Abstract
Wise prediction of discharge is vital for effective utilization of water resources and hydropower generation. There is no doubt that the future climate change will substantially affect precipitation amount, discharge and hydro-meteorology which are considered as major sources for hydropower energy. In this study, we present an application of downscaling technique on prediction of discharge of a local gage station in Turkey. Variable input set of the Third Generation Coupled Global Climate Model variables are statistically downscaled and coupled with variable forms of local discharge (Q, LnQ, MavQ, StdQ, and Q/Qmax) by using five different models as Gene-expression programming, Group Method of Data Handling, K-nearest neighbour, logistic regression and linear regression. Different sub-models are developed and calibrated based on the training period, and the best model is selected based on the testing period. Future projecting of discharge is done based on the Third Generation Coupled Global Climate Model A2 scenario, and the financial analysis is carried out by using this forecasted Q values.
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