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14 results for “coastal erosion”
Pan‐Arctic Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea‐Level Rise, and Permafrost Thaw
<p>The datasets are issued from the combination of records of the ESA EO4PAC and Permafrost_cci and HORIZON 2020 Nunataryuk projects. The EO4PAC project aimed to develop a new generation of geospatial products for the observation of permafrost and associated changes from space with a special focus on the coastal Arctic. Four components were considered in the creation of the datasets:</p> <p>(1) Landsat-7/8 for the detection of coastline changes over the 2000-2020 period (Tanguy et al., 2024).</p> <p>(2) Sentinel-1/2 for the detection and mapping of coastal infrastructures (Bartsch et al. 2024), updating Wang et al. (2021).</p> <p>(3) Permafrost_cci timeseries for retrieval of trends of ground temperature and active layer thickness for the 2000-2020 period (Obu et al. 2021a,b), evaluated based on Martin et al (2023) and CALM et al. (2024).</p> <p>(4) Sea level rise by 2100 (Garner et al. 2022).</p> <p>The respective output provides a consistent mapping of settlements along arctic and permafrost-dominated coasts (2), and associated coastline and permafrost conditions changes during the last 20 years (1, 3). Combined together, an assessment of Arctic infrastructures at risk due to permafrost change (GT, ALT) and coastline erosion was possible, the latter with projections for the years 2030, 2050 and 2100.<a name="_heading=h.jkogrw14ymt"></a></p> <p>References</p> <p>Bartsch, Annett, Pointner, Georg, & Nitze, Ingmar. (2023). Sentinel-1/2 derived Arctic Coastal Human Impact dataset (SACHI) (Version 2) [Data set]. Zenodo. https://zenodo.org/records/10160636.</p> <p>CALM, GTN-P, Wieczorek, M., Heim, B., Streletskiy, D., Bartsch, A., 2024, GTN-P CALM: 34 years of Active Layer Thickness (ALT) across latitudinal and elevational gradients in the Northern Hemisphere [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.972777</p> <p>Garner, G. G., Hermans, T., Kopp, R. E., Slangen, A. B. A., Edwards, T. L., Levermann, A., et al. (2022). IPCC AR6 sea level projections [Dataset]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6382554">https://doi.org/10.5281/zenodo.6382554</a></p> <p>Martin, Julia; Boike, Julia; Chadburn, Sarah; Zwieback, Simon; Anselm, Norbert; Goldau, Maybrit; Hammar, Jennika; Abramova, Ekatarina N; Lisovski, Simeon; Coulombe, Stéphanie; Dakin, Brampton; Wilcox, Evan James; Giamberini, Mariasilvia; Rader, Fieke; Suominen, Otso; Rudd, Daniel Alexander; Mastepanov, Mikhail; Young, Amanda (2023): T-MOSAiC 2021 myThaw data set [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.956039, In: Boike, Julia; Hammar, Jennika; Goldau, Maybrit; Miesner, Frederieke; Anselm, Norbert (2024): Circumarctic seasonal measurements of permafrost parameters (thaw depth, snow depth, vegetation and tree height, water level and soil properties) [dataset publication series]. PANGAEA, https://doi.org/10.1594/PANGAEA.971787</p> <p>Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G., Irrgang, A., Kääb, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T., Wegmüller, U., Wieczorek, M., and Wiesmann, A.: ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0, CEDA, 2021. <a href="https://doi.org/10.5285/29C4AF5986BA4B9C8A3CFC33CA8D7C85">https://doi.org/10.5285/29C4AF5986BA4B9C8A3CFC33CA8D7C85</a></p> <p>Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G., Irrgang, A., Kääb, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T., Wegmüller, U., Wieczorek, M., and Wiesmann, A.: ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0, CEDA, 2021. <a href="https://doi.org/10.5285/29C4AF5986BA4B9C8A3CFC33CA8D7C85">https://doi.org/10.5285/29C4AF5986BA4B9C8A3CFC33CA8D7C85</a></p> <p>Tanguy, R., Bartsch, A., Nitze, I., Irrgang, A., Petzold, P., Widhalm, B., von Baeckmann, C., Boike, J., Martin, J., Efimova, A., Vieira, G., Whalen, D., Heim, B., Wieszorek, M., Grosse, G.: Pan‐Arctic Assessment of Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea‐Level Rise, and Permafrost Thaw, Earth’s Future, 10.1029/2024EF005013.</p> <p>Wang, S., Ramage, J., Bartsch, A., & Efimova, A. (2021). Population in the Arctic Circumpolar Permafrost Region at settlement level (Version 2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.4529610" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.4529610</a></p>
