Pub Date : 2024-06-14DOI: 10.3390/geosciences14060167
Roberta Somma
In the past fifteen years, the contamination of the Italian marine coastal environments by asbestos cement materials (ACMs) represents a known crux mostly reported or denounced by mass media and environmental associations. A recent research reporting compositional and textural data related to ACMs found in the beach deposits of a protected natural reserve (Cape Peloro, Messina, Italy) induced the author to perform new petrographic and textural analyses on the Cape Peloro beach sands, pebbles, cobbles (BSPC), and technofossils (bricks, tails, slab, concrete), associated with the previously studied ACMs, in order to compare the data with those of the ACMs previously reported in the literature. The petrographic investigations allowed the author to determine that beach sands and weakly gravelly sands were characterized by a quartzo–lithic signature, being mainly composed of metamorphic grains of quartz (50–60%) and metamorphic lithics (40–50%, mainly composed of polymineral quartz + microcline, quartz + plagioclase, quartz + biotite, quartz + muscovite grains, and monomineral opaque minerals, plagioclase, k-feldspar, and almandine garnet grains), whereas the pebbles and cobbles were made of acid intrusive (granitoids) and metamorphic rocks (gneiss, augen gneiss prevailing). Pebbles and cobbles made up of porphyroids could derive from the cannibalization of the underlying lower to middle Pleistocene siliciclastic deposits of the Messina Formation. Differently, the gneiss, augen gneiss, and granitoids forming the beach pebbles and cobbles, being present both in the crystalline rocks of the Aspromonte Unit and in the clasts of the SGMF, could originate from both of them. Textural investigations allowed the author to characterize grain size, shape parameters, and roundness in the beach deposits. These were mostly composed of sands and weakly gravelly sands with medium grains. Parameters, such as elongation and flatness, showed higher values in the BSPC than in the technofossils. The shapes of the BSPC were mostly from oblate to equant, whereas the shapes of the technofossils were mostly from bladed to oblate. The main differences depended on the original shape of the technofossils, being mostly platy, and their softer composition. The roundness was from angular to sub-rounded. In the Ionian coast of the Cape Peloro peninsula, the source areas for the well-rounded ACM found on the beach and in the beach deposits could have at least four different origins: (i) Possible landfills widespread since the 1970s in the intensively urbanized coastal areas. (ii) Direct abandonment in the coastal area. (iii) Direct abandonment in the streams. (iv) Activities to counteract the erosion/lack of sediment using non-conforming materials. Considering the diffused damage caused by the coastal erosion affecting most of the Italian coast and the obvious increasing dispersion of the asbestos fibers from the ACMs over time, effectual counter actions to prevent further contamina
{"title":"Petrographic and Textural Characterization of Beach Sands Contaminated by Asbestos Cement Materials (Cape Peloro, Messina, Italy): Hazardous Human-Environmental Relationships","authors":"Roberta Somma","doi":"10.3390/geosciences14060167","DOIUrl":"https://doi.org/10.3390/geosciences14060167","url":null,"abstract":"In the past fifteen years, the contamination of the Italian marine coastal environments by asbestos cement materials (ACMs) represents a known crux mostly reported or denounced by mass media and environmental associations. A recent research reporting compositional and textural data related to ACMs found in the beach deposits of a protected natural reserve (Cape Peloro, Messina, Italy) induced the author to perform new petrographic and textural analyses on the Cape Peloro beach sands, pebbles, cobbles (BSPC), and technofossils (bricks, tails, slab, concrete), associated with the previously studied ACMs, in order to compare the data with those of the ACMs previously reported in the literature. The petrographic investigations allowed the author to determine that beach sands and weakly gravelly sands were characterized by a quartzo–lithic signature, being mainly composed of metamorphic grains of quartz (50–60%) and metamorphic lithics (40–50%, mainly composed of polymineral quartz + microcline, quartz + plagioclase, quartz + biotite, quartz + muscovite grains, and monomineral opaque minerals, plagioclase, k-feldspar, and almandine garnet grains), whereas the pebbles and cobbles were made of acid intrusive (granitoids) and metamorphic rocks (gneiss, augen gneiss prevailing). Pebbles and cobbles made up of porphyroids could derive from the cannibalization of the underlying lower to middle Pleistocene siliciclastic deposits of the Messina Formation. Differently, the gneiss, augen gneiss, and granitoids forming the beach pebbles and cobbles, being present both in the crystalline rocks of the Aspromonte Unit and in the clasts of the SGMF, could originate from both of them. Textural investigations allowed the author to characterize grain size, shape parameters, and roundness in the beach deposits. These were mostly composed of sands and weakly gravelly sands with medium grains. Parameters, such as elongation and flatness, showed higher values in the BSPC than in the technofossils. The shapes of the BSPC were mostly from oblate to equant, whereas the shapes of the technofossils were mostly from bladed to oblate. The main differences depended on the original shape of the technofossils, being mostly platy, and their softer composition. The roundness was from angular to sub-rounded. In the Ionian coast of the Cape Peloro peninsula, the source areas for the well-rounded ACM found on the beach and in the beach deposits could have at least four different origins: (i) Possible landfills widespread since the 1970s in the intensively urbanized coastal areas. (ii) Direct abandonment in the coastal area. (iii) Direct abandonment in the streams. (iv) Activities to counteract the erosion/lack of sediment using non-conforming materials. Considering the diffused damage caused by the coastal erosion affecting most of the Italian coast and the obvious increasing dispersion of the asbestos fibers from the ACMs over time, effectual counter actions to prevent further contamina","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"40 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141338387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.3390/geosciences14060169
