Estimation of dam lake water level change using different artificial intelligence methods

Dam reservoir level prediction is important for dam construction, operation, design and safety. In this study, dam reservoir level change predictions were investigated using M5 Decision Tree (M5 Tree) and Adaptive Neural Fuzzy Inference System (ANFIS) models. For modelling of the daily dam reservoir water level (t), stream-flow (t) and precipitation heights in the dam basin (t) were used. Models were created for different input combinations. The model results were compared with the results of conventional Multiple Linear Regression (MLR) models. The models were analyzed with graphical and statistical results. The coefficient of determination (R2), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) performance criteria were taken into account when comparing the prediction models. The outputs showed that ANFIS model results gave better performance in predicting the dam reservoir level change.