Abstract

AbstractA common source of uncertainty in flood inundation forecasting is the hydrograph used. Given the role of sea‐air‐hydro‐land chain processes on the water cycle, flood hydrographs in coastal areas can be indirectly affected by sea state. This study investigates sea‐state effects on precipitation, discharge, and flood inundation forecasting implementing atmospheric, ocean wave, hydrological, and hydraulic‐hydrodynamic coupled models. The Chemical Hydrological Atmospheric Ocean wave System (CHAOS) was used for coupled hydro‐meteorological‐wave simulations ‘accounting’ or ‘not accounting’ the impact of sea state on precipitation and, subsequently, on flood hydrograph. CHAOS includes the WRF‐Hydro hydrological model and the WRF‐ARW meteorological model two‐way coupled with the WAM wave model through the OASIS3‐MCT coupler. Subsequently, the 2D HEC‐RAS hydraulic‐hydrodynamic model was forced by the flood hydrographs and map the inundated areas. A flash flood event occurred on 15 November 2017 in Mandra, Attica, Greece, causing 24 fatalities, and damages was selected as case study. The calibration of models was performed exploiting historical flood records and previous studies. Human interventions such as hydraulic works and the urban areas were included in the hydraulic modelling geometry domain. The representation of the resistance caused by buildings was based on Unmanned Aerial System (UAS) data while the local elevation rise method was used in the urban‐flood simulation. The flood extent results were assessed using the Critical Success Index (CSI), and CSI penalize. Integrating sea‐state affected the forecast of precipitation and discharge peaks, causing up to +24% and from −8% to +36% differences, respectively, improving inundation forecast by 4.5% and flooding additional approximately 70 building blocks. The precipitation forcing time step was also highlighted as significant factor in such a small‐scale flash flood. The integrated multidisciplinary methodological approach could be adopted in operational forecasting for civil protection applications facilitating the protection of socio‐economic activities and human lives during similar future events.

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