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Publication - Dr Gemma Coxon

    Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional-local flood modeling system


    Bermúdez, M, Neal, JC, Bates, PD, Coxon, G, Freer, JE, Cea, L & Puertas, J, 2017, ‘Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional-local flood modeling system’. Water Resources Research, vol 53., pp. 2770-2785


    Inflow discharge and outflow stage estimates for hydraulic flood models are generally derived from river gauge data. Uncertainties in the measured inflow data and the neglect of rainfall-runoffcontributions to the modeled domain downstream of the gauging locations can have a significant impact on these estimated "whole reach" inflows and consequently on flood predictions. In this study, a method to incorporate rating curve uncertainty and local rainfall-runoffdynamics into the predictions of a reach-scale flood model is proposed. The methodology is applied to the July 2007 floods of the River Severn in UK. Discharge uncertainty bounds are generated applying a nonparametric local weighted regression approach to stage-discharge measurements for two gauging stations. Measured rainfall downstream from these locations is used as input to a series of subcatchment regional hydrological model to quantify additional local inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these contributions and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Accurate prediction of the flood peak was obtained with the proposed method, which was only possible by resolving the additional complexity of the extreme rainfall contributions over the modeled area. The findings highlight the importance of estimating boundary condition uncertainty and local rainfall contributions for accurate prediction of river flows and inundation at regional scales.

    Full details in the University publications repository