Uttarakhand cmip aoi
lon 79.30500, lat 30.08500 · 1 km MGRS cell 44RLU3629
ingest/geocode.py: "Nominatim geocodes to a place, so precision is place-level (~3 km), never a street fix." The lon/lat above is a named-place point, not an address; the card describes its 1 km cell.
| This-week probability | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
|---|---|
| Band | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Top reasons | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Relative risk (within city) | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Return period (RSK-06) | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Depth, 1-in-10 yr | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Depth, 1-in-50 yr | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
| Depth, 1-in-100 yr | not computable — this point lies outside the 4 flood AOIs (delhi, mumbai, bengaluru, chandigarh) — not modelled, not safe |
- This is a per-cell card, not a per-address one: geocoding is place-level (~3 km) and the grid coarsens to 1 km.
- The 'why' reasons come from a street-waterlogging relative ranking, not a probability — results/<city>_why.json labels itself that way and the card must repeat it.
- The probability is the climatology baseline over 28 cells in 2 cities unless is_learned is true; a cell not in the panel is 'not modelled', not 'safe'.
- Depth rows read 'not computable' until the HYD depth layer passes its own gate — they are not zero.
built 2026-10-14 05:41 UTC