Rainfall data frequency analysis and probability distribution enable future extreme events. Determining the magnitude of an extreme rainfall event for a given probability level is crucial for constructing irrigation and other hydraulic systems. On Earth, rainfall is a rare but significant hydrological characteristic. The analysis was for one to three consecutive days of maximum annual rainfall using a variety of widely used probability distributions. In order to determine the best-fit probability distribution, daily rainfall data for Gimbi Town were taken from 1995 to 2019 and gathered from the Ethiopian Meteorological Institute (EMI). The chi-square (χ²) test was used to measure the goodness of fit between the expected and observed values. The chi-square value of the 1, 2 and 3-day maximum annual daily rainfall was 8.8, 3.8, and 5.4 respectively. Chow method was the best-fit probability distribution for predicting the annual 1 and 2-day maximum rainfall for various return periods and the log-Pearson type-III distribution was the best-fit probability distribution for predicting the annual 3-day maximum rainfall for various return periods. The results of this study would be useful for agricultural scientists, decision-makers, policy planners, and researchers for agricultural development and construction of small soil and water conservation structures, irrigation, and drainage systems in Gimbi Town, Ethiopia.
| Published in | Science Futures (Volume 1, Issue 1) |
| DOI | 10.11648/j.scif.20250101.19 |
| Page(s) | 70-83 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2025. Published by Science Publishing Group |
Chi-square Test, Gimbi, Gumbel, Rainfall, Return Period, Probability Distribution
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APA Style
Mosisa, G. (2025). Probability Analysis for One Day to Three Consecutive Days of Annual Maximum Rainfall: The Case of Gimbi Town, Oromia Region, Ethiopia. Science Futures, 1(1), 70-83. https://doi.org/10.11648/j.scif.20250101.19
ACS Style
Mosisa, G. Probability Analysis for One Day to Three Consecutive Days of Annual Maximum Rainfall: The Case of Gimbi Town, Oromia Region, Ethiopia. Sci. Futures 2025, 1(1), 70-83. doi: 10.11648/j.scif.20250101.19
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Download@article{10.11648/j.scif.20250101.19,
author = {Gemechu Mosisa},
title = {Probability Analysis for One Day to Three Consecutive Days of Annual Maximum Rainfall: The Case of Gimbi Town, Oromia Region, Ethiopia},
journal = {Science Futures},
volume = {1},
number = {1},
pages = {70-83},
doi = {10.11648/j.scif.20250101.19},
url = {https://doi.org/10.11648/j.scif.20250101.19},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20250101.19},
abstract = {Rainfall data frequency analysis and probability distribution enable future extreme events. Determining the magnitude of an extreme rainfall event for a given probability level is crucial for constructing irrigation and other hydraulic systems. On Earth, rainfall is a rare but significant hydrological characteristic. The analysis was for one to three consecutive days of maximum annual rainfall using a variety of widely used probability distributions. In order to determine the best-fit probability distribution, daily rainfall data for Gimbi Town were taken from 1995 to 2019 and gathered from the Ethiopian Meteorological Institute (EMI). The chi-square (χ²) test was used to measure the goodness of fit between the expected and observed values. The chi-square value of the 1, 2 and 3-day maximum annual daily rainfall was 8.8, 3.8, and 5.4 respectively. Chow method was the best-fit probability distribution for predicting the annual 1 and 2-day maximum rainfall for various return periods and the log-Pearson type-III distribution was the best-fit probability distribution for predicting the annual 3-day maximum rainfall for various return periods. The results of this study would be useful for agricultural scientists, decision-makers, policy planners, and researchers for agricultural development and construction of small soil and water conservation structures, irrigation, and drainage systems in Gimbi Town, Ethiopia.},
year = {2025}
}
TY - JOUR T1 - Probability Analysis for One Day to Three Consecutive Days of Annual Maximum Rainfall: The Case of Gimbi Town, Oromia Region, Ethiopia AU - Gemechu Mosisa Y1 - 2025/12/11 PY - 2025 N1 - https://doi.org/10.11648/j.scif.20250101.19 DO - 10.11648/j.scif.20250101.19 T2 - Science Futures JF - Science Futures JO - Science Futures SP - 70 EP - 83 PB - Science Publishing Group UR - https://doi.org/10.11648/j.scif.20250101.19 AB - Rainfall data frequency analysis and probability distribution enable future extreme events. Determining the magnitude of an extreme rainfall event for a given probability level is crucial for constructing irrigation and other hydraulic systems. On Earth, rainfall is a rare but significant hydrological characteristic. The analysis was for one to three consecutive days of maximum annual rainfall using a variety of widely used probability distributions. In order to determine the best-fit probability distribution, daily rainfall data for Gimbi Town were taken from 1995 to 2019 and gathered from the Ethiopian Meteorological Institute (EMI). The chi-square (χ²) test was used to measure the goodness of fit between the expected and observed values. The chi-square value of the 1, 2 and 3-day maximum annual daily rainfall was 8.8, 3.8, and 5.4 respectively. Chow method was the best-fit probability distribution for predicting the annual 1 and 2-day maximum rainfall for various return periods and the log-Pearson type-III distribution was the best-fit probability distribution for predicting the annual 3-day maximum rainfall for various return periods. The results of this study would be useful for agricultural scientists, decision-makers, policy planners, and researchers for agricultural development and construction of small soil and water conservation structures, irrigation, and drainage systems in Gimbi Town, Ethiopia. VL - 1 IS - 1 ER -
Department of Hydraulic and Water Resources Engineering, Wallaga University, Nekemte, Ethiopia
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