Uncertainty induced by hydrodynamic and morphological boundary conditions in Coastal Flood Early Warning System predictions

Abstract. Early Warning Systems (EWSs) are increasingly used to support coastal flood risk management, yet uncertainties in hydrodynamic and morphological boundary conditions can substantially affect forecast reliability. This study investigates the impact of hydrodynamic forcing and beach profile characteristics on coastal flooding hazard predictions using a validated process-based EWS in Zarautz beach (Basque Country, Spain). A database of 2,880 simulations was generated by combining representative storm conditions and synthetic beach profiles spanning the observed hydrodynamic and morphological variability of the study area. Univariate and multivariate sensitivity analyses were performed to quantify the influence of individual boundary conditions and their interactions on predicted hazard levels. The effects of realistic acquisition errors in operational wave forecasts and real-time morphological observations were also assessed using historical storm events. Results show that the uncertainty on hazard level predictions is predominantly controlled by the variability in hydrodynamic boundary conditions, which can alter predicted hazard levels by up to three levels, whereas morphological variability leads to changes of up to two levels. Among morphological parameters, beach slope and dry beach width exert the strongest influence. The role of morphology strongly depends on the hydrodynamic regime: under energetic wave conditions or low seawall freeboard configurations, hazard predictions become largely insensitive to morphological variability, whereas morphology plays a greater role under low-to-moderate forcing and high seawall freeboard conditions. Operational analyses indicate that extreme hydrodynamic errors remain the dominant source of variability. Regarding average hydrodynamic and morphological acquisition errors, hydrodynamic errors have a slightly stronger influence, however, morphological errors generate comparable forecast uncertainty. These findings provide practical guidance for optimizing beach monitoring strategies and improving the reliability of coastal flood EWS predictions.