Correlation analysis of lightning and flash flood events using pearson model in southeast peninsular Malaysia.
Flash flood is a natural disaster that causes many casualties and economic losses; it has become prevalent in Malaysia, where several events have been reported showing a possible correlation between lightning, rain, and flash floods. The lightning and rainfall intensity associated with flash flood e...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/107745/ http://dx.doi.org/10.1109/APL57308.2023.10181418 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Flash flood is a natural disaster that causes many casualties and economic losses; it has become prevalent in Malaysia, where several events have been reported showing a possible correlation between lightning, rain, and flash floods. The lightning and rainfall intensity associated with flash flood events, are analyzed between January and April 2022 for three events (cases) within a distance of 100 km from Universiti Teknologi Malaysia, Johor. The data supplied by Tenaga Nasional Berhad Research Sdn. Bhd. (TNBR), Department of Irrigation and Drainage (DID) and Malaysia Meteorological Department (MetMalaysia) were evaluated for statistical discrepancies, which is a different approachable method by limiting the criteria for each data source. This research aims to investigate the relationship between the number of lightning occurrences with the amount of rain in 24 hours by applying the Pearson correlation coefficient (r) and determine the relationship strength between lightning and rainfall intensity parameters by implementing the rainfall-lightning ratio (RLR) change to rainfall-lightning rate, which is commonly used to evaluate the relationship between rainfall and lightning. This study found that the r-values between lightning and rain range from 0.4 to 0.7, which correlates well with rainfall and is considered an acceptable correlation. The different values due to the number of lightning and rain occurrences are inconsistent for each independent case. According to the findings, lightning data may be utilized in association with rain. Therefore, the accuracy of the existing flood forecasting system may be improved. |
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