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Activity Number: 380 - Advances in Bayesian Extreme Value Analysis
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2022 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract #323421
Title: Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations
Author(s): Jonathan Jalbert and Christian Genest and Luc Perreault and Paul Mathivon*
Companies: Polytechnique Montréal and McGill University and Hydro-Québec and Polytechnique Montréal
Keywords: Extremes; Precipitation; Interpolation; Bayesian Hierarchical Model; IDF curves

An intensity-duration-frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada.

Authors who are presenting talks have a * after their name.

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