2021 Vol. 12, No. 5
2021, 12(5): 101154.
doi: 10.1016/j.gsf.2021.101154
Abstract:
The groundwater potential map is an important tool for a sustainable water management and land use planning, particularly for agricultural countries like Vietnam. In this article, we proposed new machine learning ensemble techniques namely AdaBoost ensemble (ABLWL), Bagging ensemble (BLWL), Multi Boost ensemble (MBLWL), Rotation Forest ensemble (RFLWL) with Locally Weighted Learning (LWL) algorithm as a base classifier to build the groundwater potential map of Gia Lai province in Vietnam. For this study, eleven conditioning factors (aspect, altitude, curvature, slope, Stream Transport Index (STI), Topographic Wetness Index (TWI), soil, geology, river density, rainfall, land-use) and 134 wells yield data was used to create training (70%) and testing (30%) datasets for the development and validation of the models. Several statistical indices were used namely Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SST), Specificity (SPF), Accuracy (ACC), Kappa, and Receiver Operating Characteristics (ROC) curve to validate and compare performance of models. Results show that performance of all the models is good to very good (AUC: 0.75 to 0.829) but the ABLWL model with AUC = 0.89 is the best. All the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters.
The groundwater potential map is an important tool for a sustainable water management and land use planning, particularly for agricultural countries like Vietnam. In this article, we proposed new machine learning ensemble techniques namely AdaBoost ensemble (ABLWL), Bagging ensemble (BLWL), Multi Boost ensemble (MBLWL), Rotation Forest ensemble (RFLWL) with Locally Weighted Learning (LWL) algorithm as a base classifier to build the groundwater potential map of Gia Lai province in Vietnam. For this study, eleven conditioning factors (aspect, altitude, curvature, slope, Stream Transport Index (STI), Topographic Wetness Index (TWI), soil, geology, river density, rainfall, land-use) and 134 wells yield data was used to create training (70%) and testing (30%) datasets for the development and validation of the models. Several statistical indices were used namely Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SST), Specificity (SPF), Accuracy (ACC), Kappa, and Receiver Operating Characteristics (ROC) curve to validate and compare performance of models. Results show that performance of all the models is good to very good (AUC: 0.75 to 0.829) but the ABLWL model with AUC = 0.89 is the best. All the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters.
2021, 12(5): 101171.
doi: 10.1016/j.gsf.2021.101171
Abstract:
Changbaishan, an intraplate volcano, is characterized by an approximately 6 km wide summit caldera and last erupted in 1903. Changbaishan experienced a period of unrest between 2002 and 2006. The activity developed in three main stages, including shield volcano (basalts), cone-construction (trachyandesites to trachytes with minor basalts), and caldera-forming stages (trachytes to comendites). This last stage is associated with one of the more energetic eruptions of the last millennium on Earth, the 946 CE, VEI 7 Millennium Eruption (ME), which emitted over 100 km3 of pyroclastics. Compared to other active calderas, the plumbing system of Changbaishan and its evolution mechanisms remain poorly constrained. Here, we merge new whole-rock, glass, mineral, isotopic, and geobarometry data with geophysical data and present a model of the plumbing system. The results show that the volcano is characterized by at least three main magma reservoirs at different depths: a basaltic reservoir at the Moho/lower crust depth, an intermediate reservoir at 10–15 km depth, and a shallower reservoir at 0.5–3 km depth. The shallower reservoir was involved in the ME eruption, which was triggered by a fresh trachytic melt entering a shallower reservoir where a comenditic magma was stored. The trachytes and comendites originate from fractional crystallization processes and minor assimilation of upper crust material, while the less evolved melts assimilate lower crust material. Syn-eruptive magma mingling occurred during the ME eruption phase. The magma reservoirs of the caldera-forming stage partly reactivate those of the cone-construction stage. The depth of the magma storage zones is controlled by the layering of the crust. The plumbing system of Changbaishan is vertically extensive, with crystal mush reservoirs renewed by the replenishment of new trachytic to trachyandesitic magma from depth. Unlike other volcanoes, evidence of a basaltic recharge is lacking. The interpretation of the signals preceding possible future eruptions should consider the multi-level nature of the Changbaishan plumbing system. A new arrival of magma may destabilize a part of or the entire system, thus triggering eruptions of different sizes and styles. The reference model proposed here for Changbaishan represents a prerequisite to properly understand periods of unrest to potentially anticipate future volcanic eruptions and to identify the mechanisms controlling the evolution of the crust below volcanoes.
Changbaishan, an intraplate volcano, is characterized by an approximately 6 km wide summit caldera and last erupted in 1903. Changbaishan experienced a period of unrest between 2002 and 2006. The activity developed in three main stages, including shield volcano (basalts), cone-construction (trachyandesites to trachytes with minor basalts), and caldera-forming stages (trachytes to comendites). This last stage is associated with one of the more energetic eruptions of the last millennium on Earth, the 946 CE, VEI 7 Millennium Eruption (ME), which emitted over 100 km3 of pyroclastics. Compared to other active calderas, the plumbing system of Changbaishan and its evolution mechanisms remain poorly constrained. Here, we merge new whole-rock, glass, mineral, isotopic, and geobarometry data with geophysical data and present a model of the plumbing system. The results show that the volcano is characterized by at least three main magma reservoirs at different depths: a basaltic reservoir at the Moho/lower crust depth, an intermediate reservoir at 10–15 km depth, and a shallower reservoir at 0.5–3 km depth. The shallower reservoir was involved in the ME eruption, which was triggered by a fresh trachytic melt entering a shallower reservoir where a comenditic magma was stored. The trachytes and comendites originate from fractional crystallization processes and minor assimilation of upper crust material, while the less evolved melts assimilate lower crust material. Syn-eruptive magma mingling occurred during the ME eruption phase. The magma reservoirs of the caldera-forming stage partly reactivate those of the cone-construction stage. The depth of the magma storage zones is controlled by the layering of the crust. The plumbing system of Changbaishan is vertically extensive, with crystal mush reservoirs renewed by the replenishment of new trachytic to trachyandesitic magma from depth. Unlike other volcanoes, evidence of a basaltic recharge is lacking. The interpretation of the signals preceding possible future eruptions should consider the multi-level nature of the Changbaishan plumbing system. A new arrival of magma may destabilize a part of or the entire system, thus triggering eruptions of different sizes and styles. The reference model proposed here for Changbaishan represents a prerequisite to properly understand periods of unrest to potentially anticipate future volcanic eruptions and to identify the mechanisms controlling the evolution of the crust below volcanoes.
2021, 12(5): 101173.
doi: 10.1016/j.gsf.2021.101173
Abstract:
To constrain the ore-fluid source(s) of the Laoshankou Fe-Cu-Au deposit (Junggar orogen, NW China), we analyzed the fluid inclusion (FI) noble gas (Ar, Kr and Xe) and halogen (Cl, Br and I) compositions in the hydrothermal epidote and quartz. Four hypogene alteration/mineralization stages, including (I) pre-ore Ca-silicate, (II) early-ore amphibole-epidote-magnetite, (III) late-ore pyrite-chalcopyrite, and (IV) post-ore hydrothermal veining, have been identified at Laoshankou. Stage II FIs have salinity of 15.7 wt.% (NaCl eq.), I/Cl molar ratios of 75 × 10−6–135 × 10−6, and Br/Cl molar ratios of 1.4 × 10−3–2.1 × 10−3. The moderately-high seawater-corrected Br*/I ratios (0.5–1.5) and low 40ArE/Cl slope (~10−5) indicate the presence of sedimentary marine pore fluid, which was modified by seawater reacting with the Beitashan Fm. volcanic rocks. Stage III fluid is more saline than their stage II and IV counterparts, reaching up to 23.3 wt.% (NaCl+CaCl2 eq.) close to halite saturation (~26 wt.%). The fluid has I/Cl ratios of 75 × 10−6–90 × 10−6 and Br/Cl ratios of 1.5 × 10−3–1.8 × 10−3. Considering the increasing 40ArE/Cl trend toward bittern brine and the higher 36Ar content than air-saturated water (ASW), a bittern fluid source is inferred from seawater evaporation, which was modified by interaction with organic-rich marine sedimentary rocks. Stage IV FIs have lower temperature (110–228 °C) and Br/Cl (0.90 × 10−3–1.2 × 10−3), but higher 36Ar content than ASW, indicative of dissolved evaporite or halite input. Considering also the low δDfluid (−114‰ to −144‰) and δ18Ofluid (2.1‰–3.5‰) values, meteoric water (with minor dissolved evaporites) likely dominated the stage IV fluid. The evaporites may have formed through continuous evaporation of the stage III surface-derived bittern. Involvement of non-magmatic fluids and different ore-fluid origins in stages II and III suggest that the ore-forming process was different from a typical magmatic-hydrothermal fluid-dominated skarn mineralization, which was previously proposed for Laoshankou. Our noble gas and halogen study at Laoshankou provide new insights on the fluid sources for the Paleozoic Fe−Cu (−Au) deposits in the Central Asian Orogenic Belt (CAOB), and our non-magmatic fluid source interpretation is consistent with the basin inversion setting for the mineralization.
To constrain the ore-fluid source(s) of the Laoshankou Fe-Cu-Au deposit (Junggar orogen, NW China), we analyzed the fluid inclusion (FI) noble gas (Ar, Kr and Xe) and halogen (Cl, Br and I) compositions in the hydrothermal epidote and quartz. Four hypogene alteration/mineralization stages, including (I) pre-ore Ca-silicate, (II) early-ore amphibole-epidote-magnetite, (III) late-ore pyrite-chalcopyrite, and (IV) post-ore hydrothermal veining, have been identified at Laoshankou. Stage II FIs have salinity of 15.7 wt.% (NaCl eq.), I/Cl molar ratios of 75 × 10−6–135 × 10−6, and Br/Cl molar ratios of 1.4 × 10−3–2.1 × 10−3. The moderately-high seawater-corrected Br*/I ratios (0.5–1.5) and low 40ArE/Cl slope (~10−5) indicate the presence of sedimentary marine pore fluid, which was modified by seawater reacting with the Beitashan Fm. volcanic rocks. Stage III fluid is more saline than their stage II and IV counterparts, reaching up to 23.3 wt.% (NaCl+CaCl2 eq.) close to halite saturation (~26 wt.%). The fluid has I/Cl ratios of 75 × 10−6–90 × 10−6 and Br/Cl ratios of 1.5 × 10−3–1.8 × 10−3. Considering the increasing 40ArE/Cl trend toward bittern brine and the higher 36Ar content than air-saturated water (ASW), a bittern fluid source is inferred from seawater evaporation, which was modified by interaction with organic-rich marine sedimentary rocks. Stage IV FIs have lower temperature (110–228 °C) and Br/Cl (0.90 × 10−3–1.2 × 10−3), but higher 36Ar content than ASW, indicative of dissolved evaporite or halite input. Considering also the low δDfluid (−114‰ to −144‰) and δ18Ofluid (2.1‰–3.5‰) values, meteoric water (with minor dissolved evaporites) likely dominated the stage IV fluid. The evaporites may have formed through continuous evaporation of the stage III surface-derived bittern. Involvement of non-magmatic fluids and different ore-fluid origins in stages II and III suggest that the ore-forming process was different from a typical magmatic-hydrothermal fluid-dominated skarn mineralization, which was previously proposed for Laoshankou. Our noble gas and halogen study at Laoshankou provide new insights on the fluid sources for the Paleozoic Fe−Cu (−Au) deposits in the Central Asian Orogenic Belt (CAOB), and our non-magmatic fluid source interpretation is consistent with the basin inversion setting for the mineralization.
