Identifying the Best-Fit Probability Distribution for Monthly Low Flows Frequency Analysis (Case study: The Rivers of Lorestan Province)

Low streamflows play an important role in the efficient management of water resources، design of reservoirs، agricultural planning، and aquatic ecosystems. Appropriate estimation of low flow values for different return periods enhances the level of confidence in water resources planning. In this study، the monthly low flow data of all the months for 24 hydrometric stations in Lorestan Province were used. These data were fitted with 65 probability distributions using Easyfit software. First، only the results of Kolmogorov – Smirnov fitting test were compared to determine the best-fit distribution for several months. The results showed that among 65 distributions applied in this procedure، Wakeby distribution with the 36. 6 percent was recognized as superior distribution. Then، the suitability of this distribution was tested again using three tests of Kolmogorov- Smirnov، Anderson - Darling and Chi – square. The results represented that in 57. 8% of cases the first rank was allocated to the Wakeby probability distribution. Assessing the rankings of other probabilistic distributions showed that the Wakeby distribution، in 84. 3% of station-month time series، was located in the top five distributions. Therefore، the five-parameter Wakeby distribution showed so much better fitting with the data in comparison with other commonly used distributions in hydrology، such as the Pearson، Gumbel، Log-normal distributions and etc. The overall results showed that by using new techniques and evaluating a variety of probability distributions available in the science of probability and statistics، more suitable distributions can be identified to increase accuracy in hydrologic variables analysis، and consequently، optimal water resources management.