Preprints
https://doi.org/10.5194/egusphere-2024-3373
https://doi.org/10.5194/egusphere-2024-3373
13 Nov 2024
 | 13 Nov 2024
Status: this preprint is open for discussion.

Operational hydrodynamic service as a tool for coastal flood assessment

Xavier Sánchez-Artús, Vicente Gracia, Manuel Espino, Manel Grifoll, Gonzalo Simarro, Jorge Guillén, Marta González, and Agustín Sanchez-Arcilla

Abstract. A comprehensive, high-resolution hydrodynamic operational service using XBeach model is presented and tested for three urban beaches in Barcelona, NW Mediterranean Sea. The operational architecture is based on Python scripts combined with task automation tools, ensuring a user-friendly system implemented on a standard desktop computer. Hydrodynamic validation of the model is carried out using data gathered during a field campaign in 2022, when a high-intensity storm occurred, resulting in a root mean square error of around 0.4 m and a skill score assessment index of 0.82. Flooding predictions were validated using videometry systems, yielding satisfactory Euclidean distances less than 5 m for storms close to the topobathymetry collection. For storms occurring years earlier, the distances ranged between 7–15 m, underscoring the need for regular topobathymetry updates to maintain forecasting accuracy. The operational system is designed to provide early-warning coastal flooding at three-days horizon. The service provides a warning system with a specific categorisation of the event, enabling the end-users to prepare for a possible flooding. The outcome assists in decision-making of such events by utilizing the operational system. The presented methodology is easily adaptable and replicable to meet user requirements or to be applied in other areas of interest.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Xavier Sánchez-Artús, Vicente Gracia, Manuel Espino, Manel Grifoll, Gonzalo Simarro, Jorge Guillén, Marta González, and Agustín Sanchez-Arcilla

Status: open (until 13 Jan 2025)

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Xavier Sánchez-Artús, Vicente Gracia, Manuel Espino, Manel Grifoll, Gonzalo Simarro, Jorge Guillén, Marta González, and Agustín Sanchez-Arcilla
Xavier Sánchez-Artús, Vicente Gracia, Manuel Espino, Manel Grifoll, Gonzalo Simarro, Jorge Guillén, Marta González, and Agustín Sanchez-Arcilla

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Short summary
The study presents an operational service that forecasts flood impacts during extreme conditions at three beaches in Barcelona, Spain. The architecture is designed for efficient use on standard desktop computers, using data from the Copernicus Marine Environment Monitoring Service, task automation tools, Python scripts, and the XBeach model to deliver timely results. Extensive validation, including field campaigns and video analysis, ensures accuracy and reliability.