Probabilistic assessment of meteorological drought over South Korea under RCP scenarios using a hidden Markov model
- Title
- Probabilistic assessment of meteorological drought over South Korea under RCP scenarios using a hidden Markov model
- Author
- 김태웅
- Keywords
- climate change; drought; hidden Markov model; rainfall
- Issue Date
- 2018-01
- Publisher
- KOREAN SOCIETY OF CIVIL ENGINEERS-KSCE
- Citation
- KSCE JOURNAL OF CIVIL ENGINEERING, v. 22, No. 1, Page. 365-372
- Abstract
- Most drought indices are evaluated based on pre-defined thresholds, which are inadequate for demonstrating the inherent uncertainty of drought. This study employed a hidden Markov model-based drought index (HMM-DI) for probabilistic assessment of meteorological drought in South Korea. The HMM-DI was developed to take into account the inherent uncertainty embedded in daily precipitation and to assess drought severity without using pre-defined thresholds. Daily rainfall data recorded during 1973-2015 at 56 stations over South Korea were aggregated with 6- and 12-month windows to develop HMM-DIs for various time scales. The HMM-DIs were extended to assess future droughts in South Korea using synthesized monthly rainfall data (2016-2100) under Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The overall results indicated that the HMM-DI can classify drought conditions considering inherent uncertainty embedded in observations and can also demonstrate the probabilistic drought occurrence in the future.
- URI
- https://link.springer.com/article/10.1007%2Fs12205-017-0788-2https://repository.hanyang.ac.kr/handle/20.500.11754/80889
- ISSN
- 1226-7988
- DOI
- 10.1007/s12205-017-0788-2
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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