Search Results (169)

This study presents a comprehensive 35-year (1990–2025) shoreline change assessment along the southeast coast of Ireland, integrating multi-decadal Landsat satellite archives with GIS-based Digital Shoreline Analysis System (DSAS) metrics to quantify both spatial and temporal coastal dynamics. Unlike previous studies that focus on shorter timeframes or localized sectors, this research provides a regional-scale, orientation-specific comparison between the eastern-facing (SE1; County Wexford) and southern-facing (SE2; County Waterford) shorelines. Shoreline evolution was quantified using four complementary DSAS indicators—Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR), allowing robust discrimination between short-term variability and multi-decadal trends. The results reveal noticeable spatial variability in shoreline behavior with 57% accretion and 42% erosion across the eastern-facing coast (SE1) in County Wexford and the southern-facing coast (SE2) in County Waterford. SCE values ranging from 2.26 m to 663.83 m indicate considerable short-term shoreline variability, particularly within dynamic barrier and embayed systems. NSM values between −216.65 m and +663.83 m indicate erosional hotspots, particularly along soft-sediment coasts and exposed southern-facing sectors, whereas accretion is limited to embayments, sandy beaches, and zones of effective sediment trapping. Rate-based analyses show EPR values between −14.82 and +20.38 m/yr and LRR values between −5.27 and +20 m/yr, with LRR providing more reliable estimates of multi-decadal trends in highly dynamic environments. The findings highlight the strong influence of coastal orientation, sediment availability, geological controls, and human activities on shoreline change in southeastern Ireland. These findings provide valuable evidence to support coastal management, hazard mitigation, and climate adaptation planning, with the assistance of policymakers, to develop effective strategies that enhance the resilience and quality of life of coastal communities. Full article

Utilizing the InVEST coastal exposure model and multi-source geospatial data, this study evaluates coastal vulnerability to sea-level rise along a critical stretch of the North Coast of Central Java, Indonesia, specifically focusing on the Semarang, Demak, and Jepara regions. A Coastal Exposure Index (CEI) was constructed for 256.63 km of shoreline by integrating key environmental variables, including wave climate, high-resolution coastal topography, shoreline geomorphology, bathymetry, coastal habitat distribution, and observed sea-level rise trends-based satellite altimetry from AVISO. The CEI classified coastal segments into five risk categories from Very Low to Very High exposure. A comparative analysis was performed between a scenario incorporating coastal habitats and a scenario without habitats to determine the protective role of natural ecosystems. The results of the analysis show that the average sea-level rise in the study area is 4.3 mm/year. Moreover, the findings also show that the inclusion of coastal habitats significantly reduces extreme exposure levels. Without accounting for habitats, 22.8% of the coastline was classified as Very High exposure, whereas with habitats included this portion dropped to 1.8%. For example, in Jepara Regency the length of shoreline in Very High exposure class decreased from 53.7% (no habitat scenario) to 5.5% when habitats were considered. Overall, the presence of coastal ecosystems shifted large stretches of the coast to lower exposure classes. This study demonstrates that natural habitats have a critical influence on coastal exposure, substantially mitigating the vulnerability of North Java’s coastline to sea-level rise. Full article

Reservoirs are critical infrastructure for water and energy security, and require accurate and timely monitoring of reservoir water extent to make informed decisions. Optical remote sensing provides frequent, large-area observations; however, automated water extraction is often complicated by dam operation and surface heterogeneity, which increase spectral variability. Supervised methods, though widely used, generally require manual labels and often perform poorly when transferred across sensors and regions, limiting operational deployment. In this paper, we develop a geo-spectral feature-guided Self-Supervised Water Detection (SWD) framework, an automated algorithm designed for multi-source optical imagery. SWD consists of two stages: pixel-level classification and object-level refinement. Initially, SWD integrates spatial priors with spectral features to automatically derive high-confidence samples, which are then utilized to parameterize Gaussian mixture model to represent multimodal spectral distribution throughout the image. Furthermore, superpixel-constrained region growing is applied to refine shoreline and ensure object-level consistency. We validated SWD across 36 test cases comprising three sensors, six reservoirs, and two hydrological conditions. Compared with Random Forest and U-Net, SWD achieved the best performance. Specifically, (1) in cross-scale tests, SWD achieved high consistency with IoU ≥ 0.774; (2) in cross-region transfers, SWD maintained stable generalization (SD: 0.010); and (3) in hydrological response assessments, SWD captured water-level fluctuations with minimal bias variation (ΔRE < 1%). In addition, SWD framework is computationally efficient, with processing times of 0.49–1.29 s/Mpx on a standard CPU. This study demonstrates that SWD effectively addresses spectral variability and surface complexity in reservoir water area detection across multi-source optical imagery. It operates without manual labels or model training, enabling automated, large-scale and multi-temporal reservoir water monitoring. Full article