2021, 12(5): 101174.
doi: 10.1016/j.gsf.2021.101174
Abstract:
New geochronologic data from midcontinental Laurentia demonstrate that emplacement of the 1476–1470 Ma Wolf River granitic batholith was not an isolated igneous event, but was accompanied by regional metamorphism, deformation, and sedimentation. Evidence for such metamorphism and deformation is best seen in siliciclastic sedimentary rocks of the Baraboo Interval, which were deposited closely following the 1.65–1.63 Ga Mazatzal orogeny. In Baraboo Interval strata, muscovite parallel to slatey cleavage, in hydrothermal veins, in quartzite breccia, and in metamorphosed paleosol yielded 40Ar/39Ar plateau ages of 1493–1465 Ma. In addition, U–Th–total Pb dating of neoblastic overgrowths on detrital monazite gave an age of 1488 ± 20 Ma, and recrystallized hematite in folded metapelite gave a mean U/Th–He age of 1411 ± 39 Ma. Post-Baraboo, arkosic polymictic conglomerate, which contains detrital zircon with a minimum peak age of 1493 Ma, was intruded by a 1470 Ma granite porphyry at the northeastern margin of the Wolf River batholith. This episode of magmatism, regional deformation and metamorphism, and sedimentation, which is designated herein as the Baraboo orogeny, provides a midcontinental link between the Picuris orogeny to the southwest and the Pinware orogeny to the northeast, completing the extent of early Mesoproterozoic (Calymmian) orogenesis for 5000 km along the southern margin of Laurentia. This transcontinental orogen is unique among Precambrian orogenies for its great width (~1600 km), the predominance of ferroan granites derived from partial melting of lower continental crust, and the prevalence of regional high T-P metamorphism related to advective heating by granitic magmas emplaced in the middle to upper crust.
New geochronologic data from midcontinental Laurentia demonstrate that emplacement of the 1476–1470 Ma Wolf River granitic batholith was not an isolated igneous event, but was accompanied by regional metamorphism, deformation, and sedimentation. Evidence for such metamorphism and deformation is best seen in siliciclastic sedimentary rocks of the Baraboo Interval, which were deposited closely following the 1.65–1.63 Ga Mazatzal orogeny. In Baraboo Interval strata, muscovite parallel to slatey cleavage, in hydrothermal veins, in quartzite breccia, and in metamorphosed paleosol yielded 40Ar/39Ar plateau ages of 1493–1465 Ma. In addition, U–Th–total Pb dating of neoblastic overgrowths on detrital monazite gave an age of 1488 ± 20 Ma, and recrystallized hematite in folded metapelite gave a mean U/Th–He age of 1411 ± 39 Ma. Post-Baraboo, arkosic polymictic conglomerate, which contains detrital zircon with a minimum peak age of 1493 Ma, was intruded by a 1470 Ma granite porphyry at the northeastern margin of the Wolf River batholith. This episode of magmatism, regional deformation and metamorphism, and sedimentation, which is designated herein as the Baraboo orogeny, provides a midcontinental link between the Picuris orogeny to the southwest and the Pinware orogeny to the northeast, completing the extent of early Mesoproterozoic (Calymmian) orogenesis for 5000 km along the southern margin of Laurentia. This transcontinental orogen is unique among Precambrian orogenies for its great width (~1600 km), the predominance of ferroan granites derived from partial melting of lower continental crust, and the prevalence of regional high T-P metamorphism related to advective heating by granitic magmas emplaced in the middle to upper crust.
2021, 12(5): 101175.
doi: 10.1016/j.gsf.2021.101175
Abstract:
The flood hazard management is one of the major challenges in the floodplain regions worldwide. With the rise in population growth and the spread of infrastructural development, the level of risk has increased over time. Therefore, the prediction of flood susceptible area is a key challenge for the adoption of management plans. Flood susceptibility modeling is technically a common work, but it is still a very tough job to validate flood susceptible models in a very rigorous and scientific manner. Therefore, the present work in the Atreyee River Basin of India and Bangladesh was planned to establish artificial neural network (ANN), radial basis function (RBF), random forest (RF) and their ensemble-based flood susceptibility models. The flood susceptible models were constructed based on nine flood conditioning parameters. The flood susceptibility models were validated in a conventional way using the receiver operating curve (ROC). To validate the flood-susceptible models, a two dimensional (2D) hydraulic flood simulation model was developed. Also, the index of flood vulnerability model was developed and applied for validating the flood susceptible models, which was a very unique way to validate the predictive models. Friedman test and Wilcoxon Signed rank test were employed to compare the generated flood susceptible models. Results showed that 11.95%–12.99% of the entire basin area (10188.4 km2) comes under very high flood-susceptible zones. Accuracy evaluation results have shown that the performance of ensemble flood susceptible models outperforms other standalone machine learning models. The flood simulation model and IFV model were also spatially adjusted with the flood susceptibility models. Therefore, the present study recommended for the ensemble flood susceptibility prediction and IFV based validation along with conventional ways.
The flood hazard management is one of the major challenges in the floodplain regions worldwide. With the rise in population growth and the spread of infrastructural development, the level of risk has increased over time. Therefore, the prediction of flood susceptible area is a key challenge for the adoption of management plans. Flood susceptibility modeling is technically a common work, but it is still a very tough job to validate flood susceptible models in a very rigorous and scientific manner. Therefore, the present work in the Atreyee River Basin of India and Bangladesh was planned to establish artificial neural network (ANN), radial basis function (RBF), random forest (RF) and their ensemble-based flood susceptibility models. The flood susceptible models were constructed based on nine flood conditioning parameters. The flood susceptibility models were validated in a conventional way using the receiver operating curve (ROC). To validate the flood-susceptible models, a two dimensional (2D) hydraulic flood simulation model was developed. Also, the index of flood vulnerability model was developed and applied for validating the flood susceptible models, which was a very unique way to validate the predictive models. Friedman test and Wilcoxon Signed rank test were employed to compare the generated flood susceptible models. Results showed that 11.95%–12.99% of the entire basin area (10188.4 km2) comes under very high flood-susceptible zones. Accuracy evaluation results have shown that the performance of ensemble flood susceptible models outperforms other standalone machine learning models. The flood simulation model and IFV model were also spatially adjusted with the flood susceptibility models. Therefore, the present study recommended for the ensemble flood susceptibility prediction and IFV based validation along with conventional ways.
2021, 12(5): 101177.
doi: 10.1016/j.gsf.2021.101177
Abstract:
This paper introduces an intelligent framework for predicting the advancing speed during earth pressure balance (EPB) shield tunnelling. Five artificial intelligence (AI) models based on machine and deep learning techniques—back-propagation neural network (BPNN), extreme learning machine (ELM), support vector machine (SVM), long-short term memory (LSTM), and gated recurrent unit (GRU)—are used. Five geological and nine operational parameters that influence the advancing speed are considered. A field case of shield tunnelling in Shenzhen City, China is analyzed using the developed models. A total of 1000 field datasets are adopted to establish intelligent models. The prediction performance of the five models is ranked as GRU > LSTM > SVM > ELM > BPNN. Moreover, the Pearson correlation coefficient (PCC) is adopted for sensitivity analysis. The results reveal that the main thrust (MT), penetration (P), foam volume (FV), and grouting volume (GV) have strong correlations with advancing speed (AS). An empirical formula is constructed based on the high-correlation influential factors and their corresponding field datasets. Finally, the prediction performances of the intelligent models and the empirical method are compared. The results reveal that all the intelligent models perform better than the empirical method.
This paper introduces an intelligent framework for predicting the advancing speed during earth pressure balance (EPB) shield tunnelling. Five artificial intelligence (AI) models based on machine and deep learning techniques—back-propagation neural network (BPNN), extreme learning machine (ELM), support vector machine (SVM), long-short term memory (LSTM), and gated recurrent unit (GRU)—are used. Five geological and nine operational parameters that influence the advancing speed are considered. A field case of shield tunnelling in Shenzhen City, China is analyzed using the developed models. A total of 1000 field datasets are adopted to establish intelligent models. The prediction performance of the five models is ranked as GRU > LSTM > SVM > ELM > BPNN. Moreover, the Pearson correlation coefficient (PCC) is adopted for sensitivity analysis. The results reveal that the main thrust (MT), penetration (P), foam volume (FV), and grouting volume (GV) have strong correlations with advancing speed (AS). An empirical formula is constructed based on the high-correlation influential factors and their corresponding field datasets. Finally, the prediction performances of the intelligent models and the empirical method are compared. The results reveal that all the intelligent models perform better than the empirical method.
2021, 12(5): 101178.
doi: 10.1016/j.gsf.2021.101178
Abstract:
Chromite, a crucial high-conductivity mineral phase of peridotite in ophiolite suites, has a significant effect on the electrical structure of subduction zones. The electrical conductivities of sintered polycrystalline olivine containing various volume percents of chromite (0, 4, 7, 10, 13, 16, 18, 21, 23, 100 vol.%) were measured using a complex impedance spectroscopic technique in the frequency range of 10−1–106 Hz under the conditions of 1.0–3.0 GPa and 873–1223 K. The relationship between the conductivities of the chromite-bearing olivine aggregates and temperatures conformed to the Arrhenius equation. The positive effect of pressure on the conductivities of the olivine–chromite systems was much weaker than that of temperature. The chromite content had an important effect on the conductivities of the olivine–chromite systems, and the bulk conductivities increased with increasing volume fraction of chromite to a certain extent. The inclusion of 16 vol.% chromites dramatically enhanced the bulk conductivity, implying that the percolation threshold of interconnectivity of chromite in the olivine–chromite systems is ~16 vol.%. The fitted activation enthalpies for pure polycrystalline olivine, polycrystalline olivine with isolated chromite, polycrystalline olivine with interconnected chromites, and pure polycrystalline chromite were 1.25, 0.78–0.87, 0.48–0.54, and 0.47 eV, respectively. Based on the chemical compositions and activation enthalpies, small polaron conduction was proposed to be the dominant conduction mechanism for polycrystalline olivine with various chromite contents. Furthermore, the conductivities of polycrystalline olivine with interconnected chromite (10–1.5–100.5 S/m) provides a reasonable explanation for the high conductivity anomalies in subduction-related tectonic environments.
