GFDRR / GFDRR/thinkhazard

TH scores update: TSUNAMI

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@stufraser1 is already working on this.

Since Oct 30, 2025.

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Python
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Description

Hazard Processing Method

  • Data Source: 3 return periods (RP100, RP500, RP2500) - inundation depth rasters
  • Unit: m (meters)
  • Default RP-Specific Thresholds:
    • RP100: 2.0 m
    • RP500: 1.0 m
    • RP2500: 0.5 m
  • Default Area Threshold: 0%

Workflow: Different from Earthquake/Cyclone - uses MAJORITY values

  1. Extract all pixel values for each RP raster within each admin unit
  2. For each RP, calculate:
    • MAJORITY inundation depth = most common positive value (ignoring zero/nodata)
    • Area percentage = % of pixels above RP-specific threshold > using 0% due to sparse data format
  3. Check if unit has ANY inundation data (majority > 0 in any RP)
  4. Check if majority value meets RP-specific threshold AND area threshold % is met for each RP
  5. Score = count of RPs meeting both thresholds (0-3)

Scoring Logic (different from earthquake/cyclone):

  • No inundation data in any RP → Score -1 (not affected)
  • Has inundation but 0 RPs meet thresholds → Score 0 (below threshold)
  • 1 RP meets thresholds → Score 1
  • 2 RPs meet thresholds → Score 2
  • 3 RPs meet thresholds → Score 3

Comparison

Image
New score distribution: ADM2
Image
New score distribution: URBAN
Image

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