George H. Scott
Because of their excellent preservation record, testate zooplankters provide valuable proxy ocean climate data through the Quaternary–Recent. Commonly, specimen abundances are sought, which are time-consuming to collect manually and require taxonomic expertise. While machine learning models obviate these problems, it is questioned whether the current use of specimens selected by experts to train the models impartially captures the variation within the source populations. To illustrate the potential value of the latter and their relevance to the selection of representative specimens, the 2D outline shape of the planktonic foraminifer Truncorotalia crassaformis from four globally distributed, late-Quaternary–modern collections is examined. Large intra-sample variation is attributed to changes in the size and shape of the last-formed chamber, which often departs radically from its predecessors. Similar outlines occur in each collection, and no single axial shape is dominant when the aggregated data, aligned on their centroids and adjusted for size and position, are projected onto their principal components. Several partitions based on distance from the centroid of the standardized data are considered as sources of representative specimens, with that at ±1.645σ (standard deviations, nominally 90%) suggested as suitable. This procedure obviates the need for expert-based consensus sampling; for greater environmental resolution, it can be applied to individual water mass samples. It assists, but does not fully resolve, the following basic diagnostic question: which characters separate Truncorotalia crassaformis from its relatives?
{"title":"Representing Zooplankters: An Example from the Foraminifera","authors":"George H. Scott","doi":"10.3390/geosciences14060169","DOIUrl":"https://doi.org/10.3390/geosciences14060169","url":null,"abstract":"Because of their excellent preservation record, testate zooplankters provide valuable proxy ocean climate data through the Quaternary–Recent. Commonly, specimen abundances are sought, which are time-consuming to collect manually and require taxonomic expertise. While machine learning models obviate these problems, it is questioned whether the current use of specimens selected by experts to train the models impartially captures the variation within the source populations. To illustrate the potential value of the latter and their relevance to the selection of representative specimens, the 2D outline shape of the planktonic foraminifer Truncorotalia crassaformis from four globally distributed, late-Quaternary–modern collections is examined. Large intra-sample variation is attributed to changes in the size and shape of the last-formed chamber, which often departs radically from its predecessors. Similar outlines occur in each collection, and no single axial shape is dominant when the aggregated data, aligned on their centroids and adjusted for size and position, are projected onto their principal components. Several partitions based on distance from the centroid of the standardized data are considered as sources of representative specimens, with that at ±1.645σ (standard deviations, nominally 90%) suggested as suitable. This procedure obviates the need for expert-based consensus sampling; for greater environmental resolution, it can be applied to individual water mass samples. It assists, but does not fully resolve, the following basic diagnostic question: which characters separate Truncorotalia crassaformis from its relatives?","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"74 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141338208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-13DOI: 10.3390/geosciences14060166
G. Tomasello, D. Porcino
During an earthquake, excess pore water pressure generation in saturated silty sands causes a reduction in shear strength and even liquefaction of the soil. A comprehensive experimental program consisting of undrained cyclic simple-shear tests was undertaken to explore the key factors affecting the energy-based excess pore water pressure generation models for non-plastic silty sands. The examined influencing factors were non-plastic fines content (less than and greater than the threshold value ≅ 25%), packing density, vertical effective stress, applied cyclic stress ratio, and soil fabric. The relationship between excess pore water pressure ratio and dissipated energy per unit volume was found to be mainly dependent on the relative density and fines content of soil, whereas the cyclic stress ratio, initial vertical effective stress, and soil fabric (i.e. the reconstitution method) appeared to have a minor impact. A revision of the original energy-based model developed for clean sand by Berrill and Davis was proposed to improve prediction accuracy in terms of residual excess pore water pressures versus normalised cumulative dissipated energy. Nonlinear multivariable regression analyses were performed to develop correlations for the calibration parameters of the revised model. Lastly, these correlations were validated through additional cyclic simple-shear tests performed on different silty sands recovered at a site where liquefaction occurred after the 2012 Emilia Romagna (Italy) earthquake.
