Pub Date : 2024-07-13DOI: 10.3390/geosciences14070188
Uroš Barudžija, Matteo Blatančić, T. Malvić
This study involves an investigation into the grain size distribution and provenance of the sand deposited near Zagreb (Croatia) in the riverbed of the regionally important, almost 1000 km long Sava River, which connects several SE European countries. Recent research in the study area has mainly focused on the deposits forming the Zagreb alluvial aquifer system, rather on the Sava River sediment deposited in its riverbed, which is the focus of this study. The grain size distribution results obtained by dry sieving and laser granulometry showed a predominately fine and medium sand deposition at riverbanks and sand point bars. Medium sand increased downstream towards the east, within the artificially more channelized riverbed in the urban area. Fine sand prevailed 50 km further downstream in a more meandering low-relief area, near the city of Sisak and Lonjsko Polje Nature Park. Provenance analysis showed predominately carbonate sand in the western part of the city of Zagreb, originating from distant (Alpine) and local (Medvednica Mt. and Samobor Hills) sources. More siliciclastic sand was deposited in the Sava riverbed in the middle and eastern parts of Zagreb, originating mainly from the Medvednica Mt. The prevailing siliciclastic sand further downstream of the Sava River is probably sourced from the Kupa River tributary. Although various studies of the Zagreb alluvial aquifer system have been conducted so far, this study represents a novelty in its investigation into the grain size distribution of the Sava riverbed sand itself, setting the foundations for investigations in the future.
{"title":"Grain Size Distribution and Provenance of Holocene Sand from the Sava River (Zagreb, Croatia)","authors":"Uroš Barudžija, Matteo Blatančić, T. Malvić","doi":"10.3390/geosciences14070188","DOIUrl":"https://doi.org/10.3390/geosciences14070188","url":null,"abstract":"This study involves an investigation into the grain size distribution and provenance of the sand deposited near Zagreb (Croatia) in the riverbed of the regionally important, almost 1000 km long Sava River, which connects several SE European countries. Recent research in the study area has mainly focused on the deposits forming the Zagreb alluvial aquifer system, rather on the Sava River sediment deposited in its riverbed, which is the focus of this study. The grain size distribution results obtained by dry sieving and laser granulometry showed a predominately fine and medium sand deposition at riverbanks and sand point bars. Medium sand increased downstream towards the east, within the artificially more channelized riverbed in the urban area. Fine sand prevailed 50 km further downstream in a more meandering low-relief area, near the city of Sisak and Lonjsko Polje Nature Park. Provenance analysis showed predominately carbonate sand in the western part of the city of Zagreb, originating from distant (Alpine) and local (Medvednica Mt. and Samobor Hills) sources. More siliciclastic sand was deposited in the Sava riverbed in the middle and eastern parts of Zagreb, originating mainly from the Medvednica Mt. The prevailing siliciclastic sand further downstream of the Sava River is probably sourced from the Kupa River tributary. Although various studies of the Zagreb alluvial aquifer system have been conducted so far, this study represents a novelty in its investigation into the grain size distribution of the Sava riverbed sand itself, setting the foundations for investigations in the future.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"46 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652344","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 : 2024-07-13DOI: 10.3390/geosciences14070189
H. Syaeful, Syaiful Bakhri, B. Muljana, A. Sumaryanto, I. Sukadana, Hendra Adhi Pratama, Adi Gunawan Muhammad, Ngadenin, F. D. Indrastomo, R. C. Ciputra, Susilo Widodo, Nunik Madyaningarum, Puji Santosa, Muhammad Burhannudinnur, Zufialdi Zakaria
Research of the depositional environment using geological mapping, petrography, gamma-ray (GR) log, palynology, and foraminifera fossils of the Bojongmanik Formation has led to the formation of several different conclusions about the transition to the marine environment, which are attractive to revisit. The expected results of this research are to determine the paleoenvironment of the Bojongmanik and Serpong Formations based on elemental geochemistry, the development of paleoenvironment proxies based on portable X-ray fluorescence (pXRF) in fluvial to transitional environments studies, and the contribution of paleoenvironment analysis to GR-log facies interpretation. The research methodology starts with GR-log facies analysis, Pearson’s correlation, paleoenvironment analysis based on elemental affinity and elemental ratio, and comparing the paleoenvironment with GR-log-based facies. The paleoenvironment analysis based on elemental geochemistry resulted in the Bojongmanik Formation in the research area deposited at the tidal point bar, lagoon, and shoreface, while the Serpong Formation was deposited at the fluvial point bar and floodplain. Compared to previous research, the Bojongmanik Formation in the research area could be stratigraphically related to the upper Bojongmanik Formation. Proxies based on elemental geochemical affinities of carbonate-associated, carbonate-productivity, terrigenous-associated elements, and redox-sensitive trace elements show contrast changes between facies. Proxies based on the specific ratio show a detailed paleoenvironment for paleoclimate (Sr/Cu), paleosalinity (Sr/Ba), paleoredox (Cu/Zn), paleo-hydrodynamics and water depth (Zr/Rb and Fe/Mn), sediment provenance (Cr/Zr), and siliciclastic-dominated (Zr + Rb)/Sr. Adding a geochemistry element-based paleoenvironment analysis benefits from a more specific justification for GR-log facies interpretation.
