Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/101366
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Type: Journal article
Title: Assessing the performance of the independence method in modeling spatial extreme rainfall
Author: Zheng, F.
Thibaud, E.
Leonard, M.
Westra, S.
Citation: Water Resources Research, 2015; 51(9):7744-7758
Publisher: American Geophysical Union
Issue Date: 2015
ISSN: 0043-1397
1944-7973
Statement of
Responsibility: 
Feifei Zheng, Emeric Thibaud, Michael Leonard and Seth Westra
Abstract: Spatial statistical methods are often employed to improve precision when estimating marginal distributions of extreme rainfall. Methods such as max-stable and copula models parameterize the spatial dependence and provide a continuous spatial representation. Alternatively, the independence method can be used to estimate marginal parameters without the need for parameterizing the spatial dependence, and this method has been under-utilized in hydrologic applications. This paper investigates the effectiveness of the independence method for marginal parameter estimation of spatially dependent extremes. Its performance is compared with three spatial dependence models (max-stable Brown-Resnick, max-stable Schlather, and Gaussian copula) by means of a simulation study. The independence method is statistically robust in estimating parameters and their associated confidence intervals for spatial extremes with various underlying dependence structures. The spatial dependence models perform comparably with the independence method when the spatial dependence structure is correctly specified; otherwise they exhibit considerably worse performance. We conclude that the independence method is more appealing for modeling the marginal distributions of spatial extremes (e.g., regional estimation of trends in rainfall extremes) due to its greater robustness and simplicity. The four statistical methods are illustrated using a spatial data set comprising 69 subdaily rainfall series from the Greater Sydney region, Australia.
Rights: © 2015. American Geophysical Union. All Rights Reserved.
RMID: 0030037530
DOI: 10.1002/2015WR016893
Grant ID: http://purl.org/au-research/grants/arc/DP150100411
Appears in Collections:Civil and Environmental Engineering publications

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