地震期间，饱和淤泥质砂中产生的过剩孔隙水压力会导致土壤的抗剪强度降低，甚至液化。为了探索影响非塑性淤泥质砂基于能量的过剩孔隙水压力产生模型的关键因素，我们开展了一项综合实验计划，包括不排水循环单剪试验。所研究的影响因素包括非塑性细粒含量（小于和大于临界值≅25%）、堆积密度、垂直有效应力、外加循环应力比和土壤结构。研究发现，过剩孔隙水压力比与单位体积耗散能量之间的关系主要取决于土壤的相对密度和细粒含量，而循环应力比、初始垂直有效应力和土壤结构（即重组方法）似乎影响较小。建议对 Berrill 和 Davis 针对洁净砂土开发的基于能量的原始模型进行修订，以提高残余过剩孔隙水压力与归一化累积耗散能量的预测精度。对修订模型的校准参数进行了非线性多变量回归分析，以建立相关关系。最后，通过在 2012 年意大利艾米利亚-罗马涅地震后发生液化的一个地点对不同的淤泥质砂进行额外的循环简单剪切试验，对这些相关性进行了验证。
{"title":"Energy-Based Pore Pressure Generation Models in Silty Sands under Earthquake Loading","authors":"G. Tomasello, D. Porcino","doi":"10.3390/geosciences14060166","DOIUrl":"https://doi.org/10.3390/geosciences14060166","url":null,"abstract":"During an earthquake, excess pore water pressure generation in saturated silty sands causes a reduction in shear strength and even liquefaction of the soil. A comprehensive experimental program consisting of undrained cyclic simple-shear tests was undertaken to explore the key factors affecting the energy-based excess pore water pressure generation models for non-plastic silty sands. The examined influencing factors were non-plastic fines content (less than and greater than the threshold value ≅ 25%), packing density, vertical effective stress, applied cyclic stress ratio, and soil fabric. The relationship between excess pore water pressure ratio and dissipated energy per unit volume was found to be mainly dependent on the relative density and fines content of soil, whereas the cyclic stress ratio, initial vertical effective stress, and soil fabric (i.e. the reconstitution method) appeared to have a minor impact. A revision of the original energy-based model developed for clean sand by Berrill and Davis was proposed to improve prediction accuracy in terms of residual excess pore water pressures versus normalised cumulative dissipated energy. Nonlinear multivariable regression analyses were performed to develop correlations for the calibration parameters of the revised model. Lastly, these correlations were validated through additional cyclic simple-shear tests performed on different silty sands recovered at a site where liquefaction occurred after the 2012 Emilia Romagna (Italy) earthquake.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"46 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141345245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.3390/geosciences14060162
Adel Asadi, Snehamoy Chatterjee
Multiple-point geostatistics (MPS) is an established tool for the uncertainty quantification of Earth systems modeling, particularly when dealing with the complexity and heterogeneity of geological data. This study presents a novel pixel-based MPS method for modeling spatial data using advanced machine-learning algorithms. Pixel-based multiple-point simulation implies the sequential modeling of individual points on the simulation grid, one at a time, by borrowing spatial information from the training image and honoring the conditioning data points. The developed methodology is based on the mapping of the training image patterns database using the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm for dimensionality reduction, and the clustering of patterns by applying the Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, as an efficient unsupervised classification technique. For the automation, optimization, and input parameter tuning, multiple stages are implemented, including entropy-based determination of the template size and a k-nearest neighbors search for clustering parameter selection, to ensure the proposed method does not require the user’s interference. The proposed model is validated using synthetic two- and three-dimensional datasets, both for conditional and unconditional simulations, and runtime information is provided. Finally, the method is applied to a case study gold mine for stochastic orebody modeling. To demonstrate the computational efficiency and accuracy of the proposed method, a two-dimensional training image with 101 by 101 pixels is simulated for 100 conditional realizations in 453 s (~4.5 s per realization) using only 361 hard data points (~3.5% of the simulation grid), and the resulting average simulation has a good visual match and only an 11.8% pixel-wise mismatch with the training image.