{"title":"Elemental Geochemistry on Paleoenvironment Reconstruction: Proxies on Miocene-Pliocene of Marine to Fluvial Sediment in Serpong, Banten, Indonesia","authors":"H. Syaeful, Syaiful Bakhri, B. Muljana, A. Sumaryanto, I. Sukadana, Hendra Adhi Pratama, Adi Gunawan Muhammad, Ngadenin, F. D. Indrastomo, R. C. Ciputra, Susilo Widodo, Nunik Madyaningarum, Puji Santosa, Muhammad Burhannudinnur, Zufialdi Zakaria","doi":"10.3390/geosciences14070189","DOIUrl":"https://doi.org/10.3390/geosciences14070189","url":null,"abstract":"Research of the depositional environment using geological mapping, petrography, gamma-ray (GR) log, palynology, and foraminifera fossils of the Bojongmanik Formation has led to the formation of several different conclusions about the transition to the marine environment, which are attractive to revisit. The expected results of this research are to determine the paleoenvironment of the Bojongmanik and Serpong Formations based on elemental geochemistry, the development of paleoenvironment proxies based on portable X-ray fluorescence (pXRF) in fluvial to transitional environments studies, and the contribution of paleoenvironment analysis to GR-log facies interpretation. The research methodology starts with GR-log facies analysis, Pearson’s correlation, paleoenvironment analysis based on elemental affinity and elemental ratio, and comparing the paleoenvironment with GR-log-based facies. The paleoenvironment analysis based on elemental geochemistry resulted in the Bojongmanik Formation in the research area deposited at the tidal point bar, lagoon, and shoreface, while the Serpong Formation was deposited at the fluvial point bar and floodplain. Compared to previous research, the Bojongmanik Formation in the research area could be stratigraphically related to the upper Bojongmanik Formation. Proxies based on elemental geochemical affinities of carbonate-associated, carbonate-productivity, terrigenous-associated elements, and redox-sensitive trace elements show contrast changes between facies. Proxies based on the specific ratio show a detailed paleoenvironment for paleoclimate (Sr/Cu), paleosalinity (Sr/Ba), paleoredox (Cu/Zn), paleo-hydrodynamics and water depth (Zr/Rb and Fe/Mn), sediment provenance (Cr/Zr), and siliciclastic-dominated (Zr + Rb)/Sr. Adding a geochemistry element-based paleoenvironment analysis benefits from a more specific justification for GR-log facies interpretation.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"34 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141651049","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 : 2024-07-11DOI: 10.3390/geosciences14070184
Haiyan Tong, Lu Li, Yuzheng Ke, Yanyin Wang, Gongqing Jie, Laiping Yi
Two nanhsiungchelyid carapaces from the Upper Cretaceous of Ganzhou Basin, Jiangxi Province, Southern China, are reported and assigned to Nanhsiungchelys sp. The new material reveals an unusual carapace morphology that was either not or poorly preserved in previously known Nanhsiungchelys specimens, including differentiated neurals, alternating costals, significantly modified scutes with vertebrals 4–5 contacting each other at a point, reduced pleurals 2–4 and greatly expanded lateral and posterior marginals. The discovery extends the geographical distribution of Nanhsiungchelys to the Ganzhou Basin.
