Establishing rainfall depth-duration-frequency relationships at daily raingauge stations in Hong Kong

Peishi Jiang*, Yeou-Koung Tung

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Rainfall intensity (depth)-duration-frequency (IDF/DDF) relationships provide information essential for urban stormwater drainage system design and other hydrosystem infrastructures. For catchments where drainage areas are small, rainfall DDF relationships with short duration can be established based on rainfall records from automatic raingauges. Due to the progression of technology development, wide spread installation of automatic raingauges does not happen until 2-3 decades ago. Therefore, record lengths at majority of automatic raingauges are relatively short and the derived rainfall DDF relationships on the basis of at-site frequency analysis are potentially subject to significant sampling error. On the other hand, many conventional raingauges exist long before automatic raingauges were deployed. However, daily rainfall data with long records at conventional raingauges are of limited use to establish rainfall DDF relationships in areas with small catchment size like Hong Kong where design storm duration significantly shorter than 24-h are needed. This study presents a practical methodological framework to derive rainfall DDF relationships with short duration at conventional raingauge locations. The core components of the framework include the scaling model of rainfalls of different durations, the establishment of relationship between annual maximum daily rainfall and rolling-time 1440. min rainfall, the quantification of statistical features of estimated annual maximum 1440. min rainfalls, and the assessment of uncertainty of derived rainfall DDF relationships at conventional raingauges.

Original languageEnglish
Pages (from-to)80-93
Number of pages14
JournalJournal of Hydrology
StatePublished - 11 Nov 2013


  • Cluster analysis
  • GEV
  • Rainfall IDF/DDF
  • Scaling model
  • Uncertainty analysis
  • WLS

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