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Research Article

Prediction of the Debris Flow Runout Range by Combining Simple Flow Algorithms and Statistical Techniques

Simple Flow Algorithm과 통계 기법을 결합한 토석류 확산 범위 예측 연구

Jung-Hyun Lee1
,
Hyuck-Jin Park2*
,
Jin-Ho Lee3
,
Kwang-Youn Lee4
이 정현1
,
박 혁진2*
,
이 진호3
,
이 광연4
1Post-Doctoral Fellow, Department of Energy Resources and Geosystem Engineering, Sejong University
2Professor, Department of Energy Resources and Geosystem Engineering, Sejong University
3Deputy Director, Landslide and Debris Flow Control Division, Korea Forest Service
4Senior Manager, Korea Association of Forest Envior-conservation Technology
1세종대학교 지구자원시스템공학과 박사후 연구원
2세종대학교 지구자원시스템공학과 교수
3산림청 산사태방지과 임업사무관
4한국치산기술협회 차장
*Corresponding Author
30 September 2025. pp. 325-340
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Abstract

This study evaluates the performance of the Flow-R model, which combines a simple flow routing algorithm with the travel-angle-based simplified friction-limited model (SFLM) to predict debris flow runout. A comparative analysis is also conducted with the numerical model FLO-2D. Case studies were performed in three debris flow-affected areas in South Korea, using high-resolution digital elevation models (DEMs) and inventory maps derived from aerial photographs. In Flow-R, runout distances are estimated based on the travel angle, and flow paths and extents are subsequently simulated using flow direction algorithms and persistence functions. Model performance was assessed using quantitative indicators derived from confusion matrices, including the true positive rate (TPR), false positive rate (FPR), false negative rate (FNR), and the area under the ROC curve (AUC). The results show that Flow-R achieved strong predictive performance across all study areas (Geochang: AUC = 0.862; Chungju: AUC = 0.904; Hoengseong: AUC = 0.901), outperforming FLO-2D (AUC = 0.874, 0.627, and 0.765, respectively). Notably, Flow-R exhibited lower Type I and Type II Error rates than FLO-2D. These results suggest that Flow-R effectively captures terrain-driven flow behavior without requiring complex rheological parameters. Thus, Flow-R is a promising tool for preliminary assessments of debris flow hazard, especially in contexts requiring rapid, large-scale screening.

Keywords
debris flow runout prediction
statistical-based debris flow model
simple flow routing algorithm
simplified friction-limited model
confusion matrix

토석류 확산 범위 예측 모델은 분석에 활용되는 유동 모델에 따라 다양한 예측 모델이 제안되었으며 각 기법은 뚜렷한 장단점을 가지고 있다. 본 연구에서는 simple flow routing algorithm과 travel-angle 기반의 simplified friction-limited model (SFLM)을 통합한 Flow-R 모델을 활용하여 토석류 확산 범위를 예측하고, 현재 가장 범용적으로 활용되는 수치해석 기반 모델인 FLO-2D와 예측 결과를 비교하였다. 이를 위해 토석류 피해가 보고된 3개 지역(거창군, 충주시, 횡성군)을 대상으로 고해상도 DEM과 항공사진 기반의 토석류 피해 현황도를 구축하여 모델에 적용하였다. 즉, 각각의 연구 지역에 대하여 Flow-R과 FLO-2D를 활용하여 토석류 확산 범위를 산정하고 그 결과를 비교하였으며, 모델의 성능 평가는 confusion matrix 기반의 정량적 지표인 true positive rate (TPR), false positive rate (FPR), false negative rate (FNR), 그리고 area under the ROC curve (AUC)를 통해 수행하였다. 분석 결과, Flow-R은 세 지역에서 우수한 예측 성능을 보였으며(거창군: AUC = 0.862, 충주시: AUC = 0.904, 횡성군: AUC = 0.901), 이는 FLO-2D의 성능(AUC = 0.874, 0.627, 0.765)보다 우수한 성능을 보여준다. 특히 예측 오류를 나타내는 Type I Error 및 Type II Error에서도 FLO-2D보다 낮은 값을 보였으며, Flow-R이 복잡한 유동학적 해석 없이도 지형 특성을 효과적으로 반영할 수 있음을 확인하였다. 따라서 Flow-R은 향후 통계 기반의 예비 조사 목적으로서 토석류 피해 대책 연구에 활용 가능성이 높다고 판단된다.

키워드
토석류 확산 범위 예측
통계 기반 예측 모델
simple flow routing algorithm
simplified friction-limited model
confusion matrix
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Information
  • Publisher :Korean Society of Engineering Geology
  • Publisher(Ko) :대한지질공학회
  • Journal Title :The Journal of Engineering Geology
  • Journal Title(Ko) :지질공학
  • Volume : 35
  • No :3
  • Pages :325-340
  • Received Date : 2025-06-23
  • Revised Date : 2025-07-30
  • Accepted Date : 2025-08-12
  • DOI :https://doi.org/10.9720/kseg.2025.3.325
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