Search Results (196)

The Ranchería River delta, located in Riohacha, Colombia, exemplifies the complex dynamics of coastal systems influenced by environmental and anthropogenic factors. This study analyzes the spatial and temporal evolution of the delta’s shoreline over the past two decades (2003–2023) using Google Earth imagery, the Digital Shoreline Analysis System (DSAS) within a GIS environment, and statistical methods such as ANOVA and Tukey’s test. Satellite images from 2003 to 2023 were processed to evaluate shoreline evolution through metrics like the Net Shoreline Movement (NSM) and Linear Regression Rate (LRR). The results reveal a predominant trend of accretion, with values reaching up to 260 m of NSM, particularly between 2003 and 2018. However, the 2018–2023 period shows a shift toward stabilization and localized erosion (e.g., the NSM ranges from 96 m of erosion to 32 m of accretion), with significant changes in the northeastern area (the delta’s Santa Rita arm) attributed to anthropic and natural factors (e.g., absence of mangroves or ongoing human activities). The comparison of LRR and NSM values reveals consistent linearity in shoreline behavior across the study period, suggesting stable coastal processes during accretion-dominated phases and increased variability during recent erosion. Variability across zones highlights the role of natural barriers like mangroves in mitigating erosion. The findings underscore the importance of integrating long-term data with recent trends for shoreline management and emphasize adaptive strategies to conserve critical ecosystems while addressing the socio-economic needs of local communities. Full article

Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). The results show that the Random Forest algorithm, utilizing spectral bands and indices (NDVI, NDWI, MNDWI, SAVI), achieved the highest classification accuracy (98.17%) and a Kappa coefficient of 0.9432, enabling reliable delineation of land and water boundaries. The extracted annual shorelines were validated with high accuracy, yielding RMSE values of 13.59 m (2018) and 8.90 m (2023). The DSAS analysis identified significant spatial and temporal variations in shoreline erosion and accretion. Between 1988 and 2006, the most intense erosion occurred in regions 4 and 5, influenced by sea-level rise, strong monsoonal currents, and human activities. However, from 2006 to 2018, erosion rates declined significantly, attributed to coastal protection structures and mangrove restoration. The period 2018–2023 exhibited a combination of erosion and accretion, reflecting dynamic sediment transport processes and the impact of coastal management measures. Over time, erosion rates declined due to the implementation of protective structures (e.g., bamboo fences, rock revetments) and the natural expansion of mangrove forests. However, localized erosion remains persistent in low-lying, vulnerable areas, exacerbated by tidal forces, rising sea levels, and seasonal monsoons. Anthropogenic activities, including urban development, mangrove deforestation, and aquaculture expansion, continue to destabilize shorelines. The findings underscore the importance of sustainable coastal management strategies, such as mangrove restoration, soft engineering coastal protection, and integrated land-use planning. This study demonstrates the effectiveness of combining machine learning and geoinformatics for shoreline monitoring and provides valuable insights for coastal erosion mitigation and enhancing coastal resilience in the Upper Gulf of Thailand. Full article

Coastal regions are increasingly vulnerable to sea-level rise and extreme storm events, making the accurate prediction of wave run-up on seawalls crucial for effective flood and erosion protection. This study presents a novel hybrid approach combining K-means clustering with artificial neural networks (ANNs) to predict wave run-up distance. The method begins with dimensionless analysis to scale all the variables, followed by data segmentation using K-means clustering to group wave characteristics such as the Froude number, scaled distance from the wave front to the shoreline, and wave nonlinearity. These clusters help to focus the ANN on more homogeneous wave conditions, significantly improving prediction accuracy. Two-dimensional flume experiments systematically varied wave height, period, and steepness, producing a robust dataset that accounts for a range of wave conditions. The model’s performance is demonstrated through a high $R^2$ value of 0.97 and low mean squared error (MSE) of 0.0092, surpassing traditional ANN models in its ability to capture complex wave dynamics. Full article

