台灣地區降雨等級分類之研究─子計畫：台灣北部地區降雨等級分類之研究(III)
Date Issued
2001
Date
2001
Author(s)
DOI
892625Z002065
Abstract
In this study we propose a simple-scaling, Gaussian-Markov
model for rainfall process of storm events. We explain the
simple-scaling characteristics in terms of the IDF curves. Rainfall
depths of storm events were initially normalized with respect to storm
duration and total depth. Our Gaussian-Markov model is a
nonstationary first-order Markov process. We proved that, under
simple-scaling assumption, the normalized rain rate (expressed in
percentages ) process is an IID random process and thus normalized
rainfall data of different storm durations can be combined together for
parameter estimations. We showed that the maximum likelihood
estimator of the dimensionless hyetograph is the average hyetograph.
We also propose a method for regionalization of design hyetographs.
By combining the Ward’s cluster analysis technique and a
indicator-variable-based probabilistic algorithm, we demonstrate that a
map of regionalized hyetographs could be developed and used to determine the design hyetograph of any ungaged site in the study area.
Subjects
hyetograph
Gaussian-Markov process
cluster analysis
regionalization hyetograph
Publisher
臺北市：國立臺灣大學水工試驗所
Type
report
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