Satellite-Based energy balance for estimating actual sugarcane evapotranspiration in the Ethiopian Rift Valley

Satellite-derived actual evapotranspiration (ETa) maps are essential for the development of innovative water management strategies. Over the past decades, multiple novel satellite remote sensing-based surface energy balance (SEB) ETa modeling tools have been widely used to account for field-scale crop water use and irrigation monitoring. However, their predictive capabilities for intensively irrigated commercial sugarcane plantations in the semiarid ecosystems of the Main Ethiopian Rift remain unclear. In this study, we applied and evaluated the comparative performance of four well-established SEB models-SEBAL (Surface Energy Balance Algorithm for Land), METRIC (Mapping Evapotranspiration with Internalized Calibration), SSEB (Simplified Surface Energy Balance), and SSEBop (Operational Simplified Surface Energy Balance)-to estimate ETa using Landsat imagery and weather measurements for the 2021-2022 season, along with an independent validation benchmark, actual evapotranspiration and interception (ETIa), and sugarcane evapotranspiration (ETc) data over irrigated sugarcane monoculture fields at the Metehara Sugar Estate in the Ethiopian Rift Valley. Cumulatively, the Landsat ETa maps derived from the SEB models tracked spatially explicit patterns in the temporal dynamics of sugarcane water use footprint with a higher coefficient of determination (R2) of > 0.90, with irrigation consumption accounting for more than 80 % of the water fluxes. At the field scale, SSEBop estimated average ETa with superior accuracy (R2 > 0.96; root mean square error (RMSE) = 0.29-5.9 mm; Nash-Sutcliffe model efficiency coefficient (NSE) = 0.86-0.92), resulting in a strong agreement with ETIa (d = 0.95-0.98) and lower percentage bias (PBIAS approximate to 4 %), followed by SSEB (R2 > 0.91; RMSE = 0.25-12 mm, NSE = 0.64-0.89, PBIAS <= 8 %), while SEBAL and METRIC estimated ETa with higher relative mean errors (RMSE = 0.83-24 mm) and PBIAS of 17 %. We found a reasonable concordance of the model-predicted average ETa with ETIa and ETc values during the early sugarcane growth phases, with a higher deviation during the mid-peak atmospheric demand season and late growth phases. The estimated annual ETa (mm yr-1) ranged from 1303 to 1628 (2021) and 1185-1737 (2022), resulting in a two-year (2021-2022) average-of 1318-1682 mm and seasonal ETa of 2238-2673 mm. Furthermore, we established a hierarchical rating method based on selected performance-metrics, which ranked the proposed models as follows: SSEBop > SSEB > METRIC > SEBAL. In this sense, our findings showed how the optimal method for estimating ETa, which serves as a proxy for-consumptive water use, can be prioritized for irrigated dryland crops with limited in situ measurements by assimilating model sets with publicly available Earth observation satellite imagery and locally recorded weather data.