This research examines the transformation of the Lake Pontchartrain coastal landscape, including the New Orleans shoreline. The paper addresses the critical need to understand long-term environmental change through a comprehensive geospatial analysis of historical cartographic representations. The study employs a methodology involving three key steps: (1) georeferencing maps using QGis v. 3.4.8., (2) vectorization using AutoCAD v. 2013, and (3) comparative spatial analysis to quantify coastal morphological changes. The quantitative results reveal significant coastal dynamics, with Lake Pontchartrain experiencing a total erosion balance of −36.42 km², although the New Orleans coastal zone has experienced land reclamation. This loss can be attributed to the synergistic interaction of natural (e.g., subsidence, sea level rise, hurricanes) and anthropogenic (e.g., urban development, infrastructure, ecological fragmentation) processes that have accelerated coastal erosion in the study area. The research provides a critical historical analysis of the evolution of coastal landscapes in response to anthropogenic influences. However, the methodology is constrained when it comes to addressing the socioeconomic impacts. Nevertheless, the study considered the profound environmental and societal consequences of historical governmental and social decisions, thereby underscoring the intricate interplay between natural processes and human intervention in coastal ecosystems. These findings contribute to a more profound comprehension of the processes of coastal landscape transformation, underscoring the dynamic and fragile nature of coastal environments. Full article

The Málaga coast, in the south of Spain, is a densely populated tourist destination where ports, marinas and coastal protection structures of various typologies (e.g., groins, breakwaters, revetments) and shapes (e.g., “Y”, “L”, etc., shaped groins) have been emplaced. Such structures have modified the long- and cross-shore sediment transport and produced changes in beach morphology and the evolution of nearby areas. To characterize the changes related to shore-normal structures, beach erosion/accretion areas close to coastal anthropic structures were measured using a sequence of aerial orthophotos between 1956 and 2019, and the potential littoral sediment transport for the two main littoral transport directions was determined by means of the CMS (Coastal Modeling System). Available data on wave propagation and coastal sediment transport reflect the complex dynamics of the study area, often characterized by the coexistence of opposing longshore transport directions. Accretion was observed on both sides of ports in all studied periods and groins and groups of groins presented mixed results that reflect the heterogeneity of the study area; in certain sectors where the wave regime is bidirectional, changes in the shoreline trend were observed during the study period. The study cases described in this paper emphasize the difficulties in finding clear spatial and temporal trends in the artificially induced erosion/accretion patterns recorded along a heavily modified shoreline. Full article

The Falakra geosite is located at the northern shoreline of the island of Limnos, Greece, and exhibits an array of unusual geomorphological features developed in late Cenozoic sandstones. Deposition of the primary clastic sediments was overprinted by later, low-temperature hydrothermal fluid flow and interstitial secondary calcite formation associated with nearby volcanic activity. Associated sandstone cannonballs take center stage in a landscape built by joints, Liesengang rings and iron (hydr)oxide precipitates, constituting an intriguing site of high aesthetic value. The Falakra geosite is situated in an area with dynamic erosion processes occurring under humid weather conditions. These have evidently sculpted and shaped the sandstone landscape through a complex interaction of wave- and wind-induced erosional processes aided by salt spray wetting. This type of geosite captivates scientists and nature enthusiasts due to its unique geological and landscape features, making its sustainable conservation a significant concern and topic of debate. Here, we provide detailed geological and remote sensing mapping of the area to improve the understanding of geological processes and their overall impact. Given the significance of the Falakra geosite as a unique tourist destination, we emphasize the importance of developing it under sustainable management. We propose the segmentation of the geosite into four sectors based on the corresponding geological features observed on site. Sector A, located to the west, is occupied by a lander-like landscape; to the southeast, sector B contains clusters of cannonballs and concretions; sector C is characterized by intense jointing and complex iron (hydr)oxide precipitation patterns, dominated by Liesengang rings, while sector D displays cannonball or concretion casts. Finally, we propose a network of routes and platforms to highlight the geological heritage of the site while reducing the impact of direct human interaction with the outcrops. For constructing the routes and platforms, we propose the use of serrated steel grating. Full article

