Retrained on the gap-filled DB (592k -> 976k rows) and re-examined the
flood backtests, now reproducible via scripts/backtest_render.py (renders
the three docs/img charts and gates on a >=12h 2024 first-alert lead —
currently failing by design and documented as such).
Findings, all documented in FLOOD_FORECASTING.md: the true 2024 crossing
was 24 Sep 17:00 (8h earlier than recorded; confirmed against the
independent HII sensor), the historical 24h-warning claim was partly a
missing-data artifact, and retrained warn classifiers collapse on the
filled grid (P.1 24h PR-AUC 0.900 -> 0.288) while regression MAE improves
(11.3 -> 10.5 cm). Serving therefore becomes max(classifier,
sigmoid(regression)) so alerting is never worse than the regression path;
metrics table, head-gating tiers, honest-limits and runbook expectations
all updated to the current model (hgb-v1+d2d0e65).
Perf, from Locust load testing (scripts/locustfile.py + load_test.py):
single-flight lock around /forecast inference (concurrent cache misses
previously each ran ~18s inference and starved the shared thread pool;
200-user run after: 105 rps, 0.01% errors), and /measurements/latest +
/health moved off the event loop (synchronous DB/network calls in async
handlers were stalling every request under load).