Modelling NBSs for coastal erosion and marine flooding: the Emilia-Romagna case studies
<p>The study was conducted in the context of the OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM) project which is an H2020 project which aims at providing tools and methodologies for the assessment of NBS efficiency around the world. Two NBs were tested via modelling simulations on the Bellocchio Beach at Lido di Spina (Italy) located in the northern part of the Emilia-Romagna coast (northern Adriatic Sea): an artificial dune built with natural materials and a marine seagrass meadow.</p> <p>The artificial dune is an engineered structure that will mimic the functioning of natural dunes. Its aims are reducing both natural dune erosion and flooding in adjacent coastal lowlands. It consists of a barrier between the sea and land, in a similar way to a seawall. Unlike the latter, the NBS are ‘dynamic’, i.e. the dune/beach system interacts a great deal and is constantly undergoing small adjustments in response to changes in wind and wave climate or sea level. Its construction involves the placement of sediment from dredged sources on the beach and it will be reinforced with a structure composed of biodegradable material. Different typologies of experimental solutions are foreseen.</p> <p>The second NBS consists of an alongshore seagrass belt located in front of the coastal area. It was investigated as a potential mechanism for wave amplitude reduction. Among the few species that can live in the northern Adriatic Sea, Zostera Marina was chosen due to its ability to live in a marine environment influenced by freshwaters. A more detailed description can be found in (Pillai et al., 2021).</p> <p>The numerical model chain, specifically developed for the study, consists of an Ocean Circulation model, so-called SHYFEM (Umgiesser et al., 2004), a wave model, so-called WWIII (Alves and Ardhuin, 2016), and a morphological model, so-called XBeach (Roelvink et al., 2009). Ten years of XBeach simulations have been executed to simulate the morphological impacts on the coastal strip for the present (2010-19) and future climate (2040-49). For each 10 years period, four scenarios were simulated: the baseline scenario without NBS (baseline_run), the scenario with the dune (dune_run), the scenario with the seagrass effect (seagrass_run) and the scenario with the two NBS integration (dune_seagrass_run).XBeach was forced with sea level and wave time series predicted by the SHYFEM and WWIII models respectively.</p> <p>The model domain consists in a curvilinear structured grid of about 3.2 km (longshore) x 2.8 km (cross-shore) covering the coastal stretch of Bellocchio beach at Lido di Spina (Italy) and extends seaward up to about 10 m depth.</p> <p>The performance of the NBSs and their impact on coastal erosion and marine flooding were investigated. For both present and future scenarios (201-2019 and 2040-2049), the reduction in wave intensity obtained with the seagrass provided greater benefits in terms of erosion mitigation and flood reduction. The analysis highlighted the limited scale of the dune intervention, in particular under present conditions, highlighting that the longer the artificial dune implemented, the larger the beach and dune area protected. For the future scenarios, the results are still significant and even small projects are expected to help in mitigating coastal erosion and marine flooding.</p> <p>For long-period simulations, no relevant improvements in reducing beach erosion was observed when the artificial dune was combined with the seagrass meadows with respect to the seagrass effects only. Instead, a dominant increase in sea levels will probably highlight the dune functions in hindering the marine ingression into the lagoon area behind and the consequent sediment redistribution.