Although successful in protecting planted mangrove plants, the effectiveness of emergent detached offshore structures in increasing vegetation cover has yet to be definitively determined. We selected Tien Giang Province, Vietnam as an appropriate case study to address this question. We analyzed multiyear (2000 and 2022) shoreline changes and calculated the enhanced vegetation index (EVI) together with ground truthing in pursuit of the objectives of the study. Our findings suggest that emergent detached offshore structures have yet to lead to an increase in vegetation cover or promote mangrove growth. The vegetation growth steadily increased, as did the high level of natural mangrove growth with fully grown mangrove trees, even before the structures were constructed. By 2015, all the categories increased slightly except for low vegetation cover (LVC) and medium vegetation cover (MVC). LVC decreased from 390 ha in 2010 to 291 ha in 2015, while MVC decreased from 305 ha in 2010 to 275 ha in 2015. By 2020, all the categories decreased slightly except for non-vegetation cover—Barren lands (NVC2) and MVC. NVC2 decreased slightly from 404 ha in 2015 to 368 ha in 2015. The MVC decreased slightly from 275 ha in 2015 to 212 ha in 2020. Non-vegetation cover—Intertidal mudflats (NVC1)—LVC, and high vegetation cover (HVC) increased slightly from 2015 (326 ha, 291 ha, and 249 ha, respectively) to 2020 (368 ha, 292 ha, and 298 ha, respectively). By 2022, NVC2, MVC, and HVC remained unchanged, while NVC1 and LVC increased slightly from 368 ha and 292 ha in 2015, respectively, to 380 ha and 302 ha, respectively. The increase in vegetation cover and the natural regeneration of mangrove species were partly due to the adaptation of mangrove species to the site (river mouth areas), particularly the protection provided by Ngang Island offshore, and the construction of these structures. In addition, these structures were constructed in a rather stable area (slightly eroded and estuarine area) and therefore have yet to provide any noticeable benefits for mangrove regeneration three to five years after their construction. In the future, the morpho dynamic and hydrodynamic elements of the site should be adequately considered during the design and construction of these structures to increase vegetation cover and promote natural mangrove regeneration. Full article

Coastal zones, at the interface between land and sea, face increasing challenges from erosion, sea-level rise, and anthropogenic interventions, necessitating innovative tools for effective management and protection. This study introduces COAST-PRO_SIM, a novel numerical model specifically designed to predict shoreline evolution and assess the impacts of coastal defence structures on coastal morphology. Unlike existing models that often face a trade-off between computational efficiency and physical accuracy, COAST-PRO_SIM balances these demands by integrating two-dimensional wave propagation routines with advanced shoreline evolution equations. The model evaluates the effects of interventions such as breakwaters and groynes, enabling simulations of shoreline dynamics with reduced computational effort. By using high-resolution input data, COAST-PRO_SIM captures the interplay between hydrodynamics, sediment transport, and structural impacts. Tested on real-world case studies along the coasts of San Leone, Porto Empedocle, and Villafranca Tirrena, the model demonstrates its adaptability to diverse coastal environments. The results highlight its potential as a reliable tool for sustainable coastal management, allowing stakeholders to anticipate long-term changes in coastal morphology and design targeted mitigation strategies. Full article

Freshwater turtle species preservation relies on understanding their population dynamics and geographical distribution. Amur softshell turtles (ASTs [Pelodiscus maackii]) are poorly protected due to insufficient awareness and the population in Northeastern China has experienced a steep decline compared to previous years. This study aims to investigate the population density and structure of ASTs in the Jewellery Island area of the Ussuri River in Northeast China using continuous-time capture–recapture methods in closed populations. A three-month mark–recapture study was conducted in 2022, resulting in 35 juvenile captures, including 12 recaptures from 23 marked individuals. The estimated population size in the study area was 40.79 ± 9.75 (95% confidence interval, 95% CI = 27–65), translating to 0.663 ± 0.158 turtles/ha (95% CI = 0.44–1.06 individuals/ha). Approximately 35.4–85.2% of the estimated population was marked. Additionally, we explored the influence of environmental variables on turtle distribution by dividing the surveyed sites into seven sections based on their natural characteristics. The ASTs distribution inferred from trapping successes was considerably different among sections, with most turtles (91%) captured at the vegetated shoreline and in water channel 2. This research offers essential baseline data to support future assessments of ASTs population on a larger scale and to inform the development of conservation strategies. Full article

