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Prediction of Consecutive Days Maximum Rainfall Using Frequency Analysis for Nekemte Town, Oromia, Ethiopia

Rain is a scanty and vital hydrological factor in arid and semi-arid regions. The amount of runoff produced and rainfall received determine the development of water resources in any region. An important step in the analysis of rainfall frequency is to choose an appropriate distribution to represent the depth of rainfall to study rainfall. Analyzing the frequency of various rainfall data was attempted by Gumbel, Log normal, and Log person type III distribution method. The projected rainfall can be calculated with the aid of frequency analysis. Annual rainfall data for 22 years (2000-2021) were collected from the Ethiopian Meteorological Institute (EMI) for Nekemte station. The goal of this study is to identify the optimal theoretical probability distribution by fitting it to the maximum yearly rainfall for one day, two days, and three days distribution for the prediction of maximum annual rainfall for daily, two consecutive days, and three consecutive days. For the determination of goodness of fit chi-square, percentage absolute deviation, and the integral square error was carried out by comparing the expected values with the observed values. The results found showed that the log-normal, distribution emerged to be the best fit for the prediction of annual maximum rainfall values of Nekemte for one day. And also, another best fit was Gumbel distribution for two, and three consecutive days.

Chi-Square, Rainfall, Gumbel, Log Normal, Log Pearson Type III

Gemechu Mosisa. (2023). Prediction of Consecutive Days Maximum Rainfall Using Frequency Analysis for Nekemte Town, Oromia, Ethiopia. Journal of Water Resources and Ocean Science, 12(1), 12-22.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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