Pub Date : 2024-08-08DOI: 10.3390/geosciences14080212
E. Kasatkina, O. Shumilov, M. Timonen
The sun’s activity role in climate change has become a topic of debate. According to data from the IPCC, the global average temperature has shown an increasing trend since 1850, with an average increase of 0.06 °C/decade. Our analysis of summer temperature records from five weather stations in northern Fennoscandia (65°–70.4° N) revealed an increasing trend, with a range of 0.09 °C/decade to 0.15 °C/decade. However, due to the short duration of instrumental records, it is not possible to accurately assess and predict climate changes on centennial and millennial timescales. In this study, we used the Finnish super-long (~7600 years) tree-ring chronology to create a climate prediction for the 21st century. We applied a method that combines a long short-term memory (LSTM) neural network with the continuous wavelet transform and wavelet filtering in order to make climate change predictions. This approach revealed a significant decrease in tree-ring growth over the near term (2063–2073). The predicted decrease in tree-ring growth (and regional temperature) is thought to be a result of a new grand solar minimum, which may lead to Little Ice Age-like climatic conditions. This result is significant for understanding current climate processes and assessing potential environmental and socio-economic risks on a global and regional level, including in the area of the Arctic shipping routes.
{"title":"Neural Network-Based Climate Prediction for the 21st Century Using the Finnish Multi-Millennial Tree-Ring Chronology","authors":"E. Kasatkina, O. Shumilov, M. Timonen","doi":"10.3390/geosciences14080212","DOIUrl":"https://doi.org/10.3390/geosciences14080212","url":null,"abstract":"The sun’s activity role in climate change has become a topic of debate. According to data from the IPCC, the global average temperature has shown an increasing trend since 1850, with an average increase of 0.06 °C/decade. Our analysis of summer temperature records from five weather stations in northern Fennoscandia (65°–70.4° N) revealed an increasing trend, with a range of 0.09 °C/decade to 0.15 °C/decade. However, due to the short duration of instrumental records, it is not possible to accurately assess and predict climate changes on centennial and millennial timescales. In this study, we used the Finnish super-long (~7600 years) tree-ring chronology to create a climate prediction for the 21st century. We applied a method that combines a long short-term memory (LSTM) neural network with the continuous wavelet transform and wavelet filtering in order to make climate change predictions. This approach revealed a significant decrease in tree-ring growth over the near term (2063–2073). The predicted decrease in tree-ring growth (and regional temperature) is thought to be a result of a new grand solar minimum, which may lead to Little Ice Age-like climatic conditions. This result is significant for understanding current climate processes and assessing potential environmental and socio-economic risks on a global and regional level, including in the area of the Arctic shipping routes.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141928162","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 : 2024-07-26DOI: 10.3390/geosciences14080199
Artur Dyczko
The quality of coking coal is vital in steelmaking, impacting final product quality and process efficiency. Conventional forecasting methods often rely on empirical models and expert judgment, which may lack accuracy and scalability. Previous research has explored various methods for forecasting coking coal quality parameters, yet these conventional methods frequently fall short in terms of accuracy and adaptability to different mining conditions. Existing forecasting techniques for coking coal quality are limited in their precision and scalability, necessitating the development of more accurate and efficient methods. This study aims to enhance the accuracy and efficiency of forecasting coking coal quality parameters by employing neural networks and artificial intelligence algorithms, specifically in the context of Knurow and Szczyglowice mines. The research involves gathering historical data on various coking coal quality parameters, including a proximate and ultimate analysis, to train and test neural network models using the Group Method of Data Handling (GMDH). Real-world data from Knurow and Szczyglowice mines’ coal production facilities form the basis of this case study. The integration of neural networks and artificial intelligence techniques significantly improves the accuracy of predicting key quality parameters such as ash content, sulfur content, volatile matter, and calorific value. This study also examines the impact of these quality indicators on operational costs and highlights the importance of final indicators like the Coke Reactivity Index (CRI) and Coke Strength after Reaction (CSR) in expanding industrial reserve concepts. Model performance is evaluated using metrics such as mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The findings demonstrate the effectiveness of these advanced techniques in enhancing predictive modeling in the mining industry, optimizing production processes, and improving overall operational efficiency. Additionally, this research offers insights into the practical implementation of advanced analytics tools for predictive maintenance and decision-making support within the mining sector.
