PREDICTING DUNE EROSION WITH COMBINED PROCESS-BASED AND MULTIVARIATE STATISTICAL MODELS

  • Thomas Wahl
  • Nathaniel G. Plant
  • Joseph W. Long
  • Victor Malagon Santos

Abstract

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Storm erosion of dunes, which often protect coastal communities and built infrastructure from flooding, poses a major risk. Dune erosion is also a challenge to analyze and predict, due to the complex processes involved and the computational costs that come with it. Here, we introduce a novel framework that combines advanced statistical techniques and a process-based numerical model to efficiently simulate storm-induced dune erosion.

References

Wahl, T., Plant, N.G., Long, J.W. (2016). Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico, Journal of Geophysical Research Oceans, 121, 3029-3043.

Published
2018-12-30
How to Cite
Wahl, T., Plant, N. G., Long, J. W., & Santos, V. M. (2018). PREDICTING DUNE EROSION WITH COMBINED PROCESS-BASED AND MULTIVARIATE STATISTICAL MODELS. Coastal Engineering Proceedings, 1(36), sediment.70. https://doi.org/10.9753/icce.v36.sediment.70