feat(collector): forecast and ntfy in ping-collector; ThaiWater keeps alerts current at night

Phase 2b/2c of docs/RUST_REWRITE.md. With FORECAST_IN_COLLECTOR=true (shared
.env) ping-collector, after each cycle that brought newer RID or HII readings
and at least hourly: loads the last 336 h (RID + HII mirror fill), fetches the
rain forecast, runs every exported model (rust/forecast), stores
forecast_history and forecast_current, and sends the ntfy notifications.
The Python API then serves forecast_current as /forecast (computing in-process
only when it is older than FORECAST_MAX_AGE_SECONDS) and neither forecasts nor
notifies.

ntfy (collector/src/notify.rs): a port of src/notify.py with the same topics,
texts, hysteresis, capacity guard and notification_state keys, checked word
for word on 751 messages generated by Python (testdata/gen_notify_cases.py).
The change: for stations whose ThaiWater twin is the same sensor, a reading
newer than RID's drives the level alerts (marked as ThaiWater telemetry), and
the feed counts as stale only when neither source has a reading for 3 h. RID
alone lagging is reported once after RID_STALE_ALERT_HOURS (18). This ends the
nightly "gauge feed stale" / "recovered" pairs caused by RID's late reports.

Commands: `forecast [--json] [--save] [--now] [--rain-file]`,
`notify --dry-run`. scripts/forecast_parity.py compares Python and the
collector on the live database (same moment, same rain); locally 48/48 rows
identical. install_collector.sh: models export + that check on every install,
--cutover-forecast (refuses on a failed check) and --rollback-forecast.

Trees are packed into 24-byte nodes: 70 MB peak with all 15 models (was 140).
Forecast values are written to NUMERIC as shortest round-trip text, so they
round as psycopg2's do. DB test schemas get a counter (parallel tests collided
on Windows' coarse clock).

docs/FLOOD_FORECASTING.md

@@ -616,6 +616,13 @@ fix, the served features match what this section evaluates.
 
 ### API
 
+With `FORECAST_IN_COLLECTOR=true` the forecast is computed by `ping-collector`
+(`rust/forecast`, a parity-tested port of this serving path) from
+`models/flood_<station>.json.gz`, which `train_all()` exports next to each
+joblib bundle; `/forecast` serves its `forecast_current` row and computes
+in-process only when that is older than `FORECAST_MAX_AGE_SECONDS` (2 h). See
+`rust/README.md`. The rest of this section describes the in-process path.
+
 `GET /forecast` (`src/web_api.py`) returns one JSON row per station × horizon with
 the fields listed in section 1. Results are cached in-process for
 `FORECAST_TTL = 900` seconds (15 minutes), which matches the data cadence — the