Which data assimilation method to use and when: unlocking the potential of observations in shoreline modelling DOI Creative Commons
Moisés Álvarez-Cuesta, Alexandra Toimil, Íñigo J. Losada

et al.

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(4), P. 044023 - 044023

Published: March 15, 2024

Abstract Shoreline predictions are essential for coastal management. In this era of increasing amounts data from different sources, it is imperative to use observations ensure the reliability shoreline forecasts. Data assimilation has emerged as a powerful tool bridge gap between episodic and imprecise spatiotemporal incomplete mathematical equations describing physics dynamics. This research seeks maximize potential by assessing effectiveness algorithms considering observational characteristics initial system knowledge guide models towards delivering results close possible real world. Two statistical (stochastic ensemble extended Kalman filters) one variational algorithm (4D-Var) incorporated into an equilibrium cross-shore model one-line longshore model. A twin experimental procedure conducted determine observation requirements these in terms accuracy, length collection campaign sampling frequency. Similarly, needed ability methods track nonstationarity evaluated under synthetic scenarios. The indicate that with noisy observations, filter variants outperform 4D-Var. However, 4D-Var less restrictive tracks nonstationary parametrizations more accurately processes. findings demonstrated at two beaches governed processes sources used calibration. contribution, assimilated thus far modelling extended, applied first time field modelling, guidelines on which method can be most beneficial available provided.

Language: Английский

Shoreline Seasonality of California's Beaches DOI Creative Commons
Jonathan A. Warrick, Daniel Buscombe, Kilian Vos

et al.

Journal of Geophysical Research Earth Surface, Journal Year: 2025, Volume and Issue: 130(2)

Published: Jan. 30, 2025

Abstract We report on remote sensing techniques developed to characterize seasonal shoreline cycles from satellite‐derived measurements. These are applied 22‐yr of measurements for over 777 km beach along California's 1,700‐km coast, which the general understanding is that shorelines exhibit winter‐narrow and summer‐recovery seasonality. find approximately 90% transects significant recurring in position. Seasonal excursions twice as large northern central California (17.5–32.2 m) than southern (7.3–15.9 m; interquartile ranges). Clustering analyses were effective at characterizing temporal patterns seasonality, revealing ∼459 (59%) conditions, whereas ∼189 (24%) ∼50 (6.4%) spring‐narrow summer‐narrow respectively. spring‐ conditions most common California, where they represent half total length shoreline. Multivariate reveal wave climate geomorphic setting significantly related magnitude timing cycles. Combinations these variables explain 44% seasonality variance complete data set 85% a subset 93 long (>1 km) continuous beaches. conclude diversity waves cause broad range Combined, this indicates overly generalized “winter‐narrow/summer‐recovery” conventions beaches not expressed universally far more diverse simple canonical rules.

Language: Английский

Citations

3

Monitoring interdecadal coastal change along dissipative beaches via satellite imagery at regional scale DOI Creative Commons
Marcan Graffin, Mohsen Taherkhani, Meredith Leung

et al.

Cambridge Prisms Coastal Futures, Journal Year: 2023, Volume and Issue: 1

Published: Jan. 1, 2023

Abstract Coastal morphological changes can be assessed using shoreline position observations from space. However, satellite-derived waterline (SDW) and (SDS; SDW corrected for hydrodynamic contributions outliers) detection methods are subject to several sources of uncertainty inaccuracy. We extracted high-spatiotemporal-resolution (~50 m-monthly) time series mean high water along the Columbia River Littoral Cell (CRLC), located on US Pacific Northwest coast, Landsat missions (1984–2021). examined accuracy SDS mesotidal, mildly sloping, high-energy wave climate dissipative beaches CRLC by validating them against 20 years quarterly in situ beach elevation profiles. found that heavily depends capability identify remove outliers correct biases stemming tides runup. we show only correcting data is sufficient accurately measure change trends CRLC. Ultimately, strong agreement with data, facilitating spatiotemporal analysis coastal highlighting an overall accretion signal during past four decades.

Language: Английский

Citations

19

Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments DOI Creative Commons

Richelle U. Moskvichev,

Anna B. Mikkelsen,

Tiffany R. Anderson

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 28, 2025

Coastal erosion, intensified by sea level rise, poses significant threats to coastal communities in Hawaiʻi and similar island communities. This study projects long-term shoreline change on the Hawaiian Island of O'ahu using data-assimilated CoSMoS-COAST model. models four key processes: (1) Alongshore transport, (2) Recession due (3) Cross-shore transport waves, (4) Residual processes represented a linear trend term. marks first application for an oceanic equatorial with narrow beaches dynamic wave climate. The model is informed novel combination data derived from high-resolution imagery Planet, Sentinel-2, Landsat satellites, wave-climate hindcasts specific Hawai'i, regional beach-slope surveys. On northern Oʻahu beach, achieved root mean square error 9.4 m between observations output. predicts that 81% O'ahu's sandy beach coastline could experience loss 2100; 39.8% this happening 2030. represents increase, 43.3%, net landward compared previous erosion forecasts, 0.3 rise (2050). Additionally, such as cross-shore equilibrium alongshore sediment play large contribution gross within next decade, particularly O 'ahu's north west shores. In long term, we find recession residual dominate, but dynamic, wave-driven (longshore transport) still account 34% present 2100. We assert are crucial addition accurate modeling environments. These findings have implications planning development, suggesting updates policies rely upon forecasting, highlights importance incorporating other Pacific islands.