Chromite, a crucial high-conductivity mineral phase of peridotite in ophiolite suites, has a significant effect on the electrical structure of subduction zones. The electrical conductivities of sintered polycrystalline olivine containing various volume percents of chromite (0, 4, 7, 10, 13, 16, 18, 21, 23, 100 vol.%) were measured using a complex impedance spectroscopic technique in the frequency range of 10−1–106 Hz under the conditions of 1.0–3.0 GPa and 873–1223 K. The relationship between the conductivities of the chromite-bearing olivine aggregates and temperatures conformed to the Arrhenius equation. The positive effect of pressure on the conductivities of the olivine–chromite systems was much weaker than that of temperature. The chromite content had an important effect on the conductivities of the olivine–chromite systems, and the bulk conductivities increased with increasing volume fraction of chromite to a certain extent. The inclusion of 16 vol.% chromites dramatically enhanced the bulk conductivity, implying that the percolation threshold of interconnectivity of chromite in the olivine–chromite systems is ~16 vol.%. The fitted activation enthalpies for pure polycrystalline olivine, polycrystalline olivine with isolated chromite, polycrystalline olivine with interconnected chromites, and pure polycrystalline chromite were 1.25, 0.78–0.87, 0.48–0.54, and 0.47 eV, respectively. Based on the chemical compositions and activation enthalpies, small polaron conduction was proposed to be the dominant conduction mechanism for polycrystalline olivine with various chromite contents. Furthermore, the conductivities of polycrystalline olivine with interconnected chromite (10–1.5–100.5 S/m) provides a reasonable explanation for the high conductivity anomalies in subduction-related tectonic environments.
Aeolian dust dynamics in the Fergana Valley, Central Asia, since ~30 ka inferred from loess deposits
2021, 12(5): 101180.
doi: 10.1016/j.gsf.2021.101180
Abstract:
Knowledge of the interactions among atmospheric dynamics, dust emissions and climate system is essential to understand the physical mechanisms for the dust lifecycle, their role in loess formation as well as the predictions of future dust concentration. However, these issues still remain relatively poorly known in Central Asia (CA). The extensive loess deposits on the CA pediments provide a promising archive to explore atmospheric dust dynamics and climatic conditions in the past and their association with loess formation. This study investigates the granulometric and magnetic properties of a loess section (named Osh section) in the Fergana Valley, which provides a sensitive record of atmospheric dust dynamics since 30 ka based on radiometric (AMS 14C) dating. The frequency-dependent magnetic susceptibility (χfd) and the mean grain size are used to reconstruct the broad-scale effective moisture and summer atmospheric dynamics pattern in CA, respectively. The results show that the precession forcing exerts a huge influence on the wind-regime variabilities in CA, but with different physical processes under the impact of the Northern Hemisphere ice sheet (NHIS) before and after 15 ka. The origin of the sedimentation rate variations in the Osh loess is also linked to the NHIS-modulated changes of the atmospheric circulation patterns. Either the strengthened westerlies or the increased surface roughness from higher vegetation cover in loess-deposition areas have significantly accelerated the loess accumulation. As a result, these complicated influence factors of sedimentation rate change in the Osh loess section, especially during the Holocene epoch, may hamper accessibility of the authentic dust emission flux and atmospheric dust concentration in CA.
Knowledge of the interactions among atmospheric dynamics, dust emissions and climate system is essential to understand the physical mechanisms for the dust lifecycle, their role in loess formation as well as the predictions of future dust concentration. However, these issues still remain relatively poorly known in Central Asia (CA). The extensive loess deposits on the CA pediments provide a promising archive to explore atmospheric dust dynamics and climatic conditions in the past and their association with loess formation. This study investigates the granulometric and magnetic properties of a loess section (named Osh section) in the Fergana Valley, which provides a sensitive record of atmospheric dust dynamics since 30 ka based on radiometric (AMS 14C) dating. The frequency-dependent magnetic susceptibility (χfd) and the mean grain size are used to reconstruct the broad-scale effective moisture and summer atmospheric dynamics pattern in CA, respectively. The results show that the precession forcing exerts a huge influence on the wind-regime variabilities in CA, but with different physical processes under the impact of the Northern Hemisphere ice sheet (NHIS) before and after 15 ka. The origin of the sedimentation rate variations in the Osh loess is also linked to the NHIS-modulated changes of the atmospheric circulation patterns. Either the strengthened westerlies or the increased surface roughness from higher vegetation cover in loess-deposition areas have significantly accelerated the loess accumulation. As a result, these complicated influence factors of sedimentation rate change in the Osh loess section, especially during the Holocene epoch, may hamper accessibility of the authentic dust emission flux and atmospheric dust concentration in CA.
2021, 12(5): 101181.
doi: 10.1016/j.gsf.2021.101181
Abstract:
The Zhaojue (ZJ) tracksites represent multiple steeply-inclined, track-bearing exposures in the clastic Feitianshan Formation of Sichuan Province that have been sequentially, excavated, mapped, expanded and destroyed, by quarrying, erosion or collapse, for almost three decades. The quarried area extends for more almost 1.0 km from north to south and ~ 0.5 km from east to west. Four important track-bearing surfaces have been identified and identified as ZJ-I, ZJ-II, ZJ-IIN and ZJ-III, some of which are newly exposed surfaces or expanded surfaces that were previously partially described. Others represent surfaces lost since they were first reported in papers published in 2014–2016. The ZJ-II site represents a hugely expanded continuation of a much smaller track-bearing surface described in 2014. It was mapped using drone technology, and now represents the largest tracksite in China, with a minimum count of 933 recognizable tracks, and the longest recorded sauropod and ornithopod trackways from China (~80 m and ~52 m respectively), which also reveal a pronounced change in the direction of trackmaker movement. The ZJ-II surface represents the best Zhaojue paleo-census sample giving a count of 68 individuals from 61 trackways (37 ornithopod, 10 theropod, 14 sauropod) and isolated tracks (representing 7 individuals). Thus, ornithopods (both large and small trackmakers) represent ~54% of the total number of trackways. The smaller ZJ-III surface was mapped using traditional methods, and reveals at least 6 ornithopod- and 4 theropod trackways. Both the ZJ-II and ZJ-III surfaces reveal parallel ornithopod trackways suggestive of social or gregarious behavior. The combined data from all four Zhaojue surfaces reveal a total of 1928 tracks, and include a few previously reported pterosaurs and theropod swim tracks. The Zhaojue quarry complex provide a good example of multiple track-bearing sites (surfaces) that require long term study and monitoring to extract as much trackway data as possible before in situ physical evidence is lost.
The Zhaojue (ZJ) tracksites represent multiple steeply-inclined, track-bearing exposures in the clastic Feitianshan Formation of Sichuan Province that have been sequentially, excavated, mapped, expanded and destroyed, by quarrying, erosion or collapse, for almost three decades. The quarried area extends for more almost 1.0 km from north to south and ~ 0.5 km from east to west. Four important track-bearing surfaces have been identified and identified as ZJ-I, ZJ-II, ZJ-IIN and ZJ-III, some of which are newly exposed surfaces or expanded surfaces that were previously partially described. Others represent surfaces lost since they were first reported in papers published in 2014–2016. The ZJ-II site represents a hugely expanded continuation of a much smaller track-bearing surface described in 2014. It was mapped using drone technology, and now represents the largest tracksite in China, with a minimum count of 933 recognizable tracks, and the longest recorded sauropod and ornithopod trackways from China (~80 m and ~52 m respectively), which also reveal a pronounced change in the direction of trackmaker movement. The ZJ-II surface represents the best Zhaojue paleo-census sample giving a count of 68 individuals from 61 trackways (37 ornithopod, 10 theropod, 14 sauropod) and isolated tracks (representing 7 individuals). Thus, ornithopods (both large and small trackmakers) represent ~54% of the total number of trackways. The smaller ZJ-III surface was mapped using traditional methods, and reveals at least 6 ornithopod- and 4 theropod trackways. Both the ZJ-II and ZJ-III surfaces reveal parallel ornithopod trackways suggestive of social or gregarious behavior. The combined data from all four Zhaojue surfaces reveal a total of 1928 tracks, and include a few previously reported pterosaurs and theropod swim tracks. The Zhaojue quarry complex provide a good example of multiple track-bearing sites (surfaces) that require long term study and monitoring to extract as much trackway data as possible before in situ physical evidence is lost.
2021, 12(5): 101182.
doi: 10.1016/j.gsf.2021.101182
Abstract:
Zinc isotopes may act as a new tool of tracking recycling of crustal materials that causes compositional heterogeneity of the mantle. This application relies on an investigation of Zn isotopic behaviors during slab subduction. In this study, we report Zn isotopic compositions for a suite of metabasalts (greenschists, amphibolites, and coesite-bearing eclogites) from the Dabie Orogen (China), which were formed via the subduction of mafic rocks into different depths and up to > 200 km. Three out of eight greenschists are characterized by lighter δ66ZnJMC-Lyon (0.10‰–0.16‰) than those of global basalts (0.28‰ ± 0.05‰), which may be caused by crustal assimilation of the protoliths by sedimentary rocks due to their extremely high 87Sr/86Sr (up to 0.7130) and low εNd values (down to −12.3). The remaining greenschists have relatively low 87Sr/86Sr and their δ66Zn values (0.21‰–0.38‰) overlap the ranges of amphibolites (0.18‰–0.32‰) and coesite-bearing eclogites (0.18‰–0.36‰). There is no correlation between δ66Zn and sensitive indicators of dehydration (Rb/TiO2, Ba/Yb, and H2O+), suggesting that no detectable Zn isotope fractionation has occurred during the deep subduction of mafic rocks even into > 200 km, which is attributed to the limited loss of Zn during prograde metamorphism and dehydration. Thus, Zn isotopic compositions of the deeply subducted mafic rocks are inherited from their protoliths. Considering that these metamorphosed rocks have higher δ66Zn than that of the mantle value by up to 0.2‰, the recycled/subducted mafic crust can incorporate isotopically heavy Zn into the mantle. The subducted slabs may partially melt and generate a metasomatized mantle, resulting in changes of Zn isotopic composition of the hybridized mantle as have been observed in some mantle xenoliths and basaltic lavas.
Zinc isotopes may act as a new tool of tracking recycling of crustal materials that causes compositional heterogeneity of the mantle. This application relies on an investigation of Zn isotopic behaviors during slab subduction. In this study, we report Zn isotopic compositions for a suite of metabasalts (greenschists, amphibolites, and coesite-bearing eclogites) from the Dabie Orogen (China), which were formed via the subduction of mafic rocks into different depths and up to > 200 km. Three out of eight greenschists are characterized by lighter δ66ZnJMC-Lyon (0.10‰–0.16‰) than those of global basalts (0.28‰ ± 0.05‰), which may be caused by crustal assimilation of the protoliths by sedimentary rocks due to their extremely high 87Sr/86Sr (up to 0.7130) and low εNd values (down to −12.3). The remaining greenschists have relatively low 87Sr/86Sr and their δ66Zn values (0.21‰–0.38‰) overlap the ranges of amphibolites (0.18‰–0.32‰) and coesite-bearing eclogites (0.18‰–0.36‰). There is no correlation between δ66Zn and sensitive indicators of dehydration (Rb/TiO2, Ba/Yb, and H2O+), suggesting that no detectable Zn isotope fractionation has occurred during the deep subduction of mafic rocks even into > 200 km, which is attributed to the limited loss of Zn during prograde metamorphism and dehydration. Thus, Zn isotopic compositions of the deeply subducted mafic rocks are inherited from their protoliths. Considering that these metamorphosed rocks have higher δ66Zn than that of the mantle value by up to 0.2‰, the recycled/subducted mafic crust can incorporate isotopically heavy Zn into the mantle. The subducted slabs may partially melt and generate a metasomatized mantle, resulting in changes of Zn isotopic composition of the hybridized mantle as have been observed in some mantle xenoliths and basaltic lavas.
