Comparison of two different data-driven techniques in modeling lake level fluctuations in Turkey

This study compares the potential of two different data-driven techniques, support vector machines (SVM) and artificial neural network (ANN) in modeling lake level fluctuations. The SVM method which is a new regression procedure in water resources is applied to the monthly level data of Lake Van which is the biggest lake in Turkey and Lake Egirdir. The estimated lake levels are found to be in good agreement with the corresponding observed values. The results of the SVM based models are compared with those of the ANN. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria. Based on the comparison, it is found that the SVM based model performs better than the ANN.