Selecting a probability distribution for extreme rainfall series in Malaysia
This paper discusses the comparative assessment of eight candidate distributions in providing accurate and reliable maximum rainfall estimates for Malaysia. The models considered were the Gamma, Generalised Normal, Generalised Pareto, Generalised Extreme Value, Gumbel, Log Pearson Type III, Pearson...
| Veröffentlicht in: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 45(2002), 2 vom: 09., Seite 63-8 |
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| Format: | Aufsatz |
| Sprache: | English |
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2002
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| Zugriff auf das übergeordnete Werk: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Schlagworte: | Journal Article |
| Zusammenfassung: | This paper discusses the comparative assessment of eight candidate distributions in providing accurate and reliable maximum rainfall estimates for Malaysia. The models considered were the Gamma, Generalised Normal, Generalised Pareto, Generalised Extreme Value, Gumbel, Log Pearson Type III, Pearson Type III and Wakeby. Annual maximum rainfall series for one-hour resolution from a network of seventeen automatic gauging stations located throughout Peninsular Malaysia were selected for this study. The length of rainfall records varies from twenty-three to twenty-eight years. Model parameters were estimated using the L-moment method. The quantitative assessment of the descriptive ability of each model was based on the Probability Plot Correlation Coefficient test combined with root mean squared error, relative root mean squared error and maximum absolute deviation. Bootstrap resampling was employed to investigate the extrapolative ability of each distribution. On the basis of these comparisons, it can be concluded that the GEV distribution is the most appropriate distribution for describing the annual maximum rainfall series in Malaysia |
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| Beschreibung: | Date Completed 10.09.2002 Date Revised 12.03.2002 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |