Pub Date : 2023-10-02DOI: 10.3390/geosciences13100298
Nicola Angelo Famiglietti, Pietro Miele, Luigi Petti, Domenico Guida, Francesco Maria Guadagno, Raffaele Moschillo, Annamaria Vicari
This study focuses on analyzing and monitoring urban subsidence, particularly in the city of Palermo, Italy. Land subsidence, induced by natural and human factors, poses threats to infrastructure and urban safety. Remote sensing (RS), specifically synthetic-aperture radar interferometry (In-SAR), is employed due to its ability to detect ground displacements over large areas with great precision. The persistent scatterer InSAR (PS-InSAR) technique is utilized to identify stable targets and track millimeter-level surface deformations. This research spans from October 2014 to October 2021, using Sentinel-1 satellite data to capture ground deformation from various angles. The findings are integrated into an accessible web app (ArcGIS) for local authorities that could be used aiding in urban planning and enhancing safety measures. This study’s results offer updated deformation maps, serving as an operational tool to support decision-making and community resilience, emphasizing risk awareness and responsible practices. This study highlights that the exponential expansion of urban areas, which does not take into account historical information, can gravely jeopardize both the integrity of urban infrastructure and the well-being of its inhabitants. In this context, remote sensing technologies emerge as an invaluable ally, used in monitoring and safeguarding the urban landscape.
{"title":"What Have We Learned from the Past? An Analysis of Ground Deformations in Urban Areas of Palermo (Sicily, Italy) by Means of Multi-Temporal Synthetic Aperture Radar Interferometry Techniques","authors":"Nicola Angelo Famiglietti, Pietro Miele, Luigi Petti, Domenico Guida, Francesco Maria Guadagno, Raffaele Moschillo, Annamaria Vicari","doi":"10.3390/geosciences13100298","DOIUrl":"https://doi.org/10.3390/geosciences13100298","url":null,"abstract":"This study focuses on analyzing and monitoring urban subsidence, particularly in the city of Palermo, Italy. Land subsidence, induced by natural and human factors, poses threats to infrastructure and urban safety. Remote sensing (RS), specifically synthetic-aperture radar interferometry (In-SAR), is employed due to its ability to detect ground displacements over large areas with great precision. The persistent scatterer InSAR (PS-InSAR) technique is utilized to identify stable targets and track millimeter-level surface deformations. This research spans from October 2014 to October 2021, using Sentinel-1 satellite data to capture ground deformation from various angles. The findings are integrated into an accessible web app (ArcGIS) for local authorities that could be used aiding in urban planning and enhancing safety measures. This study’s results offer updated deformation maps, serving as an operational tool to support decision-making and community resilience, emphasizing risk awareness and responsible practices. This study highlights that the exponential expansion of urban areas, which does not take into account historical information, can gravely jeopardize both the integrity of urban infrastructure and the well-being of its inhabitants. In this context, remote sensing technologies emerge as an invaluable ally, used in monitoring and safeguarding the urban landscape.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135895697","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 : 2023-10-02DOI: 10.3390/geosciences13100297
Daniil V. Popov
Most recent studies consider the formation of individual pegmatite bodies to be a fast process with estimated crystal growth rates reaching a walloping 10 m/day. This opinion is presumably underpinned by the traditional way of thinking of them as the end products of magmatic fractionation. Indeed, modelling has shown that if a pegmatite-forming substance with a temperature near granitic solidus intrudes into a much colder host rock, as recorded in some outcrops, it must cool rapidly. From here, a conclusion is made that the crystallisation must likewise be rapid. However, this view is challenged by several studies that published isotopic dates supported by petrological characterisation of the analysed materials, which suggested or can be used to suggest that some minerals in pegmatites grew over millions of years. Surprisingly, such in-depth work on the geochronology of individual pegmatite bodies is relatively uncommon, so it is early to make generalisations. Here, I highlight some of the existing evidence with the aim to stimulate further research into the timescales of pegmatite crystallisation, including the use of petrologically constrained isotopic dating.
