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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sg-ntu-dr.10356-1589712022-06-08T03:30:25Z Analysis of rainfall extremes based on grid data Koh, Wei Theng Qin Xiaosheng School of Civil and Environmental Engineering XSQIN@ntu.edu.sg Engineering::Civil engineering::Water resources 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. Bachelor of Engineering (Civil) 2022-06-08T03:30:24Z 2022-06-08T03:30:24Z 2022 Final Year Project (FYP) Koh, W. T. (2022). Analysis of rainfall extremes based on grid data. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158971 https://hdl.handle.net/10356/158971 en WR-13 application/pdf Nanyang Technological University |
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Engineering::Civil engineering::Water resources Koh, Wei Theng Analysis of rainfall extremes based on grid data |
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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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Qin Xiaosheng |
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Qin Xiaosheng Koh, Wei Theng |
format |
Final Year Project |
author |
Koh, Wei Theng |
author_sort |
Koh, Wei Theng |
title |
Analysis of rainfall extremes based on grid data |
title_short |
Analysis of rainfall extremes based on grid data |
title_full |
Analysis of rainfall extremes based on grid data |
title_fullStr |
Analysis of rainfall extremes based on grid data |
title_full_unstemmed |
Analysis of rainfall extremes based on grid data |
title_sort |
analysis of rainfall extremes based on grid data |
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Nanyang Technological University |
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2022 |
url |
https://hdl.handle.net/10356/158971 |
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1735491109886361600 |