CMU Water Center's Chiang Mai flood hazard map (CMFlood) replaces the older
municipal map. It is built on the October 2024 flood and has the Ping leave
its banks above P.1 4.20 m, with five stages: 4.30, 4.50, 4.70, 5.00 and
5.30 m (the 2024 record). The old map's seven stages (3.70-4.60 m) said the
city floods from 3.70 m; CMU calls that map out of date.
- P1_FLOOD_STAGES: the five CMU stages, discharge on RID's 2024 rating.
/forecast's P.1 `stages` now has five entries (same format). Thresholds
are unchanged: 4.20 m danger is the bank top, 3.70 m warning half a metre
below (as on CMU's gauge page). flood_config.json and the Rust parity
fixtures regenerated (only the stages changed).
- flood-zones-p1.geojson: CMU's KML (L1..L5) as five disjoint zones, zone k
floods first at stage k; scripts/build_flood_zones.py rebuilds it.
- Dashboard: CMU's colours and credit (map attribution); the stage grid follows
the number of stages; zone lookup for markers honours holes. The city
verdict uses statusOf's classes: flooding (over the banks) from 4.20 m,
high water from 3.70 m. Zones show by themselves when the river is over its
banks or stage 1 is >= 50 % likely. Alert, replay and verdict texts no
longer call 3.70 m city flooding (EN + TH).
- Docs: DATA_SOURCES 5.1 (CMFlood: the map, flood marks, poles, city gauges),
FLOOD_FORECASTING, DASHBOARD_REDESIGN, NOTIFICATIONS, README credits.
Phase 2a of docs/RUST_REWRITE.md. rust/forecast (ping-forecast) ports the
serving half of src/ml: the HII mirror gap fill, the hourly grid, every
feature (pandas' Kahan rolling sums included), the Mae Ngat dam frame,
HistGradientBoosting tree inference, the heuristic fallback, stale-threshold
handling and the P.1 flood-stage probabilities.
Hand-over from Python (src/ml/export.py):
- models/flood_<station>.json.gz next to each joblib bundle; train_all() writes
it, retrain.sh promotes it, `python -m src.ml.export` exports existing ones.
- rust/forecast/flood_config.json: thresholds, stages, leads and notify
constants, compiled in. tests/test_model_export.py fails while it differs
from the Python source.
Parity (rust/forecast/tests/parity.rs, fixtures from
testdata/gen_forecast_fixtures.py on the production code path): four
scenarios incl. the 2024 flood with RID lagging behind HII. Merged readings,
all features and all levels identical; with all 15 local models 377/384
probabilities bit-identical, the rest within 2 ulp (exp).
Python refactor without behaviour change: predict.forecasts_from_long, and
get_latest_forecasts/load_latest/serving_frame take now/rain for
reproducible comparisons; the HII query orders its rows.
grabowski