Akademik Veri Yönetim Sistemi
4th International Conference on Water Resources and Wetlands, Tulcea, Romanya, 5 - 09 Eylül 2018, ss.169-176
In water systems planning, it is essential to use an objective criterion to determine the information content of hydrological data. The Entropy concept, defined by Shannon in information theory, has been applied in hydrology and water resources for measuring the information content of hydrologic processes. The presented study aims to determine the best fitting probability distribution function for the observed time series of precipitation data. There are numerous of tests to evaluate the goodness of fit of probability functions such as Chi-squared, Kolmogorov Smirnov and Anderson Darling tests. An alternative method for the mentioned tests is the Informational Entropy method. Informational Entropy method has been studied for the precipitation data of the selected Precipitation Gaging Stations of Turkey. Results showed that Informational Entropy method can be a valuable alternative method to test the goodness of fit. For a further step, in the presented study, it is studied for a selected case area and execution is done for the 22 gaging stations of State Hydraulic Works (DSI), which have long-term precipitation data located in the Gediz River Basin. Results by testing the goodness of fit of probability functions by Informational Entropy method show that Informational Entropy can be applied for fitting the probability function according to the investigated datasets.