{"title":"Do Pegmatites Crystallise Fast? A Perspective from Petrologically-Constrained Isotopic Dating","authors":"Daniil V. Popov","doi":"10.3390/geosciences13100297","DOIUrl":"https://doi.org/10.3390/geosciences13100297","url":null,"abstract":"Most recent studies consider the formation of individual pegmatite bodies to be a fast process with estimated crystal growth rates reaching a walloping 10 m/day. This opinion is presumably underpinned by the traditional way of thinking of them as the end products of magmatic fractionation. Indeed, modelling has shown that if a pegmatite-forming substance with a temperature near granitic solidus intrudes into a much colder host rock, as recorded in some outcrops, it must cool rapidly. From here, a conclusion is made that the crystallisation must likewise be rapid. However, this view is challenged by several studies that published isotopic dates supported by petrological characterisation of the analysed materials, which suggested or can be used to suggest that some minerals in pegmatites grew over millions of years. Surprisingly, such in-depth work on the geochronology of individual pegmatite bodies is relatively uncommon, so it is early to make generalisations. Here, I highlight some of the existing evidence with the aim to stimulate further research into the timescales of pegmatite crystallisation, including the use of petrologically constrained isotopic dating.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135895084","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 : 2023-10-01DOI: 10.3390/geosciences13100296
Alexandros Aristotelis Koupatsiaris, Hara Drinia
The relationship between humans and the environment in the modern world is challenging. UNESCO Global Geoparks are current holistic approaches for protecting and managing geographical areas that emphasise local communities and sustainability. This paper attempts to review the grey literature of Greek universities through their academic repositories, regarding the research field referred to as Greek UNESCO Global Geoparks from 2000 to 2022 and using the keyword “Geopark” to determine possible future research directions. Through the systematic literature review methodology, from 138 bibliographic sources, 28 were selected, which met the predefined criteria. In general, there is a growing scientific–academic interest in Geoparks, which mainly concerns the aspects of geotourism (n = 7), geology (n = 6), management (n = 4), and education (n = 4). Future research directions may focus on promoting the socio-economic and cultural aspects of Geoparks, investing in collaborative management and governance of Geoparks, facing climate change and environmental challenges in Geoparks, and enhancing Geoenvironmental Education in Geoparks. Such approaches may serve the United Nation’s Seventeen Sustainable Development Goals and cultivate cognitive and emotional bonds between local populations and the geoenvironment.
{"title":"Exploring Greek UNESCO Global Geoparks: A Systematic Review of Grey Literature οn Greek Universities and Future Research Avenues for Sustainable Development","authors":"Alexandros Aristotelis Koupatsiaris, Hara Drinia","doi":"10.3390/geosciences13100296","DOIUrl":"https://doi.org/10.3390/geosciences13100296","url":null,"abstract":"The relationship between humans and the environment in the modern world is challenging. UNESCO Global Geoparks are current holistic approaches for protecting and managing geographical areas that emphasise local communities and sustainability. This paper attempts to review the grey literature of Greek universities through their academic repositories, regarding the research field referred to as Greek UNESCO Global Geoparks from 2000 to 2022 and using the keyword “Geopark” to determine possible future research directions. Through the systematic literature review methodology, from 138 bibliographic sources, 28 were selected, which met the predefined criteria. In general, there is a growing scientific–academic interest in Geoparks, which mainly concerns the aspects of geotourism (n = 7), geology (n = 6), management (n = 4), and education (n = 4). Future research directions may focus on promoting the socio-economic and cultural aspects of Geoparks, investing in collaborative management and governance of Geoparks, facing climate change and environmental challenges in Geoparks, and enhancing Geoenvironmental Education in Geoparks. Such approaches may serve the United Nation’s Seventeen Sustainable Development Goals and cultivate cognitive and emotional bonds between local populations and the geoenvironment.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135459348","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 : 2023-09-28DOI: 10.3390/geosciences13100294
Chuanqi Li, Jian Zhou, Daniel Dias, Kun Du, Manoj Khandelwal
The uniaxial compressive strength (UCS) of rocks is one of the key parameters for evaluating the safety and stability of civil and mining structures. In this study, 386 rock samples containing four properties named the load strength (PLS), the porosity (Pn), the P-wave velocity (Vp), and the Schmidt hardness rebound number (SHR) are utilized to predict the UCS using several typical empirical equations (EA) and artificial intelligence (AI) methods, i.e., 16 single regression (SR) equations, 2 multiple regression (MR) equations, and the random forest (RF) models optimized by grey wolf optimization (GWO), moth flame optimization (MFO), lion swarm optimization (LSO), and sparrow search algorithm (SSA). The root mean square error (RMSE), determination coefficient (R2), Willmott’s index (WI), and variance accounted for (VAF) are used to evaluate the predictive performance of all developed models. The evaluation results show that the overall performance of AI models is superior to empirical approaches, especially the LSO-RF model. In addition, the most important input variable is the Pn for predicting the UCS. Therefore, AI techniques are considered as more efficient and accurate approaches to replace the empirical equations for predicting the UCS of these collected rock samples, which provides a reliable and effective idea to predict the rock UCS in the filed site.
