Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique

Rainfall depth duration frequency (DDF) curves are used extensively in many engineering designs.However, due to the sampling error and the uncertainty associated with the parameter estimation process,the DDF curves are subjected to parameter uncertainty. In this study, an evaluation of t...

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Main Authors: Ng, Jing Lin, Abd Aziz, Samsuzana, Huang, Yuk Feng, Mirzaei, Majid, Wayayok, Aimrun, Rowshon, M. K.
Format: Article
Language:English
Published: Springer Verlag 2019
Online Access:http://psasir.upm.edu.my/id/eprint/82662/
http://psasir.upm.edu.my/id/eprint/82662/1/Uncertainty%20analysis%20of%20rainfall%20depth%20duration%20frequency%20.pdf
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author Ng, Jing Lin
Abd Aziz, Samsuzana
Huang, Yuk Feng
Mirzaei, Majid
Mirzaei, Majid
Wayayok, Aimrun
Rowshon, M. K.
author_facet Ng, Jing Lin
Abd Aziz, Samsuzana
Huang, Yuk Feng
Mirzaei, Majid
Mirzaei, Majid
Wayayok, Aimrun
Rowshon, M. K.
author_sort Ng, Jing Lin
building UPM Institutional Repository
collection Online Access
description Rainfall depth duration frequency (DDF) curves are used extensively in many engineering designs.However, due to the sampling error and the uncertainty associated with the parameter estimation process,the DDF curves are subjected to parameter uncertainty. In this study, an evaluation of the uncertaintyof the DDF curves in the Kelantan river basin was performed using the bootstrap resampling method.Annual maximum rainfall series for durations of 24, 48, 72, 96 and 120 h were derived from the stochasticrainfall model outputs and fitted to the generalised extreme value (GEV) distribution. The bootstrapsamples were generated by resampling with replacement from the annual maximum rainfall series. Therelationships that describe the GEV parameters as a function of duration were used to establish theDDF curves. The 95% confidence intervals were used as an indicator to quantify the uncertainty in theDDF curves. The bootstrap distribution of the rainfall depth quantiles was represented by a normalprobability density function. The results showed that uncertainty increased with the return period andthere was significant uncertainty in the DDF curves. The suggested procedure is expected to contributeto endeavours in obtaining reliable DDF curves, where the uncertainty features are assessed.
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institution Universiti Putra Malaysia
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language English
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spelling upm-826622021-06-05T09:45:44Z http://psasir.upm.edu.my/id/eprint/82662/ Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique Ng, Jing Lin Abd Aziz, Samsuzana Huang, Yuk Feng Mirzaei, Majid Mirzaei, Majid Wayayok, Aimrun Rowshon, M. K. Rainfall depth duration frequency (DDF) curves are used extensively in many engineering designs.However, due to the sampling error and the uncertainty associated with the parameter estimation process,the DDF curves are subjected to parameter uncertainty. In this study, an evaluation of the uncertaintyof the DDF curves in the Kelantan river basin was performed using the bootstrap resampling method.Annual maximum rainfall series for durations of 24, 48, 72, 96 and 120 h were derived from the stochasticrainfall model outputs and fitted to the generalised extreme value (GEV) distribution. The bootstrapsamples were generated by resampling with replacement from the annual maximum rainfall series. Therelationships that describe the GEV parameters as a function of duration were used to establish theDDF curves. The 95% confidence intervals were used as an indicator to quantify the uncertainty in theDDF curves. The bootstrap distribution of the rainfall depth quantiles was represented by a normalprobability density function. The results showed that uncertainty increased with the return period andthere was significant uncertainty in the DDF curves. The suggested procedure is expected to contributeto endeavours in obtaining reliable DDF curves, where the uncertainty features are assessed. Springer Verlag 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/82662/1/Uncertainty%20analysis%20of%20rainfall%20depth%20duration%20frequency%20.pdf Ng, Jing Lin and Abd Aziz, Samsuzana and Huang, Yuk Feng and Mirzaei, Majid and Mirzaei, Majid and Wayayok, Aimrun and Rowshon, M. K. (2019) Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique. Journal of Earth System Science, 128. art. no. 113. pp. 1-15. ISSN 0253-4126 ; ESSN 0973-774X https://link.springer.com/article/10.1007/s12040-019-1154-1 10.1007/s12040-019-1154-1
spellingShingle Ng, Jing Lin
Abd Aziz, Samsuzana
Huang, Yuk Feng
Mirzaei, Majid
Mirzaei, Majid
Wayayok, Aimrun
Rowshon, M. K.
Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title_full Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title_fullStr Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title_full_unstemmed Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title_short Uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
title_sort uncertainty analysis of rainfall depth duration frequency curves using the bootstrap resampling technique
url http://psasir.upm.edu.my/id/eprint/82662/
http://psasir.upm.edu.my/id/eprint/82662/
http://psasir.upm.edu.my/id/eprint/82662/
http://psasir.upm.edu.my/id/eprint/82662/1/Uncertainty%20analysis%20of%20rainfall%20depth%20duration%20frequency%20.pdf