Abstract
This paper demonstrates the application of fuzzy inference system (FIS) employed by mapping meteorological data between known inputs (wind speed, relative humidity, temperature, and sunshine radiation) and output (evapotranspiration). The results after training show that the FIS is able to capture the nonlinear feature for evapotranspiration. Moreover, the trained FIS is integrated into geographical statistical technology for the estimation of the regional evapotranspiration, forest and farmland in Dan-Shui Basin as an example. It is found that FIS simulation effectively reduces the amounts of formula parameters, computation time, and diverse procedure, which it can be another efficient mathematical tool to deal with the study of evapotranspiration estimation.
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