多点地质统计（MPS）是地球系统建模不确定性量化的一种成熟工具，尤其是在处理地质数据的复杂性和异质性时。本研究提出了一种新颖的基于像素的 MPS 方法，利用先进的机器学习算法对空间数据进行建模。基于像素的多点模拟意味着通过从训练图像中借用空间信息并尊重调节数据点，对模拟网格上的单个点进行一次一个的顺序建模。所开发的方法基于使用 t 分布随机邻域嵌入（t-SNE）算法对训练图像模式数据库进行映射以降低维度，并通过应用基于密度的有噪声应用空间聚类（DBSCAN）算法对模式进行聚类，以此作为一种高效的无监督分类技术。在自动化、优化和输入参数调整方面，实现了多个阶段，包括基于熵的模板大小确定和用于聚类参数选择的 k 近邻搜索，以确保所提出的方法无需用户干预。利用合成的二维和三维数据集对所提出的模型进行了有条件和无条件模拟验证，并提供了运行时间信息。最后，该方法被应用于一个案例研究金矿的随机矿体建模。为了证明所提方法的计算效率和准确性，仅使用 361 个硬数据点（约占模拟网格的 3.5%），在 453 秒（约 4.5 秒/次）内对 101 x 101 像素的二维训练图像进行了 100 次有条件实现模拟，所得到的平均模拟结果与训练图像具有良好的视觉匹配，像素错配率仅为 11.8%。
{"title":"Pixel-MPS: Stochastic Embedding and Density-Based Clustering of Image Patterns for Pixel-Based Multiple-Point Geostatistical Simulation","authors":"Adel Asadi, Snehamoy Chatterjee","doi":"10.3390/geosciences14060162","DOIUrl":"https://doi.org/10.3390/geosciences14060162","url":null,"abstract":"Multiple-point geostatistics (MPS) is an established tool for the uncertainty quantification of Earth systems modeling, particularly when dealing with the complexity and heterogeneity of geological data. This study presents a novel pixel-based MPS method for modeling spatial data using advanced machine-learning algorithms. Pixel-based multiple-point simulation implies the sequential modeling of individual points on the simulation grid, one at a time, by borrowing spatial information from the training image and honoring the conditioning data points. The developed methodology is based on the mapping of the training image patterns database using the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm for dimensionality reduction, and the clustering of patterns by applying the Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, as an efficient unsupervised classification technique. For the automation, optimization, and input parameter tuning, multiple stages are implemented, including entropy-based determination of the template size and a k-nearest neighbors search for clustering parameter selection, to ensure the proposed method does not require the user’s interference. The proposed model is validated using synthetic two- and three-dimensional datasets, both for conditional and unconditional simulations, and runtime information is provided. Finally, the method is applied to a case study gold mine for stochastic orebody modeling. To demonstrate the computational efficiency and accuracy of the proposed method, a two-dimensional training image with 101 by 101 pixels is simulated for 100 conditional realizations in 453 s (~4.5 s per realization) using only 361 hard data points (~3.5% of the simulation grid), and the resulting average simulation has a good visual match and only an 11.8% pixel-wise mismatch with the training image.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"105 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.3390/geosciences14060164
Jamaluddin, Kateřina Schöpfer, M. Wagreich, Maria, S. Gier, Douaa Fathy
The Upper Miocene–Pliocene Kampungbaru Formation crops out in the easternmost part of the Lower Kutai Basin, Indonesia. The sedimentological analysis of seven outcrops was carried out, and a total of twenty-five samples from these outcrops was analyzed for bulk geochemistry, organic petrography, and bulk and clay mineralogy to assess the effect of the climate and depositional environment on organic matter enrichment. The Kampungbaru Formation consists of interbedded sandstone, siltstone, claystone, and thick coal beds, which were classified into eleven lithofacies. Subsequently, seven facies associations were identified, namely the fluvial-dominated distributary channel, sheet-like sandstone, tide-influenced distributary channel, mouth bar, crevasse splay, delta plain, and delta front. The coal facies generally have a high amount of total organic carbon (TOC, 5.1–16.9; avg. 10.11 wt.%), and non-coal layers range from 0.03 to 4.22 wt.% (avg. 1.54 wt.%). The dominant maceral is vitrinite, while liptinite occurs only rarely in the samples. Organic matter is inferred to have originated from terrestrial plants growing in mangrove swamps. Identified clay minerals include varying proportions of kaolinite, illite, chlorite, and mixed layer illite/smectite (I/S). Kaolinite, which commonly constitutes up to 30% of the clay volume, indicates intensive chemical weathering during a warm and humid climate. In accordance with the Köppen climate classification, the paleoclimate during the deposition of the Kampungbaru Formation is classified as type Af, which is a tropical rainforest. Tropical climate was favorable for the growth of higher plants and deposition of organic matter under anoxic conditions and led to higher amounts of TOC in the Kampungbaru Formation.