Language: Английский

Citations

1

Assessment of satellite-derived shorelines automatically extracted from Sentinel-2 imagery using SAET DOI Creative Commons
Josep E. Pardo‐Pascual, Jaime Almonacid-Caballer, Carlos Cabezas-Rabadán

et al.

Coastal Engineering, Journal Year: 2023, Volume and Issue: 188, P. 104426 - 104426

Published: Nov. 13, 2023

The definition of the shoreline position from satellite imagery is great interest among coastal monitoring techniques. Understanding reality mapped by resulting shorelines and defining their accuracy paramount importance. assessment described in this paper constitutes a validation obtained using novel tool SAET (Shoreline Analysis Extraction Tool) for automatic extraction. applying different parameters available are assessed 9 test sites with diverse morphology oceanographic conditions along Atlantic European Western Mediterranean coasts. reference data large segments (covering up to about 240 km) nearly coincident very high-resolution images. Different image processing levels extraction methods have been tested, showing key role position. When approximate Automated Water Index images without shadows (AWEInsh) 0 threshold generally best segmentation method. In turn, employment mathematical morphological operations dilation or erosion considerably improves results certain typologies. On contrary, atmospherically-corrected has smaller influence on SDSs. Results support idea that magnitude errors strongly related specific conditions- general, lowest appear low-energetic microtidal sites, contrary energetic mesotidal coasts gentle slopes. range between 3.7 m 13.5 RMSE (root-mean-square error) types when selecting most appropriate parameters. identified shows similar better other tools.

Language: Английский

Citations

14

Bayesian Network Analysis for Shoreline Dynamics, Coastal Water Quality, and Their Related Risks in the Venice Littoral Zone, Italy DOI Creative Commons
Hung Vuong Pham, Maria Katherina Dal Barco,

Mohsen Pourmohammad Shahvar

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(1), P. 139 - 139

Published: Jan. 10, 2024

The coastal environment is vulnerable to natural hazards and human-induced stressors. assessment management of risks have become a challenging task, due many environmental socio-economic risk factors together with the complex interactions that might arise through pressures. This work evaluates combined effect climate-related stressors on low-lying areas by applying multi-risk scenario analysis Bayesian Network (BN) approach for Venice coast. Based available open-source remote sensing data detecting shoreline changes, developed BN model was trained validated oceanographic variables 2015–2019 timeframe, allowing us understand dynamics local-scale erosion related water quality parameters. Three “what-if” scenarios were carried out analyze relationships between boundary conditions, evolution, results demonstrate changes in sea surface height significant wave may significantly increase probability high-erosion high-accretion states. Moreover, altering direction, show higher-risk class. outcome this study allowed identify current future scenarios, supporting local authorities developing adaptation plans.

Language: Английский

Citations

6

VedgeSat: An automated, open‐source toolkit for coastal change monitoring using satellite‐derived vegetation edges DOI Creative Commons
Freya Muir, Martin D. Hurst, Luke Richardson‐Foulger

et al.

Earth Surface Processes and Landforms, Journal Year: 2024, Volume and Issue: 49(8), P. 2405 - 2423

Published: May 14, 2024

Abstract Public satellite platforms offer regular observations for global coastal monitoring and climate change risk management strategies. Unfortunately, shoreline positions derived from imagery, representing changes in intertidal topography, are noisy subject to tidal bias that requires correction. The seaward‐most vegetation boundary reflects a indicator which shifts on event–decadal timescales, informs practitioners of storm damage, sediment availability landform health. We present validate new open‐source tool VedgeSat identifying edges (VEs) high (3 m) moderate (10–30 resolution imagery. methodology is based the CoastSat toolkit, with streamlined image processing using cloud‐based data via Google Earth Engine. Images classified newly trained vegetation‐specific neural network, VEs extracted at subpixel level dynamic Weighted Peaks thresholding. performed validation against ground surveys manual digitisation aerial imagery across eroding accreting open coasts estuarine environments site Scotland. Smaller‐than‐pixel detection was achieved 83% Sentinel‐2 (Root Mean Square Error 9.3 m). An overall RMSE 19.0 m Landsat 5 & 8, PlanetScope images. Performance varied by geomorphology, highest accuracies sandy owing spectral contrast less false positives vegetation. can be readily applied tandem waterlines near‐globally, support adaptation decisions historic trends whole shoreface, even normally data‐scarce areas.