2021, 12(5): 101183.
doi: 10.1016/j.gsf.2021.101183
Abstract:
The morphology and internal structure of the Horaine Bank (Bay of Saint-Brieuc, NW France) are described based on multibeam echosounder and high-resolution seismic datasets coupled with vibro-core data. The Horaine Bank shows large-scale bedforms in the lee of a submerged rocky shoal, which allowed defining it as a Banner Bank. The internal structure of the sandbank reveals four seismic units (U1–U4) on a Cambrian basement (U0). The basal unit U1 is interpreted as reworked lowstand fluvial sediments those infilled micro incised valleys during a rise in sea level. This unit is overlain by paleo-coastal barrier sand-spit (U2) whose development was controlled by swell in the context of a rapid rise in sea level. The successive prograding unit (U3) is interpreted as flooding deposits in continuity with unit U2. The unit U4 is characterized by oblique reflectors oriented in two opposite directions. This last unit, dated post 3500 yr BP, corresponds to migrating dunes superimposed on the bank and observable in the high-resolution bathymetric data. The strong correlation between tidal currents and the apparent clockwise migration of dune crests suggests the presence of a tidal gyre controlling the present-day dynamics of most of the Horaine bank dunes. This study proposes a new model for the construction of banner banks characterized by the gradual transition of a sand spit to a banner bank during marine transgression and ensuing hydrodynamic variability.
The morphology and internal structure of the Horaine Bank (Bay of Saint-Brieuc, NW France) are described based on multibeam echosounder and high-resolution seismic datasets coupled with vibro-core data. The Horaine Bank shows large-scale bedforms in the lee of a submerged rocky shoal, which allowed defining it as a Banner Bank. The internal structure of the sandbank reveals four seismic units (U1–U4) on a Cambrian basement (U0). The basal unit U1 is interpreted as reworked lowstand fluvial sediments those infilled micro incised valleys during a rise in sea level. This unit is overlain by paleo-coastal barrier sand-spit (U2) whose development was controlled by swell in the context of a rapid rise in sea level. The successive prograding unit (U3) is interpreted as flooding deposits in continuity with unit U2. The unit U4 is characterized by oblique reflectors oriented in two opposite directions. This last unit, dated post 3500 yr BP, corresponds to migrating dunes superimposed on the bank and observable in the high-resolution bathymetric data. The strong correlation between tidal currents and the apparent clockwise migration of dune crests suggests the presence of a tidal gyre controlling the present-day dynamics of most of the Horaine bank dunes. This study proposes a new model for the construction of banner banks characterized by the gradual transition of a sand spit to a banner bank during marine transgression and ensuing hydrodynamic variability.
2021, 12(5): 101184.
doi: 10.1016/j.gsf.2021.101184
Abstract:
Late Mesozoic Nb-rich basaltic andesites and high-Mg adakitic volcanic rocks from the Hailar–Tamtsag Basin, northeast China, provide important insights into the recycling processes of crustal materials and their role in late Mesozoic lithospheric thinning. The Late Jurassic Nb-rich basaltic andesites (154 ± 4 Ma) are enriched in large-ion lithophile and light rare earth elements, slightly depleted in high-field-strength elements, and have high TiO2, P2O5, and Nb contents, and (Nb/Th)PM and Nb/U ratios, which together with the relatively depleted Sr–Nd–Hf isotopic compositions indicate a derivation from a mantle wedge metasomatized by hydrous melts from subducted oceanic crust. The Early Cretaceous high-Mg adakitic volcanic rocks (129–117 Ma) are characterized by low Y and heavy rare earth element contents, and high Sr contents and Sr/Y ratios, similar to those of rocks derived from partial melting of an eclogitic source. They also have high Rb/Sr, K2O/Na2O, and Mg# values, and high MgO, Cr, and Ni contents. These geochemical features suggest that the adakitic lavas were derived from partial melting of delaminated lower continental crust, followed by interaction of the resulting melts with mantle material during their ascent. Our data, along with available geological, paleomagnetic, and geophysical evidence, lead us to propose that recycling of Paleo-Pacific oceanic crustal materials into the upper mantle due to flat-slab subduction and rollback of the Paleo-Pacific Plate during the late Mesozoic likely provided the precondition for lithospheric thinning in northeast China, with consequent lithospheric delamination causing recycling of continental crustal materials and further lithospheric thinning.
Late Mesozoic Nb-rich basaltic andesites and high-Mg adakitic volcanic rocks from the Hailar–Tamtsag Basin, northeast China, provide important insights into the recycling processes of crustal materials and their role in late Mesozoic lithospheric thinning. The Late Jurassic Nb-rich basaltic andesites (154 ± 4 Ma) are enriched in large-ion lithophile and light rare earth elements, slightly depleted in high-field-strength elements, and have high TiO2, P2O5, and Nb contents, and (Nb/Th)PM and Nb/U ratios, which together with the relatively depleted Sr–Nd–Hf isotopic compositions indicate a derivation from a mantle wedge metasomatized by hydrous melts from subducted oceanic crust. The Early Cretaceous high-Mg adakitic volcanic rocks (129–117 Ma) are characterized by low Y and heavy rare earth element contents, and high Sr contents and Sr/Y ratios, similar to those of rocks derived from partial melting of an eclogitic source. They also have high Rb/Sr, K2O/Na2O, and Mg# values, and high MgO, Cr, and Ni contents. These geochemical features suggest that the adakitic lavas were derived from partial melting of delaminated lower continental crust, followed by interaction of the resulting melts with mantle material during their ascent. Our data, along with available geological, paleomagnetic, and geophysical evidence, lead us to propose that recycling of Paleo-Pacific oceanic crustal materials into the upper mantle due to flat-slab subduction and rollback of the Paleo-Pacific Plate during the late Mesozoic likely provided the precondition for lithospheric thinning in northeast China, with consequent lithospheric delamination causing recycling of continental crustal materials and further lithospheric thinning.
2021, 12(5): 101186.
doi: 10.1016/j.gsf.2021.101186
Abstract:
Ganga-Brahmaputra-Meghna (GBM) river basin is the third-largest and one of the most populated river basins in the world. As climate change is affecting most of the hydrometeorological variables across the globe, this study investigated the existence of climate change signal in all four climatological seasons in the GBM river basin and assessed the contribution of anthropogenic activities, i.e., Greenhouse Gases (GHGs) emission in the change. Significant decreasing trends in the monsoon and a small increase in pre-monsoon precipitation were observed. Negligible change was detected in post-monsoon and winter season precipitation. CMIP5 GCMs were used for climate change detection, change point estimation, and attribution studies. Support Vector Machine (SVM) regression method was adopted to downscale GCM variables at the local scale. Monte-Carlo simulation approach was used to detect changes in different seasons. The climate change ‘signals’ were detectable after the year 1980 using Signal to Noise ratio (SNR) method in the majority of central and north-western regions. The change point was detectable only in annual monsoon precipitation at the basin level. Attribution analysis indicated >50% contribution of anthropogenic activities (GHGs) to annual monsoon precipitation changes. So, there is high confidence that monsoon precipitation in GBM has significantly changed due to anthropogenic activities. Different mitigation and adaption measures are also suggested, which may be adopted to manage the growing demand and water availability in the basin.
Ganga-Brahmaputra-Meghna (GBM) river basin is the third-largest and one of the most populated river basins in the world. As climate change is affecting most of the hydrometeorological variables across the globe, this study investigated the existence of climate change signal in all four climatological seasons in the GBM river basin and assessed the contribution of anthropogenic activities, i.e., Greenhouse Gases (GHGs) emission in the change. Significant decreasing trends in the monsoon and a small increase in pre-monsoon precipitation were observed. Negligible change was detected in post-monsoon and winter season precipitation. CMIP5 GCMs were used for climate change detection, change point estimation, and attribution studies. Support Vector Machine (SVM) regression method was adopted to downscale GCM variables at the local scale. Monte-Carlo simulation approach was used to detect changes in different seasons. The climate change ‘signals’ were detectable after the year 1980 using Signal to Noise ratio (SNR) method in the majority of central and north-western regions. The change point was detectable only in annual monsoon precipitation at the basin level. Attribution analysis indicated >50% contribution of anthropogenic activities (GHGs) to annual monsoon precipitation changes. So, there is high confidence that monsoon precipitation in GBM has significantly changed due to anthropogenic activities. Different mitigation and adaption measures are also suggested, which may be adopted to manage the growing demand and water availability in the basin.
2021, 12(5): 101187.
doi: 10.1016/j.gsf.2021.101187
Abstract:
Large phosphorite deposits in Central Guizhou, China, were formed around the Precambrian/Cambrian boundary (PC/C), including the Ediacaran (Doushantuo stage) and early Cambrian (Gezhongwu stage). Among them, Gezhongwu phosphorite from Zhijin are enriched in rare earth elements (REE) plus yttrium (REY), reaching 3.503 million tons. Although phosphorites have attracted great attention, the specific sources P and REY remained unclear. To determine the P and REY sources and establish a phosphogenic model of PC/C phosphorite, we present an integrated dataset of Mo and phosphate O isotopes for the first time, along with carbonate C and O isotopes, geology, petrology, and geochemistry. In all samples, δ18Op, Y/Ho, and Zr/Hf decreased from the Ediacaran to the early Cambrian, indicating increased terrigenous weathering fluxes while decreased upwelling water input. Furthermore, terrigenous weathering delivery significantly elevated marine REY concentrations in the Cambrian in Zhijin. The Ceanom and δ98/95Mo suggest that seawater was oxidized in the later Ediacaran and became entirely oxic in the early Cambrian. The positive feedback between oxygen levels in atmosphere and primary productivity caused progressive oxygenation in ocean–atmosphere system and enable phosphorites to be formed by different mechanisms. Results show that the Lower Doushantuo consist of abiotic intraclasts and exhibited “seawater-like” REY types, indicating abiological and mechanical reworking phosphogenesis. The Upper Doushantuo and Gezhongwu Formation contained mainly microbial debris and abiogenic intraclasts, and exhibit “hat-shaped” REY plots, suggesting microbially mediated phosphogenesis. Based on this data set, we developed a phosphogenic model illustrating formation of these two phosphorite deposits, wherein the Lower Doushantuo phosphorite formed through the reworking of pre-existing phosphatic sediments in anoxic and abiotic ocean, whereas the Upper Doushantuo and Gezhongwu phosphorite formed via microbial metabolisms in oxic and biotic conditions. Our study has implications on the PC/C phosphorite generative processes, as well as paleoenvironmental conditions.
