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FastFlood East Africa Flood Case Studies

FastFlood reproductions of the 11 ICPAC flood case studies, driven by the same event inputs as the RIM2D simulations in E4DRR/rim2d-simulations, and packaged in the same layout so the two methods compare map-for-map.

FastFlood (FastHazard, NL) is a fast steady-state flood method: DEM + rainfall (+ optional Manning / infiltration) β†’ maximum inundation in seconds on CPU. RIM2D (GFZ Potsdam) is GPU 2D shallow-water hydrodynamics. This dataset lets you see how a lightweight screening method lines up against full 2D physics on identical events.

Produced under the ICPAC E4DRR / CRAF'D project.

Layout

Each <case>/ mirrors the RIM2D case layout:

<case>/
β”œβ”€β”€ input/
β”‚   β”œβ”€β”€ dem.tif              Copernicus GLO-30 elevation (m), stream-burned
β”‚   β”œβ”€β”€ roughness.tif        Manning's n
β”‚   β”œβ”€β”€ infiltration.tif     infiltration capacity (mm/hr)
β”‚   β”œβ”€β”€ rain_mean_mmhr.tif   event-mean rainfall intensity (mm/hr)
β”‚   └── permanent_water.tif  lake / reservoir / sea mask (1 = permanent water)
β”œβ”€β”€ output/
β”‚   β”œβ”€β”€ <case>_wd_max.tif    FastFlood maximum water-depth envelope
β”‚   β”œβ”€β”€ frames/wh_*.tif      inundation at successive elapsed times
β”‚   └── preview.gif          RIM2D-style water-depth animation
β”œβ”€β”€ run_command.txt          the FastFlood invocation (β‰ˆ RIM2D .def)
└── METHOD.md                per-case method notes

Cases

Case Country Event Duration
nairobi_2026-03-06 Kenya flash flood, Nairobi metro 24 h
ssd_2025-10-05 South Sudan Upper Nile / Renk 24 h
dji_2019-11-21 Djibouti Djibouti City flash flood 72 h
eth_2021-08-16 Ethiopia Addis Akaki river 72 h
som_2023-11-19 Somalia Lower Shabelle 72 h
uga_2019-05-26 Uganda central Uganda / Kampala 72 h
eri_2019-08-10 Eritrea Asmara plateau highlands 120 h
rwa_2023-05-01 Rwanda western + northern provinces 120 h
nile_2024_abu_hamad Sudan Abu Hamad (Nile) 144 h
tza_2024-04-10 Tanzania Dar es Salaam metro 168 h
bdi_2024-04-01 Burundi Bujumbura + central 504 h

Method

The RIM2D case NetCDFs (dem.nc, roughness.nc, pervious_surface.nc, and the per-30-min rain/imerg_t*.nc frames) are converted 1:1 to GeoTIFFs on the same 30 m UTM grid. FastFlood's -rain is an intensity applied as rain Γ— dur, so the IMERG frames are reduced to an event-mean intensity map (total_mm = Ξ£(rateΒ·0.5), mean = total_mm / duration_h).

Animations drive FastFlood with the cumulative IMERG hyetograph so inundation grows monotonically to the full-event result. Permanent water bodies (lakes, reservoirs, ocean) are masked (Natural Earth lakes + DEM sea) and shown as static dark water, not flood.

FastFlood vs RIM2D β€” flood-on-land extent

Wet area = depth > 5 cm; permanent water excluded from both models via the same per-case mask. RIM2D = case_v1_wd_max.nc reference.

Case FF max (m) FF wet % RIM2D max (m) RIM2D wet %
nairobi 10.53 6.2 20.08 11.8
ssd 0.97 4.2 5.24 5.7
dji 2.38 0.6 23.41 30.9
eth 2.22 1.8 21.45 3.9
som 1.43 3.1 7.57 37.0
uga 1.65 4.6 9.75 11.7
eri 1.55 0.8 12.91 3.6
rwa 3.02 5.2 16.78 11.7
nile 0.28 2.0 5.44 19.2
tza 2.54 4.0 11.58 32.6
bdi 2.14 1.5 16.93 27.7

FastFlood reproduces the same flood locations but under-predicts RIM2D. For inland cases the FastFlood/RIM2D wet-area ratio is a stable ~0.4–0.7; for coastal / lake cases (dji, som, tza, bdi) RIM2D floods extensive low coastal land that the steady pluvial FastFlood barely wets. This is expected for a fast steady-state approximation vs full 2D hydrodynamics β€” a screening tool, not a calibrated hazard product.

Reproduce

Pipeline code: https://github.com/nishadhka/DevOps-hazard-modeling/tree/main/fastflood (rim2d_nc_to_fastflood.py, run_all_cases.sh, make_fastflood_animation.py, build_water_mask.py, package_fastflood_case.sh).

License

CC BY 4.0. FastFlood is proprietary software of FastHazard (NL); this dataset contains only its inputs/outputs for these cases, not the software.

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