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A review on urban inundation modeling research in South Korea: 2001-2022

도시침수 모의 기술 국내 연구동향 리뷰: 2001-2022

  • Lee, Seungsoo (Water and Land Research Group) ;
  • Kim, Bomi (Department of Civil Engineering, Kumoh National Institute of Technology) ;
  • Choi, Hyeonjin (Department of Civil Engineering, Kumoh National Institute of Technology) ;
  • Noh, Seong Jin (Department of Civil Engineering, Kumoh National Institute of Technology)
  • 이승수 (한국환경연구원 물국토연구본부) ;
  • 김보미 (금오공과대학교 토목공학과) ;
  • 최현진 (금오공과대학교 토목공학과) ;
  • 노성진 (금오공과대학교 토목공학과)
  • Received : 2022.09.06
  • Accepted : 2022.10.04
  • Published : 2022.10.31

Abstract

In this study, a state-of-the-art review on urban inundation simulation technology was presented summarizing major achievements and limitations, and future research recommendations and challenges. More than 160 papers published in major domestic academic journals since the 2000s were analyzed. After analyzing the core themes and contents of the papers, the status of technological development was reviewed according to simulation methodologies such as physically-based and data-driven approaches. In addition, research trends for application purposes and advances in overseas and related fields were analyzed. Since more than 60% of urban inundation research used Storm Water Management Model (SWMM), developing new modeling techniques for detailed physical processes of dual drainage was encouraged. Data-based approaches have become a new status quo in urban inundation modeling. However, given that hydrological extreme data is rare, balanced research development of data and physically-based approaches was recommended. Urban inundation analysis technology, actively combined with new technologies in other fields such as artificial intelligence, IoT, and metaverse, would require continuous support from society and holistic approaches to solve challenges from climate risk and reduce disaster damage.

본 총설연구에서는 도시침수 모의 기술의 체계와 발전 과정을 정리하고, 주요 성과와 한계점을 파악하여 향후 연구 방향과 도전 과제를 제시하였다. 이를 위해 2000년대 이후 국내 주요 학술논문집에 수록된 도시침수 모의 관련 논문 160여편을 분석하여 연구의 핵심 주제와 내용을 살펴본 후, 물리 및 데이터 기반 모형의 침수모의 세부 방법론별로 기술의 발전 현황에 대해 정리하였다. 또한, 국내 도시침수 모의 기술의 활용목적별 동향, 국외 및 연관 분야 연구동향에 대해서도 분석하였다. 국내 도시침수 모의 연구에서 Storm Water Management Model (SWMM) 모형을 활용하는 비율이 60%를 넘는 것으로 조사되었으며, 이중 배제(dual drainage)의 도시침수 물리 과정을 상세히 해석하는 국내 기술에 대한 연구가 필요한 것으로 판단되었다. 한편, 딥러닝(deep learning) 등 데이터 기반 모의 기술은 도시침수 해석의 새로운 분야로 자리매김하였다. 다만, 모형 훈련을 위한 극한기상조건에 대한 침수자료는 관측 만으로 확보할 수 없으므로, 고정확도 물리 모형과 데이터 기반 모형 연구는 상호보완적으로 진행되어야 할 필요가 있다. 도시침수 모의 기술은 인공지능이나 IoT, 메타버스 등 타 분야 신기술과의 접목이 활발히 이루어지고 있으며, 기후 위기 적응과 재해 피해 저감을 위해 지속적인 사회적 투자와 융합 연구가 필요한 분야로 판단된다.

Keywords

Acknowledgement

이 성과는 한국환경연구원의 2022년도 기본과제 '기후위기 대응을 위한 도시침수 관리 정책 개선방안 연구(RE2022-15)'와 한국수자원공사(K-water)의 개방형 혁신 R&D (21-BC-001) 사업 및 정부(과학기술정보통신부)의 재원으로 한국연구재단(No. 2022R1A4A5028840)의 지원을 받아 수행된 연구임.

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