Method
Risk = √(Hazard × Exposure), a geometric mean, so a county needs both hazard and assets to rank high. Each score runs from 0 to 100.
Hazard (0–1 percentile among Kenyan grid cells)
- Wind: median annual maximum of daily max 10 m wind, and mean days per year ≥ m/s.
- Extreme rain / flood: median annual maximum 1-day rainfall (daily values over 200 mm in a ~55 km cell are treated as data artefacts), and mean days per year ≥ mm.
- Heat: mean days per year with Tmax ≥ °C, and the trend in annual mean Tmax (°C/decade).
- Drought: share of long rains (MAM) and short rains (OND) seasons with totals below % of their mean. This matters for hydropower and for cooling water.
The composite hazard is the weighted mean of the four, using the sliders. County values average the grid cells whose centre falls in the county. Small counties without a cell centre (e.g. Nairobi, Mombasa) take the nearest cell.
Exposure
Weighted count of critical assets in the county plus high-voltage (≥132 kV) line length, ranked among counties (0–1). Weights: power plant 5, fuel depot 4, port 4, substation 3, airport 3, hospital 2, water/dam 2, telecom 1, and 1 per 50 km of HV line.
Data
Limitations
- MERRA-2 cells are ~55 km, which smooths local extremes. Thresholds are set to match, and the AI-downscaled 1 km fields will replace these in the next version.
- OSM coverage of Kenyan infrastructure is uneven. Missing assets lower exposure. Utility asset registers (KPLC, KETRACO, KenGen) would fix this.
- Riverine and coastal flood depth, landslides and lightning aren't modelled yet; extreme rainfall is a proxy.
- This is a screening tool, not an engineering assessment.