ORCID
- Gerd Masselink: 0000-0001-6079-7611
- Timothy Scott: 0000-0002-3357-7485
Abstract
Equilibrium shoreline change models with calibrated, time-invariant free parameters have demonstrated good skill in hindcasting shoreline evolution at sites dominated by cross-shore sediment transport. However, their performance can be biased by the specific conditions present during the calibration period. In this study, a dual parameter-state ensemble Kalman filter (EnKF) was applied to track non-stationarity in model free parameters at three sites along the west coast of Europe. Introducing time-varying parameters did not substantially improve performance relative to an already well-calibrated stationary model. Model skill improvement occurred mainly during the EnKF correction step, highlighting the potential of real-time data assimilation for maintaining model stability. Although variations in model parameters may compensate for unresolved processes and should be interpreted cautiously, incorporating climate-driven, time-varying parameters could improve extreme-event predictions at seasonally dominated sites and enhance overall model performance in regions influenced by complex, multimodal wave climates.
DOI Link
Publication Date
2025-12-21
Publication Title
Earth Surface Processes and Landforms
Volume
50
Issue
15
ISSN
0197-9337
Acceptance Date
2025-11-28
Deposit Date
2026-03-03
Additional Links
Keywords
data assimilation, ensemble Kalman filter, non-stationary parameters, shoreline modelling, wave climate
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Recommended Citation
Azorakos, G., Castelle, B., Idier, D., Marieu, V., Ibaceta, R., Splinter, K., Bertin, S., Masselink, G., & Scott, T. (2025) 'Investigating the potential of time-varying free parameters in equilibrium shoreline change models through data assimilation', Earth Surface Processes and Landforms, 50(15). Available at: 10.1002/esp.70221