{"title":"The Perspective of Using Neural Networks and Machine Learning Algorithms for Modelling and Forecasting the Quality Parameters of Coking Coal—A Case Study","authors":"Artur Dyczko","doi":"10.3390/geosciences14080199","DOIUrl":"https://doi.org/10.3390/geosciences14080199","url":null,"abstract":"The quality of coking coal is vital in steelmaking, impacting final product quality and process efficiency. Conventional forecasting methods often rely on empirical models and expert judgment, which may lack accuracy and scalability. Previous research has explored various methods for forecasting coking coal quality parameters, yet these conventional methods frequently fall short in terms of accuracy and adaptability to different mining conditions. Existing forecasting techniques for coking coal quality are limited in their precision and scalability, necessitating the development of more accurate and efficient methods. This study aims to enhance the accuracy and efficiency of forecasting coking coal quality parameters by employing neural networks and artificial intelligence algorithms, specifically in the context of Knurow and Szczyglowice mines. The research involves gathering historical data on various coking coal quality parameters, including a proximate and ultimate analysis, to train and test neural network models using the Group Method of Data Handling (GMDH). Real-world data from Knurow and Szczyglowice mines’ coal production facilities form the basis of this case study. The integration of neural networks and artificial intelligence techniques significantly improves the accuracy of predicting key quality parameters such as ash content, sulfur content, volatile matter, and calorific value. This study also examines the impact of these quality indicators on operational costs and highlights the importance of final indicators like the Coke Reactivity Index (CRI) and Coke Strength after Reaction (CSR) in expanding industrial reserve concepts. Model performance is evaluated using metrics such as mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The findings demonstrate the effectiveness of these advanced techniques in enhancing predictive modeling in the mining industry, optimizing production processes, and improving overall operational efficiency. Additionally, this research offers insights into the practical implementation of advanced analytics tools for predictive maintenance and decision-making support within the mining sector.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"9 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801771","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 : 2024-07-26DOI: 10.3390/geosciences14080198
Shiyin Sha, A. Dyson, Gholamreza Kefayati, A. Tolooiyan
Protective structures play a vital role in mitigating the risks associated with debris flows, yet assessing their performance poses crucial challenges for their real-world effectiveness. This study proposes a comprehensive procedure for evaluating the performance of protective structures exposed to impacts from media transported by large debris flow events. The method combines numerical modelling with site conditions for existing structures along the Hobart Rivulet in Tasmania, Australia. The Coupled Eulerian Lagrangian (CEL) model was validated by comparing simulation results with experimental data, demonstrating high agreement. Utilising three-dimensional modelling of debris flow–boulder interactions over the Hobart Rivulet terrain, boulder velocities were estimated for subsequent finite element analyses. Importantly, a model of interaction between boulders and I-beam posts was established, facilitating a comparative assessment of five distinct I-beam barrier systems defined as Type A to E, which are currently in use at the site. Simulation results reveal larger boulders display a slower increase in their velocities over the 3D terrain. Introducing a key metric, the failure ratio, enable a mechanism for comparative assessments of these barrier systems. Notably, the Type E barriers demonstrate superior performance due to fewer weak points within the structure. The combined CEL and FE assessments allow for multiple aspects of the interactions between debris flows, boulders, and structures to be considered, including structural failure and deformability, to enhance the understanding of debris flow risk mitigation in Tasmania.
