Estimation of predictive hydrological uncertainty

This discussion paper is/has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS if available. Abstract In this paper, a technique is presented for assessing the predictive uncertainty of rainfall-runoff and hydraulic forecasts that conditions forecasts uncertainty on the forecasted value itself, based on retrospective quantile regression of hindcasted water level forecasts and forecast errors. To test the robustness of the method, a number of retro-5 spective forecasts for different catchments across England and Wales having different size and hydrological characteristics have been used to derive in a probabilistic sense the relation between simulated values of discharges and water levels, and matching errors. From this study, we can conclude that using quantile regression for estimating forecast errors conditional on the forecasted water levels provides an extremely simple, 10 efficient and robust means for uncertainty estimation of deterministic forecasts.