Application of SEBAL for Western US Water Rights Regulation and Planning

Abstract

Quantifying evapotranspiration (ET) from irrigated projects is important for water rights management, water resources planning and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (K c ) determined according to the crop type and the crop growth stage. However, there is typically some question regarding whether the crops grown compare with the conditions represented by the K c values, especially in water short areas. In addition, it is difficult to predict the correct crop growth stage dates for large populations of crops and fields. Recent developments in satellite remote sensing ET models have enabled us to accurately estimate ET and K c for large populations of fields and water users and to quantify net ground-water pumpage in areas where water extraction from underground is not measured. SEBAL (Surface Energy Balance Algorithm for Land) is an image-processing model comprised of twenty-five submodels for calculating evapotranspiration (ET) as a residual of the surface energy balance. SEBAL was developed in the Netherlands by Bastiaanssen and was extended during Idaho applications for mountainous terrain and with tighter integration with ground-based reference evapotranspiration. SEBAL has been applied with Landsat images in southern Idaho to predict monthly and seasonal ET for water rights accounting and for operation of ground water models. ET “maps” (i.e., images) via SEBAL provide the means to quantify, in terms of both the amount and spatial distribution, the ET on a field by field basis. The ET images generated by SEBAL show a progression of ET during the year as well as distribution in space. ET from satellite images may ultimately replace current procedures used by state departments of Water Resources and other management entities and ministries that rely on ground-based ET equations and generalized crop coefficients that have substantial uncertainty. Initial application and testing of SEBAL indicates substantial promise as an efficient, accurate, and inexpensive procedure to predict the actual evaporation fluxes from irrigated lands throughout a growing season.