Decision Support System for Estimating Reference Evapotranspiration

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 climatological data, and the accuracy of these methods varies with climatic conditions. Therefore, a user-friendly decision support system (DSS) was developed for estimation of the reference value, ETo. For given data availability and climatic conditions, the developed model estimates ETo with the best available method out of the nine methods. The ETo estimation methods are based on combination theory, radiation, temperature, and pan evaporation; the model selects the best ETo estimation method based on ASCE rankings. In order to evaluate the DSS, various tests were conducted with different data availability conditions for five climatological stations (Davis, Bellary, Kharagpur, Jagdalpur, and Bombay). The decisions made by the model exactly matched the ASCE rankings. For the three climatic stations Davis, Jagdalpur, and Kharagpur, ETo values were estimated by all applicable methods using the user defined options menu and were compared with the Penman-Monteith ETo estimates, which were taken as the standard. Based on the weighted average standard error of the estimate, the Hargreaves and FAO-24 Blaney-Criddle methods ranked first, respectively, for the Davis and Jagdalpur stations. The 1982 Kimberly-Penman method ranked first for Kharagpur. The DSS model is a user-friendly tool for estimating ETo under different data availability and climatic conditions.