防护结构在降低与泥石流相关的风险方面发挥着至关重要的作用，然而，对其性能进行评估却对其在现实世界中的有效性提出了严峻的挑战。本研究提出了一套全面的程序，用于评估受到大型泥石流事件传播介质影响的防护结构的性能。该方法将数值建模与澳大利亚塔斯马尼亚州霍巴特河口沿岸现有结构的现场条件相结合。通过将模拟结果与实验数据进行比较，对耦合欧拉格拉格朗日（CEL）模型进行了验证，结果表明两者具有很高的一致性。利用霍巴特河口地形上泥石流与巨石相互作用的三维模型，对巨石速度进行了估算，以便进行后续的有限元分析。重要的是，建立了巨石与工字钢柱之间的相互作用模型，有助于对目前在现场使用的 A 至 E 型五种不同的工字钢护栏系统进行比较评估。模拟结果显示，较大的巨石在三维地形上的速度增加较慢。通过引入一个关键指标--故障率，可以对这些护栏系统进行比较评估。值得注意的是，由于结构中的薄弱点较少，E 型护栏表现出更优越的性能。结合 CEL 和 FE 评估，可以从多个方面考虑泥石流、巨石和结构之间的相互作用，包括结构失效和变形能力，从而加深对塔斯马尼亚泥石流风险缓解的理解。
{"title":"Analysis of Debris Flow Protective Barriers Using the Coupled Eulerian Lagrangian Method","authors":"Shiyin Sha, A. Dyson, Gholamreza Kefayati, A. Tolooiyan","doi":"10.3390/geosciences14080198","DOIUrl":"https://doi.org/10.3390/geosciences14080198","url":null,"abstract":"Protective structures play a vital role in mitigating the risks associated with debris flows, yet assessing their performance poses crucial challenges for their real-world effectiveness. This study proposes a comprehensive procedure for evaluating the performance of protective structures exposed to impacts from media transported by large debris flow events. The method combines numerical modelling with site conditions for existing structures along the Hobart Rivulet in Tasmania, Australia. The Coupled Eulerian Lagrangian (CEL) model was validated by comparing simulation results with experimental data, demonstrating high agreement. Utilising three-dimensional modelling of debris flow–boulder interactions over the Hobart Rivulet terrain, boulder velocities were estimated for subsequent finite element analyses. Importantly, a model of interaction between boulders and I-beam posts was established, facilitating a comparative assessment of five distinct I-beam barrier systems defined as Type A to E, which are currently in use at the site. Simulation results reveal larger boulders display a slower increase in their velocities over the 3D terrain. Introducing a key metric, the failure ratio, enable a mechanism for comparative assessments of these barrier systems. Notably, the Type E barriers demonstrate superior performance due to fewer weak points within the structure. The combined CEL and FE assessments allow for multiple aspects of the interactions between debris flows, boulders, and structures to be considered, including structural failure and deformability, to enhance the understanding of debris flow risk mitigation in Tasmania.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141799148","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 : 2024-07-24DOI: 10.3390/geosciences14080197
F. De Smedt, P. Kayastha
Several methods and approaches have been proposed to assess landslide susceptibility. The likelihood of landslides occurring can be determined by applying statistical models to historical landslides, taking into account controlling factors. Popular methods for predicting the probability of landslides are weights-of-evidence and logistic regression. We discuss the assumptions and interpretations of these methods, the relationships between them, and their strengths and weaknesses in case of categorical factors. Of particular interest is the conditional independence of the controlling factors and its effect on model bias. To avoid lack of conditional independence of factors and model bias, we present a unique conditions model that is always unbiased. To illustrate the theoretical developments, a practical application is given using observed landslides and geo-environmental factors from a previous study. The unique conditions model appears superior to the other models.