The coast is the most dynamic part of the Earth’s surface due to its strategic position at the interface of the land and the sea. It is, therefore, exposed to hazards and specific risks because of the geography as well as the geological and environmental characteristics of different countries. The coastal environment is essentially dynamic and evolving in time and space, marked by waves, tides, and seasons; moreover, it is subjected to many marine and continental processes (forcing). This succession of events significantly influences the frequency and severity of coastal hazards. The present paper aims at describing and characterizing the hazards and vulnerabilities on the Cameroonian coast. Cameroon possesses 400 km of coastline, which is exposed to various hazards. It is important to determine the probabilities of these hazards, the associated effects, and the related vulnerabilities. In this study, in this stable intraplate setting, the methodology used was diverse and combined techniques for the study of the shore and methods for the treatment of climatic data. Also, historical data were collected during field observations and from the CRED website for all the natural hazards recorded in Cameroon. In addition, documents on climate change were consulted. Remotely sensed data, combined with GIS tools, helped to determine and assess the associated risks. A critical grid combining a severity and frequency analysis was used to better understand these hazards and the coastal vulnerabilities of Cameroon. The results show that Cameroon’s coastal margins are subject to natural processes that cause shoreline changes, including inundation, erosion, and accretion. This study identified seven primary hazard types (earthquakes, volcanism, landslides, floods, erosion, sea level rise, and black tides) affecting the Cameroonian coastline, with the erosion rate exceeding 1.15 m/year at Cape Cameroon. Coastal populations are continuously threatened by these natural or man-induced hazards, and they are periodically subjected to catastrophic disasters such as floods and landslides, as experienced in Cameroon. In addition, despite the existence of the National Contingency Plan devised by the Directorate of Civil Protection, National Risk, and Climate Change Observatories, the implementation of disaster risk reduction and mitigation strategies is suboptimal. Full article

This study aims to establish a scientific and methodological basis for predicting shoreline positions using modern data analysis and machine learning techniques. The focus area is a 5 km section of the Ural coast along Baydaratskaya Bay in the Kara Sea. This region was selected due to its diverse geomorphological features, varied lithological composition, and significant presence of permafrost processes, all contributing to complex patterns of shoreline change. Applying advanced data analysis methods, including correlation and factor analysis, enables the identification of natural signs that highlight areas of active coastal retreat. These insights are valuable in arctic development planning, as they help to recognize zones at the highest risk of significant shoreline transformation. The erosion process can be conceptualized as comprising two primary components to construct a predictive model for coastal retreat. The first is a random variable that encapsulates the effects of local structural changes in the coastline alongside fluctuations due to climatic conditions. This component can be statistically characterized to define a confidence interval for natural variability. The second component represents a systematic shift, which reflects regular changes in average shoreline positions over time. This systematic component is more suited to predictive modeling. Thus, modern information processing methods allow us to move from descriptive to numerical assessments of the dynamics of coastal processes. The goal is ultimately to support responsible and sustainable development in the highly sensitive arctic region. Full article

Landslide-generated surge waves are significant natural hazards, posing severe risks to engineering safety. Despite extensive research on the dynamics of landslide-generated waves, studies analyzing controlling factors and their mechanisms remain limited, leaving key influencing processes inadequately understood. This study utilizes computational fluid dynamics (CFD) to perform a numerical simulation of a semi-submerged landslide in a hydropower station reservoir area. The research systematically investigated the effects of key variables, including slide volume, velocity, centroid height, and water depth, on the behavior of semi-submerged landslide-generated surge waves. Results demonstrate a positive correlation of slide volume, velocity, and centroid height with the initial wave height and run-up on the opposing shoreline. However, the impact of water depth reveals a more complex pattern, exhibiting distinct surge characteristics in the near-field and far-field zones. Via correlation and sensitivity analyses, this study elucidated the relationships between these factors and surge dynamics, identifying the primary factors influencing the size of the semi-submerged landslide-generated surge. The findings provide critical insights for predicting and mitigating surge disasters, offering both theoretical foundations and practical application value for landslide disaster prevention and management. Full article

