Correlation analysis of lightning and flash flood events using pearson model in southeast peninsular Malaysia

• Main Author: Bahari, Noraishah
• Format: Thesis
• Language: English
• Published: 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/101741/1/NoraishahBahariMSKE2023.pdf.pdf; http://eprints.utm.my/id/eprint/101741/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:152291
• Institution: Universiti Teknologi 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. Previous researchers have studied lightning activity during flash floods in Spain, Italy, and Greece. The lightning and rainfall intensity and other variables, which is radar data associated with flash flood events, are analyzed between January to April 2022 for 7 different days of events within a distance of 100 km from Universiti Teknologi Malaysia, Johor. The data supplied by Tenaga Nasional Berhad Research Sdn. Bhd., Department of Irrigation and Drainage, and Malaysia Meteorological Department 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 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 0.9, 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. Another significant finding from this study shows that 2 hours before the events, the increase in lightning number is related to the rainfall intensity. In order to further scrutinize these correlations, several parameters, such as radar and lightning, are gathered since a gauging station may miss enormous rainfall intensity associated with a relatively local flood event. 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.