International Journal of Mathematics Trends and Technology
Volume 69 | Issue 1 | Year 2023 | Article Id. IJMTT-V69I1P512 | DOI : https://doi.org/10.14445/22315373/IJMTT-V69I1P512
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 07 Dec 2022 | 09 Jan 2023 | 20 Jan 2023 | 31 Jan 2023 |
Storm amount (SA), storm intensity (SI), and storm duration (SD) are three external measurements that can be used to describe short-scale rainfall modeling based on storm process. This study displays the distribution that fits the SI series the best, which is based on hourly rainfall data from 1970 to 2008 at the Alor Setar station in Peninsular Malaysia. Gamma, Weibull, and Log Normal distributions with two parameters are taken into consideration. The Bayesian Maximum Likelihood (MLE) approach is used to determine these distributions' parameters. Then it is determined how well theoretical data and model distributions fit one another (GOF). The outcome demonstrates that the stations discovered that the MLE method may provide the best SI modeling, specifically for Log-Normal distribution. We can reliably forecast the future risks associated with the SI based on the stated model.
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Lisa Rahayu, Rado Yendra, Muhammad Marizal, Ari Pani Desvina, Rahmadeni, "The Short Scale (Hourly) Rainfall Modelling For Intensity Based On Strom Analysis Events (SEA) Using Some Probability Distributions," International Journal of Mathematics Trends and Technology (IJMTT), vol. 69, no. 1, pp. 79-85, 2023. Crossref, https://doi.org/10.14445/22315373/IJMTT-V69I1P512
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