</p> <p>This dataset consists of XBeach model results, mainly:</p> <ul> <li>Morphological evolution of the coastal bottom at Bellocchio beach (Lido di Spina, Italy) in terms of initial and final bed levels, for the current (201-2019) and the future (2040-2049) scenarios. Results are available for the four NBS scenarios described above (and detailed in the Presentation.pdf)</li> <li>Maximum flood depth, defined as the non-simultaneous maximum water depth on the beach domain of Bellocchio (Lido di Spina, Italy) for the current (201-2019) and the future (2040-2049) scenarios. Results are available for the four NBS scenarios described above (and detailed in the Presentation.pdf) </li> <li>Erosion-deposition maps for the current (201-2019) and the future (2040-2049) scenarios. Results are available for the four NBS scenarios described above (and detailed in the Presentation.pdf).</li> </ul>
Monitoring NBS for coastal erosion and marine flooding: the Emilia-Romagna case study
<p>The study was conducted in the context of the OPERANDUM project which is an H2020 project which aims at providing tools and methodologies for the assessment of NBS efficiency around the world. As NBS will be tested an artificial dune built with natural materials. </p> <p>The artificial dune is an engineered structure that will mimic the functioning of natural dunes. Its aims are reducing both natural dune erosion and flooding in adjacent coastal lowlands. It consists of a barrier between the sea and land, in a similar way to a seawall. Unlike the latter, the NBS are ‘dynamic’, i.e. the dune/beach system interacts a great deal and is constantly undergoing small adjustments in response to changes in wind and wave climate or sea level. Its construction involves the placement of sediment from dredged sources on the beach and it will be reinforced with a structure composed of biodegradable material. Different typologies of experimental solutions are foreseen.</p> <p>The Bellocchio Beach at Lido di Spina (Italy) was initially chosen for the study, however the Volano beach was selected as the new study area because of the strong erosion caused by an intense storm event in December 2020 at Bellocchio. The dune was built on the Volano beach and monitoring surveys were carried out on this new site. </p> <p>A morphological monitoring aimed to assess the beach evolution and the performance of the NBS were performed. Monitoring of morphology evolution of shoreline and inland area provide information about impact of the NBS on coastal erosion. Furthermore, the changes in the form of the work give information about the resistance of the NBS to wave attacks. Sedimentological campaigns have been planned in order to provide information regarding the texture of the sediments present in the area detected and possibly highlight changes after the construction of the dune.</p> <p>Three monitoring campaigns were carried out before, immediately after and six months later the construction of the dune (January, May and October 2022). All data were analysed to assess local coastal dynamics and NBS evolution. </p> <p>The monitoring consisted of: </p> <ul> <li> <p>topographic and bathymetric surveys (GNSS and multibeam/singlebeam echosounder) to generate DTMs of the entire area (10 m cell size); </p> </li> <li> <p>aerial photogrammetric surveys by UAV for the production of orthophotos and high resolutions DTMs of the emerged beach (1m cell size) and of the dune area (0.2 m cell size); </p> </li> <li> <p>sediment sampling and grain size analysis. </p> </li> </ul> <p>Surveys show that morphological and sedimentological changes are determined mostly by anthropic actions to the beach and seabed maintenance (artificial winter banks and Sacca di Goro channel). </p> <p>Regarding the dune area no significant changes in morphology were observed due to the limited period between the surveys. Appreciable signals were detected, such as the natural recolonization by pioneer plant species and the slight sand accumulation on the dune foot.</p> <p>This dataset consists of data related to monitoring activities. </p>
Victorian Coastal Monitoring Program: (1) VCMP Sites; (2) VCMP Coastal Erosion Indicators