Seasonal hydrological fluctuations strongly influence riparian habitats in the middle Yangtze River, yet the relationships of inundation duration with soil properties and riparian vegetation remain insufficiently understood in representative riparian sections. Here, field surveys and laboratory analyses were conducted to examine (1) inundation–soil associations and (2) soil–vegetation relationships. Soil moisture (W), pH, particle-size composition, soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) were measured, and vegetation parameters were compared among inundation-duration zones. Partial redundancy analysis (pRDA) was used to evaluate the relationships between environmental factors and vegetation parameters after controlling for elevation and shoreline distance. Vegetation occurrence, coverage, and diversity decreased with increasing inundation duration, and no vascular plants were recorded in the severe-inundation zone. After accounting for topographic factors, TN and gravel were the main soil variables associated with vegetation variation. Overall, inundation duration was closely associated with soil variation, whereas vegetation variation was mainly associated with selected soil environmental factors. These findings provide site-based evidence for riparian ecological restoration in representative riparian sections of the middle Yangtze River. Full article

Satellite-derived shorelines (SDSs) are increasingly used to monitor beach morphology worldwide, yet their application remains poorly validated in microtidal environments strongly influenced by atmospheric forcing. In this study, the performance of CoastSat and CoastSat.slope using nine years of in situ beach profiles from six sandy beaches in Buenos Aires (Argentina) was evaluated. The analysis compares alternative sea level forcings—including global tidal predictions (FES2022), a regional barotropic model with meteorological forcing (MSAS), and wave setup from reanalysis products—and evaluates the effect of using locally trained classifiers on shoreline detection. The results show that locally trained classifiers markedly reduced RMSE values, from 9–21 m with the default classifier to 7–12 m with the locally trained one, while the MSAS model consistently outperforms FES2022 for sea level corrections across all sites. CoastSat.slope provided effective slope estimates for tidal corrections but tended to overestimate values relative to field data. Sensitivity tests confirmed that overestimation has a smaller impact on water level correction than underestimation, explaining why validation metrics improved when using CS.slope-derived slopes. These findings translate into actionable guidelines: (i) prioritize regional sea level models when nontidal variability is large; (ii) apply wave setup corrections cautiously in microtidal coasts; and (iii) use locally trained classifiers in heterogeneous or urbanized beaches. Overall, this study demonstrates that with appropriate parameterization, CoastSat is a reliable tool for shoreline monitoring in atmospherically forced, microtidal coasts, and its methodological insights are transferable to other low-energy, data-scarce regions worldwide. Full article

Arctic regions are experiencing accelerated environmental change, yet integrated assessments of terrain-scale responses remain limited. This study quantifies the spatial-temporal variability of glaciers, shorelines, and outwash plains in Kaffiøyra, Svalbard, Norway, over four decades (1985–2023) using cross-evaluated Landsat and Sentinel imagery. Our results reveal systematic retreat across all eight glaciers (R² = 0.83–0.96), with tidewater glaciers experiencing substantially greater terminus area loss (62.8% and 72.1%) compared to land-terminating glaciers (34.5–69.0%). Coastal changes were highly variable: erosion (up to −3.2 m/yr) was most pronounced on shores exposed to southwesterly summer waves, while significant accretion (+13.0 m/yr) occurred near the tidewater glacier terminus. The insignificant outwash changes (−6.4% to +2.7%) despite substantial land-terminating glacier retreat indicate these systems respond to different controls. A moderate negative correlation between glacier terminus area and summer temperatures (r = −0.55 to −0.69) enabled a simple projection model. Diagnostic projections to 2020–2039 showed that both downscaled climate models and extrapolated local data overestimated retreat. However, extrapolated local data proved more accurate, with its projection gap averaging 11% for land-terminating and 46% for tidewater glaciers. The study provides crucial insights into Arctic terrain behaviors, highlighting complex and divergent responses. These findings emphasize the need for enhanced localized monitoring systems through ongoing high-resolution image surveys and planned modeling to understand accelerating polar environmental changes. Full article