{"title":"A Unique Conditions Model for Landslide Susceptibility Mapping","authors":"F. De Smedt, P. Kayastha","doi":"10.3390/geosciences14080197","DOIUrl":"https://doi.org/10.3390/geosciences14080197","url":null,"abstract":"Several methods and approaches have been proposed to assess landslide susceptibility. The likelihood of landslides occurring can be determined by applying statistical models to historical landslides, taking into account controlling factors. Popular methods for predicting the probability of landslides are weights-of-evidence and logistic regression. We discuss the assumptions and interpretations of these methods, the relationships between them, and their strengths and weaknesses in case of categorical factors. Of particular interest is the conditional independence of the controlling factors and its effect on model bias. To avoid lack of conditional independence of factors and model bias, we present a unique conditions model that is always unbiased. To illustrate the theoretical developments, a practical application is given using observed landslides and geo-environmental factors from a previous study. The unique conditions model appears superior to the other models.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"60 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806862","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 : 2024-07-24DOI: 10.3390/geosciences14080196
R. Arjwech, Sutatcha Hongsresawat, Suriyachai Chaisuriya, Jetsadarat Rattanawannee, P. Kanjanapayont, W. Youngme
Identifying the movement of the branches of the hidden Thakhek fault in Thailand is challenging due to the absence of evident landforms indicating an active fault. In this study, we analyzed a digital elevation model (DEM) to identify potential landforms. A 2D Electrical Resistivity Tomography (ERT) survey was conducted to locate the hidden Thakhek fault. The results reveal vivid images of resistivity contrast, interpreted as two reverse faults, with mudstone exhibiting low resistivity in the middle, flanked by thick sediment layers with higher resistivity. Three trenches were excavated perpendicular to the two interpreted reverse faults. The displacement of reverse faulting appears to have shifted mudstone over Quaternary sediments, with vertical offsets revealed in trenches NWY-1, NWY-2, and NWY-3. This movement could be identified as a positive flower structure. Additionally, lakes are identified as a negative flower structure along the traces. These features result from strike-slip strains under a locally appropriate compressional and extensional environment in a shearing strike-slip fault.
{"title":"Identification and Verification of the Movement of the Hidden Active Fault Using Electrical Resistivity Tomography and Excavation","authors":"R. Arjwech, Sutatcha Hongsresawat, Suriyachai Chaisuriya, Jetsadarat Rattanawannee, P. Kanjanapayont, W. Youngme","doi":"10.3390/geosciences14080196","DOIUrl":"https://doi.org/10.3390/geosciences14080196","url":null,"abstract":"Identifying the movement of the branches of the hidden Thakhek fault in Thailand is challenging due to the absence of evident landforms indicating an active fault. In this study, we analyzed a digital elevation model (DEM) to identify potential landforms. A 2D Electrical Resistivity Tomography (ERT) survey was conducted to locate the hidden Thakhek fault. The results reveal vivid images of resistivity contrast, interpreted as two reverse faults, with mudstone exhibiting low resistivity in the middle, flanked by thick sediment layers with higher resistivity. Three trenches were excavated perpendicular to the two interpreted reverse faults. The displacement of reverse faulting appears to have shifted mudstone over Quaternary sediments, with vertical offsets revealed in trenches NWY-1, NWY-2, and NWY-3. This movement could be identified as a positive flower structure. Additionally, lakes are identified as a negative flower structure along the traces. These features result from strike-slip strains under a locally appropriate compressional and extensional environment in a shearing strike-slip fault.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"22 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806274","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 : 2024-07-18DOI: 10.3390/geosciences14070195
Laszlo Podolszki, Nikola Gizdavec, M. Gašparović, Tihomir Frangen
The evolution of map development has been shaped by advancing techniques and technologies. Nevertheless, field and remote mapping with cabinet data analysis remains essential in this process. Geological maps are thematic maps that delineate diverse geological features. These maps undergo updates reflecting changes in the mapped area, technological advancements, and the availability of new data. Herein, a geological assessment example focused on enhancing mapped data using digitally processed historical (legacy) aerial images is presented for a case study in the Dinarides karst area in Croatia. The study area of Bribirske Mostine is covered by the Basic Geological Map of Yugoslavia (BGMY) at a 100,000 scale, which was developed during the 1960s. As the BGMY was developed 60+ years ago, one of its segments is further analyzed and discussed, namely, faults. Moreover, applying modern-day technologies and reinterpretation, its data, scale, presentation, and possible areas of improvement are presented. Georeferenced digital historical geological data (legacy), comprising BGMY, archive field maps, and aerial images from 1959 used in BGMY development, are reviewed. Original faults were digitalized and reinterpreted within the geographic information system with the following conclusions: (i) more accurate data (spatial positioning) on faults can be gained by digitally processing aerial photographs taken 60+ years ago with detailed review and analysis; (ii) simultaneously, new data were acquired (additional fault lines were interpreted); (iii) the map scale can be up-scaled to 1:25,000 for the investigated area of Bribirske Mostine; and (iv) a newly developed map for the Bribirske Mostine study area is presented.
