Montano, Jenifer, Coco, Giovanni, Antolinez, J A A, Beuzen, T, Bryan, Karin, Cagigal, L, Castelle, Bruno, Davidson, Mark, Goldstein, E B, Vega, R I, Idier, D, Ludka, B C, Ansari, S M, Mendez, Fernando, Murray, Brad, Plant, Nathanial, Robinet, A, Rueda, A, Senechal, N, Simmons, J A, Splinter, K D, Stephens, S, Townend, Ian, Vitousek, S and Vos, K (2019) Shorecasts: a blind-test of shoreline models. Wang, Ping, Rosati, Julie D. and Vallee, Mathieu (eds.) In Coastal Sediments 2019: Proceedings of the 9th International Conference. World Scientific. pp. 627-631 . (doi:10.1142/9789811204487_0055).
Abstract
Predictions of shoreline change are of great societal importance, but models tend to be tested and tuned for the specific site of interest. To overcome this issue and test the ability of numerical models to simulate shoreline change over the medium scale (order of years) we have organized a non-competitive competition where participants were given data to train their model (1999–2014) and data to predict seasonal to inter-annual future changes (2014–2017). Participants were shown the observed shoreline changes only after submission of their modelling results. Overall, 19 numerical models were tested, the vast majority falling in the broad categories of “hybrid models” or “machine learning”. Models were able to reproduce the mean characteristics of shoreline change but often failed to reproduce the observed rapid changes induced by storms.
This record has no associated files available for download.
More information
Identifiers
Catalogue record
Export record
Altmetrics
Contributors
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.