Pages: 12-23

Abstract

Statistical distribution of rainfall in a geographic area and the potential positive and negative effects of the most fundamental issues in environmental planning and optimization of rainfall is true. Accordingly, to calculate of this parameter in the various return periods and its spatial variation, statistical analysis and selection of appropriate distribution is essential. In this research to obtain the best statistical distributions to estimate monthly rainfall, monthly rainfall data from 6 meteorological stations West Azerbaijan province named Sariqamish, Pole Miandoab Zarrineh River, Qareh Papaq, Shahid Kazemi dam, Shahin Dezh and Nezam Abad were collected during the 30-year statistical periods (1989 to 2018). This study was designed to find the best-fit probability distribution of monthly rainfall in the Zarrineh river watershed at Iran using six probability distributions: Normal, 2 Parameter Log Normal, 3 Parameter Log Normal, Pearson Type 3, Log Pearson Type 3 and Gumbel distribution. The randomness of the data was tested with Run Test method and then with all kinds of statistical distributions the relevant SMADA software that is based on the Method of Moments were fitted. Finally, the best distribution by using statistical indicators root mean square error (RMSE) and the mean absolute error (MAE) was determined for all meteorological stations. The results showed that monthly rainfall data of Pole Miandoab Zarrineh River and Sariqamish stations with the 3 Parameter Log Normal distribution, Qareh Papaq and Shahid Kazemi dam stations with the Pearson Type III distribution, Shahin Dezh station with the Gumble Type I Extremal distribution and the Nezam Abad station with the 2 Parameter Log Normal distribution indicate the most fitting and compliance. Normal distribution was found to be the distribution to gives the unsuitable estimate of monthly rainfall data among six others. The results of this study by providing an optimized method to estimate rainfall and hence the sustainability of water resources of the watershed to be used by decision makers and researchers.