Response of a vulnerable barrier island to multi-year storm impacts: LiDAR-data-inferred morphodynamic changes on Ship Island, Mississippi, USA

Landcover-based detection of rapid impacts of extreme storm on coastal landscape

On September 24, 2022, Post-Tropical Hurricane Fiona made landfall in Atlantic Canada and caused unprecedented damages to the coastal communities and ecosystems therein. The aftermath triggered local government and communities in Prince Edward Island (PEI), Canada to rethink current policies and practices for coastal protection in the context of climate change. This historic hazard represents the escalating frequency and intensity of extreme weather events that globally threaten coastal regions, accelerating coastal erosion and endangering communities. This study employs landcover-based detection to assess rapid storm impact of Fiona on coastline of PEI using Sentinel-2 satellite images, to gauge the efficacy of landcover-based detection and quantify storm-induced coastal environmental changes. Our results indicate that, following Fiona, over 51 km2 coastal land loss due to the erosion at beach foreshore and inundation at tidal flat, and over 11 km2 sand dune loss mainly on the PEI north shore. This constitutes a 3.5 % loss of coastal land resources within the 1798 km2 PEI coastal zone. Fiona also caused over 194 km2 area in coastal buffer zone showed temporal fluid-mud from the eroded sediments of sand dunes, cliffs, and tidal flats, suggesting the significant sediment loss from vertical structures in addition to the direct retreat. The landcover-based method can be regarded as a valuable tool for the storm impacts on coastal environments. Based on the coastal change pattern, more sustainable coastal protection and adaptation measures should be developed, focusing on reducing hydrodynamic intensity and improving erosion capacity, with consideration of the increasing likelihood of more intense and frequent storm events in a warming climate.

Long-term washover fan accretion on a transgressive barrier island challenges the assumption that paleotempestites represent individual tropical cyclones

Barrier island overwash occurs when the elevation of wave runup exceeds the dune crest and induces landward transport of sediment across a barrier island and deposition of a washover deposit. Washover deposition is generally attributed to major storms, is important for the maintenance of barrier island resilience to sea-level rise and is used to extend hurricane records beyond historical accounts by reconstructing the frequency and extent of washover deposits preserved in the sedimentary record. Here, we present a high-fidelity 3-year record of washover evolution and overwash at a transgressive barrier island site. During the first year after establishment, washover volume and area increased 1595% and 197%, respectively, from at least monthly overwash. Most of the washover accretion resulted from the site morphology having a low resistance to overwash, as opposed to being directly impacted by major storms. Washover deposits can accrete landward over multi-year time scales in the absence of large storms; therefore, paleotempestites can be more complex than single event beds.

Spatial Variability of Coastal Foredune Evolution, Part A: Timescales of Months to Years

Coastal foredunes are topographically high features that can reduce vulnerability to storm-related flooding hazards. While the dominant aeolian, hydrodynamic, and ecological processes leading to dune growth and erosion are fairly well-understood, predictive capabilities of spatial variations in dune evolution on management and engineering timescales (days to years) remain relatively poor. In this work, monthly high-resolution terrestrial lidar scans were used to quantify topographic and vegetation changes over a 2.5 year period along a micro-tidal intermediate beach and dune. Three-dimensional topographic changes to the coastal landscape were used to investigate the relative importance of environmental, ecological, and morphological factors in controlling spatial and temporal variability in foredune growth patterns at two 50 m alongshore stretches of coast. Despite being separated by only 700 m in the alongshore, the two sites evolved differently over the study period. The northern dune retreated landward and lost volume, whereas the southern dune prograded and vertically accreted. At the start of and throughout the study, the erosive site had steeper foredune faces with less overall vegetation coverage, and dune growth varied spatially and temporally within the site. Deposition occurred mainly at or behind the vegetated dune crest and primarily during periods with strong, oblique winds (>∼45 ∘ from shore normal). Minimal deposition was observed on the mostly bare-sand dune face, except where patchy vegetation was present. In contrast, the response of the accretive site was more spatially uniform, with growth focused on the heavily vegetated foredune face. The largest differences in dune response between the two sections of dunes occurred during the fall storm season, when each of the systems’ geomorphic and ecological properties modulated dune growth patterns. These findings highlight the complex eco-morphodynamic feedback controlling dune dynamics across a range of spatial scales.

Low-Cost UAV for High-Resolution and Large-Scale Coastal Dune Change Monitoring Using Photogrammetry

In this paper, coastal dune data are collected at Truc Vert, SW France, using photogrammetry via Unmanned Aerial Vehicles (UAVs). A low-cost GoPro-equipped DJI Phantom 2 quadcopter and a 20 MPix camera-equipped DJI Phantom 4 Pro quadcopter UAVs were used to remotely sense the coastal dune morphology over large spatial scales (4 km alongshore, i.e., approximately 1 km2 of beach-dune system), within a short time (less than 2 h of flight). The primary objective of this paper is to propose a low-cost and replicable approach which, combined with simple and efficient permanent Ground Control Point (GCP) set-up, can be applied to routinely survey upper beach and coastal dune morphological changes at high frequency (after each storm) and high resolution (0.1 m). Results show that a high-resolution and accurate Digital Surface Model (DSM) can be inferred with both UAVs if enough permanent GCPs are implemented. The more recent DJI Phantom 4 gives substantially more accurate DSM with a root-mean-square vertical error and bias of 0.05 m and −0.03 m, respectively, while the DSM inferred from the DJI Phantom 2 still largely meets the standard for coastal monitoring. The automatic flight plan procedure allows replicable surveys to address large-scale morphological evolution at high temporal resolution (e.g., weeks, months), providing unprecedented insight into the coastal dune evolution driven by marine and aeolian processes. The detailed morphological evolution of a 4-km section of beach-dune system is analyzed over a 6-month winter period, showing highly alongshore variable beach and incipient foredune wave-driven erosion, together with wind-driven inland migration of the established foredune by a few meters, and alongshore-variable sand deposition on the grey dune. In a context of widespread erosion, this photogrammetry approach via low-cost flexible and lightweight UAVs is well adapted for coastal research groups and coastal dune management stakeholders, including in developing countries where data are lacking.

Evaluation of the Accuracy of Bathymetry on the Nearshore Coastlines of Western Korea from Satellite Altimetry, Multi-Beam, and Airborne Bathymetric LiDAR

Bathymetric mapping is traditionally implemented using shipborne single-beam, multi-beam, and side-scan sonar sensors. Procuring bathymetric data near coastlines using shipborne sensors is difficult, however, this type of data is important for maritime safety, marine territory management, climate change monitoring, and disaster preparedness. In recent years, the bathymetric light detection and ranging (LiDAR) technique has been tried to get seamless geospatial data from land to submarine topography. This paper evaluated the accuracy of bathymetry generated near coastlines from satellite altimetry-derived gravity anomalies and multi-beam bathymetry using a tuning density contrast of 5000 kg/m³ determined by the gravity-geologic method. Comparing with the predicted bathymetry of using only multi-beam depth data, 78% root mean square error from both multi-beam and airborne bathymetric LiDAR was improved in shallow waters of nearshore coastlines of the western Korea. As a result, the satellite-derived bathymetry estimated from the multi-beam and the airborne bathymetric LiDAR was enhanced to the accuracy of about 0.2 m.