{"title":"Comparative Evaluation of Empirical Approaches and Artificial Intelligence Techniques for Predicting Uniaxial Compressive Strength of Rock","authors":"Chuanqi Li, Jian Zhou, Daniel Dias, Kun Du, Manoj Khandelwal","doi":"10.3390/geosciences13100294","DOIUrl":"https://doi.org/10.3390/geosciences13100294","url":null,"abstract":"The uniaxial compressive strength (UCS) of rocks is one of the key parameters for evaluating the safety and stability of civil and mining structures. In this study, 386 rock samples containing four properties named the load strength (PLS), the porosity (Pn), the P-wave velocity (Vp), and the Schmidt hardness rebound number (SHR) are utilized to predict the UCS using several typical empirical equations (EA) and artificial intelligence (AI) methods, i.e., 16 single regression (SR) equations, 2 multiple regression (MR) equations, and the random forest (RF) models optimized by grey wolf optimization (GWO), moth flame optimization (MFO), lion swarm optimization (LSO), and sparrow search algorithm (SSA). The root mean square error (RMSE), determination coefficient (R2), Willmott’s index (WI), and variance accounted for (VAF) are used to evaluate the predictive performance of all developed models. The evaluation results show that the overall performance of AI models is superior to empirical approaches, especially the LSO-RF model. In addition, the most important input variable is the Pn for predicting the UCS. Therefore, AI techniques are considered as more efficient and accurate approaches to replace the empirical equations for predicting the UCS of these collected rock samples, which provides a reliable and effective idea to predict the rock UCS in the filed site.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135425334","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}
An effort is exerted to investigate the recurrence pattern of large earthquakes (Mw ≥ 6.0) in the Kefalonia Transform Fault Zone (KTFZ), Greece, by considering the incorporation of the 74-year (1948–2022) evolving stress field. Four earthquake occurrence models—the Poisson, Poisson with the incorporation of the static stress changes (Poisson + ΔCFF), Brownian passage time (BPT) and Brownian passage time with the incorporation of the static stress changes (BPT + ΔCFF)—have been applied to estimate the occurrence probabilities of nearly characteristic earthquakes for the seven fault segments of the study area. The mean recurrence time, Tr, is estimated using the physics-based seismic moment rate conservation method. The results show large variability depending upon fault parameters. Incorporating the state of stress into Tr results in both advanced and delayed recurrence patterns. The occurrence probability estimates for the next 10, 20 and 30 years indicate that the fault segment most likely to be ruptured is the Paliki North fault segment in all models. Overall, the occurrence probabilities, combined with the state of stress along the fault segments, emphasize the high seismic moment rate of the study area. The application of time-dependent models (BPT, BPT + ΔCFF) resulted in significant increases or decreases in the associated seismic hazard.
{"title":"Long-Term Recurrence Pattern and Stress Transfer along the Kefalonia Transform Fault Zone (KTFZ), Greece: Implications in Seismic Hazard Evaluation","authors":"Christos Kourouklas, Eleftheria Papadimitriou, Vasileios Karakostas","doi":"10.3390/geosciences13100295","DOIUrl":"https://doi.org/10.3390/geosciences13100295","url":null,"abstract":"An effort is exerted to investigate the recurrence pattern of large earthquakes (Mw ≥ 6.0) in the Kefalonia Transform Fault Zone (KTFZ), Greece, by considering the incorporation of the 74-year (1948–2022) evolving stress field. Four earthquake occurrence models—the Poisson, Poisson with the incorporation of the static stress changes (Poisson + ΔCFF), Brownian passage time (BPT) and Brownian passage time with the incorporation of the static stress changes (BPT + ΔCFF)—have been applied to estimate the occurrence probabilities of nearly characteristic earthquakes for the seven fault segments of the study area. The mean recurrence time, Tr, is estimated using the physics-based seismic moment rate conservation method. The results show large variability depending upon fault parameters. Incorporating the state of stress into Tr results in both advanced and delayed recurrence patterns. The occurrence probability estimates for the next 10, 20 and 30 years indicate that the fault segment most likely to be ruptured is the Paliki North fault segment in all models. Overall, the occurrence probabilities, combined with the state of stress along the fault segments, emphasize the high seismic moment rate of the study area. The application of time-dependent models (BPT, BPT + ΔCFF) resulted in significant increases or decreases in the associated seismic hazard.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135425608","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 : 2023-09-27DOI: 10.3390/geosciences13100293
