Short-duration, high-intensity flooding — the burst case of the rainfall proxy.
The classifier decides between Flood and Flash Flood from the driver tensor alone. On the committed snapshot the two classes are almost never both plausible for the same unit, and the physics track cannot arbitrate between them.
Same softmax caveat as Flood: uncalibrated, and published with that label.
Nothing above the WATCH level can be published automatically while no calibration map exists, and nothing at all can be published while the pipeline stamps no model version — the alert engine records that as `publication_blocked` rather than issuing the alert.
Identical to Flood in this implementation. The intensity term is what makes a burst score higher than a drizzle of the same total, but nothing in the proxy separates a flash flood from a slow one.
Drivers: precipitation accumulated over the horizon (P_total) · wettest 24 hours in that horizon (P_peak).
clip(x) clamps a term to [0, 1] — max(0, min(1, x)) — which is how every formula in the pipeline bounds its terms. Each term is clipped before it is weighted, so no single driver can run away with a score.
In the run this deployment ships (prediction date 2026-09-16), 71 district-horizon units are classified as Flash Flood: 49 at 15 days · 22 at 7 days.
Highest model severity: Sunamganj (1.00, 15 days), Sylhet (1.00, 7 days), Khulna (1.00, 15 days), Sunamganj (1.00, 7 days), Kishoreganj (1.00, 15 days).
These are classifications from the current run, not a forecast of impact. The model version behind them is not stamped yet, and PRODUCT_SPEC §1.6 keeps publication closed above the WATCH level until one exists.
Typical season: March–May (pre-monsoon convection) and June–September. This describes when the hazard is climatologically plausible, not when this run flags it.
Ground-truth reports (district, hazard, horizon, date, what was observed) are the only route by which this project can publish skill metrics. The contact page reaches the maintainers.
No. The severity index is the model's continuous score for how strongly the drivers resemble this class, on a 0.00–1.00 scale. It is not a probability, not a percentage, and it does not model exposure. The physics cross-check is a second, independent estimate; where the two diverge, both numbers are shown rather than averaged.
The published confidence is the model's own softmax over its eight classes, labelled uncalibrated_model_softmax in the data. It says how certain the classifier is about the class it picked, not how often that class actually materialises. No calibration map has been fitted yet, which is also why nothing above the WATCH level can be published automatically.
The district pages cover all 64 districts. This page summarises the districts the current run covers — a run can be partial, and the coverage stamp on the snapshot says exactly how partial, which the status page reports.
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