行政院國家科學委員會專題研究計畫成果報告:具自我相似性高斯馬可夫模式之設計暴雨雨型
Date Issued
2000
2000-07-31
Date
2000
2000-07-31
Author(s)
DOI
892313B002038
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.
Subjects
hyetograph
self-similarity
Gaussian-Markov process
design storm
Publisher
臺北市：國立臺灣大學生物環境系統工程學系暨研究所
Type
report
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