{"title":"Effect of Depositional Environment and Climate on Organic Matter Enrichment in Sediments of the Upper Miocene—Pliocene Kampungbaru Formation, Lower Kutai Basin, Indonesia","authors":"Jamaluddin, Kateřina Schöpfer, M. Wagreich, Maria, S. Gier, Douaa Fathy","doi":"10.3390/geosciences14060164","DOIUrl":"https://doi.org/10.3390/geosciences14060164","url":null,"abstract":"The Upper Miocene–Pliocene Kampungbaru Formation crops out in the easternmost part of the Lower Kutai Basin, Indonesia. The sedimentological analysis of seven outcrops was carried out, and a total of twenty-five samples from these outcrops was analyzed for bulk geochemistry, organic petrography, and bulk and clay mineralogy to assess the effect of the climate and depositional environment on organic matter enrichment. The Kampungbaru Formation consists of interbedded sandstone, siltstone, claystone, and thick coal beds, which were classified into eleven lithofacies. Subsequently, seven facies associations were identified, namely the fluvial-dominated distributary channel, sheet-like sandstone, tide-influenced distributary channel, mouth bar, crevasse splay, delta plain, and delta front. The coal facies generally have a high amount of total organic carbon (TOC, 5.1–16.9; avg. 10.11 wt.%), and non-coal layers range from 0.03 to 4.22 wt.% (avg. 1.54 wt.%). The dominant maceral is vitrinite, while liptinite occurs only rarely in the samples. Organic matter is inferred to have originated from terrestrial plants growing in mangrove swamps. Identified clay minerals include varying proportions of kaolinite, illite, chlorite, and mixed layer illite/smectite (I/S). Kaolinite, which commonly constitutes up to 30% of the clay volume, indicates intensive chemical weathering during a warm and humid climate. In accordance with the Köppen climate classification, the paleoclimate during the deposition of the Kampungbaru Formation is classified as type Af, which is a tropical rainforest. Tropical climate was favorable for the growth of higher plants and deposition of organic matter under anoxic conditions and led to higher amounts of TOC in the Kampungbaru Formation.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"9 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.3390/geosciences14060165
Gregor M. Rink, Eugene J. Farrell, Gordon R. M. Bromley
Globally, the rapid retreat of coastal cliffs poses a profound risk to property, transport infrastructure, and public safety. To quantify and compare cliff top and cliff face retreat and identify erosion processes, this study combines historical (1842–2000) maps and orthophotos with contemporary UAV surveys (2019–2023) to quantify cliff top and cliff face retreat along a 240 m wide coastal drumlin in Galway Bay, Ireland. Retreat rates for the cliff top and cliff face were calculated using 2D mapping and 3D modelling, respectively. Critically, the choice of method has a significant impact on calculated rates of cliff top retreat, with output from the 2D mapping approach (0.14 +/− 0.02 m yr−1) being double that of the 3D modelling approach (0.08 +/− 0.02 m year−1). The aperiodic development of a talus cone, which temporarily protects the cliff from storm waves, also influences estimates of cliff retreat. The repeat cycles of talus slope formation and removal in this high wave energy environment suggest that the drumlin scarp transitions between a periodically transport-limited and supply-limited system over short- and long-time periods, respectively, on the continuum of cliff types. These results warrant further research to identify and quantify the rates, patterns, drivers (marine and subaerial processes), and timing of cliff retreat in response to climate change.