Large phosphorite deposits in Central Guizhou, China, were formed around the Precambrian/Cambrian boundary (PC/C), including the Ediacaran (Doushantuo stage) and early Cambrian (Gezhongwu stage). Among them, Gezhongwu phosphorite from Zhijin are enriched in rare earth elements (REE) plus yttrium (REY), reaching 3.503 million tons. Although phosphorites have attracted great attention, the specific sources P and REY remained unclear. To determine the P and REY sources and establish a phosphogenic model of PC/C phosphorite, we present an integrated dataset of Mo and phosphate O isotopes for the first time, along with carbonate C and O isotopes, geology, petrology, and geochemistry. In all samples, δ18Op, Y/Ho, and Zr/Hf decreased from the Ediacaran to the early Cambrian, indicating increased terrigenous weathering fluxes while decreased upwelling water input. Furthermore, terrigenous weathering delivery significantly elevated marine REY concentrations in the Cambrian in Zhijin. The Ceanom and δ98/95Mo suggest that seawater was oxidized in the later Ediacaran and became entirely oxic in the early Cambrian. The positive feedback between oxygen levels in atmosphere and primary productivity caused progressive oxygenation in ocean–atmosphere system and enable phosphorites to be formed by different mechanisms. Results show that the Lower Doushantuo consist of abiotic intraclasts and exhibited “seawater-like” REY types, indicating abiological and mechanical reworking phosphogenesis. The Upper Doushantuo and Gezhongwu Formation contained mainly microbial debris and abiogenic intraclasts, and exhibit “hat-shaped” REY plots, suggesting microbially mediated phosphogenesis. Based on this data set, we developed a phosphogenic model illustrating formation of these two phosphorite deposits, wherein the Lower Doushantuo phosphorite formed through the reworking of pre-existing phosphatic sediments in anoxic and abiotic ocean, whereas the Upper Doushantuo and Gezhongwu phosphorite formed via microbial metabolisms in oxic and biotic conditions. Our study has implications on the PC/C phosphorite generative processes, as well as paleoenvironmental conditions.
2021, 12(5): 101188.
doi: 10.1016/j.gsf.2021.101188
Abstract:
The global geological volatile cycle (H, C, N) plays an important role in the long term self-regulation of the Earth system. However, the complex interaction between its deep, solid Earth components (i.e. crust and mantle), Earth’s fluid envelopes (i.e. atmosphere and hydrosphere) and plate tectonic processes is a subject of ongoing debate. In this study we want to draw attention to how the presence of primary melt (MI) and fluid (FI) inclusions in high-grade metamorphic minerals could help constrain the crustal component of the volatile cycle. To that end, we review the distribution of MI and FI throughout Earth’s history, from ca. 3.0 Ga ago up to the present day. We argue that the lower crust might constitute an important, long-term, volatile storage unit, capable to influence the composition of the surface envelopes through the mean of weathering, crustal thickening, partial melting and crustal assimilation during volcanic activity. Combined with thermodynamic modelling, our compilation indicates that periods of well-established plate tectonic regimes at <0.85 Ga and 1.7–2.1 Ga, might be more prone to the reworking of supracrustal lithologies and the storage of volatiles in the lower crust. Such hypothesis has implication beyond the scope of metamorphic petrology as it potentially links geodynamic mechanisms to habitable surface conditions. MI and FI in metamorphic crustal rocks then represent an invaluable archive to assess and quantify the co-joint evolution of plate tectonics and Earth’s external processes.
The global geological volatile cycle (H, C, N) plays an important role in the long term self-regulation of the Earth system. However, the complex interaction between its deep, solid Earth components (i.e. crust and mantle), Earth’s fluid envelopes (i.e. atmosphere and hydrosphere) and plate tectonic processes is a subject of ongoing debate. In this study we want to draw attention to how the presence of primary melt (MI) and fluid (FI) inclusions in high-grade metamorphic minerals could help constrain the crustal component of the volatile cycle. To that end, we review the distribution of MI and FI throughout Earth’s history, from ca. 3.0 Ga ago up to the present day. We argue that the lower crust might constitute an important, long-term, volatile storage unit, capable to influence the composition of the surface envelopes through the mean of weathering, crustal thickening, partial melting and crustal assimilation during volcanic activity. Combined with thermodynamic modelling, our compilation indicates that periods of well-established plate tectonic regimes at <0.85 Ga and 1.7–2.1 Ga, might be more prone to the reworking of supracrustal lithologies and the storage of volatiles in the lower crust. Such hypothesis has implication beyond the scope of metamorphic petrology as it potentially links geodynamic mechanisms to habitable surface conditions. MI and FI in metamorphic crustal rocks then represent an invaluable archive to assess and quantify the co-joint evolution of plate tectonics and Earth’s external processes.
2021, 12(5): 101195.
doi: 10.1016/j.gsf.2021.101195
Abstract:
The variation of crustal thickness is a critical index to reveal how the continental crust evolved over its four billion years. Generally, ratios of whole-rock trace elements, such as Sr/Y, (La/Yb)n and Ce/Y, are used to characterize crustal thicknesses. However, sometimes confusing results are obtained since there is no enough filtered data. Here, a state-of-the-art approach, based on a machine-learning algorithm, is proposed to predict crustal thickness using global major- and trace-element geochemical data of intermediate arc rocks and intraplate basalts, and their corresponding crustal thicknesses. After the validation processes, the root-mean-square error (RMSE) and the coefficient of determination (R2) score were used to evaluate the performance of the machine learning algorithm based on the learning dataset which has never been used during the training phase. The results demonstrate that the machine learning algorithm is more reliable in predicting crustal thickness than the conventional methods. The trained model predicts that the crustal thickness of the eastern North China Craton (ENCC) was ~45 km from the Late Triassic to the Early Cretaceous, but ~35 km from the Early Cretaceous, which corresponds to the paleo-elevation of 3.0 ± 1.5 km at Early Mesozoic, and decease to the present-day elevation in the ENCC. The estimates are generally consistent with the previous studies on xenoliths from the lower crust and on the paleoenvironment of the coastal mountain of the ENCC, which indicates that the lower crust of the ENCC was delaminated abruptly at the Early Cretaceous.
The variation of crustal thickness is a critical index to reveal how the continental crust evolved over its four billion years. Generally, ratios of whole-rock trace elements, such as Sr/Y, (La/Yb)n and Ce/Y, are used to characterize crustal thicknesses. However, sometimes confusing results are obtained since there is no enough filtered data. Here, a state-of-the-art approach, based on a machine-learning algorithm, is proposed to predict crustal thickness using global major- and trace-element geochemical data of intermediate arc rocks and intraplate basalts, and their corresponding crustal thicknesses. After the validation processes, the root-mean-square error (RMSE) and the coefficient of determination (R2) score were used to evaluate the performance of the machine learning algorithm based on the learning dataset which has never been used during the training phase. The results demonstrate that the machine learning algorithm is more reliable in predicting crustal thickness than the conventional methods. The trained model predicts that the crustal thickness of the eastern North China Craton (ENCC) was ~45 km from the Late Triassic to the Early Cretaceous, but ~35 km from the Early Cretaceous, which corresponds to the paleo-elevation of 3.0 ± 1.5 km at Early Mesozoic, and decease to the present-day elevation in the ENCC. The estimates are generally consistent with the previous studies on xenoliths from the lower crust and on the paleoenvironment of the coastal mountain of the ENCC, which indicates that the lower crust of the ENCC was delaminated abruptly at the Early Cretaceous.
2021, 12(5): 101198.
doi: 10.1016/j.gsf.2021.101198
Abstract:
Rock mechanical parameters and their uncertainties are critical to rock stability analysis, engineering design, and safe construction in rock mechanics and engineering. The back analysis is widely adopted in rock engineering to determine the mechanical parameters of the surrounding rock mass, but this does not consider the uncertainty. This problem is addressed here by the proposed approach by developing a system of Bayesian inferences for updating mechanical parameters and their statistical properties using monitored field data, then integrating the monitored data, prior knowledge of geotechnical parameters, and a mechanical model of a rock tunnel using Markov chain Monte Carlo (MCMC) simulation. The proposed approach is illustrated by a circular tunnel with an analytical solution, which was then applied to an experimental tunnel in Goupitan Hydropower Station, China. The mechanical properties and strength parameters of the surrounding rock mass were modeled as random variables. The displacement was predicted with the aid of the parameters updated by Bayesian inferences and agreed closely with monitored displacements. It indicates that Bayesian inferences combined the monitored data into the tunnel model to update its parameters dynamically. Further study indicated that the performance of Bayesian inferences is improved greatly by regularly supplementing field monitoring data. Bayesian inference is a significant and new approach for determining the mechanical parameters of the surrounding rock mass in a tunnel model and contributes to safe construction in rock engineering.
Rock mechanical parameters and their uncertainties are critical to rock stability analysis, engineering design, and safe construction in rock mechanics and engineering. The back analysis is widely adopted in rock engineering to determine the mechanical parameters of the surrounding rock mass, but this does not consider the uncertainty. This problem is addressed here by the proposed approach by developing a system of Bayesian inferences for updating mechanical parameters and their statistical properties using monitored field data, then integrating the monitored data, prior knowledge of geotechnical parameters, and a mechanical model of a rock tunnel using Markov chain Monte Carlo (MCMC) simulation. The proposed approach is illustrated by a circular tunnel with an analytical solution, which was then applied to an experimental tunnel in Goupitan Hydropower Station, China. The mechanical properties and strength parameters of the surrounding rock mass were modeled as random variables. The displacement was predicted with the aid of the parameters updated by Bayesian inferences and agreed closely with monitored displacements. It indicates that Bayesian inferences combined the monitored data into the tunnel model to update its parameters dynamically. Further study indicated that the performance of Bayesian inferences is improved greatly by regularly supplementing field monitoring data. Bayesian inference is a significant and new approach for determining the mechanical parameters of the surrounding rock mass in a tunnel model and contributes to safe construction in rock engineering.
2021, 12(5): 101200.
doi: 10.1016/j.gsf.2021.101200
Abstract:
An early Paleozoic Proto-Tethys ocean in western Yunnan has long been postulated although no robust geological evidence has been identified. Here we investigated the recently-identified Mayidui and Wanhe ophiolitic mélanges in SW Yunnan, which occurs in a N–S trending belt east of the late Paleozoic Changning–Menglian suture zone. The ophiolites consist mainly of meta-basalts (amphibole schists), meta- (cumulate) gabbros and gabbroic diorites, and meta- chert-shale, representing ancient oceanic crust and pelagic and hemipelagic sediments, respectively. Six samples of gabbros and gabbroic diorites from 3 profiles (Mayidui, Kongjiao and Yinchanghe) yielded zircon U-Pb ages between 462 ± 6 Ma and 447 ± 9 Ma, constraining the formation of the Mayidui and Wanhe ophiolites to Middle Ordovician. Gabbros from the Mayidui and Kongjiao profiles share similar geochemical characteristics with affinities to tholeiitic series, and are characterized by depleted to slightly enriched LREEs relative to HREEs with (La/Sm)N = 0.69–1.87, (La/Yb)N = 0.66–4.72). These, along with their predominantly positive whole-rock εNd(t) and zircon εHf(t) values, indicate a MORB-like magma source. By contrast, the meta-mafic rocks from the Yinchanghe profile show significantly enriched LREEs ((La/Sm)N = 0.97–3.33, (La/Yb)N = 1.19–14.93), as well as positive whole-rock εNd(t) and positive to negative zircon εHf(t) values, indicating an E-MORB-type mantle source. These geochemical features are consistent with an intra-oceanic setting for the formation of the Mayidui–Wanhe ophiolites. Our data, integrated with available geological evidence, provide robust constraints on the timing and nature of the Mayidui–Wanhe ophiolitic mélange, and suggest that the ophiolites represent remnants of the Proto-Tethys Ocean, which opened through separation of the Indochina and Simao blocks from the northern margin of Gondwana before the Early Cambrian, and evolved through to the Silurian.
