Probability distributions comparative analysis in assessing rainfall process in time and space
The need for a reliable rainfall model to produce accurate simulation of rainfall series is imperative in water resources planning. Simulated series are used when there are shortages of observed series at location of interest. This study focuses on modelling of rainfall series with a range of pro...
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| Format: | Article |
| Language: | English English |
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IAEME Publication
2017
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| Online Access: | http://irep.iium.edu.my/63000/ http://irep.iium.edu.my/63000/1/63000_Probability%20distributions%20comparative%20analysis_article.pdf http://irep.iium.edu.my/63000/2/63000_Probability%20distributions%20comparative%20analysis_scopus.pdf |
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| author | Abas, Norzaida M. R., Siti Musliha M. D., Zalina Abdul Halim, Syafrina |
| author_facet | Abas, Norzaida M. R., Siti Musliha M. D., Zalina Abdul Halim, Syafrina |
| author_sort | Abas, Norzaida |
| building | IIUM Repository |
| collection | Online Access |
| description | The need for a reliable rainfall model to produce accurate simulation of rainfall series
is imperative in water resources planning. Simulated series are used when there are
shortages of observed series at location of interest. This study focuses on modelling of
rainfall series with a range of probability distributions representing rainfall intensity of
the Space-Time Neyman Scott (ST-NS) model. Theoretically, the ST-NS model is
constructed by having parameters to represent the physical attributes of rainfall process.
Therefore having appropriate distributions to describe the parameters are critical so that
credible rainfall series could be generated. In this study, the performance of four
probability distributions namely Mixed-Exponential, Gamma, Weibull and Generalized
Pareto in representing rainfall intensity are assessed and compared. Model construction
of the ST-NS model involved the merging of rainfall data from sixteen stations located all
over Peninsular Malaysia. Simulations of hourly rainfall series for each distribution are
carried at out of sample site. Performance assessments between the distributions are
conducted using Root Mean Square Error, Akaike Information Criterion, Bayesian
Information Criterion, Kolmogrov-Smirnov Test and Anderson-Darling Test. Results
revealed that mixture type distributions tend to perform better. The performance of both
Mixed-Exponential and Generalized Pareto are very similar and both are equally good at
representing rain intensity in Peninsular Malaysia. The adopted method and the results
could also be extended to other tropical regions. |
| first_indexed | 2025-11-14T17:01:17Z |
| format | Article |
| id | iium-63000 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:01:17Z |
| publishDate | 2017 |
| publisher | IAEME Publication |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-630002018-04-09T00:47:50Z http://irep.iium.edu.my/63000/ Probability distributions comparative analysis in assessing rainfall process in time and space Abas, Norzaida M. R., Siti Musliha M. D., Zalina Abdul Halim, Syafrina GB Physical geography TD Environmental technology. Sanitary engineering The need for a reliable rainfall model to produce accurate simulation of rainfall series is imperative in water resources planning. Simulated series are used when there are shortages of observed series at location of interest. This study focuses on modelling of rainfall series with a range of probability distributions representing rainfall intensity of the Space-Time Neyman Scott (ST-NS) model. Theoretically, the ST-NS model is constructed by having parameters to represent the physical attributes of rainfall process. Therefore having appropriate distributions to describe the parameters are critical so that credible rainfall series could be generated. In this study, the performance of four probability distributions namely Mixed-Exponential, Gamma, Weibull and Generalized Pareto in representing rainfall intensity are assessed and compared. Model construction of the ST-NS model involved the merging of rainfall data from sixteen stations located all over Peninsular Malaysia. Simulations of hourly rainfall series for each distribution are carried at out of sample site. Performance assessments between the distributions are conducted using Root Mean Square Error, Akaike Information Criterion, Bayesian Information Criterion, Kolmogrov-Smirnov Test and Anderson-Darling Test. Results revealed that mixture type distributions tend to perform better. The performance of both Mixed-Exponential and Generalized Pareto are very similar and both are equally good at representing rain intensity in Peninsular Malaysia. The adopted method and the results could also be extended to other tropical regions. IAEME Publication 2017-10 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63000/1/63000_Probability%20distributions%20comparative%20analysis_article.pdf application/pdf en http://irep.iium.edu.my/63000/2/63000_Probability%20distributions%20comparative%20analysis_scopus.pdf Abas, Norzaida and M. R., Siti Musliha and M. D., Zalina and Abdul Halim, Syafrina (2017) Probability distributions comparative analysis in assessing rainfall process in time and space. International Journal of Civil Engineering and Technology, 8 (10). pp. 1679-1688. ISSN 0976-6308 E-ISSN 0976-6316 http://www.iaeme.com/MasterAdmin/uploadfolder/IJCIET_08_10_168/IJCIET_08_10_168.pdf |
| spellingShingle | GB Physical geography TD Environmental technology. Sanitary engineering Abas, Norzaida M. R., Siti Musliha M. D., Zalina Abdul Halim, Syafrina Probability distributions comparative analysis in assessing rainfall process in time and space |
| title | Probability distributions comparative analysis in assessing rainfall process in time and space |
| title_full | Probability distributions comparative analysis in assessing rainfall process in time and space |
| title_fullStr | Probability distributions comparative analysis in assessing rainfall process in time and space |
| title_full_unstemmed | Probability distributions comparative analysis in assessing rainfall process in time and space |
| title_short | Probability distributions comparative analysis in assessing rainfall process in time and space |
| title_sort | probability distributions comparative analysis in assessing rainfall process in time and space |
| topic | GB Physical geography TD Environmental technology. Sanitary engineering |
| url | http://irep.iium.edu.my/63000/ http://irep.iium.edu.my/63000/ http://irep.iium.edu.my/63000/1/63000_Probability%20distributions%20comparative%20analysis_article.pdf http://irep.iium.edu.my/63000/2/63000_Probability%20distributions%20comparative%20analysis_scopus.pdf |