{"title":"Quantifying Aperiodic Cliff Top and Cliff Face Retreat Rates for an Eroding Drumlin on Ireland’s Atlantic Coast Using Structure-from-Motion","authors":"Gregor M. Rink, Eugene J. Farrell, Gordon R. M. Bromley","doi":"10.3390/geosciences14060165","DOIUrl":"https://doi.org/10.3390/geosciences14060165","url":null,"abstract":"Globally, the rapid retreat of coastal cliffs poses a profound risk to property, transport infrastructure, and public safety. To quantify and compare cliff top and cliff face retreat and identify erosion processes, this study combines historical (1842–2000) maps and orthophotos with contemporary UAV surveys (2019–2023) to quantify cliff top and cliff face retreat along a 240 m wide coastal drumlin in Galway Bay, Ireland. Retreat rates for the cliff top and cliff face were calculated using 2D mapping and 3D modelling, respectively. Critically, the choice of method has a significant impact on calculated rates of cliff top retreat, with output from the 2D mapping approach (0.14 +/− 0.02 m yr−1) being double that of the 3D modelling approach (0.08 +/− 0.02 m year−1). The aperiodic development of a talus cone, which temporarily protects the cliff from storm waves, also influences estimates of cliff retreat. The repeat cycles of talus slope formation and removal in this high wave energy environment suggest that the drumlin scarp transitions between a periodically transport-limited and supply-limited system over short- and long-time periods, respectively, on the continuum of cliff types. These results warrant further research to identify and quantify the rates, patterns, drivers (marine and subaerial processes), and timing of cliff retreat in response to climate change.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.3390/geosciences14060161
Riccardo Salvini, C. Vanneschi, C. Lanciano, Renzo Maseroli
Change of Affiliation [...]
更改隶属关系 [...]
{"title":"Correction: Salvini et al. Ground Displacements Estimation through GNSS and Geometric Leveling: A Geological Interpretation of the 2016–2017 Seismic Sequence in Central Italy. Geosciences 2022, 12, 167","authors":"Riccardo Salvini, C. Vanneschi, C. Lanciano, Renzo Maseroli","doi":"10.3390/geosciences14060161","DOIUrl":"https://doi.org/10.3390/geosciences14060161","url":null,"abstract":"Change of Affiliation [...]","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"35 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141355565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.3390/geosciences14060163
Kuo Chieh Chao, Tanawoot Kongsung, K. Saowiang
Road embankments along irrigation canals, constructed on soft Bangkok clay, have always been unstable. Numerous studies have shown that rapid drawdown of water level may be one of the main causes, while vehicle cyclic loading may also contribute to embankment failure. This study aims to investigate the impact of vehicle loading on the failure of embankments built on Bangkok soft clay. The behavior of soft Bangkok clay under vehicle load has been investigated by employing conventional and dynamic triaxial techniques, and finite element method (FEM). This study also examined the effects of soft clay thickness and cyclic loading with different magnitudes and frequencies. The laboratory testing results indicate that the threshold stress of the soft clay is estimated to be approximately three-fourths of the undrained shear strength of the soil. The reduction in effective stress in the soft clay is caused by varied frequencies and thicknesses of the clay. Based on the analysis results, it has been proven that the cyclic loads exerted by vehicles solely are insufficient to cause the embankment to collapse. Nevertheless, the repetitive loading of vehicles may result in a one-quarter decrease in the embankment’s factor of safety.
{"title":"Effect of Vehicle Cyclic Loading on the Failure of Canal Embankment on Soft Clay Deposit","authors":"Kuo Chieh Chao, Tanawoot Kongsung, K. Saowiang","doi":"10.3390/geosciences14060163","DOIUrl":"https://doi.org/10.3390/geosciences14060163","url":null,"abstract":"Road embankments along irrigation canals, constructed on soft Bangkok clay, have always been unstable. Numerous studies have shown that rapid drawdown of water level may be one of the main causes, while vehicle cyclic loading may also contribute to embankment failure. This study aims to investigate the impact of vehicle loading on the failure of embankments built on Bangkok soft clay. The behavior of soft Bangkok clay under vehicle load has been investigated by employing conventional and dynamic triaxial techniques, and finite element method (FEM). This study also examined the effects of soft clay thickness and cyclic loading with different magnitudes and frequencies. The laboratory testing results indicate that the threshold stress of the soft clay is estimated to be approximately three-fourths of the undrained shear strength of the soil. The reduction in effective stress in the soft clay is caused by varied frequencies and thicknesses of the clay. Based on the analysis results, it has been proven that the cyclic loads exerted by vehicles solely are insufficient to cause the embankment to collapse. Nevertheless, the repetitive loading of vehicles may result in a one-quarter decrease in the embankment’s factor of safety.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"35 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141358977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-09DOI: 10.3390/geosciences14060160
K. Nikolakopoulos, A. Kyriou, Ioannis K. Koukouvelas
Intense long-duration rainfall or extreme precipitation in a few hours can provoke many simultaneous shallow landslides. In the past, the term multi-occurrence regional landslides (MORLEs) was proposed to describe such phenomena. In the current study, unmanned aerial vehicles in combination with a global navigation satellite system sensor and geographical information systems seem to be the ideal solution for the rapid assessment of many landslides occurring in Aitoloakarnania Prefecture, Western Greece. Fourteen landslides were accurately mapped within a few working days, and precise orthophotos and reports were created and submitted to the local authorities. The analysis of meteorological data proved that there is a peak in precipitation height that triggers the MORLEs in the specific area. Specifically, the value of the daily precipitation was defined at 80 mm.
