate Land Surface Temperature (LST) using Single-Channel Algorithm. The estimated LST is validated with the in-situ canopy temperature measurement via Infrared Thermometer (IRT). Then, the validated LST is used to predict the crop stress coefficient (Ks) based on its relationship with the crop water stress index (CWSI). The crop coefficient (Kc) is obtained from the Surface Energy Balance Algorithm for Land (SEBAL) algorithm. The predicted Ks and Kc with the 8-day temporal resolution are assumed to be constant during the eight days and are utilized to calculate daily ETa by multiplying by the daily reference evapotranspiration (ET0) obtained from local meteorological data. The calculated Ks based on the LST result showed that nRMSE ranged from 0.03 to 0.07 from April to September. The results indicate that the crop coefficients of sugarcane in the initial and mid-stage are 12% and 18%, respectively, higher than the proposed figures by the FAO56 guideline. The aggregated decadal and monthly ETa have shown remarkable similarity with the WaPOR datasets, represented by an RMSE of 8.7 and 1.93 mm, respectively. We think this naval approach can significantly overcome the challenge of remote sensing data availability with the desired higher temporal resolution.