Rainfall Data Analysis in Kerian River Basin Using HYFRAN-PLUS Model, Malaysia

This study analyzes 11 years of rainfall data from stations within the Kerian River Basin using HYFRAN-PLUS software. The statistical values generated for each station were used to test data independence and stationarity. The results showed that most p-values were below 0.05, indicating potential no...

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Bibliographic Details
Published in:Lecture Notes in Mechanical Engineering
Main Author: Rahman N.F.A.; Mondelly Y.; Tai V.C.; Mohammad M.; Shariff M.S.M.; Khalid K.; Siew E.L.
Format: Conference paper
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201538895&doi=10.1007%2f978-981-97-0169-8_62&partnerID=40&md5=3cc552d3a6483e7f138de531b23a598b
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Summary:This study analyzes 11 years of rainfall data from stations within the Kerian River Basin using HYFRAN-PLUS software. The statistical values generated for each station were used to test data independence and stationarity. The results showed that most p-values were below 0.05, indicating potential non-independence and non-stationarity in the data. Four stations, namely Pusat Kesihatan Kecil, Kolam Air JKR, Terap, and Kawasan Sg. Acheh, underwent independent and stationary analysis, and it was found that the annual maximum rainfall data remained within the lower and upper control bands of 95% confidence intervals. This suggests that the best-fitted probability density function (PDF) accurately describes the rainfall. The study emphasizes the importance of validating data to ensure the accuracy and reliability of recorded rainfall data. It is crucial to identify and address non-independence and non-stationarity in the recorded data before using it for further analysis or decision-making. The study also highlights the usefulness of non-exceedance probability (NEP) plots in assessing the fit of PDF and estimating the return period of extreme rainfall events. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
ISSN:21954356
DOI:10.1007/978-981-97-0169-8_62