Estimating distribution parameters of extreme event using TL-moment method

Good knowledge of flood magnitude and frequency is necessary in designing different types of flood protection projects. The use of flood frequency analysis (FFA) can help hydrologists in mitigating the problem of extreme flooding. The main problem in hydrologic design faced by the hydrologists is th...

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Main Author:	Mat Jan, Nur Amalina
Format:	Thesis
Published:	2014
Subjects:	TA Engineering (General) Civil engineering (General)
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id	my-utm-ep.48435
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spelling	my-utm-ep.484352017-08-08T01:08:25Z Estimating distribution parameters of extreme event using TL-moment method 2014 Mat Jan, Nur Amalina TA Engineering (General). Civil engineering (General) Good knowledge of flood magnitude and frequency is necessary in designing different types of flood protection projects. The use of flood frequency analysis (FFA) can help hydrologists in mitigating the problem of extreme flooding. The main problem in hydrologic design faced by the hydrologists is the estimation of high flow quantile. L-Moments, popular among hydrologist in FFA, is said to be over sensitive towards the lower part of the distribution and gives insufficient weight to large sample values. As an alternative, the trimmed L-Moments (TL-moments) method is proposed to be used in FFA since it has the ability to give zero weight on the extreme values. The aim of this study is to compare the performance of L-moments, TL-moments (1,0), TL-moments (2,0), TL-moments (3,0) and TL-moments (4,0) in FFA application. The four distributions, named generalized logistic (GLO), generalized extreme value (GEV), three parameter lognormal (LN3), and Pearson 3 (P3) distributions, were chosen and an estimation of the distributions using TL-moments (r,0), r = 1, 2, 3, 4 was formulated. The comparison is done using Monte Carlo simulation and annual maximum streamflow data over stations in Peninsular Malaysia. Simulation results show that TL-moments give comparable and better parameter estimates than those by L-moments, particularly when estimating the high flow quantiles. Furthermore, the generalized extreme value (GEV) and three parameters lognormal (LN3) distributions obtained from TL-moments method suit with the actual maximum streamflows of stations in Johor 2014 Thesis http://eprints.utm.my/id/eprint/48435/ masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Mat Jan, Nur Amalina Estimating distribution parameters of extreme event using TL-moment method
description	Good knowledge of flood magnitude and frequency is necessary in designing different types of flood protection projects. The use of flood frequency analysis (FFA) can help hydrologists in mitigating the problem of extreme flooding. The main problem in hydrologic design faced by the hydrologists is the estimation of high flow quantile. L-Moments, popular among hydrologist in FFA, is said to be over sensitive towards the lower part of the distribution and gives insufficient weight to large sample values. As an alternative, the trimmed L-Moments (TL-moments) method is proposed to be used in FFA since it has the ability to give zero weight on the extreme values. The aim of this study is to compare the performance of L-moments, TL-moments (1,0), TL-moments (2,0), TL-moments (3,0) and TL-moments (4,0) in FFA application. The four distributions, named generalized logistic (GLO), generalized extreme value (GEV), three parameter lognormal (LN3), and Pearson 3 (P3) distributions, were chosen and an estimation of the distributions using TL-moments (r,0), r = 1, 2, 3, 4 was formulated. The comparison is done using Monte Carlo simulation and annual maximum streamflow data over stations in Peninsular Malaysia. Simulation results show that TL-moments give comparable and better parameter estimates than those by L-moments, particularly when estimating the high flow quantiles. Furthermore, the generalized extreme value (GEV) and three parameters lognormal (LN3) distributions obtained from TL-moments method suit with the actual maximum streamflows of stations in Johor
format	Thesis
qualification_level	Master's degree
author	Mat Jan, Nur Amalina
author_facet	Mat Jan, Nur Amalina
author_sort	Mat Jan, Nur Amalina
title	Estimating distribution parameters of extreme event using TL-moment method
title_short	Estimating distribution parameters of extreme event using TL-moment method
title_full	Estimating distribution parameters of extreme event using TL-moment method
title_fullStr	Estimating distribution parameters of extreme event using TL-moment method
title_full_unstemmed	Estimating distribution parameters of extreme event using TL-moment method
title_sort	estimating distribution parameters of extreme event using tl-moment method
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2014
_version_	1747817389606567936

Estimating distribution parameters of extreme event using TL-moment method

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