Assessment of regional drought vulnerability and risk using principal component analysis and a Gaussian mixture model
- Authors
- Kim, Ji Eun; Yu, Jisoo; Ryu, Jae-Hee; Lee, Joo-Heon; Kim, Tae-Woong
- Issue Date
- Oct-2021
- Publisher
- Kluwer Academic Publishers
- Keywords
- Drought; Risk; Vulnerability; bbbbbbbb Hazard · PCA · GMM · EWM · Copula
- Citation
- Natural Hazards, v.109, no.1, pp 707 - 724
- Pages
- 18
- Indexed
- SCIE
SCOPUS
- Journal Title
- Natural Hazards
- Volume
- 109
- Number
- 1
- Start Page
- 707
- End Page
- 724
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/110453
- DOI
- 10.1007/s11069-021-04854-y
- ISSN
- 0921-030X
1573-0840
- Abstract
- Due to the complex characteristics of drought, drought risk needs to be quantifed by combining drought vulnerability and drought hazard. Recently, the major focus in drought vulnerability has been on how to calculate the weights of indicators to comprehensively quantify drought risk. In this study, principal component analysis (PCA), a Gaussian mixture
model (GMM), and the equal-weighting method (EWM) were applied to objectively determine the weights for drought vulnerability assessment in Chungcheong Province, located
in the west-central part of South Korea. The PCA provided larger weights for agricultural
and industrial factors, whereas the GMM computed larger weights for agricultural factors
than did the EWM. The drought risk was assessed by combining the drought vulnerability
index (DVI) and the drought hazard index (DHI). Based on the DVI, the most vulnerable
region was CCN9 in the northwestern part of the province, whereas the most droughtprone region based on the DHI was CCN12 in the southwest. Considering both DVI and
DHI, the regions with the highest risk were CCN12 and CCN10 in the southern part of the
province. Using the proposed PCA and GMM, we validated drought vulnerability using
objective weighting methods and assessed comprehensive drought risk considering both
meteorological hazard and socioeconomic vulnerability.
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