Geoskill: Debris Flow Risk Screening

Debris Flow Risk Screening

Identifies potential debris-flow gullies from DEM terrain analysis, integrates material source availability, rainfall triggering thresholds, and downstream exposure to produce basin-level hazard and risk screening.

Trigger

Use when the user wants to:

• Identify potential debris-flow gullies from DEM data
• Produce basin-level debris-flow hazard screening
• Assess downstream exposure and risk from debris flows
• Evaluate runout zones using conservative geometric diffusion
• Generate risk maps integrating hazard, exposure, and vulnerability

CLI Usage

# Synthetic demo mode (no input files needed)
python scripts/debris_flow_risk.py --output-dir ./dfr-output

# With custom parameters
python scripts/debris_flow_risk.py \
  --rainfall-scenario 100yr \
  --runout-method geometric \
  --risk-schema three_class \
  --output-dir ./dfr-output

# With custom outlet points
python scripts/debris_flow_risk.py \
  --outlet-points ./outlets.geojson \
  --material-source sparse \
  --output-dir ./dfr-output

Parameters

Output

Key Algorithms

D8 Flow Direction

Standard D8 encoding: 1=E, 2=SE, 4=S, 8=SW, 16=W, 32=NW, 64=N, 128=NE. Flow accumulation computed by recursive upslope contribution.

Basin Delineation

Watershed basins delineated from outlet points using flow direction. Basins filtered by slope, curvature, and flow accumulation criteria.

Hazard Index

Composite index integrating:

• Terrain factor: slope, profile curvature, basin relief
• Material source: loose sediment availability
• Rainfall trigger: intensity-duration threshold exceedance

Runout Zone (Geometric)

Conservative geometric diffusion: runout distance = H / tan(α), where H is the elevation drop and α is the average fan angle (default 11°). RAMMS/FLO-2D interfaces reserved for future implementation.

Sensitivity Analysis

Outlet position, flow accumulation threshold, and DEM resolution are key sensitive parameters. Sensitivity analysis varies each parameter ±20% and reports hazard index change.

Risk Classification

Risk = Hazard × Exposure × Vulnerability Three-class: Low, Moderate, High

Exit Codes

Important Limitations

• Output is screening-level, NOT a substitute for dynamic engineering models
• Results are sensitive to outlet position, flow threshold, and DEM resolution
• Runout uses conservative geometric diffusion; for engineering design use RAMMS/FLO-2D
• Material source estimation is approximate without field validation
• Rainfall thresholds are regional approximations

References

• Takahashi, T. (2007). Debris Flow: Mechanics, Prediction and Countermeasures.
• Hungr, O., et al. (2005). The Varnes classification of landslide types.
• Horton, P., et al. (2013). Flow-R: a model for susceptibility mapping of debris flows.
• Kang, S., & Lee, S. (2018). Debris flow susceptibility assessment using GIS and machine learning.

数据下载

本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):

python debris_flow_risk.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir 

• --bbox W,S,E,N: WGS-84 边界框 (西, 南, 东, 北)
• --date-range START,END: 日期范围 (YYYY-MM-DD,YYYY-MM-DD)
• --aoi-file : 替代 --bbox 的 GeoJSON 多边形
• --cache-dir : 缓存目录 (默认 ~/.geoskill_cache)

当用户只给 --bbox + --date-range (没有 --dem) 时，skill 自动下载数据。 当用户给 --dem 时，走原文件路径 (向后兼容)。