Syeda Zehan Farzana, Dev Raj Paudyal, Sreeni Chadalavada, Md Jahangir Alam
The effective management of surface water bodies, such as rivers, lakes, and reservoirs, necessitates a comprehensive understanding of water quality status. Altered precipitation patterns due to climate change may significantly affect the water quality and influence treatment procedures. This study aims to identify the most suitable water quality prediction models for the assessment of the water quality status for three water supply reservoirs in Toowoomba, Australia. It employed four machine learning and two deep learning models for determining the Water Quality Index (WQI) based on five parameters sensitive to rainfall impact. Temporal WQI variations over a period of 22 years (2000–2022) are scrutinised across 4 seasons and 12 months. Through regression analysis, both machine learning and deep learning models anticipate WQI gauged by seven accuracy metrics. Notably, XGBoost and GRU yielded exceptional outcomes, showcasing an R2 value of 0.99. Conversely, Bidirectional LSTM (BiLSTM) demonstrated moderate accuracy with results hovering at 88% to 90% for water quality prediction across all reservoirs. The Coefficient of Efficiency (CE) and Willmott Index (d) showed that the models capture patterns well, while MAE, MAPE and RMSE provided good performance metrics for the RFR, XGBoost and GRU models. These models have provided valuable knowledge that can be utilised to assess the adverse consequences of extreme climate events such as shifts in rainfall patterns. These insights can be used to improve strategies for managing water bodies more effectively.
{"title":"Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia","authors":"Syeda Zehan Farzana, Dev Raj Paudyal, Sreeni Chadalavada, Md Jahangir Alam","doi":"10.3390/geosciences13100293","DOIUrl":"https://doi.org/10.3390/geosciences13100293","url":null,"abstract":"The effective management of surface water bodies, such as rivers, lakes, and reservoirs, necessitates a comprehensive understanding of water quality status. Altered precipitation patterns due to climate change may significantly affect the water quality and influence treatment procedures. This study aims to identify the most suitable water quality prediction models for the assessment of the water quality status for three water supply reservoirs in Toowoomba, Australia. It employed four machine learning and two deep learning models for determining the Water Quality Index (WQI) based on five parameters sensitive to rainfall impact. Temporal WQI variations over a period of 22 years (2000–2022) are scrutinised across 4 seasons and 12 months. Through regression analysis, both machine learning and deep learning models anticipate WQI gauged by seven accuracy metrics. Notably, XGBoost and GRU yielded exceptional outcomes, showcasing an R2 value of 0.99. Conversely, Bidirectional LSTM (BiLSTM) demonstrated moderate accuracy with results hovering at 88% to 90% for water quality prediction across all reservoirs. The Coefficient of Efficiency (CE) and Willmott Index (d) showed that the models capture patterns well, while MAE, MAPE and RMSE provided good performance metrics for the RFR, XGBoost and GRU models. These models have provided valuable knowledge that can be utilised to assess the adverse consequences of extreme climate events such as shifts in rainfall patterns. These insights can be used to improve strategies for managing water bodies more effectively.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135538268","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 : 2023-09-25DOI: 10.3390/geosciences13100292
Gonzalo Farinango, Miguel Ángel Álvarez-Vázquez, Ricardo Prego
In the continuum of the land–sea interface, sediment reservoirs are often considered separately. Therefore, integrative research is necessary. This study focuses on sediments throughout the tributaries–river–estuary–ria pathway of the Ulla–Arousa system, aiming to quantify trace element contents, identify land sources, determine background levels, and assess sediment enrichment and contamination states. The elements Al, As, Cr, Cu, Fe, Ni, Pb, Sb, U, and Zn were determined in 78 sediment stations. Two approaches were considered. First, background functions and enrichment factors were estimated using Al or U as the reference element. Second, a statistical study was conducted using distribution analysis, which helped identify trace element sources and their influences throughout the basin. The results revealed two significant sources of trace elements. One source is the amphibolite massif of the Arinteiro Unit, influencing the Brandelos (Cu) and Lañas (Fe) tributaries. Another source is the Deza tributary (As, Sb). However, these alterations do not reach the estuary, where anthropogenic sources (Cr, Cu, Ni) dominate. In the inner Ria of Arousa, only a light Cr enrichment was observed. The integrated study of the Ulla–Arousa system provides valuable patterns to understand and address heterogeneous land–sea systems.
