Bibliographic Details
| Title: |
Storm Impacts on Mineral Mass Accumulation Rates of Coastal Marshes. |
| Authors: |
Cortese, L.1 (AUTHOR) lucacort@bu.edu, Zhang, X.1 (AUTHOR), Simard, Marc2 (AUTHOR), Fagherazzi, S.1 (AUTHOR) |
| Source: |
Journal of Geophysical Research. Earth Surface. Mar2024, Vol. 129 Issue 3, p1-18. 18p. |
| Subject Terms: |
*Storms, *Salt marshes, *Marshes, *Sedimentation & deposition, *Tidal flats, *Absolute sea level change, *Coastal sediments, *Storm surges |
| Geographic Terms: |
Louisiana |
| 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 (highest R2) 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. Plain Language Summary: To offset sea‐level rise and sinking land, coastal marshes need to increase their elevation through sediment deposition. Thus, sediment availability, which controls the deposition, represents a vital parameter to evaluate the resilience of these delicate ecosystems. The Terrebonne basin (Louisiana, USA) is an example of a coastal area isolated from sediment sources that is rapidly losing land. Here, storms are a vital process because they can resuspend and transport significant volumes of sediment from the ocean and coastal areas to the marshes. However, quantifying their contribution is not trivial because of their intermittent and variable nature. In general, the more intense the storm, the lower its frequency. We simulated 12 storms and calculated the amount of sediment deposited by each of them. Then, we combined deposition with frequency and found that storms bringing the largest volume of sediments are not the most intense ones, but those that balance intensity with frequency. Using a combination of our simulations, we derived long‐term deposition rates (i.e., how much sediment is deposited on a yearly basis), which allow us to identify areas where marshes are resilient. This study shows that storms are fundamental for the survival of coastal marshes with limited sediment supply. Key Points: A 2D depth averaged numerical model is coupled with a wave model to simulate sediment deposition by storms in Terrebonne Bay (Louisiana, USA)In Terrebonne Bay, storms with a return time of about 2 years have the highest geomorphological impactWe use a novel method that combines simulations of storms of different intensity and frequency to derive inorganic mass accumulation rates [ABSTRACT FROM AUTHOR] |
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| Database: |
GreenFILE |