The Licantén coastal area in central Chile was severely impacted by the 2010 Mw 8.8 Cobquecura earthquake and subsequent tsunami, exposing the high vulnerability of coastal communities. Over the past decade, urban expansion has advanced toward the shoreline, increasing exposure to coastal hazards. This study aims to quantify shoreline dynamics and urban growth in Licantén between 2010 and 2025. We integrated satellite-derived shorelines (SDSs) from Landsat and Sentinel-2 imagery, ERA5 ocean reanalysis to characterize extreme wave events, and an open-source building footprint dataset with high-resolution imagery for urban mapping. Results indicate a post-earthquake acceleration in shoreline erosion up to 5 m per year and a rise in extreme wave events linked to climate variability. Urbanized areas expanded by an average of 46.3%, intensifying risk in hazard-prone zones. These findings highlight the urgent need for evidence-based coastal planning, including zoning and land-use restrictions, to reduce exposure and enhance resilience. This research contributes to climate adaptation strategies and sustainable coastal management in Chile. Full article

Under the combined pressures of natural variability and human activities, the area of tidal flats has been gradually decreasing, with most muddy coasts experiencing varying degrees of erosion. The central coast of Jiangsu Province, a world-renowned region for extensive tidal flats, has witnessed intensifying erosion of its muddy coasts in recent years. To mitigate further coastal erosion, an ecological submerged breakwater (ESB) was constructed in the intertidal zone north of the Sheyang River estuary to reduce wave impact on the shoreline. This study evaluates the wave attenuation performance of the ESB based on wave observations conducted at stations deployed on the seaward and landward sides of the structure in May 2025. Results indicate that the breakwater effectively reduces wave height, but its performance exhibits significant dynamic characteristics. During the observation period, the maximum attenuation rate for significant wave height (H₁/₃) reached 76.3%, with an average rate of 33.8%. Wave dissipation efficiency was closely related to sea state: under calm conditions (H₁/₃ < 0.4 m), the average attenuation rate was only 18.4%, whereas under severe sea states (H₁/₃ ≥ 0.4 m), it increased markedly to 57.6%. The wave transmission coefficients (K_t) span a wide range from 0.20 to 0.99, indicating a significant dynamic variability in the wave attenuation performance of the ESB. The performance of the ESB was primarily controlled by two key factors: incident wave height and submergence depth of the structure. Compared to “zonated” natural ecosystems such as oyster reefs, coral reefs, salt marshes, and mangroves, the ESB, as a “linear” engineered structure, achieves comparable wave attenuation within a limited spatial footprint. A promising future strategy involves using the ESB as a frontline defense, integrated with landward ecological restoration measures like salt marsh rehabilitation, to establish a hybrid “grey-green” coastal protection system that synergistically enhances both coastal resilience and ecological function. This study provides a scientific basis for the design and performance evaluation of ecological engineering solutions for protecting eroding muddy coasts. Full article

Shoreline variations in closed-basin lakes are closely linked to hydrological fluctuations and long-term changes in water balance, making them important indicators of environmental change. This study analyzes historical shoreline dynamics in Lake Van (Türkiye), the world’s largest soda lake, and provides scenario-based shoreline projections for 2032 and 2042 to support hydrological assessment and water-related management. Multi-temporal Landsat satellite images from 1982, 1992, 2002, 2012, and 2022 were processed using the Digital Shoreline Analysis System (DSAS 5.0) to quantify shoreline retreat and accretion, while future shoreline positions were estimated using the Kalman filter model. The results show pronounced spatial variability, with the most significant shoreline retreat observed in the Çelebibağ and Karahan regions, where sediment supplied by major inflowing streams contributes to shoreline instability through reworking and redistribution rather than stable accretion. Net shoreline movement values reached −2580.1 m for erosion and up to 1700 m for accretion. Model projections indicate an increasing trend of shoreline retreat by 2032 and 2042, accompanied by localized accretion zones. These hydrological-driven shoreline changes have potential implications for littoral habitats, water–land interactions, and human use of the shoreline, including fisheries infrastructure. The study demonstrates the value of integrating remote sensing and statistical forecasting for monitoring shoreline dynamics in closed-basin lake systems. Full article

