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Abstract Storm surge has the potential to significantly increase suspended sediment flux to microtidal marshes. However, the overall effects of storm surge on microtidal marsh deposition have not been well quantified, with most modeling studies focusing on regular (astronomical) tidal flooding. Here we applied the Delft3D model to a microtidal bay‐marsh complex in Hog Bay, Virginia to quantify the contributions of storm surge to marsh deposition. We validated the model using spatially distributed hydrodynamic and suspended sediment data collected from the site and ran model simulations under different storm surge conditions with/without storm‐driven water level changes. Our results show that episodic storm surge events occurred 5% of the time at our study site, but contributed 40% of marsh deposition during 2009–2020. Our simulations illustrate that while wind‐driven waves control sediment resuspension on tidal flats, marsh deposition during storms was largely determined by tidal inundation associated with storm‐driven water levels. A moderate storm surge event can double sediment flux to most marshes around the bay and deliver more sediment to the marsh interior compared to simulations that include wind waves but not storm surge variations in water levels. Simulations of bay and marsh response to different storm surge events with varying magnitude of storm surge intensity reveal that total marsh deposition around the bay increased linearly with storm surge intensity, suggesting that future changes to storm magnitude and/or frequency would have significant implications for sediment supply to marshes at our study site.
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Storm Impacts on Mineral Mass Accumulation Rates of Coastal Marshes
Abstract Coastal marsh survival may be compromised by sea‐level rise, limited sediment supply, and subsidence. Storms represent a fundamental forcing for sediment accumulation in starving marshes because they resuspend bottom material in channels and tidal flats and transport it to the marsh surface. However, it is unrealistic to simulate at high resolution all storms that occurred in the past decades to obtain reliable sediment accumulation rates. Similarly, it is difficult to cover all possible combinations of water levels and wind conditions in fictional scenarios. Thus, we developed a new method that derives long‐term deposition rates from short‐term deposition generated by a finite number of storms. Twelve storms with different intensity and frequency were selected in Terrebonne Bay, Louisiana, USA and simulated with the 2D Delft3D‐FLOW model coupled with the Simulating Waves Nearshore (SWAN) module. Storm impact was analyzed in terms of geomorphic work, namely the product of deposition and frequency. To derive the long‐term inorganic mass accumulation rates, the new method generates every possible combination of the 12 chosen storms and uses a linear model to fit modeled inorganic deposition with measured inorganic mass accumulation rates. The linear model with the best fit (highestR2) was used to derive a map of inorganic mass accumulation rates. Results show that a storm with 1.7 ± 1.6 years return period provides the largest geomorphic work, suggesting that the most impactful storms are those that balance intensity with frequency. Model results show higher accumulation rates in marshes facing open areas where waves can develop and resuspend sediments. This method has the advantage of considering only a few real scenarios and can be applied in any marsh‐bay system.
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- Award ID(s):
- 2224608
- PAR ID:
- 10499664
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Earth Surface
- Volume:
- 129
- Issue:
- 3
- ISSN:
- 2169-9003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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