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http://dx.doi.org/10.21729/ksds.2020.13.4.25

Development of Snow Depth Frequency Analysis Model Based on A Generalized Mixture Distribution with Threshold  

Kim, Ho Jun (Dept. of Civil and Environmental Engineering, Sejong University)
Kim, Jang-Gyeong (Bayesian Works Research Institute)
Kwon, Hyun-Han (Dept. of Civil and Environmental Engineering, Sejong University)
Publication Information
Journal of Korean Society of Disaster and Security / v.13, no.4, 2020 , pp. 25-36 More about this Journal
Abstract
An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.
Keywords
Mixture distribution function; Maximum snow depth; Bayesian model; Frequency analysis;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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