{"title":"Geological Assessment of Faults in Digitally Processed Aerial Images within Karst Area","authors":"Laszlo Podolszki, Nikola Gizdavec, M. Gašparović, Tihomir Frangen","doi":"10.3390/geosciences14070195","DOIUrl":"https://doi.org/10.3390/geosciences14070195","url":null,"abstract":"The evolution of map development has been shaped by advancing techniques and technologies. Nevertheless, field and remote mapping with cabinet data analysis remains essential in this process. Geological maps are thematic maps that delineate diverse geological features. These maps undergo updates reflecting changes in the mapped area, technological advancements, and the availability of new data. Herein, a geological assessment example focused on enhancing mapped data using digitally processed historical (legacy) aerial images is presented for a case study in the Dinarides karst area in Croatia. The study area of Bribirske Mostine is covered by the Basic Geological Map of Yugoslavia (BGMY) at a 100,000 scale, which was developed during the 1960s. As the BGMY was developed 60+ years ago, one of its segments is further analyzed and discussed, namely, faults. Moreover, applying modern-day technologies and reinterpretation, its data, scale, presentation, and possible areas of improvement are presented. Georeferenced digital historical geological data (legacy), comprising BGMY, archive field maps, and aerial images from 1959 used in BGMY development, are reviewed. Original faults were digitalized and reinterpreted within the geographic information system with the following conclusions: (i) more accurate data (spatial positioning) on faults can be gained by digitally processing aerial photographs taken 60+ years ago with detailed review and analysis; (ii) simultaneously, new data were acquired (additional fault lines were interpreted); (iii) the map scale can be up-scaled to 1:25,000 for the investigated area of Bribirske Mostine; and (iv) a newly developed map for the Bribirske Mostine study area is presented.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826157","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 : 2024-07-18DOI: 10.3390/geosciences14070194
Nima Mirhadi, R. Macciotta
This work illustrates a semi-quantitative approach to evaluate changes in regional landslide distribution as a consequence of forecasted climate change, which can be adopted at other regions. We evaluated the relationship between climate conditions and landslide distribution at a regional scale. In this study, landslides on parts of the Battle, Red Deer, and Bow Rivers that are located within the Bearpaw Formation in Southern Alberta, Canada, were mapped, and their characteristics were compared. In order to find a relationship between the climate conditions and the mapped landslides, 30-year annual precipitation and other factors, such as slope aspect and geology, were compared between the river valleys. The results show that climatic conditions and the size and shape of the landslides are different in the Battle River area compared to the Red Deer and Bow Rivers regions. The weak Bearpaw overconsolidated shale and the bentonite layers throughout the region are sensitive to moisture and create favorable conditions for landslides in the river valleys. Further investigations into the long-term impact of climate on the formation of river valleys and the Bearpaw Formation support the argument that climate is one of the main factors in causing variations in landslide distribution across the study areas. These findings provide insight into possible changes in regional landslide distribution as a consequence of climate change.
{"title":"Regional-Scale Evaluation of Landslide Distribution and Its Relation to Climate in Southern Alberta, Canada","authors":"Nima Mirhadi, R. Macciotta","doi":"10.3390/geosciences14070194","DOIUrl":"https://doi.org/10.3390/geosciences14070194","url":null,"abstract":"This work illustrates a semi-quantitative approach to evaluate changes in regional landslide distribution as a consequence of forecasted climate change, which can be adopted at other regions. We evaluated the relationship between climate conditions and landslide distribution at a regional scale. In this study, landslides on parts of the Battle, Red Deer, and Bow Rivers that are located within the Bearpaw Formation in Southern Alberta, Canada, were mapped, and their characteristics were compared. In order to find a relationship between the climate conditions and the mapped landslides, 30-year annual precipitation and other factors, such as slope aspect and geology, were compared between the river valleys. The results show that climatic conditions and the size and shape of the landslides are different in the Battle River area compared to the Red Deer and Bow Rivers regions. The weak Bearpaw overconsolidated shale and the bentonite layers throughout the region are sensitive to moisture and create favorable conditions for landslides in the river valleys. Further investigations into the long-term impact of climate on the formation of river valleys and the Bearpaw Formation support the argument that climate is one of the main factors in causing variations in landslide distribution across the study areas. These findings provide insight into possible changes in regional landslide distribution as a consequence of climate change.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825016","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 : 2024-07-16DOI: 10.3390/geosciences14070192
