Articles | Volume 22, issue 12
https://doi.org/10.5194/nhess-22-3897-2022
https://doi.org/10.5194/nhess-22-3897-2022
Research article
 | 
07 Dec 2022
Research article |  | 07 Dec 2022

Estimating dune erosion at the regional scale using a meta-model based on neural networks

Panagiotis Athanasiou, Ap van Dongeren, Alessio Giardino, Michalis Vousdoukas, Jose A. A. Antolinez, and Roshanka Ranasinghe

Related authors

Global Coastal Characteristics (GCC): a global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators
Panagiotis Athanasiou, Ap van Dongeren, Maarten Pronk, Alessio Giardino, Michalis Vousdoukas, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 16, 3433–3452, https://doi.org/10.5194/essd-16-3433-2024,https://doi.org/10.5194/essd-16-3433-2024, 2024
Short summary
Global distribution of nearshore slopes with implications for coastal retreat
Panagiotis Athanasiou, Ap van Dongeren, Alessio Giardino, Michalis Vousdoukas, Sandra Gaytan-Aguilar, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 11, 1515–1529, https://doi.org/10.5194/essd-11-1515-2019,https://doi.org/10.5194/essd-11-1515-2019, 2019
Short summary

Related subject area

Sea, Ocean and Coastal Hazards
Brief communication: From modelling to reality – flood modelling gaps highlighted by a recent severe storm surge event along the German Baltic Sea coast
Joshua Kiesel, Claudia Wolff, and Marvin Lorenz
Nat. Hazards Earth Syst. Sci., 24, 3841–3849, https://doi.org/10.5194/nhess-24-3841-2024,https://doi.org/10.5194/nhess-24-3841-2024, 2024
Short summary
Inundation and evacuation of shoreline populations during landslide-triggered tsunamis: an integrated numerical and statistical hazard assessment
Emmie Malika Bonilauri, Catherine Aaron, Matteo Cerminara, Raphaël Paris, Tomaso Esposti Ongaro, Benedetta Calusi, Domenico Mangione, and Andrew John Lang Harris
Nat. Hazards Earth Syst. Sci., 24, 3789–3813, https://doi.org/10.5194/nhess-24-3789-2024,https://doi.org/10.5194/nhess-24-3789-2024, 2024
Short summary
Rapid simulation of wave runup on morphologically diverse, reef-lined coasts with the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process model
Robert McCall, Curt Storlazzi, Floortje Roelvink, Stuart G. Pearson, Roel de Goede, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci., 24, 3597–3625, https://doi.org/10.5194/nhess-24-3597-2024,https://doi.org/10.5194/nhess-24-3597-2024, 2024
Short summary
A brief history of tsunamis in the Vanuatu Arc
Jean H. M. Roger and Bernard Pelletier
Nat. Hazards Earth Syst. Sci., 24, 3461–3478, https://doi.org/10.5194/nhess-24-3461-2024,https://doi.org/10.5194/nhess-24-3461-2024, 2024
Short summary
Tsunami inundation and vulnerability analysis on the Makran coast, Pakistan
Rashid Haider, Sajid Ali, Gösta Hoffmann, and Klaus Reicherter
Nat. Hazards Earth Syst. Sci., 24, 3279–3290, https://doi.org/10.5194/nhess-24-3279-2024,https://doi.org/10.5194/nhess-24-3279-2024, 2024
Short summary

Cited articles

Almar, R., Ranasinghe, R., Bergsma, E. W. J., Diaz, H., Melet, A., Papa, F., Vousdoukas, M., Athanasiou, P., Dada, O., Almeida, L. P., and Kestenare, E.: A global analysis of extreme coastal water levels with implications for potential coastal overtopping, Nat. Commun., 12, 3775, https://doi.org/10.1038/s41467-021-24008-9, 2021. 
Antolínez, J. A. A., Méndez, F. J., Anderson, D., Ruggiero, P., and Kaminsky, G. M.: Predicting Climate-Driven Coastlines With a Simple and Efficient Multiscale Model, J. Geophys. Res.-Earth Surf., 124, 1596–1624, https://doi.org/10.1029/2018JF004790, 2019. 
Arcadis/Deltares: Validation of dune erosion model XBeach. Development of “BOI Sandy Coasts,” Tech. report D10029117:2.0., 2022. 
Athanasiou, P., de Boer, W., Yoo, J., Ranasinghe, R., and Reniers, A.: Analysing decadal-scale crescentic bar dynamics using satellite imagery: A case study at Anmok beach, South Korea, Mar. Geol., 405, 1–11, https://doi.org/10.1016/j.margeo.2018.07.013, 2018. 
Download
Short summary
Sandy dunes protect the hinterland from coastal flooding during storms. Thus, models that can efficiently predict dune erosion are critical for coastal zone management and early warning systems. Here we develop such a model for the Dutch coast based on machine learning techniques, allowing for dune erosion estimations in a matter of seconds relative to available computationally expensive models. Validation of the model against benchmark data and observations shows good agreement.
Altmetrics
Final-revised paper
Preprint