Entropy as a Variation of Information for Testing the Goodness of Fit

Abstract

Increasing population, higher levels of human and industrial activities have affected water resources in the last decades. In addition, per capita demand for water in most countries is steadily increasing as more and more people achieve higher standards of living. Researchers need more information about water resources for their efficient use and effective management. In this respect, getting sufficient, accurate and quick information has great significance in water resources planning and management in parallel to the determination of the characteristics of water resources. To this end, useful and easily applicable methods have been explored to get optimum results and several test techniques have been investigated to get much more information based on available water resources data. In the presented study, Informational Entropy method is introduced as an alternative test method to test the goodness of fit of probability functions. The presented study gives a brief detail on the applicability of the concept as a goodness of fit tool on various cases from different spatial regions and varying meteorological characteristics. For this purpose, mean precipitation data for 60 stations in Turkey are investigated. Results by testing the goodness of fit of probability functions through the entropy-based method show that Informational Entropy can be applied for fitting the probability function based on the investigated datasets.