{"title":"Remarkable Carapace Morphology of Nanhsiungchelys (Testudines: Nanhsiungchelyidae) Revealed by New Material from Ganzhou Basin, Jiangxi Province, China","authors":"Haiyan Tong, Lu Li, Yuzheng Ke, Yanyin Wang, Gongqing Jie, Laiping Yi","doi":"10.3390/geosciences14070184","DOIUrl":"https://doi.org/10.3390/geosciences14070184","url":null,"abstract":"Two nanhsiungchelyid carapaces from the Upper Cretaceous of Ganzhou Basin, Jiangxi Province, Southern China, are reported and assigned to Nanhsiungchelys sp. The new material reveals an unusual carapace morphology that was either not or poorly preserved in previously known Nanhsiungchelys specimens, including differentiated neurals, alternating costals, significantly modified scutes with vertebrals 4–5 contacting each other at a point, reduced pleurals 2–4 and greatly expanded lateral and posterior marginals. The discovery extends the geographical distribution of Nanhsiungchelys to the Ganzhou Basin.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"123 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656860","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 : 2024-07-11DOI: 10.3390/geosciences14070187
Ginés A. de Gea, J. M. Castro, M. Company, L. O’Dogherty, José Sandoval, María Luisa Quijano, Cristina Sequero, Sandro Froehner, R. Aguado
We investigate a new event of accelerated environmental change that was recorded during the late Barremian in the pelagic Subbetic Basin (Western Tethys). Two pelagic sections have been studied using a multi-proxy approach based on C-isotope stratigraphy and a high-resolution quantitative study of nannofossil assemblages, along with major and trace elements and biomarkers. Our results provide a detailed biostratigraphy and C-isotope stratigraphy, and outline the paleoenvironmental conditions recorded during the early stages of the Taxy Episode. A disturbance has been identified in the C-isotope record, called the IFeNE (Intra-Feradianus negative C-excursion), which is coeval with environmental and biotic changes that predate the well-known ISNE (Intra-Sarasini negative C-excursion). The combined analysis of nannofossil associations, C-isotopes, major and trace elements, and biomarker distributions indicates a separate episode of warming heralding the ISNE, resulting in the acceleration of the hydrological cycle and a consequent increase in continental inputs and the fertilization of surface waters. The origin of the Taxy Episode (the IFeNE and ISNE) has been related to orbital factors (high-eccentricity cycles), and to a global increase in volcanism, probably related to the early phases of the Ontong Java Plateau.
{"title":"New Evidence for an Episode of Accelerated Environmental Change in the Late Barremian: Geochemical and Paleontological Records from the Subbetic Basin (Western Tethys)","authors":"Ginés A. de Gea, J. M. Castro, M. Company, L. O’Dogherty, José Sandoval, María Luisa Quijano, Cristina Sequero, Sandro Froehner, R. Aguado","doi":"10.3390/geosciences14070187","DOIUrl":"https://doi.org/10.3390/geosciences14070187","url":null,"abstract":"We investigate a new event of accelerated environmental change that was recorded during the late Barremian in the pelagic Subbetic Basin (Western Tethys). Two pelagic sections have been studied using a multi-proxy approach based on C-isotope stratigraphy and a high-resolution quantitative study of nannofossil assemblages, along with major and trace elements and biomarkers. Our results provide a detailed biostratigraphy and C-isotope stratigraphy, and outline the paleoenvironmental conditions recorded during the early stages of the Taxy Episode. A disturbance has been identified in the C-isotope record, called the IFeNE (Intra-Feradianus negative C-excursion), which is coeval with environmental and biotic changes that predate the well-known ISNE (Intra-Sarasini negative C-excursion). The combined analysis of nannofossil associations, C-isotopes, major and trace elements, and biomarker distributions indicates a separate episode of warming heralding the ISNE, resulting in the acceleration of the hydrological cycle and a consequent increase in continental inputs and the fertilization of surface waters. The origin of the Taxy Episode (the IFeNE and ISNE) has been related to orbital factors (high-eccentricity cycles), and to a global increase in volcanism, probably related to the early phases of the Ontong Java Plateau.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"121 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656886","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 : 2024-07-11DOI: 10.3390/geosciences14070185
A. Shabdirova, A. Kozhagulova, Yernazar Samenov, Rinat Merbayev, Ainur Niyazbayeva, Daryn Shabdirov
This study investigates the impact of CO2-enhanced oil recovery (CO2-EOR) on the petrophysical properties and oil recovery potential of sandstone reservoirs in the oilfields located in the east-southern Precaspian region of Kazakhstan. Despite the recognized potential of CO2-EOR for improving oil recovery and aiding carbon sequestration, there is limited understanding of how CO2-EOR specifically affects the petrophysical properties of sandstone reservoirs in this region. Laboratory experiments were conducted using two core samples from the selected oilfields to examine changes in porosity, permeability, and oil recovery coefficients. The results demonstrated that porosity changes ranged from a slight increase of 1.1% to a decrease of 1.5%, while permeability reduction was significant, with decreases ranging from 29% to 50% due to clay alteration and halite precipitation. The oil recovery coefficient after CO2 flooding was found to be between 0.49 and 0.54. These findings underscore the complex interactions between CO2 and reservoir rocks, emphasizing the need for tailored EOR strategies in different geological settings.
