SEBAL Model with Remotely Sensed Data to Improve Water-Resources Management under Actual Field Conditions

Abstract

Water management emphasis tends to shift from supply augmentation to limiting water consumption. Spatio-temporal information on actual evapotranspiration (ET) helps users to better understand evaporative depletion and to establish links between land use, water allocation, and water use. Satellite-based measurements, used in association with energy balance models, can provide the spatial distribution of ET for these linkages. This paper describes the major principles of the Surface Energy Balance Algorithm for Land (SEBAL) and summarizes its accuracy under several climatic conditions at both field and catchment scales. For a range of soil wetness and plant community conditions, the typical accuracy at field scale is 85% for