Does vegetation reduce the magnitude of dune erosion induced by storms?
Óscar Ferreira, Susana Costas e Juan Hervas ganharam mais um projeto, desta vez aprovado pela ESA – European Spatial Agency.
Este estudo propõe uma abordagem pioneira para avaliar os efeitos benéficos da vegetação na erosão das dunas em condições reais e o papel desempenhado pelas características da vegetação (densidade de cobertura e habitats das dunas). Além disso, fornecerá uma visão empírica aos gestores costeiros ao considerarem a vegetação como uma forma de proteção das dunas. Além disso, vários mapas georreferenciados serão exibidos da cobertura vegetal e serão desenvolvidas comunidades para todo o sistema de dunas da Ria Formosa, capturando os efeitos sazonais.
Many low-elevation coastal areas are under the threat of flooding and erosion. Among different approaches to protect coastal communities from these hazards, dune recovery and enhancement is gaining popularity worldwide since these systems function as the first barrier against the impact of storms, while they can adjust naturally to new environmental conditions and do not alter the surrounding ecosystems. Hence, its relevance for coastal protection has led to an extensive research regarding sandy coasts and dune system response to storm events. However, some components of these coastal features, like the vegetation cover, have not been generally included when assessing storm impacts. Previous studies have explored the different mechanisms through which vegetation may contribute to reduce erosion, for example, by reducing surface flow velocities or enhancing sediment cohesion. While these studies demonstrated the beneficial vegetation effects on dune preservation, their experiments (performed under controlled conditions) present certain limitations, and conclusions from those studies cannot be easily transferred to real dune systems. For instance, those studies did not consider the maturity of the dune systems, the spatial plant variability and did not fully reproduce the root system. Also, they don’t provide a clear physical explanation behind the mechanisms through which vegetation reduces dune erosion.
To better understand this phenomenon, we aim to design a methodology that utilizes remote sensing technology to investigate the effect of the vegetation in reducing dune erosion at a regional scale during a real storm event. This methodology will use data from the Earth Observation Third Party Missions and will be applied on a barrier island system at the Ria Formosa (Portugal) hit by the winter storm Emma in 2018. This regional scale approach reduces uncertainties and enhances the robustness of our findings by increasing the amount of available information against previous studies mainly focused on a very limited spatial scale and flow conditions. Consequently, we plan to evaluate the magnitude of erosion and its alongshore variability, in particular, dune retreat caused by the impact of this storm, by mapping the seaward limit of the dune vegetation. The vegetation will be mapped using data collected by WorldView-2, whose high-spatial resolution and multispectral nature will allow us to map different plant communities and to estimate surface plant density. The mapping of the vegetation cover will be carried out by calculating the Normalized Difference Vegetation Index (NDVI) at each pixel, which informs about the greenness of the surface. This method relates the surface reflectance at the red and the near infrared part of the electromagnetic spectrum. By using the NDVI, the mapping of the vegetation along the Ria Formosa barrier islands will be estimated before (last week of February of 2018) and after (second week of March of 2018) the passage of the storm. In situ observations carried out by the investigators of this project revealed that dune retreat was lower than 5 meters, and hence, high-resolution satellite imagery is required instead of lower resolution open resources (Landsat 8 or Sentinel). Additionally, the dynamics and seasonal cycles of the vegetation will be assessed by a monitoring plan carried out using imagery from May of 2017, October of 2017 and February of 2018.