Nazyf Salikhov, A. Shepetov, G. Pak, Vladimir Saveliev, Serik Nurakynov, Vladimir Ryabov, Valery Zhukov
The article describes in detail the equipment and method for measuring the Doppler frequency shift (DFS) on an inclined radio path, based on the principle of the phase-locked loop using an SDR receiver for the investigation of seismogenic and man-made disturbances in the ionosphere. During the two M7.8 earthquakes in Nepal (25 April 2015) and Turkey (6 February 2023), a Doppler ionosonde detected co-seismic and pre-seismic effects in the ionosphere, the appearances of which are connected with the various propagation mechanisms of seismogenic disturbance from the lithosphere up to the ionosphere. One day before the earthquake in Nepal and 90 min prior to the main shock, an increase in the intensity of Doppler bursts was detected, which reflected the disturbance of the ionosphere. A channel of geophysical interaction in the system of lithosphere–atmosphere–ionosphere coupling was traced based on the comprehensive monitoring of the DFS of the ionospheric signal, as well as of the flux of gamma rays in subsoil layers of rocks and in the ground-level atmosphere. The concept of lithosphere–atmosphere–ionosphere coupling, where the key role is assigned to ionization of the atmospheric boundary layer, was confirmed by a retrospective analysis of the DFS records of an ionospheric signal made during underground nuclear explosions at the Semipalatinsk test site. A simple formula for reconstructing the velocity profile of the acoustic pulse from a Dopplerogram was obtained, which depends on only two parameters, one of which is the dimension of length and the other the dimension of time. The reconstructed profiles of the acoustic pulses from the two underground nuclear explosions, which reached the height of the reflection point of the sounding radio wave, are presented.
{"title":"A PLL-Based Doppler Method Using an SDR-Receiver for Investigation of Seismogenic and Man-Made Disturbances in the Ionosphere","authors":"Nazyf Salikhov, A. Shepetov, G. Pak, Vladimir Saveliev, Serik Nurakynov, Vladimir Ryabov, Valery Zhukov","doi":"10.3390/geosciences14070192","DOIUrl":"https://doi.org/10.3390/geosciences14070192","url":null,"abstract":"The article describes in detail the equipment and method for measuring the Doppler frequency shift (DFS) on an inclined radio path, based on the principle of the phase-locked loop using an SDR receiver for the investigation of seismogenic and man-made disturbances in the ionosphere. During the two M7.8 earthquakes in Nepal (25 April 2015) and Turkey (6 February 2023), a Doppler ionosonde detected co-seismic and pre-seismic effects in the ionosphere, the appearances of which are connected with the various propagation mechanisms of seismogenic disturbance from the lithosphere up to the ionosphere. One day before the earthquake in Nepal and 90 min prior to the main shock, an increase in the intensity of Doppler bursts was detected, which reflected the disturbance of the ionosphere. A channel of geophysical interaction in the system of lithosphere–atmosphere–ionosphere coupling was traced based on the comprehensive monitoring of the DFS of the ionospheric signal, as well as of the flux of gamma rays in subsoil layers of rocks and in the ground-level atmosphere. The concept of lithosphere–atmosphere–ionosphere coupling, where the key role is assigned to ionization of the atmospheric boundary layer, was confirmed by a retrospective analysis of the DFS records of an ionospheric signal made during underground nuclear explosions at the Semipalatinsk test site. A simple formula for reconstructing the velocity profile of the acoustic pulse from a Dopplerogram was obtained, which depends on only two parameters, one of which is the dimension of length and the other the dimension of time. The reconstructed profiles of the acoustic pulses from the two underground nuclear explosions, which reached the height of the reflection point of the sounding radio wave, are presented.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"37 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643627","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 : 2024-07-16DOI: 10.3390/geosciences14070191
M. Orlando, A. De Santis, Mariagrazia De Caro, Loredana Perrone, Saioa A. Campuzano, G. Cianchini, A. Piscini, Serena D’Arcangelo, Massimo Calcara, Cristiano Fidani, Adriano Nardi, D. Sabbagh, M. Soldani
This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach.
