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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The Probabilistic Characterization of Severe Rainstorm Events: Applications of Threshold Analysis

Palynchuk, Barry A. 04 1900 (has links)
<p>Hourly archived rainfall records are separated into individual rainfall events with</p> <p>an Inter-Event Time Denition. Individual storms are characterized by their depth,</p> <p>duration, and peak intensity. Severe events are selected from among the events for</p> <p>a given station. A lower limit, or threshold depth is used to make this selection,</p> <p>and an upper duration limit is established. A small number of events per year are</p> <p>left, which have relatively high depth and average intensity appropriate to small</p> <p>to medium catchment responses. The Generalized Pareto Distributions are tted</p> <p>to the storm depth data, and a bounded probability distribution is tted to storm</p> <p>duration. Peak storm intensity is bounded by continuity imposed by storm depth</p> <p>and duration. These physical limits are used to develop an index measure of peak</p> <p>storm intensity, called intensity peak factor, bounded on (0; 1), and tted to the Beta</p> <p>distribution. The joint probability relationship among storm variables is established,</p> <p>combining increasing storm depth, increasing intensity peak factor, with decreasing</p> <p>storm duration as being the best description of increasing rainstorm severity. The</p> <p>joint probability of all three variables can be modelled with a bivariate copula of</p> <p>the marginal distributions of duration and intensity peak factor, combined simply</p> <p>with the marginal distribution of storm depth. The parameters of the marginal</p> <p>distributions of storm variables, and the frequency of occurrence of threshold-excess</p> <p>events are used to assess possible shifts in their values as a function of time and</p> <p>temperature, in order to evaluate potential climate change eects for several stations.</p> <p>Example applications of the joint probability of storm variables are provided that</p> <p>illustrate the need to apply the methods developed.</p> <p>The overall contributions of this research combine applications of existing probabilistic</p> <p>tools, with unique characterizations of rainstorm variables. Relationships</p> <p>between these variables are examined to produce a new description of storm severity,</p> <p>and to begin the assessment of the eects of climate change upon severe rainstorm</p> <p>events.</p> <p>i</p> / Doctor of Philosophy (PhD)

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