The small freshwater lakes of Spitsbergen remain poorly studied compared to surrounding marine ecosystems despite their sensitivity to rapid environmental changes. During the short ablation season, these shallow lakes exhibit physicochemical variability influenced by the harsh Arctic climate, local geology, and hydrology. This study analyzed six lakes located on marine terraces, moraine areas, and outwash plains in the Bellsund region to assess how physicochemical variability in their waters affects phytoplankton development. The lakes exhibited local and temporal variations in temperature, conductivity, ion composition, and nutrient levels, with generally low nutrient availability limiting biological productivity. Phytoplankton communities were quantitatively and qualitatively poor, dominated by green algae, either flagellates or mixed communities, including cyanobacteria. Green algae clearly dominated in lakes closest to the fjord shoreline, while dinoflagellates and cryptophytes dominated in inland lakes. Phytoplankton abundance and biomass were extremely low in one of the lakes situated on the raised marine terraces within the tundra vegetation zone (3 × 10³ ind L⁻¹ and 0.004 mg L⁻¹, respectively). In contrast, the much larger lake situated within the tundra zone nearer the fjord shoreline had values that were comparable to fertile lakes in the temperate zone (~30 thousand × 10³ ind L⁻¹ and ~28 mg L⁻¹, respectively). It should be noted that Monoraphidium contortum and Rhodomonas minuta dominated some of the lakes almost entirely. Phytoplankton abundance was related to physicochemical conditions: green algae increased with increasing ion concentrations (Cl⁻, Na⁺, K⁺, SO₄²⁻), P_min, Fe, and Mn; flagellates preferred colder waters with higher N_min and low TOC; cyanobacteria occurred in waters with lower COND, TOC, Ca²⁺, Si, Cu, and Zn. Phytoplankton biomass increased in July with increasing water temperature. Bird activity likely facilitated phytoplankton dispersal, increasing taxonomic diversity in frequently visited lakes. Full article

The present study has applied a probabilistic oil spill modeling framework to assess the potential risks associated with offshore oil spills in the Foz do Amazonas sedimentary basin, a region of exceptional ecological importance and increasing geopolitical and socio-environmental relevance. By integrating a large ensemble of simulations with validated hydrodynamic, atmospheric and wave-driven forcings, the analysis of said simulations has provided a robust and seasonally resolved assessment of oil drift and beaching patterns along the Guianas and the Brazilian Equatorial Margin. The model has presented a total of 47,500 simulations performed on 95 drilling sites located across the basin, using the Lagrangian Spill, Transport and Fate Model (STFM) and incorporating a six-year oceanographic and meteorological variability. The simulations have included ocean current fields provided by HYCOM, wind forcing provided by GFS and Stokes drift provided by ERA5. Model performance has been evaluated by comparisons with satellite-tracked surface drifters using normalized cumulative Lagrangian separation metrics and skill scores. Mean skill scores have reached 0.98 after 5 days and 0.95 after 10 days, remaining above 0.85 up to 20 days, indicating high reliability for short to intermediate forecasting horizons and suitability for probabilistic applications. Probabilistic simulations have revealed a pronounced seasonal effect, governed by the annual migration of the Intertropical Convergence Zone (ITCZ). During the JFMA period, shoreline impact probabilities have exceeded 40–50% along extensive portions of the French Guiana and Amapá state (Brazil) coastlines, with oil reaching the coast typically within 10–20 days. In contrast, during the JASO period, beaching probabilities have decreased to below 15%, accompanied by a substantial reduction in impact along the coastline and higher variability in arrival times. Although coastal exposure has been markedly reduced during JASO, a residual probability of approximately 2% of oil intrusion into the Amazonas river mouth has persisted. Full article

Beach nourishment is a widely used strategy to mitigate coastal erosion, yet its long-term geological impacts remain poorly understood. This study provides a multi-decadal synthesis of shoreline change and sedimentological evolution on the nourished beaches of Cape May and Wildwood, New Jersey, USA. Using shoreline positions from 1991 to 2024, we identify contrasting trajectories: Wildwood exhibits ‘persistent transition’ with severe northern erosion (EPR: −10.0 m/yr) feeding southwards accretion, while Cape May demonstrates a ‘managed equilibrium’ with widespread accretion (mean EPR: +1.15 m/yr). Wave energy correlations account for less than 15% of shoreline variability, indicating natural drivers have been superseded by human sediment inputs. Direct sediment comparison shows substantial textural transformation, with median grain sizes increasing from 153 to 435 μm to 467–982 μm and sorting degrading from very well to moderately well sorted, reflecting sustained disequilibrium. These findings are synthesized into a conceptual model where nourishment initiates feedback cycles that create human-dependent morphodynamic trajectories. This study concludes that the long-term resilience of developed coasts will depend on a strategic evolution from managing ‘sand as volume’ toward stewarding ‘sediment as a system,’ where textural compatibility is a primary determinant of success. Full article