Headland and groyne sand bypassing greatly influences embayment dynamics at medium to long timescales, but is often disregarded or partially included in reduced-complexity shoreline models. This study explores how accounting for subaqueous sediment bypassing in a shoreline model affects mean embayed beach planshape and spatial variability. We implement a generic parametrization of sand bypassing in the LX-Shore model, with simulations on a synthetic embayment in two configurations: “full bypassing” (FB) where the sediments bypass the obstacle in the surfzone and beyond, and “shoreline bypassing” (SB) where bypassing occurs only when the shoreline extends beyond the obstacle. Time-invariant wave simulations show significant differences in updrift shoreline position between FB and SB. Simulations with time-varying wave angles and fixed wave height and period reveal that FB significantly impacts the embayment mean planform and spatial variability: FB reduces beach rotation by about 1/3, particularly under slightly oblique and slightly asymmetrical wave climates, and decreases shoreline curvature, especially under highly oblique wave climates. Downdrift shoreline erosion may be overestimated by up to 20% under SB. Our simulations provide new insight into the influence of subaqueous sand bypassing on embayed beach dynamics and emphasize the importance of including this process when modelling shoreline evolution in coastal embayments. Full article

This study aimed to develop a methodological framework for predicting shoreline dynamics using machine learning techniques, focusing on analyzing generalized data without distinguishing areas with higher or lower retreat rates. Three sites along the southwestern Kara Sea coast were selected for this investigation. The study analyzed key coastal features, including lithology, permafrost, and geomorphology, using a combination of field studies and remote sensing data. Essential datasets were compiled and formatted for computer-based analysis. These datasets included information on permafrost and the geomorphological characteristics of the coastal zone, climatic factors influencing the shoreline, and measurements of bluff top positions and retreat rates over defined time periods. The positions of the bluff tops were determined through a combination of imagery with varying resolutions and field measurements. A novel aspect of the study involved employing geostatistical methods to analyze erosion rates, providing new insights into the shoreline dynamics. The data analysis allowed us to identify coastal areas experiencing the most significant changes. By continually refining neural network models with these datasets, we can improve our understanding of the complex interactions between natural factors and shoreline evolution, ultimately aiding in developing effective coastal management strategies. Full article

Coastal zones, particularly sandy beaches, are highly dynamic environments subject to a variety of natural and anthropogenic forcings. Instantaneous shoreline is a widely used indicator of beach changes in image-based applications, and it can display undulations at different spatial and temporal scales. Megacusps, periodic seaward and landward shoreline perturbations, are an example of such undulations that can significantly modify beach width and impact its usability. Traditionally, the study of these phenomena relied on video monitoring systems, which provide high-frequency imagery but limited spatial coverage. Instead, this study explored the potential of employing multispectral satellite-derived shorelines, specifically from Sentinel-2 (S2) and PlanetScope (PLN) platforms, for characterizing and monitoring megacusps’ formation and their dynamics over time. First, a tool was developed and validated to guarantee accurate shoreline detection, based on a combination of spectral indices, along with both thresholding and unsupervised clustering techniques. Validation of this shoreline detection phase was performed on three micro-tidal Mediterranean beaches, comparing with high-resolution orthomosaics and in-situ GNSS data, obtaining a good subpixel accuracy (with a mean absolute deviation of 1.5–5.5 m depending on the satellite type). Second, a tool for megacusp characterization was implemented and subsequent validation with reference data proved that satellite-derived shorelines could be used to robustly and accurately describe megacusps. The methodology could not only capture their amplitude and wavelength (of the order of 10 and 100 m, respectively) but also monitor their weekly–daily evolution using different potential metrics, thanks to combining S2 and PLN imagery. Our findings demonstrate that multispectral satellite imagery provides a viable and scalable solution for monitoring shoreline megacusp undulations, enhancing our understanding and offering an interesting option for coastal management. Full article