Using a Surface Energy Balance Model (ReSET-Raster) to Estimate Seasonal Crop Water Use for Large Agricultural Areas: Case Study of the Palo Verde Irrigation District

Water accounting for agricultural areas is crucial for irrigation water management. Actual crop evapotranspiration (ET) is needed as an important input for agricultural water accounting, yet obtaining accurate measurements of actual ET for all crops in an area that reflects the spatial variability in crop condition is not possible with the traditional ET estimation methods. The traditional ET estimation methods are based on using weather-based reference ET and crop coefficients (Kc). This traditional approach usually overestimates crop water use because most users assume that crops are in close to optimal growing conditions (i.e., potential ET) which is not always the case. The objective of this paper is to assess the use of actual evapotranspiration estimated by a surface energy balance model called remote sensing of evapotranspiration (ReSET-Raster) in estimating seasonal crop water use for large agricultural areas instead of the traditional ET estimation method based on reference ET and crop Kc. Daily and seasonal ${\mathrm{ET}}_a$ (actual ET from ReSET-Raster) for the Palo Verde Irrigation District (PVID) was estimated using 27 Landsat 7 images for calendar year 2002. The results show that seasonal crop water use estimates for PVID, based on the traditional approach, using weather station–based reference ET and crop Kc, was up to 16% higher than the seasonal crop water use estimated by the ReSET-Raster model. Ground surface energy balance based models (EB) give better estimates of seasonal ${\mathrm{ET}}_a$ than traditional method that use reference ET and crop Kc. The reason for this is that EB models estimate the ET under actual growing conditions, for the cultivated areas and these models capture the spatial variability in ET, although the currently used approach of weather station–based reference ET and crop Kc mostly assumes consistent ideal growing conditions in the whole area.