Analysis of rainfall extremes based on grid data
The identification, monitoring, and characterization of extreme weather events, like extreme storms and drought, are of great importance, especially in Singapore. Increasing rainfall could overwhelm our local drainage system and this may lead to flooding. Gumbel Distribution is one of the probabilit...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/158971 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The identification, monitoring, and characterization of extreme weather events, like extreme storms and drought, are of great importance, especially in Singapore. Increasing rainfall could overwhelm our local drainage system and this may lead to flooding. Gumbel Distribution is one of the probability distribution methods that makes use of the precipitation data to hydrological peaks corresponding to specific return periods or probabilities. This report uses grid data daily gridded rainfall data obtained
from APHRODITE’s Asian Precipitation dataset V1101 (1951-2007) and V1101EX_R1 (2007-2015) and MATrix LABoratory (MATLAB) matrix programming software and Quantum Geographic Information System (QGIS) to analyse and edit spatial information. Extreme Value Type I Gumbel Distribution, Frequency of Occurrences of Wet Days, Total Number of Wet Days, Longest Duration of Wet Days, and the Total Annual Precipitation of Wet Spells are computed as functions in MATLAB to study the region of 10 selected capital cities across Southeast Asia. |
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