{"title":"Core Flooding Experiments on the Impact of CO2-EOR on the Petrophysical Properties and Oil Recovery Parameters of Reservoir Sandstones in Kazakhstan","authors":"A. Shabdirova, A. Kozhagulova, Yernazar Samenov, Rinat Merbayev, Ainur Niyazbayeva, Daryn Shabdirov","doi":"10.3390/geosciences14070185","DOIUrl":"https://doi.org/10.3390/geosciences14070185","url":null,"abstract":"This study investigates the impact of CO2-enhanced oil recovery (CO2-EOR) on the petrophysical properties and oil recovery potential of sandstone reservoirs in the oilfields located in the east-southern Precaspian region of Kazakhstan. Despite the recognized potential of CO2-EOR for improving oil recovery and aiding carbon sequestration, there is limited understanding of how CO2-EOR specifically affects the petrophysical properties of sandstone reservoirs in this region. Laboratory experiments were conducted using two core samples from the selected oilfields to examine changes in porosity, permeability, and oil recovery coefficients. The results demonstrated that porosity changes ranged from a slight increase of 1.1% to a decrease of 1.5%, while permeability reduction was significant, with decreases ranging from 29% to 50% due to clay alteration and halite precipitation. The oil recovery coefficient after CO2 flooding was found to be between 0.49 and 0.54. These findings underscore the complex interactions between CO2 and reservoir rocks, emphasizing the need for tailored EOR strategies in different geological settings.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658254","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 : 2024-07-11DOI: 10.3390/geosciences14070186
Connor W. Capizzano, Alexandria C. Rhoads, Jennifer A. Croteau, Benjamin G. Taylor, M. Guarinello, Emily J. Shumchenia
Given the rapid expansion of offshore wind development in the United States (US), the accurate mapping of benthic habitats, specifically surficial sediments, is essential for mitigating potential impacts on these valuable ecosystems. However, offshore wind development has outpaced results from environmental monitoring efforts, compelling stakeholders to rely on a limited set of public geospatial data for conducting impact assessments. The present study therefore sought to develop and evaluate a systematic workflow for generating regional-scale sediment maps using public geospatial data that may pose integration and modeling challenges. To demonstrate this approach, sediment distributions were characterized on the northeastern US continental shelf where offshore wind development has occurred since 2016. Publicly available sediment and bathymetric data in the region were processed using national classification standards and spatial tools, respectively, and integrated using a machine learning algorithm to predict sediment occurrence. Overall, this approach and the generated sediment composite effectively predicted sediment distributions in coastal areas but underperformed in offshore areas where data were either scarce or of poor quality. Despite these shortcomings, this study builds on benthic habitat mapping efforts and highlights the need for regional collaboration to standardize seafloor data collection and sharing activities for supporting offshore wind energy decisions.