An early Paleozoic Proto-Tethys ocean in western Yunnan has long been postulated although no robust geological evidence has been identified. Here we investigated the recently-identified Mayidui and Wanhe ophiolitic mélanges in SW Yunnan, which occurs in a N–S trending belt east of the late Paleozoic Changning–Menglian suture zone. The ophiolites consist mainly of meta-basalts (amphibole schists), meta- (cumulate) gabbros and gabbroic diorites, and meta- chert-shale, representing ancient oceanic crust and pelagic and hemipelagic sediments, respectively. Six samples of gabbros and gabbroic diorites from 3 profiles (Mayidui, Kongjiao and Yinchanghe) yielded zircon U-Pb ages between 462 ± 6 Ma and 447 ± 9 Ma, constraining the formation of the Mayidui and Wanhe ophiolites to Middle Ordovician. Gabbros from the Mayidui and Kongjiao profiles share similar geochemical characteristics with affinities to tholeiitic series, and are characterized by depleted to slightly enriched LREEs relative to HREEs with (La/Sm)N = 0.69–1.87, (La/Yb)N = 0.66–4.72). These, along with their predominantly positive whole-rock εNd(t) and zircon εHf(t) values, indicate a MORB-like magma source. By contrast, the meta-mafic rocks from the Yinchanghe profile show significantly enriched LREEs ((La/Sm)N = 0.97–3.33, (La/Yb)N = 1.19–14.93), as well as positive whole-rock εNd(t) and positive to negative zircon εHf(t) values, indicating an E-MORB-type mantle source. These geochemical features are consistent with an intra-oceanic setting for the formation of the Mayidui–Wanhe ophiolites. Our data, integrated with available geological evidence, provide robust constraints on the timing and nature of the Mayidui–Wanhe ophiolitic mélange, and suggest that the ophiolites represent remnants of the Proto-Tethys Ocean, which opened through separation of the Indochina and Simao blocks from the northern margin of Gondwana before the Early Cambrian, and evolved through to the Silurian.
2021, 12(5): 101203.
doi: 10.1016/j.gsf.2021.101203
Abstract:
Landslide is considered as one of the most severe threats to human life and property in the hilly areas of the world. The number of landslides and the level of damage across the globe has been increasing over time. Therefore, landslide management is essential to maintain the natural and socio-economic dynamics of the hilly region. Rorachu river basin is one of the most landslide-prone areas of the Sikkim selected for the present study. The prime goal of the study is to prepare landslide susceptibility maps (LSMs) using computer-based advanced machine learning techniques and compare the performance of the models. To properly understand the existing spatial relation with the landslide, twenty factors, including triggering and causative factors, were selected. A deep learning algorithm viz. convolutional neural network model (CNN) and three popular machine learning techniques, i.e., random forest model (RF), artificial neural network model (ANN), and bagging model, were employed to prepare the LSMs. Two separate datasets including training and validation were designed by randomly taken landslide and non-landslide points. A ratio of 70:30 was considered for the selection of both training and validation points. Multicollinearity was assessed by tolerance and variance inflation factor, and the role of individual conditioning factors was estimated using information gain ratio. The result reveals that there is no severe multicollinearity among the landslide conditioning factors, and the triggering factor rainfall appeared as the leading cause of the landslide. Based on the final prediction values of each model, LSM was constructed and successfully portioned into five distinct classes, like very low, low, moderate, high, and very high susceptibility. The susceptibility class-wise distribution of landslides shows that more than 90% of the landslide area falls under higher landslide susceptibility grades. The precision of models was examined using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve and statistical methods like root mean square error (RMSE) and mean absolute error (MAE). In both datasets (training and validation), the CNN model achieved the maximum AUC value of 0.903 and 0.939, respectively. The lowest value of RMSE and MAE also reveals the better performance of the CNN model. So, it can be concluded that all the models have performed well, but the CNN model has outperformed the other models in terms of precision.
Landslide is considered as one of the most severe threats to human life and property in the hilly areas of the world. The number of landslides and the level of damage across the globe has been increasing over time. Therefore, landslide management is essential to maintain the natural and socio-economic dynamics of the hilly region. Rorachu river basin is one of the most landslide-prone areas of the Sikkim selected for the present study. The prime goal of the study is to prepare landslide susceptibility maps (LSMs) using computer-based advanced machine learning techniques and compare the performance of the models. To properly understand the existing spatial relation with the landslide, twenty factors, including triggering and causative factors, were selected. A deep learning algorithm viz. convolutional neural network model (CNN) and three popular machine learning techniques, i.e., random forest model (RF), artificial neural network model (ANN), and bagging model, were employed to prepare the LSMs. Two separate datasets including training and validation were designed by randomly taken landslide and non-landslide points. A ratio of 70:30 was considered for the selection of both training and validation points. Multicollinearity was assessed by tolerance and variance inflation factor, and the role of individual conditioning factors was estimated using information gain ratio. The result reveals that there is no severe multicollinearity among the landslide conditioning factors, and the triggering factor rainfall appeared as the leading cause of the landslide. Based on the final prediction values of each model, LSM was constructed and successfully portioned into five distinct classes, like very low, low, moderate, high, and very high susceptibility. The susceptibility class-wise distribution of landslides shows that more than 90% of the landslide area falls under higher landslide susceptibility grades. The precision of models was examined using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve and statistical methods like root mean square error (RMSE) and mean absolute error (MAE). In both datasets (training and validation), the CNN model achieved the maximum AUC value of 0.903 and 0.939, respectively. The lowest value of RMSE and MAE also reveals the better performance of the CNN model. So, it can be concluded that all the models have performed well, but the CNN model has outperformed the other models in terms of precision.
2021, 12(5): 101205.
doi: 10.1016/j.gsf.2021.101205
Abstract:
We analyze the gross crustal structure of the Atlantic Ocean passive continental margins from north to the south, comparing eleven sections of the conjugate margins. As a general result, the western margins show a sharper continental-ocean transition with respect to the eastern margins that rather show a wider stretched and thinner margin. The Moho is in average about 5.7°±1° dipping toward the interior of the continent on the western side, whereas it is about 2.7°±1° in the eastern margins. Moreover, the stretched continental crust is on average 244 km wide on the western side, whereas it is up to about 439 km on the eastern side of the Atlantic. This systematic asymmetry reflects the early stages of the diachronous Mesozoic to Cenozoic continental rifting, which is inferred as the result of a polarized westward motion of both western and eastern plates, being Greenland, Northern and Southern Americas plates moving westward faster with respect to Scandinavia, Europe and Africa, relative to the underlying mantle.
We analyze the gross crustal structure of the Atlantic Ocean passive continental margins from north to the south, comparing eleven sections of the conjugate margins. As a general result, the western margins show a sharper continental-ocean transition with respect to the eastern margins that rather show a wider stretched and thinner margin. The Moho is in average about 5.7°±1° dipping toward the interior of the continent on the western side, whereas it is about 2.7°±1° in the eastern margins. Moreover, the stretched continental crust is on average 244 km wide on the western side, whereas it is up to about 439 km on the eastern side of the Atlantic. This systematic asymmetry reflects the early stages of the diachronous Mesozoic to Cenozoic continental rifting, which is inferred as the result of a polarized westward motion of both western and eastern plates, being Greenland, Northern and Southern Americas plates moving westward faster with respect to Scandinavia, Europe and Africa, relative to the underlying mantle.
2021, 12(5): 101206.
doi: 10.1016/j.gsf.2021.101206
Abstract:
The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season. In this study, we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment. About 40 years of annual peak discharge data, historical cross-sections of different gauging sites, and 12 flood conditioning factors were considered. Our flood susceptibility mapping followed an expert knowledge-based multi-parametric analytical hierarchy process (AHP) and optimized AHP-VIP methods. Peak hydrology data indicated more than 5 times higher discharge contrasted with the mean streamflow of the peak monsoon month in all hydro-monitoring stations that correspond to possible overbank flooding in the shallow semi-alluvial reaches of the Subarnarekha River. Width-depth ratio revealed continuous changes on the channel cross-sections at decadal scale in all gauging sites. Predicted flood susceptibility map through optimized AHP-VIP method showed a great amount of areas (38%) have a high probability of flooding and demands earnest attention of administrative bodies. The AHP-VIP based flood susceptibility map was theoritically validated through AUC approach and it showed fairly high accuracy (AUC = 0.93). Our study offers an exceptionally cost and time effective solution to the flooding issues in the Subarnarekha basin.
The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season. In this study, we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment. About 40 years of annual peak discharge data, historical cross-sections of different gauging sites, and 12 flood conditioning factors were considered. Our flood susceptibility mapping followed an expert knowledge-based multi-parametric analytical hierarchy process (AHP) and optimized AHP-VIP methods. Peak hydrology data indicated more than 5 times higher discharge contrasted with the mean streamflow of the peak monsoon month in all hydro-monitoring stations that correspond to possible overbank flooding in the shallow semi-alluvial reaches of the Subarnarekha River. Width-depth ratio revealed continuous changes on the channel cross-sections at decadal scale in all gauging sites. Predicted flood susceptibility map through optimized AHP-VIP method showed a great amount of areas (38%) have a high probability of flooding and demands earnest attention of administrative bodies. The AHP-VIP based flood susceptibility map was theoritically validated through AUC approach and it showed fairly high accuracy (AUC = 0.93). Our study offers an exceptionally cost and time effective solution to the flooding issues in the Subarnarekha basin.
2021, 12(5): 101207.
doi: 10.1016/j.gsf.2021.101207
Abstract:
One of most hotly debated topics concerning the Late Mesozoic evolution of Tethyan and the Tibetan Plateau is the timing of the closure of the Meso-Tethys ocean, which is represented by the Bangong–Nujiang suture zone. The Upper Jurassic–Lower Cretaceous Shamuluo Formation, which unconformably overlies the older Mugagangri Group accretionary complex, provides important information on the closure of the Meso-Tethys Ocean. This paper precisely confines the depositional age of the Shamuluo Formation in the western segment of the Bangong–Nujiang suture zone, extending it from the Late Jurassic to the Albian. Combined with the results of previous studies, we suggest that the Shamuluo Formation in the Awengco–Baerqiong region mainly contains a bathyal Berriasian–Hauterivian subunit and a shallow-marine Albian subunit. Provenance analysis indicates that the Berriasian–Hauterivian subunit was mainly derived from the Jurassic southern Qiangtang magmatic arc, while the Albian subunit was derived from the coeval volcanic rocks and the Upper Carboniferous–Upper Permian strata in the southern Qiangtang terrane. Thus, the two subunits of the Shamuluo Formation have significant distinct sedimentary facies and provenances, indicating that they were deposited in different tectonic settings. Based on the regional geological data, we suggest that the bathyal Berriasian–Hauterivian subunit and the shallow-marine Albian subunit of the Shamuluo Formation should be interpreted as a record of the oceanic arc-continent collision and the Lhasa–Qiangtang soft-collision, respectively. Thus, the closure time of the Meso-Tethys Ocean is at least limited to the Albian.
