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http://dx.doi.org/10.3741/JKWRA.2014.47.5.469

Development of Hierarchical Bayesian Spatial Regional Frequency Analysis Model Considering Geographical Characteristics  

Kim, Jin-Young (Department of Civil Engineering, Chonbuk National University)
Kwon, Hyun-Han (Department of Civil Engineering, Chonbuk National University)
Lim, Jeong-Yeul (K-water Institute, Korea Water Resources Corporation)
Publication Information
Journal of Korea Water Resources Association / v.47, no.5, 2014 , pp. 469-482 More about this Journal
Abstract
This study developed a Bayesian spatial regional frequency analysis, which aimed to analyze spatial patterns of design rainfall by incorporating geographical information (e.g. latitude, longitude and altitude) and climate characteristics (e.g. annual maximum series) within a Bayesian framework. There are disadvantages to considering geographical characteristics and to increasing uncertainties associated with areal rainfall estimation on the existing regional frequency analysis. In this sense, this study estimated the parameters of Gumbel distribution which is a function of geographical and climate characteristics, and the estimated parameters were spatially interpolated to derive design rainfall over the entire Han-river watershed. The proposed Bayesian spatial regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis, and even better performance in terms of quantifying uncertainty of design rainfall and considering geographical information as a predictor.
Keywords
regional frequency analysis; bayesian spatial; hierarchical bayesian model;
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Times Cited By KSCI : 10  (Citation Analysis)
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