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Markov chain-mixed exponential model for daily rainfall in Hong Kong

In this study, we applied a stochastic rainfall model which is capable in generating synthetic daily rainfall sequences that exhibit similar characteristics to observed data, thereby assessing the amount of rainfall over a specific period. The model utilized for this purpose is the Markov Chain Mi...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Xu, YuChen
التنسيق: Final Year Project / Dissertation / Thesis
منشور في: 2023
الموضوعات:
HA Statistics
QA Mathematics
الوصول للمادة أونلاين:http://eprints.utar.edu.my/6334/1/Project_Report_XuYuchen_.pdf
http://eprints.utar.edu.my/6334/
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id my-utar-eprints.6334
record_format eprints
spelling my-utar-eprints.63342024-04-14T09:59:47Z Markov chain-mixed exponential model for daily rainfall in Hong Kong Xu, YuChen HA Statistics QA Mathematics In this study, we applied a stochastic rainfall model which is capable in generating synthetic daily rainfall sequences that exhibit similar characteristics to observed data, thereby assessing the amount of rainfall over a specific period. The model utilized for this purpose is the Markov Chain Mixing Index (MCME). This model integrates both rainfall occurrence, represented by a first-order two-state Markov chain, and rainfall distribution, described by a mixture index distribution. The feasibility of the MCME model was evaluated using daily rainfall data collected from 15 stations in Hong Kong over a 20-year record period (2003-2022). The evaluation revealed that the proposed MCME model adequately captures both the occurrence and quantity of rainfall across all stations. Various statistical analysis were implemented to analyze the rainfall data. In conclusion, the validation results indicate that while the model effectively describes the characteristics of rainfall and able to simulate the rainfall based on the parameters estimated. 2023 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6334/1/Project_Report_XuYuchen_.pdf Xu, YuChen (2023) Markov chain-mixed exponential model for daily rainfall in Hong Kong. Master dissertation/thesis, UTAR. http://eprints.utar.edu.my/6334/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic HA Statistics
QA Mathematics
spellingShingle HA Statistics
QA Mathematics
Xu, YuChen
Markov chain-mixed exponential model for daily rainfall in Hong Kong
description In this study, we applied a stochastic rainfall model which is capable in generating synthetic daily rainfall sequences that exhibit similar characteristics to observed data, thereby assessing the amount of rainfall over a specific period. The model utilized for this purpose is the Markov Chain Mixing Index (MCME). This model integrates both rainfall occurrence, represented by a first-order two-state Markov chain, and rainfall distribution, described by a mixture index distribution. The feasibility of the MCME model was evaluated using daily rainfall data collected from 15 stations in Hong Kong over a 20-year record period (2003-2022). The evaluation revealed that the proposed MCME model adequately captures both the occurrence and quantity of rainfall across all stations. Various statistical analysis were implemented to analyze the rainfall data. In conclusion, the validation results indicate that while the model effectively describes the characteristics of rainfall and able to simulate the rainfall based on the parameters estimated.
format Final Year Project / Dissertation / Thesis
author Xu, YuChen
author_facet Xu, YuChen
author_sort Xu, YuChen
title Markov chain-mixed exponential model for daily rainfall in Hong Kong
title_short Markov chain-mixed exponential model for daily rainfall in Hong Kong
title_full Markov chain-mixed exponential model for daily rainfall in Hong Kong
title_fullStr Markov chain-mixed exponential model for daily rainfall in Hong Kong
title_full_unstemmed Markov chain-mixed exponential model for daily rainfall in Hong Kong
title_sort markov chain-mixed exponential model for daily rainfall in hong kong
publishDate 2023
url http://eprints.utar.edu.my/6334/1/Project_Report_XuYuchen_.pdf
http://eprints.utar.edu.my/6334/
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score 13.251813

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