One of most hotly debated topics concerning the Late Mesozoic evolution of Tethyan and the Tibetan Plateau is the timing of the closure of the Meso-Tethys ocean, which is represented by the Bangong–Nujiang suture zone. The Upper Jurassic–Lower Cretaceous Shamuluo Formation, which unconformably overlies the older Mugagangri Group accretionary complex, provides important information on the closure of the Meso-Tethys Ocean. This paper precisely confines the depositional age of the Shamuluo Formation in the western segment of the Bangong–Nujiang suture zone, extending it from the Late Jurassic to the Albian. Combined with the results of previous studies, we suggest that the Shamuluo Formation in the Awengco–Baerqiong region mainly contains a bathyal Berriasian–Hauterivian subunit and a shallow-marine Albian subunit. Provenance analysis indicates that the Berriasian–Hauterivian subunit was mainly derived from the Jurassic southern Qiangtang magmatic arc, while the Albian subunit was derived from the coeval volcanic rocks and the Upper Carboniferous–Upper Permian strata in the southern Qiangtang terrane. Thus, the two subunits of the Shamuluo Formation have significant distinct sedimentary facies and provenances, indicating that they were deposited in different tectonic settings. Based on the regional geological data, we suggest that the bathyal Berriasian–Hauterivian subunit and the shallow-marine Albian subunit of the Shamuluo Formation should be interpreted as a record of the oceanic arc-continent collision and the Lhasa–Qiangtang soft-collision, respectively. Thus, the closure time of the Meso-Tethys Ocean is at least limited to the Albian.
2021, 12(5): 101209.
doi: 10.1016/j.gsf.2021.101209
Abstract:
This study presents a numerical investigation of dewatering-induced settlement and wall deflection during pumping tests in Tianjin, China. Based on the measured groundwater head and building settlement during the pumping test, a three-dimensional liquid–solid coupling model is established by using the finite element method (FEM). The void ratio, hydraulic conductivity, and elastic modulus of each layer are back-calculated through the numerical model. The groundwater drawdown, seepage field, ground settlement, horizontal ground displacement, and diaphragm wall lateral deflection are analyzed using the FEM model. The simulated results demonstrate that (i) the maximum ground settlement outside of the excavation reaches to 82 mm due to the leakage effect of aquitards; (ii) large horizontal displacement occurs in the soil during the pumping test with a maximum value of 28.3 mm, and the installation of the diaphragm wall in the aquifer can reduce the horizontal displacement of the ground; (iii) long-term pumping causes a large lateral deflection of the diaphragm wall, and a maximum value of 23.2 mm occurs at the layer where the screens of the wells are located; and (iv) long-term large-scale pumping should be avoided before excavation.
This study presents a numerical investigation of dewatering-induced settlement and wall deflection during pumping tests in Tianjin, China. Based on the measured groundwater head and building settlement during the pumping test, a three-dimensional liquid–solid coupling model is established by using the finite element method (FEM). The void ratio, hydraulic conductivity, and elastic modulus of each layer are back-calculated through the numerical model. The groundwater drawdown, seepage field, ground settlement, horizontal ground displacement, and diaphragm wall lateral deflection are analyzed using the FEM model. The simulated results demonstrate that (i) the maximum ground settlement outside of the excavation reaches to 82 mm due to the leakage effect of aquitards; (ii) large horizontal displacement occurs in the soil during the pumping test with a maximum value of 28.3 mm, and the installation of the diaphragm wall in the aquifer can reduce the horizontal displacement of the ground; (iii) long-term pumping causes a large lateral deflection of the diaphragm wall, and a maximum value of 23.2 mm occurs at the layer where the screens of the wells are located; and (iv) long-term large-scale pumping should be avoided before excavation.
An efficient probabilistic design approach for tunnel face stability by inverse reliability analysis
2021, 12(5): 101210.
doi: 10.1016/j.gsf.2021.101210
Abstract:
In order to maintain the safety of underground constructions that significantly involve geo-material uncertainties, this paper delivers a new computation framework for conducting reliability-based design (RBD) of shallow tunnel face stability, utilizing a simplified inverse first-order reliability method (FORM). The limit state functions defining tunnel face stability are established for both collapse and blow-out modes of the tunnel face failure, respectively, and the deterministic results of the tunnel face support pressure are obtained through three-dimensional finite element limit analysis (FELA). Because the inverse reliability method can directly capture the design support pressure according to prescribed target reliability index, the computational cost for probabilistic design of tunnel face stability is greatly reduced. By comparison with Monte Carlo simulation results, the accuracy and feasibility of the proposed method are verified. Further, this study presents a series of reliability-based design charts for vividly understanding the limit support pressure on tunnel face in both cohesionless (sandy) soil and cohesive soil stratums, and their optimal support pressure ranges are highlighted. The results show that in the case of sandy soil stratum, the blowout failure of tunnel face is extremely unlikely, whereas the collapse is the only possible failure mode. The parametric study of various geotechnical uncertainties also reveals that ignoring the potential correlation between soil shear strength parameters will lead to over-designed support pressure, and the coefficient of variation of internal friction angle has a greater influence on the tunnel face failure probability than that of the cohesion.
In order to maintain the safety of underground constructions that significantly involve geo-material uncertainties, this paper delivers a new computation framework for conducting reliability-based design (RBD) of shallow tunnel face stability, utilizing a simplified inverse first-order reliability method (FORM). The limit state functions defining tunnel face stability are established for both collapse and blow-out modes of the tunnel face failure, respectively, and the deterministic results of the tunnel face support pressure are obtained through three-dimensional finite element limit analysis (FELA). Because the inverse reliability method can directly capture the design support pressure according to prescribed target reliability index, the computational cost for probabilistic design of tunnel face stability is greatly reduced. By comparison with Monte Carlo simulation results, the accuracy and feasibility of the proposed method are verified. Further, this study presents a series of reliability-based design charts for vividly understanding the limit support pressure on tunnel face in both cohesionless (sandy) soil and cohesive soil stratums, and their optimal support pressure ranges are highlighted. The results show that in the case of sandy soil stratum, the blowout failure of tunnel face is extremely unlikely, whereas the collapse is the only possible failure mode. The parametric study of various geotechnical uncertainties also reveals that ignoring the potential correlation between soil shear strength parameters will lead to over-designed support pressure, and the coefficient of variation of internal friction angle has a greater influence on the tunnel face failure probability than that of the cohesion.
2021, 12(5): 101211.
doi: 10.1016/j.gsf.2021.101211
Abstract:
The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models. For this, a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points, which was randomly divided into two datasets for model training (70%) and model testing (30%). 22 factors were initially selected to establish a landslide factor database. We applied the GeoDetector and recursive feature elimination method (RFE) to address factor optimization to reduce information redundancy and collinearity in the data. Thereafter, the frequency ratio method, multicollinearity test, and interactive detector were used to analyze and evaluate the optimized factors. Subsequently, the random forest (RF) model was used to create a landslide susceptibility map with original and optimized factors. The resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve (AUC) and accuracy. The accuracy of the two hybrid models (0.868 for GeoDetector-RF and 0.869 for RFE-RF) were higher than that of the RF model (0.860), indicating that the hybrid models with factor optimization have high reliability and predictability. Both RFE-RF GeoDetector-RF had higher AUC values, respectively 0.863 and 0.860, than RF (0.853). These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.
The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models. For this, a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points, which was randomly divided into two datasets for model training (70%) and model testing (30%). 22 factors were initially selected to establish a landslide factor database. We applied the GeoDetector and recursive feature elimination method (RFE) to address factor optimization to reduce information redundancy and collinearity in the data. Thereafter, the frequency ratio method, multicollinearity test, and interactive detector were used to analyze and evaluate the optimized factors. Subsequently, the random forest (RF) model was used to create a landslide susceptibility map with original and optimized factors. The resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve (AUC) and accuracy. The accuracy of the two hybrid models (0.868 for GeoDetector-RF and 0.869 for RFE-RF) were higher than that of the RF model (0.860), indicating that the hybrid models with factor optimization have high reliability and predictability. Both RFE-RF GeoDetector-RF had higher AUC values, respectively 0.863 and 0.860, than RF (0.853). These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.
2021, 12(5): 101222.
doi: 10.1016/j.gsf.2021.101222
Abstract:
More accurate and reliable estimation of residual strength friction angle (ϕr) of clay is crucial in many geotechnical engineering applications, including riverbank stability analysis, design, and assessment of earthen dam slope stabilities. However, a general predictive equation for ϕr, with applicability in a wide range of effective parameters, remains an important research gap. The goal of this study is to develop a more accurate equation for ϕr using the Pareto Optimal Multi-gene Genetic Programming (POMGGP) approach by evaluating a comprehensive dataset of 290 experiments compiled from published literature databases worldwide. A new framework for integrated equation derivation proposed that hybridizes the Subset Selection of Maximum Dissimilarity Method (SSMD) with Multi-gene Genetic Programming (MGP) and Pareto-optimality (PO) to find an accurate equation for ϕr with wide range applicability. The final predictive equation resulted from POMGGP modeling was assessed in comparison with some previously published machine learning-based equations using statistical error analysis criteria, Taylor diagram, revised discrepancy ratio (RDR), and scatter plots. Base on the results, the POMGGP has the lowest uncertainty with U95 = 2.25, when compared with Artificial Neural Network (ANN) (U95 = 2.3), Bayesian Regularization Neural Network (BRNN) (U95 = 2.94), Levenberg-Marquardt Neural Network (LMNN) (U95 = 3.3), and Differential Evolution Neural Network (DENN) (U95 = 2.37). The more reliable results in estimation of ϕr derived by POMGGP with reliability 59.3%, and resiliency 60% in comparison with ANN (reliability = 30.23%, resiliency = 28.33%), BRNN (reliability = 10.47%, resiliency = 10.39%), LMNN (reliability = 19.77%, resiliency = 20.29%) and DENN (reliability = 27.91%, resiliency = 24.19%). Besides the simplicity and ease of application of the new POMGGP equation to a broad range of conditions, using the uncertainty, reliability, and resilience analysis confirmed that the derived equation for ϕr significantly outperformed other existing machine learning methods, including the ANN, BRNN, LMNN, and DENN equations.
More accurate and reliable estimation of residual strength friction angle (ϕr) of clay is crucial in many geotechnical engineering applications, including riverbank stability analysis, design, and assessment of earthen dam slope stabilities. However, a general predictive equation for ϕr, with applicability in a wide range of effective parameters, remains an important research gap. The goal of this study is to develop a more accurate equation for ϕr using the Pareto Optimal Multi-gene Genetic Programming (POMGGP) approach by evaluating a comprehensive dataset of 290 experiments compiled from published literature databases worldwide. A new framework for integrated equation derivation proposed that hybridizes the Subset Selection of Maximum Dissimilarity Method (SSMD) with Multi-gene Genetic Programming (MGP) and Pareto-optimality (PO) to find an accurate equation for ϕr with wide range applicability. The final predictive equation resulted from POMGGP modeling was assessed in comparison with some previously published machine learning-based equations using statistical error analysis criteria, Taylor diagram, revised discrepancy ratio (RDR), and scatter plots. Base on the results, the POMGGP has the lowest uncertainty with U95 = 2.25, when compared with Artificial Neural Network (ANN) (U95 = 2.3), Bayesian Regularization Neural Network (BRNN) (U95 = 2.94), Levenberg-Marquardt Neural Network (LMNN) (U95 = 3.3), and Differential Evolution Neural Network (DENN) (U95 = 2.37). The more reliable results in estimation of ϕr derived by POMGGP with reliability 59.3%, and resiliency 60% in comparison with ANN (reliability = 30.23%, resiliency = 28.33%), BRNN (reliability = 10.47%, resiliency = 10.39%), LMNN (reliability = 19.77%, resiliency = 20.29%) and DENN (reliability = 27.91%, resiliency = 24.19%). Besides the simplicity and ease of application of the new POMGGP equation to a broad range of conditions, using the uncertainty, reliability, and resilience analysis confirmed that the derived equation for ϕr significantly outperformed other existing machine learning methods, including the ANN, BRNN, LMNN, and DENN equations.
