Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China

Evapotranspiration (ET) estimation is important for understanding energy exchanges and water cycles. Remote sensing (RS) the main method used to obtain ET data over large scales. However, owing surface heterogeneities different model algorithms, estimated from RS products with spatial resolutions can cause significant uncertainties, whose causes need be thoroughly analyzed. In this study, Surface Energy Balance Algorithm Land (SEBAL) was selected explore resolution influences on simulations. Three satellite datasets (Landsat Thematic Mapper (TM), Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High-Resolution Radiometer (AVHRR)) were independently estimate in SEBAL identify influence of scale estimation, analyze effects aggregation. Results indicated that: (1) distributions three similar, MODIS-based having largest uncertainty; (2) aggregating input parameters had limited changes net radiation soil heat fluxes. errors sensible latent fluxes relatively larger, which caused by selection hot cold pixels NDVI albedo during The mechanisms larger than those land use/cover pattern model. Overall, study highlights impact provides a better aggregation effect RS.