{"title":"Trace Element Patterns in Heterogeneous Land–Sea Sediments: A Comprehensive Study of the Ulla–Arousa System (SW Europe)","authors":"Gonzalo Farinango, Miguel Ángel Álvarez-Vázquez, Ricardo Prego","doi":"10.3390/geosciences13100292","DOIUrl":"https://doi.org/10.3390/geosciences13100292","url":null,"abstract":"In the continuum of the land–sea interface, sediment reservoirs are often considered separately. Therefore, integrative research is necessary. This study focuses on sediments throughout the tributaries–river–estuary–ria pathway of the Ulla–Arousa system, aiming to quantify trace element contents, identify land sources, determine background levels, and assess sediment enrichment and contamination states. The elements Al, As, Cr, Cu, Fe, Ni, Pb, Sb, U, and Zn were determined in 78 sediment stations. Two approaches were considered. First, background functions and enrichment factors were estimated using Al or U as the reference element. Second, a statistical study was conducted using distribution analysis, which helped identify trace element sources and their influences throughout the basin. The results revealed two significant sources of trace elements. One source is the amphibolite massif of the Arinteiro Unit, influencing the Brandelos (Cu) and Lañas (Fe) tributaries. Another source is the Deza tributary (As, Sb). However, these alterations do not reach the estuary, where anthropogenic sources (Cr, Cu, Ni) dominate. In the inner Ria of Arousa, only a light Cr enrichment was observed. The integrated study of the Ulla–Arousa system provides valuable patterns to understand and address heterogeneous land–sea systems.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135864967","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 : 2023-09-23DOI: 10.3390/geosciences13100289
Michele Licata, Victor Buleo Tebar, Francesco Seitone, Giandomenico Fubelli
Landslides triggered by heavy rainfall pose significant threats to human settlements and infrastructure in temperate and equatorial climate regions. This study focuses on the development of the Open Landslide Project (OLP), an open source landslide inventory aimed at facilitating geostatistical analyses and landslide risk management. Using a multidisciplinary approach and open source, multisatellite imagery data, more than 3000 landslides triggered by the extreme rainfall of autumn 2019 in northwestern Italy were systematically mapped. The inventory creation process followed well-defined criteria and underwent rigorous validation to ensure accuracy and reliability. The dataset’s suitability was confirmed through multivariate correlation and Double Pareto probably density function. The OLP inventory effectiveness in assessing landslide risks was proved by the development of a landslide susceptibility model using binary logistic regression. The analysis of rainfall and lithology revealed that regions with lower rainfall levels experienced a higher occurrence of landslides compared to areas with higher peak rainfall. This was attributed to the response of the lithological composition to rainfalls. The findings of this research contribute to the understanding and management of landslide risks in anthropized climate regions. The OLP has proven to be a valuable resource for future geostatistical analysis.
{"title":"The Open Landslide Project (OLP), a New Inventory of Shallow Landslides for Susceptibility Models: The Autumn 2019 Extreme Rainfall Event in the Langhe-Monferrato Region (Northwestern Italy)","authors":"Michele Licata, Victor Buleo Tebar, Francesco Seitone, Giandomenico Fubelli","doi":"10.3390/geosciences13100289","DOIUrl":"https://doi.org/10.3390/geosciences13100289","url":null,"abstract":"Landslides triggered by heavy rainfall pose significant threats to human settlements and infrastructure in temperate and equatorial climate regions. This study focuses on the development of the Open Landslide Project (OLP), an open source landslide inventory aimed at facilitating geostatistical analyses and landslide risk management. Using a multidisciplinary approach and open source, multisatellite imagery data, more than 3000 landslides triggered by the extreme rainfall of autumn 2019 in northwestern Italy were systematically mapped. The inventory creation process followed well-defined criteria and underwent rigorous validation to ensure accuracy and reliability. The dataset’s suitability was confirmed through multivariate correlation and Double Pareto probably density function. The OLP inventory effectiveness in assessing landslide risks was proved by the development of a landslide susceptibility model using binary logistic regression. The analysis of rainfall and lithology revealed that regions with lower rainfall levels experienced a higher occurrence of landslides compared to areas with higher peak rainfall. This was attributed to the response of the lithological composition to rainfalls. The findings of this research contribute to the understanding and management of landslide risks in anthropized climate regions. The OLP has proven to be a valuable resource for future geostatistical analysis.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135966554","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 : 2023-09-23DOI: 10.3390/geosciences13100290
Al Mamun
