Performance evaluation of wave input reduction techniques for modeling inter-annual sandbar dynamics

Performance evaluation of wave input reduction techniques for modeling inter-annual sandbar dynamics

de Queiroz, Bruna (Deltares)
Scheel, F. (Deltares)
Caires, Sofia (Deltares)
Walstra, D.J.R. (TU Delft Coastal Engineering; Deltares)
Olij, Derrick (PwC)
Yoo, Jeseon (Korea Institute of Ocean Science and Technology)
Reniers, A.J.H.M. (TU Delft Environmental Fluid Mechanics)
de Boer, W.P. (TU Delft Rivers, Ports, Waterways and Dredging Engineering; Deltares)

2019

In process-based numerical models, reducing the amount of input parameters, known as input reduction (IR), is often required to reduce the computational effort of these models and to enable long-term, ensemble predictions. Currently, a comprehensive performance assessment of IR-methods is lacking, which hampers guidance on selecting suitable methods and settings in practice. In this study, we investigated the performance of 10 IR-methods and 36 subvariants for wave climate reduction to model the inter-annual evolution of nearshore bars. The performance of reduced wave climates is evaluated by means of a brute force simulation based on the full climate. Additionally, we tested how the performance is affected by the number of wave conditions, sequencing, and duration of the reduced wave climate. We found that the Sediment Transport Bins method is the most promising method. Furthermore, we found that the resolution in directional space is more important for the performance than the resolution in wave height. The results show that a reduced wave climate with fewer conditions applied on a smaller timescale performs better in terms of morphology than a climate with more conditions applied on a longer timescale. The findings of this study can be applied as initial guidelines for selecting input reduction methods at other locations, in other models, or for other domains.

Input reduction
Markov Chain
Monte Carlo
Morphodynamics
Process-based modeling
Sandbars
Sequencing
Wave climate

http://resolver.tudelft.nl/uuid:de593a28-a273-4e73-ac03-49228fe3af8c

https://doi.org/10.3390/jmse7050148

2077-1312

Journal of Marine Science and Engineering, 7 (5)

Institutional Repository

journal article

© 2019 Bruna de Queiroz, F. Scheel, Sofia Caires, D.J.R. Walstra, Derrick Olij, Jeseon Yoo, A.J.H.M. Reniers, W.P. de Boer