{"title":"Mapping Seafloor Sediment Distributions Using Public Geospatial Data and Machine Learning to Support Regional Offshore Renewable Energy Development","authors":"Connor W. Capizzano, Alexandria C. Rhoads, Jennifer A. Croteau, Benjamin G. Taylor, M. Guarinello, Emily J. Shumchenia","doi":"10.3390/geosciences14070186","DOIUrl":"https://doi.org/10.3390/geosciences14070186","url":null,"abstract":"Given the rapid expansion of offshore wind development in the United States (US), the accurate mapping of benthic habitats, specifically surficial sediments, is essential for mitigating potential impacts on these valuable ecosystems. However, offshore wind development has outpaced results from environmental monitoring efforts, compelling stakeholders to rely on a limited set of public geospatial data for conducting impact assessments. The present study therefore sought to develop and evaluate a systematic workflow for generating regional-scale sediment maps using public geospatial data that may pose integration and modeling challenges. To demonstrate this approach, sediment distributions were characterized on the northeastern US continental shelf where offshore wind development has occurred since 2016. Publicly available sediment and bathymetric data in the region were processed using national classification standards and spatial tools, respectively, and integrated using a machine learning algorithm to predict sediment occurrence. Overall, this approach and the generated sediment composite effectively predicted sediment distributions in coastal areas but underperformed in offshore areas where data were either scarce or of poor quality. Despite these shortcomings, this study builds on benthic habitat mapping efforts and highlights the need for regional collaboration to standardize seafloor data collection and sharing activities for supporting offshore wind energy decisions.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"125 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656689","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 : 2024-07-09DOI: 10.3390/geosciences14070183
Youngjae Shin
This study utilizes domain adaptation to enhance the integration of diverse geoscience datasets, aiming to improve the identification of ore bodies. Traditional mineral exploration methods often face challenges in merging different geoscience data types, which leads to models that do not perform well across varying domains. Domain adaptation is a deep learning strategy aimed at adapting a model developed in one domain (source) to perform well in a different domain (target). To adapt models trained on detailed, labeled drilling data (source) to interpret broader, unlabeled geophysical data (target), Domain-Adversarial Neural Networks (DANNs) were applied, chosen for their robust performance in scenarios where the target domain does not provide labels. This approach was indirectly validated through the minimal overlap between regions identified as candidate ore and borehole locations marked as host rocks, with qualitative validation provided by t-Distributed Stochastic Neighbor Embedding (t-SNE) visualizations showing improved data integration across domains.
{"title":"Domain Adaptation from Drilling to Geophysical Data for Mineral Exploration","authors":"Youngjae Shin","doi":"10.3390/geosciences14070183","DOIUrl":"https://doi.org/10.3390/geosciences14070183","url":null,"abstract":"This study utilizes domain adaptation to enhance the integration of diverse geoscience datasets, aiming to improve the identification of ore bodies. Traditional mineral exploration methods often face challenges in merging different geoscience data types, which leads to models that do not perform well across varying domains. Domain adaptation is a deep learning strategy aimed at adapting a model developed in one domain (source) to perform well in a different domain (target). To adapt models trained on detailed, labeled drilling data (source) to interpret broader, unlabeled geophysical data (target), Domain-Adversarial Neural Networks (DANNs) were applied, chosen for their robust performance in scenarios where the target domain does not provide labels. This approach was indirectly validated through the minimal overlap between regions identified as candidate ore and borehole locations marked as host rocks, with qualitative validation provided by t-Distributed Stochastic Neighbor Embedding (t-SNE) visualizations showing improved data integration across domains.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"61 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141665159","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 : 2024-07-08DOI: 10.3390/geosciences14070182
Pooja Somadas, Purushotham G. Sarvade, Deepak Nayak
Stabilization using industrial by-products is presently gaining importance in the construction sector for improving the geotechnical characteristics of soft soils. The optimum dosage of stabilisers has become of great interest to experimenters in terms of improved strength, time, and economy for construction projects. This work presents the utilization of biomedical waste ash for improving the strength of soft soil. In this paper, response surface methodology (RSM) was adopted to determine the optimum combination curing period (C) and biomedical waste ash (BA) quantity for attaining the maximum unconfined compressive strength (UCS) of soft soil and to reduce the number of trial tests required. The response factors C and BA were varied from 0 to 14 days and 4% to 20%, respectively, and the experiments were conducted according to the experimental plan provided by the RSM design. Based on a Face-centred Central Composite Design (FCCCD), a mathematical equation was created for the experimental results. Analysis of variance (ANOVA) was used to determine the generated model’s significance, and the results indicated a statically significant model (p ≤ 0.05). The results revealed that the curing period imparts more influence towards strength improvement, and the optimum dosage was 19.912% BA, with curing of 14 days to yield a maximum UCS of 203.008 kPa. This optimization technique may be suggested to obtain a preliminary estimation of strength prior to stabilization.
