Abstract :
This study investigates the applicability of the data mining process in
estimation of daily pan evaporation, a fundamental element in the hydrological cycle.
Firstly, the models were developed using autoregressive modeling, frequently preferred in
hydrological studies, for Lake Egirdir in the southern part of Turkey, and the suitability of
the AR(3) model was shown. Hence, the previous 1-, 2- and 3- day, daily pan evaporation
values of Lake Egirdir were used to develop the other DM models. The correlation
coecient and root mean square error criteria were used for evaluating the accuracy of the
developed models. When the results of the developed models were compared to observed
pan evaporation according to these criteria, it was determined that the AR(3) model is a
little more appropriate in estimation of daily pan evaporation. Consequently, it was shown
that DM models are useful, as they are based on only daily pan evaporation data and do
not include meteorological parameters.