<p>This dataset was produced by the Victorian Coastal Monitoring Program (VCMP), Department of Energy, Environment and Climate Action, Victoria State Government, Australia.</p><p><a href="https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program">https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program</a> </p><p><a href="https://www.marineandcoasts.vic.gov.au/__data/assets/pdf_file/0023/625352/VCMP_Erosion-Indicators_April_2023.pdf">https://www.marineandcoasts.vic.gov.au/__data/assets/pdf_file/0023/625352/VCMP_Erosion-Indicators_April_2023.pdf</a></p><p>[ADD LINK TO VCMP SITES METADATA REPORT - ONCE PUBLISHED TO VCMP WEBSITE]</p><p>Products include: </p><p>(1) Complete processed shorelines dataset ('VCMP Sites'), including drone and satellite data, with transects, shorelines, time series, and cross-sections for drone surveys</p><p>(2) Summary outputs ('VCMP Coastal Erosion Indicators'), including the Erosion Warning Indicator (<i>EWI</i>) summary statistics and Erosion Hotspot Detector (<i>EHD</i>) outputs. </p><p>Survey data in this repository were updated to the start of 2023. </p><p>Regularly updated outputs for all VCMP products, including pre-processed VCMP drone data (digital surface models and orthomosaics) can be accessed through the Victorian government (contact <a href="mailto:vcmp@delwp.vic.gov.au">vcmp@delwp.vic.gov.au</a>; <a href="https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program">https://www.marineandcoasts.vic.gov.au/marine-and-coastal-knowledge/victorian-coastal-monitoring-program</a>). </p><p>'VCMP Sites' and 'VCMP Coastal Erosion Indicator' outputs and a wide array of marine and coastal data are viewable through the decision support portal CoastKit (<a href="https://mapshare.vic.gov.au/coastkit/">https://mapshare.vic.gov.au/coastkit/</a>). </p><p>Select outputs are also downloadable in spatial file format through DataShare Victoria (<a href="https://datashare.maps.vic.gov.au/search?q=vcmp">https://datashare.maps.vic.gov.au/search?q=vcmp</a>).</p>
Data for "Neglecting the coupled effect of coastal flooding and erosion can lead to spurious projections and maladaptation"
<p>Data for the reproduction of the figures in the manuscript "Neglecting the coupled effect of coastal flooding and erosion can lead to spurious projections and maladaptation".</p>
Fig. 5 in Organismal Responses to Coastal Acidification Informed by Interrelating Erosion, Roundness and Growth of Gastropod Shells.
Fig. 5. Relationships for shell growth rate, shell roundness, and erosion index.. (A) Shell growth rate and roundness measured directly for snails from the secondary population. (B) Shell roundness plotted against erosion index for the primary population. (C) Predicted growth rate plotted against the erosion index. Regression equations and significant differences are given in the Materials and Methods section. Dashed lines represent 95% CI.
Fig. 4 in Organismal Responses to Coastal Acidification Informed by Interrelating Erosion, Roundness and Growth of Gastropod Shells.
Fig. 4. (A–B) Relationships for shell growth rate and shell size based on the secondary data set. (C) Erosion time (ET) as a function of shell size (SL), and (D) comparison of standardized erosion time (SET) between the acidified (EM) and non-acidified (UB) sites using the primary data sets. Dashed lines represent 95% CI. Red symbols indicate snails collected from the acidified site and black symbols from the non-acidified site.
Fig. 3 in Organismal Responses to Coastal Acidification Informed by Interrelating Erosion, Roundness and Growth of Gastropod Shells.
Fig. 3. (A–C) Relationships between total suture length, eroded suture length and shell length for snails from acidified (EM, red) and reference (UBD, black) sites. (D–F) Relationships between erosion index (EI), shell erosion rank (SER), and shell length (SL). Mean values are indicated by large circles. Regression equations and significant differences are given in the Materials and Methods section.
Fig. 1 in Organismal Responses to Coastal Acidification Informed by Interrelating Erosion, Roundness and Growth of Gastropod Shells.