Tritium levels in the groundwater of arid regions are very low; in most cases, these low tritium levels cannot be detected using a conventional liquid scintillation counter (LSC). To measure the tritium activity concentration, low-level tritium in groundwater needs to be enriched by a known factor so that the scintillation counter can detect it. An electrolysis process with electrolytic cells was designed and fabricated in our laboratory following the International Atomic Energy Agency (IAEA) instructions. Nine spiked samples with a known quantity of tritium were enriched, and the tritium activity concentration was measured using the scintillation counter. The enriched water exhibits a comparable level of spiked samples, albeit with some degree of uncertainty. A correlation was drawn among the tritium activity, enrichment factor, and the required time for the electrolysis procedure. This study confirmed that an enrichment process of approximately ten- to fortyfold of the initial concentration of the tritium could be achieved using the electrolysis process with the fabricated electrolytic cells. The simple design and fabrication of the electrolysis process by controlling various parameters make it affordable to measure low-level tritium using a conventional LSC. Various statistical analyses confirmed the accuracy and precision of the data obtained by the electrolysis process. This enrichment technique would prove valuable in regions where tritium levels in groundwater are extremely low, making them challenging to detect using conventional liquid scintillation counter.
{"title":"Enrichment of Low-Level Tritium in Groundwater via an Electrolysis Process for Liquid Scintillation Counting Applications","authors":"Al Mamun","doi":"10.3390/geosciences13100290","DOIUrl":"https://doi.org/10.3390/geosciences13100290","url":null,"abstract":"Tritium levels in the groundwater of arid regions are very low; in most cases, these low tritium levels cannot be detected using a conventional liquid scintillation counter (LSC). To measure the tritium activity concentration, low-level tritium in groundwater needs to be enriched by a known factor so that the scintillation counter can detect it. An electrolysis process with electrolytic cells was designed and fabricated in our laboratory following the International Atomic Energy Agency (IAEA) instructions. Nine spiked samples with a known quantity of tritium were enriched, and the tritium activity concentration was measured using the scintillation counter. The enriched water exhibits a comparable level of spiked samples, albeit with some degree of uncertainty. A correlation was drawn among the tritium activity, enrichment factor, and the required time for the electrolysis procedure. This study confirmed that an enrichment process of approximately ten- to fortyfold of the initial concentration of the tritium could be achieved using the electrolysis process with the fabricated electrolytic cells. The simple design and fabrication of the electrolysis process by controlling various parameters make it affordable to measure low-level tritium using a conventional LSC. Various statistical analyses confirmed the accuracy and precision of the data obtained by the electrolysis process. This enrichment technique would prove valuable in regions where tritium levels in groundwater are extremely low, making them challenging to detect using conventional liquid scintillation counter.","PeriodicalId":38189,"journal":{"name":"Geosciences (Switzerland)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135966555","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 : 2023-09-23DOI: 10.3390/geosciences13100291
Emilia Damiano, Martina de de Cristofaro, Antonia Brunzo, Goffredo Carrieri, Luisa Iavazzo, Nadia Netti, Lucio Olivares
Broad mountainous areas in the western Campania (southern Italy), where young pyroclastic deposits extensively outcrop, frequently experience rainfall-induced slope movements of different degrees of mobility, causing heavy damage and fatalities. Such landslides cannot be easily mitigated, and the implementation of physically based early warning systems is still not able to predict the post-failure evolution of slope movements and the exposed areas at risk. This paper is devoted to overcoming this limit. To this end, the mechanical characterization of pyroclastic soil, carried out through an extensive laboratory testing program, is presented and compared with those of two other ashy soils of different depositional mechanisms. The results show that the depositional mode influences soil properties; to begin with, it affects the unsaturated shear strength, whose intercept of cohesion is up to 5 kPa higher in ashes of flow deposition than in airfall ash deposits. The saturated undrained soil response allowed for the identification of different levels of susceptibility to the liquefaction of pyroclastic deposits, which is one of the main factors governing the post-failure evolution of landslides. Gathering all the acquired information, including saturated and unsaturated soil shear strength, permeability function, and water retention curves, into a soil database, it was possible to present all data under a unitary framework. Finally, the implementation of the proposed flowchart for a simplified assessment of post-failure evolution to be employed in regional early warning systems can enhance our knowledge of the areas at risk.
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