Identification and stochastic generation of representative rainfall temporal patterns in Hong Kong territory

Shiang Jen Wu, Jinn Chuang Yang, Yeou-Koung Tung*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

In hydrosystem engineering design and analysis, temporal pattern for rainfall events of interest is often required. In this paper, statistical cluster analysis of dimensionless rainfall pattern is applied to identify representative temporal rainfall patterns typically occurred in Hong Kong Territory. For purpose of selecting an appropriate rainfall pattern in engineering applications, factors affecting the occurrence of different rainfall patterns are examined by statistical contingency tables analysis through which the inter-dependence of the occurrence frequency of rainfall patterns with respect to geographical location, rainfall duration and depth, and seasonality is investigated. Furthermore, due to inherent variability of rainfall mass curves or hyetographs within each classified rainfall pattern, a practical procedure to probabilistically generate plausible rainfall patterns is described. The procedure preserves the inherent stochastic features of random dimensionless rainfall hyetograph ordinates, which in general are correlated non-normal multivariate compositional variables.

Original languageEnglish
Pages (from-to)171-183
Number of pages13
JournalStochastic Environmental Research and Risk Assessment
Volume20
Issue number3
DOIs
StatePublished - 1 Apr 2006

Keywords

  • Cluster analysis
  • Constrained Monte-Carlo simulation
  • Contingency table
  • Johnson distribution system
  • Rainfall pattern

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