Dozois / Bourque

Physical hydrological model (Raven), corrected by a machine learning model (per-gauge XGBoost) trained on the residuals. Where the correction stops before the last day, it fades into Raven over two days. Current validation KGE 0.960 and NSE 0.926 at a 7 day horizon, measured on the record used to calibrate and select this model, so it is not independent evidence: every live gauge clears the gate because clearing it is what makes a gauge live. These are the figures the gauge must keep clearing to stay live, re-checked at each daily revalidation on the current observation record, not a fixed score from the day it was promoted (last re-checked 2026-10-10). Over its 5 validation years the model scored KGE 0.761 to 0.970 at 7 days, each year on its own. Operational skill is worse than these figures, because the forecast starts from a modelled river state that is systematically off at issue time. The natural inflow series is the provider's, as published (provider-qc-cap-v1). In the validation years 2 days are left out of training and scoring: 2 removed by quality control. 37 days with the natural inflow above the total are trained as published (shown capped at the total). This forecast's correction reads yesterday's observed flow. On a day it has not arrived by the forecast run, the forecast is corrected instead by this gauge's previous corrector, which reads the flow observed two days before and must pass the same daily gate; such a forecast is flagged.