2021, 12(5): 101223.
doi: 10.1016/j.gsf.2021.101223
Abstract:
The estuary-bay system is a common and complex coastal environment. However, quantifying submarine groundwater discharge (SGD) and associated nutrient fluxes in the complex coastal environment is challenging due to more dynamic and complicated riverine discharge, ocean processes and human activities. In this study, SGD and SFGD (submarine fresh groundwater discharge) fluxes were evaluated by combining stable and radium isotopes in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), a typical estuary-bay system. We first built a spatially distributed radium mass balance model to quantify SGD fluxes in coastal areas of GBA integrating the Pearl River Estuary (PRE), bays and shelf. We then used the stable water isotope (δ2H and δ18O) end-member mixing model to distinguish submarine fresh groundwater discharge (SFGD) from SGD. Based on the 228Ra mass balance, the estimated SGD fluxes in the PRE, adjacent bay, and shelf areas were (6.14 ± 2.74) × 108 m3 d-1, (3.00 ± 1.11) × 107 m3 d-1, and (5.00 ± 5.64) × 108 m3 d-1, respectively. Results showed that the largest area-averaged SGD was in the PRE, followed by that in the adjacent shelf and the bay. These differences may be mainly influenced by ocean forces, urbanization and benthic topographies controlling the variability of groundwater pathways. Further, the three end-member mixing model of 228Ra and salinity was developed to confirm the validity of the estimated SGD using the Ra mass balance model. In the two models, groundwater end-member and water apparent age estimation were the main sources of uncertainty in SGD. The estimated SFGD flux was (1.39 ± 0.76) × 108 m3 d-1, which accounted for approximately 12% of the total SGD. Combining stable and radium isotopes was a useful method to estimate groundwater discharge. Moreover, the estimated SGD associated dissolved inorganic nitrogen (DIN) flux was one order of magnitude higher than other DIN sources. SGD was considered to be a significant contributor to the DIN loading to the GBA. The findings of this study are expected to provide valuable information on coastal groundwater management and environmental protection of the GBA and similar coastal areas elsewhere.
The estuary-bay system is a common and complex coastal environment. However, quantifying submarine groundwater discharge (SGD) and associated nutrient fluxes in the complex coastal environment is challenging due to more dynamic and complicated riverine discharge, ocean processes and human activities. In this study, SGD and SFGD (submarine fresh groundwater discharge) fluxes were evaluated by combining stable and radium isotopes in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), a typical estuary-bay system. We first built a spatially distributed radium mass balance model to quantify SGD fluxes in coastal areas of GBA integrating the Pearl River Estuary (PRE), bays and shelf. We then used the stable water isotope (δ2H and δ18O) end-member mixing model to distinguish submarine fresh groundwater discharge (SFGD) from SGD. Based on the 228Ra mass balance, the estimated SGD fluxes in the PRE, adjacent bay, and shelf areas were (6.14 ± 2.74) × 108 m3 d-1, (3.00 ± 1.11) × 107 m3 d-1, and (5.00 ± 5.64) × 108 m3 d-1, respectively. Results showed that the largest area-averaged SGD was in the PRE, followed by that in the adjacent shelf and the bay. These differences may be mainly influenced by ocean forces, urbanization and benthic topographies controlling the variability of groundwater pathways. Further, the three end-member mixing model of 228Ra and salinity was developed to confirm the validity of the estimated SGD using the Ra mass balance model. In the two models, groundwater end-member and water apparent age estimation were the main sources of uncertainty in SGD. The estimated SFGD flux was (1.39 ± 0.76) × 108 m3 d-1, which accounted for approximately 12% of the total SGD. Combining stable and radium isotopes was a useful method to estimate groundwater discharge. Moreover, the estimated SGD associated dissolved inorganic nitrogen (DIN) flux was one order of magnitude higher than other DIN sources. SGD was considered to be a significant contributor to the DIN loading to the GBA. The findings of this study are expected to provide valuable information on coastal groundwater management and environmental protection of the GBA and similar coastal areas elsewhere.
2021, 12(5): 101225.
doi: 10.1016/j.gsf.2021.101225
Abstract:
The absence of ultrahigh pressure (UHP) orogenic eclogite in the geological record older than c. 0.6 Ga is problematic for evidence of subduction having begun on Earth during the Archean (4.0–2.5 Ga). Many eclogites in Phanerozoic and Proterozoic terranes occur as mafic boudins encased within low-density felsic crust, which provides positive buoyancy during subduction; however, recent geochemical proxy analysis shows that Archean continental crust was more mafic than previously thought, having greater proportions of basalt and komatiite than modern-day continents. Here, we show via petrological modelling that secular change in the petrology and bulk composition of upper continental crust would make Archean continental terranes negatively buoyant in the mantle before reaching UHP conditions. Subducted or delaminated Archean continental crust passes a point of no return during metamorphism in the mantle prior to the stabilization of coesite, while Proterozoic and Phanerozoic terranes remain positively buoyant at these depths. UHP orogenic eclogite may thus readily have formed on the Archean Earth, but could not have been exhumed, weakening arguments for a Neoproterozoic onset of subduction and plate tectonics. Further, isostatic balance calculations for more mafic Archean continents indicate that the early Earth was covered by a global ocean over 1 km deep, corroborating independent isotopic evidence for large-scale emergence of the continents no earlier than c. 3 Ga. Our findings thus weaken arguments that early life on Earth likely emerged in shallow subaerial ponds, and instead support hypotheses involving development at hydrothermal vents in the deep ocean.
The absence of ultrahigh pressure (UHP) orogenic eclogite in the geological record older than c. 0.6 Ga is problematic for evidence of subduction having begun on Earth during the Archean (4.0–2.5 Ga). Many eclogites in Phanerozoic and Proterozoic terranes occur as mafic boudins encased within low-density felsic crust, which provides positive buoyancy during subduction; however, recent geochemical proxy analysis shows that Archean continental crust was more mafic than previously thought, having greater proportions of basalt and komatiite than modern-day continents. Here, we show via petrological modelling that secular change in the petrology and bulk composition of upper continental crust would make Archean continental terranes negatively buoyant in the mantle before reaching UHP conditions. Subducted or delaminated Archean continental crust passes a point of no return during metamorphism in the mantle prior to the stabilization of coesite, while Proterozoic and Phanerozoic terranes remain positively buoyant at these depths. UHP orogenic eclogite may thus readily have formed on the Archean Earth, but could not have been exhumed, weakening arguments for a Neoproterozoic onset of subduction and plate tectonics. Further, isostatic balance calculations for more mafic Archean continents indicate that the early Earth was covered by a global ocean over 1 km deep, corroborating independent isotopic evidence for large-scale emergence of the continents no earlier than c. 3 Ga. Our findings thus weaken arguments that early life on Earth likely emerged in shallow subaerial ponds, and instead support hypotheses involving development at hydrothermal vents in the deep ocean.
2021, 12(5): 101226.
doi: 10.1016/j.gsf.2021.101226
Abstract:
Nitrogen-containing heterocyclic compounds are fundamental biochemical components of all life on Earth and, presumably, life elsewhere in our solar system. Detection and characterization of these compounds by traditional solvent extraction, chromatographic separation, and GC–MS analysis require more sample mass than will be available from samples returned to Earth from Mars. With its small sample mass requirement, Surface Enhanced Raman Spectroscopy could be an appropriate technique for analysis of returned samples. We have developed a SERS method for the detection of maleimide (2,5-pyrroledione), an N-containing heterocycle with a structure that is widespread in biochemicals. This semi-quantitative methodology accurately determines maleimide concentration in the range from 60 µg/mL to 120 µg/mL. We present a maleimide SERS standard spectrum which will be useful as a reference for future works. The present work demonstrates an easy, accurate, and effective method for the non-destructive qualitative and semi-quantitative study of maleimide as a first step toward developing a method for analysis of related compounds.
Nitrogen-containing heterocyclic compounds are fundamental biochemical components of all life on Earth and, presumably, life elsewhere in our solar system. Detection and characterization of these compounds by traditional solvent extraction, chromatographic separation, and GC–MS analysis require more sample mass than will be available from samples returned to Earth from Mars. With its small sample mass requirement, Surface Enhanced Raman Spectroscopy could be an appropriate technique for analysis of returned samples. We have developed a SERS method for the detection of maleimide (2,5-pyrroledione), an N-containing heterocycle with a structure that is widespread in biochemicals. This semi-quantitative methodology accurately determines maleimide concentration in the range from 60 µg/mL to 120 µg/mL. We present a maleimide SERS standard spectrum which will be useful as a reference for future works. The present work demonstrates an easy, accurate, and effective method for the non-destructive qualitative and semi-quantitative study of maleimide as a first step toward developing a method for analysis of related compounds.
2021, 12(5): 101189.
doi: 10.1016/j.gsf.2021.101189
Abstract:
Corona Virus Disease 2019 (COVID-19) caused by the novel coronavirus, results in an acute respiratory condition coronavirus 2 (SARS-CoV-2) and is highly infectious. The recent spread of this virus has caused a global pandemic. Currently, the transmission routes of SARS-CoV-2 are being established, especially the role of environmental transmission. Here we review the environmental transmission routes and persistence of SARS-CoV-2. Recent studies have established that the transmission of this virus may occur, amongst others, in the air, water, soil, cold-chain, biota, and surface contact. It has also been found that the survival potential of the SARS-CoV-2 virus is dependent on different environmental conditions and pollution. Potentially important pathways include aerosol and fecal matter. Particulate matter may also be a carrier for SARS-CoV-2. Since microscopic particles can be easily absorbed by humans, more attention must be focused on the dissemination of these particles. These considerations are required to evolve a theoretical platform for epidemic control and to minimize the global threat from future epidemics.
Corona Virus Disease 2019 (COVID-19) caused by the novel coronavirus, results in an acute respiratory condition coronavirus 2 (SARS-CoV-2) and is highly infectious. The recent spread of this virus has caused a global pandemic. Currently, the transmission routes of SARS-CoV-2 are being established, especially the role of environmental transmission. Here we review the environmental transmission routes and persistence of SARS-CoV-2. Recent studies have established that the transmission of this virus may occur, amongst others, in the air, water, soil, cold-chain, biota, and surface contact. It has also been found that the survival potential of the SARS-CoV-2 virus is dependent on different environmental conditions and pollution. Potentially important pathways include aerosol and fecal matter. Particulate matter may also be a carrier for SARS-CoV-2. Since microscopic particles can be easily absorbed by humans, more attention must be focused on the dissemination of these particles. These considerations are required to evolve a theoretical platform for epidemic control and to minimize the global threat from future epidemics.
2021, 12(5): 101227.
doi: 10.1016/j.gsf.2021.101227
Abstract:
