Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia

Gemechu Mosisa

doi:doi:10.11648/j.es.20230802.12

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Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia

Gemechu Mosisa

Published in Engineering Science (Volume 8, Issue 2)

Received: 27 November 2023 Accepted: 12 December 2023 Published: 22 December 2023

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Abstract

Probability distribution and frequency analysis of rainfall data enable future extreme events. Rainfall is an infrequent and important hydrological parameter on the earth. When designing irrigation and other hydraulic systems, assessing the size of an extreme rainfall event for a specific probability level is extremely important. For the present study daily rainfall data from 2000-2022 for Bedele Town is collected from the Ethiopian Meteorological Institute (EMI) and analyzed for One to two consecutive days maximum annual rainfall using various three commonly used probability distribution viz., Gumbel’s, Log-normal, and Log-pearson type III distributions to determine the best-fit probability distribution. The expected values were compared with the observed values using the goodness of fit and were determined by the chi-square (χ2) test. The chi-square values of 1day maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.276, 1.548, and 3.777 respectively which shows that the Log-normal distribution was the best-fit probability distribution to forecast annual 1day maximum rainfall for different return periods. Also, predictable One day maximum annual Rainfall using Log-normal distribution for a return period of 2, 10, 25, 50,100, and 200 were 63.1mm, 85.1mm, 95.5mm, 102.3mm, 107.2mm, and 120.2mm respectively. The chi-square values of 2days maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.023, 12.171, and 10.395 respectively which shows that the Gumbel’s distribution was the best-fit probability distribution to forecast 2days maximum annual rainfall for different return periods. Also, predictable 2Days maximum annual Rainfall using Gumbel’s distribution for return periods of 2, 10, 25, 50,100, and 200 were 87.8mm, 112.8mm, 125.3mm, 134.7mm, 143.9mm and 153.2mm respectively. The comparisons between the observed and predicted maximum value of annual rainfall clearly show that the developed model can be efficiently used for the prediction of rainfall. 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 Bedele Town, Ethiopia.

Published in	Engineering Science (Volume 8, Issue 2)
DOI	10.11648/j.es.20230802.12
Page(s)	23-29
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.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Bedele Town, Chi-square, Consecutive, Rainfall, Probability Distributions

References

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Mosisa, G. (2023). Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Engineering Science, 8(2), 23-29. https://doi.org/10.11648/j.es.20230802.12

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ACS Style

Mosisa, G. Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Eng. Sci. 2023, 8(2), 23-29. doi: 10.11648/j.es.20230802.12

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AMA Style

Mosisa G. Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Eng Sci. 2023;8(2):23-29. doi: 10.11648/j.es.20230802.12

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@article{10.11648/j.es.20230802.12,
  author = {Gemechu Mosisa},
  title = {Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia},
  journal = {Engineering Science},
  volume = {8},
  number = {2},
  pages = {23-29},
  doi = {10.11648/j.es.20230802.12},
  url = {https://doi.org/10.11648/j.es.20230802.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.es.20230802.12},
  abstract = {Probability distribution and frequency analysis of rainfall data enable future extreme events. Rainfall is an infrequent and important hydrological parameter on the earth. When designing irrigation and other hydraulic systems, assessing the size of an extreme rainfall event for a specific probability level is extremely important. For the present study daily rainfall data from 2000-2022 for Bedele Town is collected from the Ethiopian Meteorological Institute (EMI) and analyzed for One to two consecutive days maximum annual rainfall using various three commonly used probability distribution viz., Gumbel’s, Log-normal, and Log-pearson type III distributions to determine the best-fit probability distribution. The expected values were compared with the observed values using the goodness of fit and were determined by the chi-square (χ2) test. The chi-square values of 1day maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.276, 1.548, and 3.777 respectively which shows that the Log-normal distribution was the best-fit probability distribution to forecast annual 1day maximum rainfall for different return periods. Also, predictable One day maximum annual Rainfall using Log-normal distribution for a return period of 2, 10, 25, 50,100, and 200 were 63.1mm, 85.1mm, 95.5mm, 102.3mm, 107.2mm, and 120.2mm respectively. The chi-square values of 2days maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.023, 12.171, and 10.395 respectively which shows that the Gumbel’s distribution was the best-fit probability distribution to forecast 2days maximum annual rainfall for different return periods. Also, predictable 2Days maximum annual Rainfall using Gumbel’s distribution for return periods of 2, 10, 25, 50,100, and 200 were 87.8mm, 112.8mm, 125.3mm, 134.7mm, 143.9mm and 153.2mm respectively. The comparisons between the observed and predicted maximum value of annual rainfall clearly show that the developed model can be efficiently used for the prediction of rainfall. 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 Bedele Town, Ethiopia.
},
 year = {2023}
}

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TY  - JOUR
T1  - Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia
AU  - Gemechu Mosisa
Y1  - 2023/12/22
PY  - 2023
N1  - https://doi.org/10.11648/j.es.20230802.12
DO  - 10.11648/j.es.20230802.12
T2  - Engineering Science
JF  - Engineering Science
JO  - Engineering Science
SP  - 23
EP  - 29
PB  - Science Publishing Group
SN  - 2578-9279
UR  - https://doi.org/10.11648/j.es.20230802.12
AB  - Probability distribution and frequency analysis of rainfall data enable future extreme events. Rainfall is an infrequent and important hydrological parameter on the earth. When designing irrigation and other hydraulic systems, assessing the size of an extreme rainfall event for a specific probability level is extremely important. For the present study daily rainfall data from 2000-2022 for Bedele Town is collected from the Ethiopian Meteorological Institute (EMI) and analyzed for One to two consecutive days maximum annual rainfall using various three commonly used probability distribution viz., Gumbel’s, Log-normal, and Log-pearson type III distributions to determine the best-fit probability distribution. The expected values were compared with the observed values using the goodness of fit and were determined by the chi-square (χ2) test. The chi-square values of 1day maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.276, 1.548, and 3.777 respectively which shows that the Log-normal distribution was the best-fit probability distribution to forecast annual 1day maximum rainfall for different return periods. Also, predictable One day maximum annual Rainfall using Log-normal distribution for a return period of 2, 10, 25, 50,100, and 200 were 63.1mm, 85.1mm, 95.5mm, 102.3mm, 107.2mm, and 120.2mm respectively. The chi-square values of 2days maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.023, 12.171, and 10.395 respectively which shows that the Gumbel’s distribution was the best-fit probability distribution to forecast 2days maximum annual rainfall for different return periods. Also, predictable 2Days maximum annual Rainfall using Gumbel’s distribution for return periods of 2, 10, 25, 50,100, and 200 were 87.8mm, 112.8mm, 125.3mm, 134.7mm, 143.9mm and 153.2mm respectively. The comparisons between the observed and predicted maximum value of annual rainfall clearly show that the developed model can be efficiently used for the prediction of rainfall. 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 Bedele Town, Ethiopia.

VL  - 8
IS  - 2
ER  -

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Gemechu Mosisa

Department of Hydraulic & Water Resource Engineering, College of Engineering and Technology, Wallaga University, Nekemte, Ethiopia

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APA Style

Mosisa, G. (2023). Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Engineering Science, 8(2), 23-29. https://doi.org/10.11648/j.es.20230802.12

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ACS Style

Mosisa, G. Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Eng. Sci. 2023, 8(2), 23-29. doi: 10.11648/j.es.20230802.12

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AMA Style

Mosisa G. Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia. Eng Sci. 2023;8(2):23-29. doi: 10.11648/j.es.20230802.12

Copy | Download

@article{10.11648/j.es.20230802.12,
  author = {Gemechu Mosisa},
  title = {Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia},
  journal = {Engineering Science},
  volume = {8},
  number = {2},
  pages = {23-29},
  doi = {10.11648/j.es.20230802.12},
  url = {https://doi.org/10.11648/j.es.20230802.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.es.20230802.12},
  abstract = {Probability distribution and frequency analysis of rainfall data enable future extreme events. Rainfall is an infrequent and important hydrological parameter on the earth. When designing irrigation and other hydraulic systems, assessing the size of an extreme rainfall event for a specific probability level is extremely important. For the present study daily rainfall data from 2000-2022 for Bedele Town is collected from the Ethiopian Meteorological Institute (EMI) and analyzed for One to two consecutive days maximum annual rainfall using various three commonly used probability distribution viz., Gumbel’s, Log-normal, and Log-pearson type III distributions to determine the best-fit probability distribution. The expected values were compared with the observed values using the goodness of fit and were determined by the chi-square (χ2) test. The chi-square values of 1day maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.276, 1.548, and 3.777 respectively which shows that the Log-normal distribution was the best-fit probability distribution to forecast annual 1day maximum rainfall for different return periods. Also, predictable One day maximum annual Rainfall using Log-normal distribution for a return period of 2, 10, 25, 50,100, and 200 were 63.1mm, 85.1mm, 95.5mm, 102.3mm, 107.2mm, and 120.2mm respectively. The chi-square values of 2days maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.023, 12.171, and 10.395 respectively which shows that the Gumbel’s distribution was the best-fit probability distribution to forecast 2days maximum annual rainfall for different return periods. Also, predictable 2Days maximum annual Rainfall using Gumbel’s distribution for return periods of 2, 10, 25, 50,100, and 200 were 87.8mm, 112.8mm, 125.3mm, 134.7mm, 143.9mm and 153.2mm respectively. The comparisons between the observed and predicted maximum value of annual rainfall clearly show that the developed model can be efficiently used for the prediction of rainfall. 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 Bedele Town, Ethiopia.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Estimation of One to Two Consecutive Days Maximum Annual Rainfall Using Probability Distributions: The Case of Bedele Town, Oromia, Ethiopia
AU  - Gemechu Mosisa
Y1  - 2023/12/22
PY  - 2023
N1  - https://doi.org/10.11648/j.es.20230802.12
DO  - 10.11648/j.es.20230802.12
T2  - Engineering Science
JF  - Engineering Science
JO  - Engineering Science
SP  - 23
EP  - 29
PB  - Science Publishing Group
SN  - 2578-9279
UR  - https://doi.org/10.11648/j.es.20230802.12
AB  - Probability distribution and frequency analysis of rainfall data enable future extreme events. Rainfall is an infrequent and important hydrological parameter on the earth. When designing irrigation and other hydraulic systems, assessing the size of an extreme rainfall event for a specific probability level is extremely important. For the present study daily rainfall data from 2000-2022 for Bedele Town is collected from the Ethiopian Meteorological Institute (EMI) and analyzed for One to two consecutive days maximum annual rainfall using various three commonly used probability distribution viz., Gumbel’s, Log-normal, and Log-pearson type III distributions to determine the best-fit probability distribution. The expected values were compared with the observed values using the goodness of fit and were determined by the chi-square (χ2) test. The chi-square values of 1day maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.276, 1.548, and 3.777 respectively which shows that the Log-normal distribution was the best-fit probability distribution to forecast annual 1day maximum rainfall for different return periods. Also, predictable One day maximum annual Rainfall using Log-normal distribution for a return period of 2, 10, 25, 50,100, and 200 were 63.1mm, 85.1mm, 95.5mm, 102.3mm, 107.2mm, and 120.2mm respectively. The chi-square values of 2days maximum annual rainfall for Gumbel’s, Log-normal, and Log-pearson type-III distributions were 3.023, 12.171, and 10.395 respectively which shows that the Gumbel’s distribution was the best-fit probability distribution to forecast 2days maximum annual rainfall for different return periods. Also, predictable 2Days maximum annual Rainfall using Gumbel’s distribution for return periods of 2, 10, 25, 50,100, and 200 were 87.8mm, 112.8mm, 125.3mm, 134.7mm, 143.9mm and 153.2mm respectively. The comparisons between the observed and predicted maximum value of annual rainfall clearly show that the developed model can be efficiently used for the prediction of rainfall. 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 Bedele Town, Ethiopia.

VL  - 8
IS  - 2
ER  -

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