Earticle

초록

영어

Accurate determination of rainfall thresholds is essential for effective landslide prediction and early warning. This study compares two methodologies for analysing landslide-triggering rainfall thresholds in South Korea: one using data from the single nearest station selected through recent site verification, and the other based on averaged rainfall data from multiple nearby observation stations. I–D and E–D curves were derived using quantile regression with consistent rainfall event thresholds, and predictive performance was evaluated using ROCbased classification accuracy (AUC). The single observation station approach exhibited considerable variability, whereas the average-based method produced more stable and consistent threshold estimates. The comparison identifies the strengths and limitations of each approach depending on the availability and distribution of observational infrastructure, providing insights into effective data utilization strategies for landslide early warning systems

키워드

저자

• Sujin Jang [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ]
• Keunchang Jang [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ]
• Song Eu [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ] Corresponding Author
• Kihwan Lee [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ]
• Junpyo Seo [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ]
• Choongshik Woo [ Landslide Division, National Institute of Forest Science, 56, Hoegi-ro, Seoul, 02455, South Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국산림공학회 학술대회

• 간기

  연간

• 수록기간

  2023~2025

• 십진분류

  KDC 526 DDC 634