THESIS
2013
xii leaves, xiii-xiv, 177 pages : illustrations (some color) ; 30 cm
Abstract
Rainfall intensity (depth)-duration-frequency (IDF/DDF) relationships provide
information essential for hydrosystem infrastructures designs. For small catchments,
rainfall DDF relationships with short duration can be established based on rainfall
records from automatic raingauges. Due to the progression of instrumentation
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 da...[
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Rainfall intensity (depth)-duration-frequency (IDF/DDF) relationships provide
information essential for hydrosystem infrastructures designs. For small catchments,
rainfall DDF relationships with short duration can be established based on rainfall
records from automatic raingauges. Due to the progression of instrumentation
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 at conventional raingauges are of limited
use to establish rainfall DDF relationships in areas with small catchments like Hong
Kong where design storm duration significantly shorter than 24-hr are needed. In
addition, the unavailability of rainfall data at ungauged sites also requires an approach to establish the rainfall DDF relationships at the location. This study presents a
practical methodological framework to derive rainfall DDF relationships with short
durations at conventional raingauge sites and ungauged locations. The core
components of the framework for establishing rainfall DDF at conventional
raingauges include a rainfall scaling model and a transformation relationship between
annual maximum rolling-time 1440min rainfall and annual maximum daily rainfall.
For ungauged sites, the framework for estimating rainfall DDF relationships at
conventional stations is linked with Ordinary Kriging (OK) approach for interpolating
the statistical moments of annual maximum daily rainfall to derive the design rainfalls.
Two types of probabilistic point estimation methods are applied to assess the
uncertainty of the estimated design rainfalls. Finally, various approaches establishing
the Kriging model for interpolating design rainfalls are investigated and their relative
performances are assessed through cross validation technique. The result shows that
the proposed method is able to provide reasonable rainfall DDF relationships at
conventional raingauge sites and ungauged locations in Hong Kong.
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