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

Abstract

<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>