Flood Risk Assessment at the Administrative District Level Based on SSP Scenarios

Owing to climate change, annual rainfall and the likelihood of extreme precipitation events are projected to increase in the future (2021-2100), raising concerns about the intensification of flood damage. This study assessed flood risk at the administrative district level using three key components—Hazard, Exposure, and Vulnerability—and 13 detailed indicators that reflect meteorological factors, historical flood records, population data, and regional characteristics. In particular, future changes in flood risk under climate change were quantitatively evaluated using the SSP scenarios. The results showed that regions with the top 10% of flood risk scores exhibited high consistency with flood-prone areas identified on existing flood inundation maps. Under current conditions, approximately 25% of the administrative regions are classified as high- or extremely-high flood-risk areas; however, under future conditions, this proportion increases to as much as 42%, depending on the SSP scenario. In addition, the maximum flood risk value increased by approximately 1.7 times compared to current conditions, with scenario-dependent increases ranging from 1.12 to 2.19 times. The flood risk assessment results and high-risk area classifications presented in this study can serve as foundational data for more detailed flood risk analyses and are expected to provide practical evidence for establishing flood risk management policies and prioritizing investments in flood control infrastructure at both the national and local government levels.

Authors

Institutions

Publication Details

Journal
Korean Society of Hazard Mitigation
Published
2026-04-28
DOI
https://doi.org/10.9798/kosham.2026.26.2.23
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flood Risk Assessment at the Administrative District Level Based on SSP Scenarios

Sangman Jeong, Tae Sung Cheong, Bongyeon Cho
Korean Society of Hazard Mitigation
Flood Risk Assessment and Management
article

Flood Risk Assessment at the Administrative District Level Based on SSP Scenarios

Sangman Jeong, Tae Sung Cheong, Bongyeon Cho
article en

Abstract

Owing to climate change, annual rainfall and the likelihood of extreme precipitation events are projected to increase in the future (2021-2100), raising concerns about the intensification of flood damage. This study assessed flood risk at the administrative district level using three key components—Hazard, Exposure, and Vulnerability—and 13 detailed indicators that reflect meteorological factors, historical flood records, population data, and regional characteristics. In particular, future changes in flood risk under climate change were quantitatively evaluated using the SSP scenarios. The results showed that regions with the top 10% of flood risk scores exhibited high consistency with flood-prone areas identified on existing flood inundation maps. Under current conditions, approximately 25% of the administrative regions are classified as high- or extremely-high flood-risk areas; however, under future conditions, this proportion increases to as much as 42%, depending on the SSP scenario. In addition, the maximum flood risk value increased by approximately 1.7 times compared to current conditions, with scenario-dependent increases ranging from 1.12 to 2.19 times. The flood risk assessment results and high-risk area classifications presented in this study can serve as foundational data for more detailed flood risk analyses and are expected to provide practical evidence for establishing flood risk management policies and prioritizing investments in flood control infrastructure at both the national and local government levels.

Korean Society of Hazard MitigationVol. 26(2)
Korea Institute of Nuclear Safety (KR), Dongbu HiTek (South Korea) (KR), National Disaster Management Research Institute (KR)
Climate action
Openalex Percentile: Top 6%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.