Fig. 1. Methods for determining shell roundness, shell dissolution and growth rate. (A) Shell roundness was assessed from shell width (SW)/ shell length (SL). Shell erosion rank (SER) was scored using eight segments, where moderate erosion (ridges still observed) covered> 50% of the numerically greatest segment. The vertical line through the shell bisects the apical angle. By forming the apical angle we could measure projected SL (the intrinsic responder), as the actual SL is influenced by extrinsic apical dissolution in acidified water. (B) Comparison of SER (upper) and Erosion Index (EI) methods (lower). EI was calculated from the spiral suture length of the eroded shell divided by the total planospiral shell spiral length (R/ (Y and R)) using severe erosion (ridges not observed) determined from apical views (lower images). Upper images show the abapertural surfaces of the same shells, giving their SERs. (C) The growth rate was estimated from the shell margin extension of marked and recaptured snails (n = 22). The marginal extension is shown to far exceed shell length (SL) extension. EA, spire whorl, EB, body whorl, S, shell suture, W1-4, shell whorls.
Fig. 2 in Organismal Responses to Coastal Acidification Informed by Interrelating Erosion, Roundness and Growth of Gastropod Shells.
Fig. 2. (A–C). Comparisons between the localities in shell length, shell width and shell roundness (SW/SL). Data are shown as median, 25–75%, min-max (see key). (D) Relationships between shell width and shell length are: EM (y = -0.55 + 0.686x; r = 0.97; p <0.001) and UB (y = 1.157 + 0.57x; r = 0.93; p <0.001). Red circles indicate the acidified locality (EM) and black circles, the non-acidified locality (UB).
Effects of mangrove cover on coastal erosion during a hurricane in Texas, USA
We tested the hypothesis that mangroves provide better coastal protection than salt marsh vegetation using ten 1,008 m2 plots in which we manipulated mangrove cover from 0 to 100 percent. Hurricane Harvey passed over the plots in 2017. Data from erosion stakes indicated up to 26 cm of vertical and 970 cm of horizontal erosion over 70 months in the plot with 0 percent mangrove cover, but relatively little erosion in other plots. The hurricane did not increase erosion, and erosion decreased after the hurricane passed. Data from drone images indicated 196 m2 of erosion in the 0 % mangrove plot, relatively little erosion in other plots, and little ongoing erosion after the hurricane. Transects through the plots indicated that the levee (near the front of the plot) and the bank (the front edge of the plot) retreated up to 9 m as a continuous function of decreasing mangrove cover. Soil strength was greater in areas vegetated with mangroves than in areas vegetated by marsh plants, or nonvegetated areas, and increased as a function of plot-level mangrove cover. Mangroves prevented erosion better than marsh plants did, but this service was non-linear, with low mangrove cover providing most of the benefits.
ICON-Coast model output for a study on the impact of Arctic coastal erosion on sea water carbonate saturation.
<p>Primary output of the ocean-biogeochemistry model ICON-Coast that has been used to create the figures in a manuscript on the impact of Arctic coastal erosion on sea water carbonate saturation.</p>
Coastal Erosion affecting historic monuments
Information about these twoo historic sites being affected by coastal erosion can be found at: https://historicengland.org.uk/listing/the-list/list-entry/1013820 and https://historicengland.org.uk/listing/the-list/list-entry/1013819 The motte of the Motte and Bailey castle is more seriously affected than the moated farm, Source: Objaverse 1.0 / Sketchfab
Coastal erosion and accretion areas along the Beaufort Sea and Laptev Sea Coasts based on Landsat 1999 - 2014
<p>The dataset covers the Laptev Sea coast from 120 to 168 E and Alaska and Canadian Beaufort Sea Coast from 130 to 168 W. </p> <p>Probabilities of erosion and accretion (change of land to water and visa versa) have been derived from Landsat for the time period 1999–2014. A probability threshold of 50% was applied to separate erosion and accretion areas which are provided as polygons (shape files).</p> <p>Further information regarding the algorithm is available in Bartsch et al. (2020). </p>
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