journal article·2026-01-20Open access

Evaluating High-Resolution LiDAR DEMs for Flood Hazard Analysis: A Comparison with 1:5000 Topographic Maps

Tae-Yun Kim, Seung-Jun Lee, Ji-Sung Kim, Seung-Ho Han, Hong-Sik Yun

Applied Sciences· Volume 16· Issue 2

Abstract

Flood disasters are increasing worldwide due to climate change, posing growing risks to infrastructure and human life. Korea, where nearly 70% of annual rainfall occurs during the summer monsoon, is particularly vulnerable to extreme precipitation events intensified by El Niño and La Niña. This study investigates how terrain resolution influences flood simulation accuracy by comparing a 1 m LiDAR digital elevation model (DEM) with a DEM generated from a 1:5000 topographic map. Flood depth and velocity fields produced by the two DEMs show notable quantitative differences: for final flood depth, the 1:5000 DEM yields a mean absolute error of approximately 56.9 cm and an RMSE of 76.4 cm relative to LiDAR results, with substantial local over- and underestimations. Flow velocity and maximum velocity also show significant deviations, with RMSE values of 58.0 cm/s and 68.4 cm/s, respectively. Although the 1:5000 DEM captures the general inundation pattern, these discrepancies—particularly in narrow channels and urbanized floodplains—demonstrate that coarse-resolution terrain data cannot reliably reproduce hydrodynamic behavior. We conclude that while 1:5000 DEMs may be acceptable for reconnaissance-level hazard screening, high-resolution LiDAR DEMs are essential for accurate flood depth and velocity simulation, supporting their integration into engineering design, urban flood risk assessment, and disaster management frameworks.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Flood Risk Assessment and Management · Hydrology and Sediment Transport Processes · Landslides and related hazards

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Geodesy Laboratory, Civil & Architectural and Environmental System Engineering, Sungkyunkwan University (SKKU), Suwon 16419, Gyeonggi, Republic of Korea

School of Geography, Faculty of Environment, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK

Disaster & Risk Management Laboratory, Interdisciplinary Program in Crisis & Disaster and Risk Management Sungkyunkwan University (SKKU), Suwon 16419, Gyeonggi, Republic of Korea

Funding

National Research Foundation of Korea · Korea government

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