Determination of the Most Appropriate Probability Distribution Models for the Meteorological Variables

Every component of the hydrological cycle is essential for controlling water supplies and assessing potential catastrophic events like floods droughts. The variables system are unexpected unique to each place. In this paper, most crucial including precipitation, temperature, relative humidity, evaporation examined Ankara province. For meteorological parameters, Lognormal, Log-logistic, Gamma, Weibull, Normal, Gumbel models used find best suitable distributions. Kolmogorov-Smirnov, Cramers-von Mises, Akaike's Information Criterion, Bayesian Anderson-Darling, Maximum Loglikelihood methods utilized test these models. Results shows that there a distinct distribution model parameter. particular, it has been determined better annual total whereas Normal minimum temperature. At stations 17130 17664, gamma observed be fit at but station 17128 found appropriate Log-logistic normal distribution. Stations 17128, 17130, 17664 maximum temperature series fitted with respectively. Gamma when analyzing mean Lognormal selected 17664. It expected results will contribute planning resources projects in region.