{"title":"The Preparation Phase of the 2022 ML 5.7 Offshore Fano (Italy) Earthquake: A Multiparametric–Multilayer Approach","authors":"M. Orlando, A. De Santis, Mariagrazia De Caro, Loredana Perrone, Saioa A. Campuzano, G. Cianchini, A. Piscini, Serena D’Arcangelo, Massimo Calcara, Cristiano Fidani, Adriano Nardi, D. Sabbagh, M. Soldani","doi":"10.3390/geosciences14070191","DOIUrl":"https://doi.org/10.3390/geosciences14070191","url":null,"abstract":"This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"19 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644286","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 : 2024-07-15DOI: 10.3390/geosciences14070190
J. Puffer, John R. McGann, James O. Brown
There are some persistent basic questions pertaining to the bedrock schist of New York City (NYC). How many mappable schist formations are exposed in NYC, and what was the sedimentary protolith of the Manhattan schists? Our proposed answers are based in part on a blending of published paleontological and radiometric dating results that constrain the timing of Taconic subduction and the best choice of a pelitic protolith for the schists of NYC. We have chemically analyzed some samples of schist and shales at key locations to evaluate the plausibility of our proposals. The compelling published evidence indicates that the Taconic Orogeny began about 475 Ma, when peri-Laurentian plates began the process of east-dipping subduction under the Moretown Terrane, resulting in a magmatic flareup of the Shelburne Falls arc that carried the Moretown Terrane west across NYC. East-dipping subduction accounts for early Ordovician metamorphism until an oceanic slab break-off event at about 466 Ma. Our review of the biostratigraphic data indicates a continuation of subduction and the deposition of pelitic sediments until about 455 Ma, during the transition to deep-water turbiditic sediment deposition. This disqualifies all post-455 Ma turbidites as viable protoliths for the NYC Manhattan schists but does include the Late Cambrian to lowermost Late Ordovician pelites of the Jutland Sequence that are exposed directly west of NYC in New Jersey. Our new chemical analyses of Jutland sediments and each of the three named schists from the NYC plot as a single geochemical population. We, therefore, propose that the schists of NYC could collectively be referred to as the Manhattan schist of the Late Cambrian to lower Late Ordovician.
{"title":"The Manhattan Schist, New York City: Proposed Sedimentary Protolith, Age, Boundaries, and Metamorphic History","authors":"J. Puffer, John R. McGann, James O. Brown","doi":"10.3390/geosciences14070190","DOIUrl":"https://doi.org/10.3390/geosciences14070190","url":null,"abstract":"There are some persistent basic questions pertaining to the bedrock schist of New York City (NYC). How many mappable schist formations are exposed in NYC, and what was the sedimentary protolith of the Manhattan schists? Our proposed answers are based in part on a blending of published paleontological and radiometric dating results that constrain the timing of Taconic subduction and the best choice of a pelitic protolith for the schists of NYC. We have chemically analyzed some samples of schist and shales at key locations to evaluate the plausibility of our proposals. The compelling published evidence indicates that the Taconic Orogeny began about 475 Ma, when peri-Laurentian plates began the process of east-dipping subduction under the Moretown Terrane, resulting in a magmatic flareup of the Shelburne Falls arc that carried the Moretown Terrane west across NYC. East-dipping subduction accounts for early Ordovician metamorphism until an oceanic slab break-off event at about 466 Ma. Our review of the biostratigraphic data indicates a continuation of subduction and the deposition of pelitic sediments until about 455 Ma, during the transition to deep-water turbiditic sediment deposition. This disqualifies all post-455 Ma turbidites as viable protoliths for the NYC Manhattan schists but does include the Late Cambrian to lowermost Late Ordovician pelites of the Jutland Sequence that are exposed directly west of NYC in New Jersey. Our new chemical analyses of Jutland sediments and each of the three named schists from the NYC plot as a single geochemical population. We, therefore, propose that the schists of NYC could collectively be referred to as the Manhattan schist of the Late Cambrian to lower Late Ordovician.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"19 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645947","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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