Coastal erosion poses a significant risk to the Romanian Black Sea coast, a region characterized by the interaction of natural geomorphological processes and anthropogenic pressures. The research focuses on developing a tool to quantify the cumulative impact of hydro-geo-morphological factors and to assess the vulnerability of the coastal zone to these influences. The approach involves adapting the Coastal Vulnerability Index (CVI)—previously applied in various methodologies—to the specific characteristics of this semi-enclosed basin, which included the exclusion of the tidal range variable due to the Black Sea’s negligible tidal amplitude. The selection of key variables, including coastal geology and geomorphology, shoreline change rates, coastal slope, sea level, and wave regime, was conducted with consideration for the specific characteristics of the Romanian coastal zone. By classifying these variables on a semi-quantitative scale and integrating them into a CVI, the study identifies and maps areas of high vulnerability. The analysis, based on a 1 × 1 km grid resolution, identified sectors of very high vulnerability in the northern Danube Delta unit, particularly along the coastlines of South Sulina–Câşla Vădanei, Sahalin, and Periboina-Edighiol-Vadu. These findings are validated through a comparison with long-term, multidecadal shoreline evolution data, confirming the model’s predictive accuracy. While the 1 × 1 km grid is effective for a macro-scale assessment, the study highlights the need for a finer resolution (e.g., 100 × 100 m) for detailed analysis in the southern region, due to localized geodynamic conditions and the significant influence of coastal infrastructure. Full article

Accurate shoreline determination is essential for the study of coastal and inland water processes, hydrography, and the monitoring of aquatic and terrestrial environments. This study compares two modern remote sensing technologies: MLS conducted with a USV and photogrammetry using a UAV. The research was carried out on Lake Kłodno, characterised by a complex shoreline with vegetation and hydrotechnical structures. Both approaches satisfied the accuracy requirements of the IHO Special Order for shoreline extraction (≤5 m at the 95% confidence level). For the UAV-derived orthophoto, the error within which 95% of shoreline points were located (corresponding to 2.45·σ) was 0.05 m for the natural shoreline and 0.06 m for the variant including piers, both well below the IHO threshold. MLS achieved a 95% error of 1.16 m, which also complies with the Special Order criteria. UAV data enable clear interpretation of the land–water boundary, whereas MLS provides complete three-dimensional spatial information, independent of lighting conditions, and allows surveys of vegetated or inaccessible areas. The results demonstrate the complementarity of the two approaches: UAV is well suited to highly accurate shoreline mapping and the identification of hydrotechnical structures, while MLS is valuable for analysing the nearshore zone and for surveying vegetated or inaccessible areas. The findings confirm the value of integrating these approaches and highlight the need to extend research to other types of waterbodies, to consider seasonal variability, and to develop methods for the automatic extraction of shorelines. Full article

Collecting accurate and reliable beach morphology data is essential for informed coastal management. The beach adjacent to the seawall on North Padre Island, Texas, USA has experienced increased erosion and disrupted natural processes. City ordinance mandates the placement of bollards to restrict vehicular traffic when the beach width from the seawall toe to mean high water (MHW) is less than 45.7 m. To aid the City of Corpus Christi’s understanding of seasonal beach changes, mobile lidar scanning (MLS) surveys with a mapping-grade system were conducted in February, June, September, and November 2023, and post-nourishment in March 2024. Concurrent uncrewed aircraft system (UAS) photogrammetry surveys were performed in February and November 2023, and March 2024 to aid beach monitoring analysis and for comparative assessment to the MLS data. MLS-derived digital elevation models (DEMs) were used to evaluate seasonal geomorphology, including beach slope, width, shoreline position, and volume change. Because MHW was submerged during all surveys, highest astronomical tide (HAT) was used for shoreline analyses. HAT-based results indicated that bollards should be placed from approximately 390 to 560 m from the northern end of the seawall, varying seasonally. The March 2024 post-nourishment survey showed 102,462 m³ of sand was placed on the beach, extending the shoreline by more than 40 m in some locations. UAS photogrammetry-derived DEMs were compared to the MLS-derived DEMs, revealing mean HAT position differences of 0.02 m in February 2023 and 0.98 m in November 2023. Elevation and volume assessments showed variability between the MLS and UAS-SfM DEMs, with neither indicating consistently higher or lower values. Full article