Measuring and modelling nearshore recovery of an eroded beach in Lake Michigan, USA
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Measuring and modelling nearshore recovery of an eroded beach in Lake Michigan, USA

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  • Journal Title:
    Journal of Great Lakes Research
  • Description:
    Erosion by storms and high-water levels impacts large enclosed basins; however there have been few attempts to numerically model cumulative impacts in large lakes. Antecedent morphology is a large determinant of coastal sensitivity to storms, so capturing the beach recovery is important for overall vulnerability assessment. To study beach recovery, we apply the numerical model XBeach to simulate a period of low to moderate wave energy when beach recovery typically occurs. Surveys were conducted one month apart during summer of 2020 on the west coast of Lake Michigan and used to initiate model runs and evaluate model performance. XBeach was used to propagate offshore wave conditions from a Great Lakes Coastal Forecasting System (GLCFS) node ∼1 km offshore into the nearshore, and results were compared to measurements from a nearshore pressure sensor. We tested for the optimal value of the asymmetry/skewness parameter (facua) for model-data convergence. We evaluated model skill using a Mean Square Error Skill Score (MSESS) and a decomposition. In our repeat surveys we observed slight landward migration of longshore bars and the initiation of bar welding to the shoreline but, overall, changes in bathymetry were small. We found that XBeach transforms offshore waves well and sediment transport volume was accurately predicted by the model. However, XBeach did not capture the morphologic evolution under low energy conditions, preventing simulation of beach recovery. Overall, higher values of facua resulted in improved skill scores and modeled nearshore morphology that was more similar to the morphology measured in our surveys.
  • Source:
    Journal of Great Lakes Research, 48(3), 633-644
  • ISSN:
    0380-1330
  • Publisher:
  • Document Type:
  • Rights Information:
    Accepted Manuscript
  • Rights Statement:
    This manuscript is made available under the Elsevier user license https://www.elsevier.com/open-access/userlicense/1.0/
  • Compliance:
    Submitted
  • Main Document Checksum:
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