{"title":"UAV, GNSS, and GIS for the Rapid Assessment of Multi-Occurrence Landslides","authors":"K. Nikolakopoulos, A. Kyriou, Ioannis K. Koukouvelas","doi":"10.3390/geosciences14060160","DOIUrl":"https://doi.org/10.3390/geosciences14060160","url":null,"abstract":"Intense long-duration rainfall or extreme precipitation in a few hours can provoke many simultaneous shallow landslides. In the past, the term multi-occurrence regional landslides (MORLEs) was proposed to describe such phenomena. In the current study, unmanned aerial vehicles in combination with a global navigation satellite system sensor and geographical information systems seem to be the ideal solution for the rapid assessment of many landslides occurring in Aitoloakarnania Prefecture, Western Greece. Fourteen landslides were accurately mapped within a few working days, and precise orthophotos and reports were created and submitted to the local authorities. The analysis of meteorological data proved that there is a peak in precipitation height that triggers the MORLEs in the specific area. Specifically, the value of the daily precipitation was defined at 80 mm.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141366859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-07DOI: 10.3390/geosciences14060159
Dimitar Ouzounov, G. Khachikyan
A joint analysis of solar wind, geomagnetic field, and earthquake catalog data showed that before the catastrophic M = 7.8 and M = 7.5 Kahramanmaras earthquake sequence on 6 February 2023, a closed strong magnetic storm occurred on 7 November 2022, SYM/H = −117 nT. The storm started at 08:04 UT. At this time, the high-latitudinal part of Turkey’s longitudinal region of future epicenters was located under the polar cusp, where the solar wind plasma would directly access the Earth’s environment. The time delay between storm onset and earthquake occurrence was ~91 days. We analyzed all seven strong (M7+) earthquakes from 1967 to 2020 to verify the initial findings. A similar pattern has been revealed for all events. The time delay between magnetic storm onset and earthquake occurrence varies from days to months. To continue these investigations, a retrospective analysis of seismic and other geophysical parameters just after preceded geomagnetic storms in the epicenter areas is desirable.
{"title":"On the Impact of Geospace Weather on the Occurrence of M7.8/M7.5 Earthquakes on 6 February 2023 (Turkey), Possibly Associated with the Geomagnetic Storm of 7 November 2022","authors":"Dimitar Ouzounov, G. Khachikyan","doi":"10.3390/geosciences14060159","DOIUrl":"https://doi.org/10.3390/geosciences14060159","url":null,"abstract":"A joint analysis of solar wind, geomagnetic field, and earthquake catalog data showed that before the catastrophic M = 7.8 and M = 7.5 Kahramanmaras earthquake sequence on 6 February 2023, a closed strong magnetic storm occurred on 7 November 2022, SYM/H = −117 nT. The storm started at 08:04 UT. At this time, the high-latitudinal part of Turkey’s longitudinal region of future epicenters was located under the polar cusp, where the solar wind plasma would directly access the Earth’s environment. The time delay between storm onset and earthquake occurrence was ~91 days. We analyzed all seven strong (M7+) earthquakes from 1967 to 2020 to verify the initial findings. A similar pattern has been revealed for all events. The time delay between magnetic storm onset and earthquake occurrence varies from days to months. To continue these investigations, a retrospective analysis of seismic and other geophysical parameters just after preceded geomagnetic storms in the epicenter areas is desirable.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":" 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141374164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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