Decision support system for estimating actual crop evapotranspiration using remote sensing, GIS and hydrological models

Abstract

Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In the past, various estimation methods have been developed for different climatologically data, and the accuracy of these methods varies with climatic conditions. Therefore, Remote Sensing and GIS techniques with Hydrological Models are used to develop a friendly decision support system (DSS) for estimating of the Actual Crop ET. For given data availability and climatic conditions, the developed model estimates ET. The ET estimation methods are based on combination theory, radiation, temperature, and Remote Sensing methods; the model selects the best ET estimation method based on ASCE rankings. In order to evaluate the DSS, various tests were conducted with different data availability conditions for three climatological studies at the stations CAMA, NWRA, and Al-Irra. The decisions made by the model exactly matched the ASCE rankings. For the two climatic stations NWRA, and CAMA, ET values were estimated by all applicable methods using this models was developed for ERDAS Imagine and Arc-GIS software and were compared with the Penman-Monteith ET estimates, which were taken as the standard. Based on the weighted average standard error of the estimate, the modified SEBAL , and Biophysical model methods ranked first, respectively, for areas near the CAMA and NWRA stations. The SEBALID ranked first for Al-Irra station. The DSS model is developed as user tool for estimating ET under different data availability and climatic conditions.