Language: Английский

Citations

6

CoastSeg: an accessible and extendable hub for satellite-derived-shoreline (SDS) detection and mapping DOI Creative Commons
Sharon Fitzpatrick, Daniel Buscombe, Jonathan A. Warrick

et al.

The Journal of Open Source Software, Journal Year: 2024, Volume and Issue: 9(99), P. 6683 - 6683

Published: July 1, 2024

Fitzpatrick et al., (2024). CoastSeg: an accessible and extendable hub for satellite-derived-shoreline (SDS) detection mapping. Journal of Open Source Software, 9(99), 6683, https://doi.org/10.21105/joss.06683

Language: Английский

Citations

5

Significant challenges to the sustainability of the California coast considering climate change DOI Creative Commons
Karen M. Thorne, Glen M. MacDonald, Francisco P. Chávez

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(32)

Published: July 29, 2024

Climate change is an existential threat to the environmental and socioeconomic sustainability of coastal zone impacts will be complex widespread. Evidence from California across United States shows that climate impacting communities challenging managers with a plethora stressors already present. Widespread action could taken would sustain California's ecosystems communities. In this perspective, we highlight main sustainability: compound effects episodic events amplified ongoing change, which present unprecedented challenges state. We two key for in zone: 1) accelerating sea-level rise combined storm impacts, 2) continued warming oceans marine heatwaves. Cascading these types compounding occur within context stressed system has experienced extensive alterations due intensive development, resource extraction harvesting, spatial containment, other human use pressures. There are critical components used address immediate concerns, including comanagement strategies include diverse groups organizations, strategic planning integrated large areas, rapid implementation solutions, cohesive policy relevant research agenda coast. Much been started state, but scale increased, timelines accelerated. The ideas information presented here intended help expand discussions sharpen focus on how encourage iconic region.

Language: Английский

Citations

5

Pan‐Arctic Assessment of Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea‐Level Rise, and Permafrost Thaw DOI Creative Commons
Rodrigue Tanguy, Annett Bartsch, Ingmar Nitze

et al.

Earth s Future, Journal Year: 2024, Volume and Issue: 12(12)

Published: Dec. 1, 2024

Abstract This study assesses the vulnerability of Arctic coastal settlements and infrastructure to erosion, Sea‐Level Rise (SLR) permafrost warming. For first time, we characterize coastline retreat consistently along at regional scale for Northern Hemisphere. We provide a new method automatically derive long‐term change rates coasts. In addition, identify total number associated that could be threatened by marine terrestrial changes using remote sensing techniques. extended Coastal Infrastructure data set (SACHI) include road types, airstrips, artificial water reservoirs. The analysis coastline, Ground Temperature (GT) Active Layer Thickness (ALT) from 2000 2020, in addition with SLR projection, allowed exposed 2030, 2050, 2100. validated SACHI‐v2, GT ALT sets through comparisons in‐situ data. 60% detected is built on low‐lying coast (10 m a.s.l). results show 2100, 45% all will affected 21% erosion. On average, increasing 0.8°C per decade, 6 cm decade. become positive 77% area. Our highlight circumpolar international amplitude problem emphasize need immediate adaptation measures current future environmental counteract deterioration living conditions ensure sustainability.

Language: Английский

Citations

5

Characterizing longshore transport potential and divergence of drift to inform beach loss trends DOI Creative Commons
Daniel T. Kahl, Lawrence Vulis, Jochen E. Schubert

et al.

Coastal Engineering, Journal Year: 2024, Volume and Issue: 189, P. 104473 - 104473

Published: Jan. 24, 2024

Beach loss is a growing global challenge that threatens the safety of coastal communities, health ecosystems, recreational amenities, and regional economies dependent on tourism. Spatial gradients in longshore sediment transport, or divergence drift (DoD), primary driver beach width change over multi-annual time scales, but response any particular can be challenging to characterize predict. Here we present new method DoD using non-uniform segmentation coastline informed by spatial distribution transport potential, including location physical barriers identified orthoimagery, both maxima reversals potential derived from nearshore wave data. The demonstrates improved capacity predict trends at sandy beaches compared methods rely uniform coastline. In an application southern California where satellite data documents two decades trends, correctly predicts sign 93% transects within littoral cell achieves linear correlation between exceeding 0.8. Moreover, find minimum five years are required establish consistently strong correlations changes. Conversely, use shown unreliable for estimating due sensitivities shoreline segment size. This work shows leverage satellite-based characterization dynamics relevant erosion management.

Language: Английский

Citations

4