Estimating actual evapotranspiration (ETa) and crop coefficients (Kc) is crucial for efficient water management in sugarcane crops in Colombia. Because the implementation of water use policies in agriculture has made water management strategies increasingly demanding, the use of surface energy modeling tools such as the Surface Energy Balance Algorithm for Land (SEBAL) and the Simple Algorithm for Evapotranspiration Retrieving (SAFER) has gained importance. These tools not only estimate the amount of water based on evapotranspiration for each satellite-image pixel, but also determine Kc values along with information gathered by weather stations. This study aimed to estimate the ETa and Kc of sugarcane using the SEBAL and SAFER algorithms. Thirteen central pivots located in the sugarcane-growing region of the Cauca river valley were studied for three consecutive crop cycles between 2018 and 2021. Analyses were performed on Landsat 8 satellite images for both modeling algorithms. Reference evapotranspiration (ETo) data from 37 weather stations of the Colombian sugar sector were also interpolated to determine Kc values. SEBAL-based analysis results for ETa showed maximum values of 4.2 mm.day-1 and minimum values of 1.02 mm.day-1, while SAFER yielded maximum values of 3.8 mm.day-1 and minimum values of 1.02mm.day-1. SEBAL-based analysis results for Kc indicated maximum values of 0.9 and minimum values of 0.2, while those of SAFER indicated maximum values of 0.7 and minimum values of 0.1. Although the ETa and Kc values estimated using these models were lower compared with those of FAO 56 and should be calibrated using a direct method, these models showed potential to be applied in water management programs for Colombia’s Cauca river valley.
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