{"title":"Advancements in Soft Soil Stabilization by Employing Novel Materials through Response Surface Methodology","authors":"Pooja Somadas, Purushotham G. Sarvade, Deepak Nayak","doi":"10.3390/geosciences14070182","DOIUrl":"https://doi.org/10.3390/geosciences14070182","url":null,"abstract":"Stabilization using industrial by-products is presently gaining importance in the construction sector for improving the geotechnical characteristics of soft soils. The optimum dosage of stabilisers has become of great interest to experimenters in terms of improved strength, time, and economy for construction projects. This work presents the utilization of biomedical waste ash for improving the strength of soft soil. In this paper, response surface methodology (RSM) was adopted to determine the optimum combination curing period (C) and biomedical waste ash (BA) quantity for attaining the maximum unconfined compressive strength (UCS) of soft soil and to reduce the number of trial tests required. The response factors C and BA were varied from 0 to 14 days and 4% to 20%, respectively, and the experiments were conducted according to the experimental plan provided by the RSM design. Based on a Face-centred Central Composite Design (FCCCD), a mathematical equation was created for the experimental results. Analysis of variance (ANOVA) was used to determine the generated model’s significance, and the results indicated a statically significant model (p ≤ 0.05). The results revealed that the curing period imparts more influence towards strength improvement, and the optimum dosage was 19.912% BA, with curing of 14 days to yield a maximum UCS of 203.008 kPa. This optimization technique may be suggested to obtain a preliminary estimation of strength prior to stabilization.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":" June","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141669837","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 : 2024-07-08DOI: 10.3390/geosciences14070181
F. Luino, S. Bonetto, Barbara Bono, C. Comina, William W. Little, Sabina Porfido, Paolo Sassone, L. Turconi
Coniolo and Brusaschetto, are two small towns located in the Monferrato area of the Alessandria Province, northern Italy. These communities have similar histories related to development and subsequent abandonment of marl quarry activity that began more than a century ago and continued until recently. Quarrying occurred until soil conditions, water infiltration, and excessive depth made cost of extracting and7 lifting material prohibitive. Quarries consisted of tunnels located directly beneath the towns at about 150 m below ground surface. Collapse of the tunnels led to surface subsidence and destruction of overlying homes and much of the municipal infrastructure. In the early Twentieth Century, regulations pertaining to mine and quarry safety were typically deficient, entirely absent, or not followed. Extractive activities of non-energy mineral resources from quarries and mines were and continue to be widespread in Italy, which currently ranks fifth among what are now countries of the European Union (EU). Mining sites are present in all regions of Italy, particularly in the northern part of the country and along coasts, often in areas of geohydrogeological risk. Consequences of anthropogenic pressures that alter the natural environment, such as the physical size of aquifer drawdowns, are linked to issues for a number of extractive sites across the country. This report analyzes historical and technical documents, conducts a geomorphological analysis of hilly slopes surrounding these communities, and examines urban planning and geophysical surveys to determine the impact of subsurface quarrying activities on the overlying ground surface. The study highlights significant problems that are applicable to other localities globally. This research demonstrates: (a) the importance of geological considerations to development and abandonment of mining activity in inhabited areas; (b) the importance of establishing and following safety protocols; and (c) the manner in which economic interests can take precedence over the well-being and lives of those employed to extract resources.
