Estimating daily pan evaporation using data mining process

This study investigates the applicability of the data mining process inestimation of daily pan evaporation, a fundamental element in the hydrological cycle.firstly, the models were developed using autoregressive modeling, frequently preferred inhydrological studies, for lake egirdir in the southern part of turkey, and the suitability ofthe ar(3) model was shown. hence, the previous 1-, 2- and 3- day, daily pan evaporationvalues of lake egirdir were used to develop the other dm models. the correlationcoecient and root mean square error criteria were used for evaluating the accuracy of thedeveloped models. when the results of the developed models were compared to observedpan evaporation according to these criteria, it was determined that the ar(3) model is alittle more appropriate in estimation of daily pan evaporation. consequently, it was shownthat dm models are useful, as they are based on only daily pan evaporation data and donot include meteorological parameters.