{"title":"Marl Mining Activity and Negative Repercussions for Two Hillside Villages (Northern Italy)","authors":"F. Luino, S. Bonetto, Barbara Bono, C. Comina, William W. Little, Sabina Porfido, Paolo Sassone, L. Turconi","doi":"10.3390/geosciences14070181","DOIUrl":"https://doi.org/10.3390/geosciences14070181","url":null,"abstract":"Coniolo and Brusaschetto, are two small towns located in the Monferrato area of the Alessandria Province, northern Italy. These communities have similar histories related to development and subsequent abandonment of marl quarry activity that began more than a century ago and continued until recently. Quarrying occurred until soil conditions, water infiltration, and excessive depth made cost of extracting and7 lifting material prohibitive. Quarries consisted of tunnels located directly beneath the towns at about 150 m below ground surface. Collapse of the tunnels led to surface subsidence and destruction of overlying homes and much of the municipal infrastructure. In the early Twentieth Century, regulations pertaining to mine and quarry safety were typically deficient, entirely absent, or not followed. Extractive activities of non-energy mineral resources from quarries and mines were and continue to be widespread in Italy, which currently ranks fifth among what are now countries of the European Union (EU). Mining sites are present in all regions of Italy, particularly in the northern part of the country and along coasts, often in areas of geohydrogeological risk. Consequences of anthropogenic pressures that alter the natural environment, such as the physical size of aquifer drawdowns, are linked to issues for a number of extractive sites across the country. This report analyzes historical and technical documents, conducts a geomorphological analysis of hilly slopes surrounding these communities, and examines urban planning and geophysical surveys to determine the impact of subsurface quarrying activities on the overlying ground surface. The study highlights significant problems that are applicable to other localities globally. This research demonstrates: (a) the importance of geological considerations to development and abandonment of mining activity in inhabited areas; (b) the importance of establishing and following safety protocols; and (c) the manner in which economic interests can take precedence over the well-being and lives of those employed to extract resources.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"120 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666916","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/geosciences14060168
Edwin Badillo-Rivera, Manuel Olcese, Ramiro Santiago, Teófilo Poma, Neftalí Muñoz, Carlos Rojas-León, Teodosio Chávez, Luz Eyzaguirre, César Rodríguez, Fernando Oyanguren
This study addresses the importance of conducting mass movement susceptibility mapping and hazard assessment using quantitative techniques, including machine learning, in the Northern Lima Commonwealth (NLC). A previous exploration of the topographic variables revealed a high correlation and multicollinearity among some of them, which led to dimensionality reduction through a principal component analysis (PCA). Six susceptibility models were generated using weights of evidence, logistic regression, multilayer perceptron, support vector machine, random forest, and naive Bayes methods to produce quantitative susceptibility maps and assess the hazard associated with two scenarios: the first being El Niño phenomenon and the second being an earthquake exceeding 8.8 Mw. The main findings indicate that machine learning models exhibit excellent predictive performance for the presence and absence of mass movement events, as all models surpassed an AUC value of >0.9, with the random forest model standing out. In terms of hazard levels, in the event of an El Niño phenomenon or an earthquake exceeding 8.8 Mw, approximately 40% and 35% respectively, of the NLC area would be exposed to the highest hazard levels. The importance of integrating methodologies in mass movement susceptibility models is also emphasized; these methodologies include the correlation analysis, multicollinearity assessment, dimensionality reduction of variables, and coupling statistical models with machine learning models to improve the predictive accuracy of machine learning models. The findings of this research are expected to serve as a supportive tool for land managers in formulating effective disaster prevention and risk reduction strategies.
{"title":"A Comparative Study of Susceptibility and Hazard for Mass Movements Applying Quantitative Machine Learning Techniques—Case Study: Northern Lima Commonwealth, Peru","authors":"Edwin Badillo-Rivera, Manuel Olcese, Ramiro Santiago, Teófilo Poma, Neftalí Muñoz, Carlos Rojas-León, Teodosio Chávez, Luz Eyzaguirre, César Rodríguez, Fernando Oyanguren","doi":"10.3390/geosciences14060168","DOIUrl":"https://doi.org/10.3390/geosciences14060168","url":null,"abstract":"This study addresses the importance of conducting mass movement susceptibility mapping and hazard assessment using quantitative techniques, including machine learning, in the Northern Lima Commonwealth (NLC). A previous exploration of the topographic variables revealed a high correlation and multicollinearity among some of them, which led to dimensionality reduction through a principal component analysis (PCA). Six susceptibility models were generated using weights of evidence, logistic regression, multilayer perceptron, support vector machine, random forest, and naive Bayes methods to produce quantitative susceptibility maps and assess the hazard associated with two scenarios: the first being El Niño phenomenon and the second being an earthquake exceeding 8.8 Mw. The main findings indicate that machine learning models exhibit excellent predictive performance for the presence and absence of mass movement events, as all models surpassed an AUC value of >0.9, with the random forest model standing out. In terms of hazard levels, in the event of an El Niño phenomenon or an earthquake exceeding 8.8 Mw, approximately 40% and 35% respectively, of the NLC area would be exposed to the highest hazard levels. The importance of integrating methodologies in mass movement susceptibility models is also emphasized; these methodologies include the correlation analysis, multicollinearity assessment, dimensionality reduction of variables, and coupling statistical models with machine learning models to improve the predictive accuracy of machine learning models. The findings of this research are expected to serve as a supportive tool for land managers in formulating effective disaster prevention and risk reduction strategies.","PeriodicalId":509137,"journal":{"name":"Geosciences","volume":"37 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141339976","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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