Geoscience frontiers最新文献

Extreme fractionation of elements and isotopes in mafic igneous rocks is abnormal in deciphering the source nature and melting conditions of mafic magmatism. Especially, identification of geochemically ultra-depleted mafic melts and their mantle sources has great bearing on the property of crust-mantle differentiation at plate margins. This is illustrated by extreme Hf-Nd isotope fractionation in ultrahigh-pressure eclogites from the Sulu orogen in east-central China. In addition to the previous finding of ultrahigh ε_Nd(0) values, we report here new data of whole-rock trace elements and Lu-Hf isotopes in eclogites and related rocks from the same region. The present results show extremely high Lu/Hf ratios and abnormally high ε_Hf(0) values of up to 576 for the eclogites, significantly different from the garnet amphibolites and other eclogite-facies metamorphic rocks in the same orogen. This feature is coupled with the ultrahigh ε_Nd(0) values as well as the severe depletion of light rare earth elements (LREE) and high field strength elements (HFSE). Because HFSE and LREE are immobile in aqueous solutions and the effect of melt extraction is insignificant during the continental deep subduction, the extreme fractionation of Lu/Hf and Sm/Nd indicate their origination from a geochemically ultra-depleted mantle source. These eclogites have the depleted mantle Hf model ages of 1.27 Ga to 1.61 Ga, similar to the depleted mantle Nd model ages of 1.39 Ga to 1.67 Ga as previously reported. This suggests that the protolith of the extremely high ε_Hf-ε_Nd eclogites was a kind of mafic igneous rocks derived from fractional crystallization of geochemically ultra-depleted mafic melts, which were produced by partial melting of the highly refractory lithospheric mantle during a series of seafloor spreading initiation-failure cycles at a divergent plate margin after the breakup of supercontinent Columbia in the Early Mesoproterozoic. The mafic igneous rocks were located in a passive continental margin in the Late Paleozoic and experienced deep subduction and exhumation in the Triassic, giving rise to the presently studied eclogites. The ancient geochemical signatures were retained without considerable influence by mantle convection, providing insights into the nature of crust-mantle differentiation during the tectonic transition from supercontinental breakup to seafloor spreading beneath the sub-ridge lithospheric mantle.

The Permian Fengcheng Formation of the Western Junggar region in the Southwestern Central Asian Orogenic Belt (CAOB) represents one of Earth’s oldest alkali lake deposits. Here, we present a comprehensive study of the stratigraphy, petrography, two-dimensional seismic data, U–Pb geochronology, and Hf isotope analysis of detrital zircons of this deposit. The results, in conjunction with published data, reflect the tectonic evolution of southwestern CAOB. The ages of detrital zircons indicate that the Fengcheng Formation deposition is inferred to have concluded the early Permian Kungurian. The Hf isotopes of detrital zircons indicate that the detritus for the Fengcheng Formation was derived from upper crustal magmatic sources. The West Junggar Basin preserves the records of three Paleozoic tectonic stages. The first stage occurred in the Early Paleozoic and involved intraoceanic subduction and arc-continent collision. The second stage involved the Carboniferous closure of the Junggar Ocean following successive filling of oceanic basins. The final stage occurred in the Early Permian and was related to intracontinental rifting and tectonic inversion. The results of comparing the comprehensive data of U–Pb ages and Hf isotopes of 2537 zircons from West Junggar, Tianshan and Altay show that the orogenic belts to the south of the CAOB experienced similar plate kinematics and vertical crustal growth in the Paleozoic.

Flood disasters pose serious threats to human life and property worldwide. Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts. This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability, while considering spatial heterogeneity. In this framework, the Optimal Parameter-based Geographic Detector (OPGD), Recursive Feature Estimation (RFE), and Light Gradient Boosting Machine (LGBM) models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters. The SHapley Additive ExPlanation (SHAP) interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters. Yunnan Province, a typical mountainous and plateau area in Southwest China, was selected to implement the proposed framework and conduct a case study. For this purpose, a flood disaster inventory of 7332 historical events was prepared, and 22 potential driving factors related to precipitation, surface environment, and human activity were initially selected. Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity, with geomorphic zoning accounting for 66.1% of the spatial variation in historical flood disasters. The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts. Moreover, the simulation performance shows a slight improvement (a 6% average decrease in RMSE and an average increase of 1% in R²) even with reduced factor data. Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions; nevertheless, precipitation-related factors, such as precipitation intensity index (SDII), wet days (R10MM), and 5-day maximum precipitation (RX5day), were the main driving factors controlling flood disasters. This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity, offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.

Landslide susceptibility assessment is crucial in predicting landslide occurrence and potential risks. However, traditional methods usually emphasize on larger regions of landsliding and rely on relatively static environmental conditions, which exposes the hysteresis of landslide susceptibility assessment in refined-scale and temporal dynamic changes. This study presents an improved landslide susceptibility assessment approach by integrating machine learning models based on random forest (RF), logical regression (LR), and gradient boosting decision tree (GBDT) with interferometric synthetic aperture radar (InSAR) technology and comparing them to their respective original models. The results demonstrated that the combined approach improves prediction accuracy and reduces the false negative and false positive errors. The LR-InSAR model showed the best performance in dynamic landslide susceptibility assessment at both regional and smaller scale, particularly when identifying areas of high and very high susceptibility. Modeling results were verified using data from field investigations including unmanned aerial vehicle (UAV) flights. This study is of great significance to accurately assess dynamic landslide susceptibility and to help reduce and prevent landslide risk.

High arsenic (As) groundwater is a global problem primarily originating from As-enriched sediments. The provenance (source) and release mechanisms (sinks) of high As sediment have been identified, but the source-sink transfer is poorly understood, especially the influence of geological and surface processes. In this study, we explore the roles of tectonic movement and Yellow River evolution in provenance formation processes and evaluate the combined effects of provenance and sediment age on the As content of aquifer sediments in the northern Hetao Basin of Inner Mongolia. Based on optically stimulated luminescence (OSL) and ¹⁴C dating and detrital zircon U-Pb, As content, and lithological analyses of a 400 m core, we reconstructed As changes over the last 160 ka. Our results show clay deposited in a paleo-lake during the Gonghe movement period in the late Pleistocene (∼100 ka B.P.) is enriched in As (31.8 μg/g) due to significant provenance contributions of the As-bearing Langshan Group under tectonic uplift and mountain erosion. In contrast, clay deposited in the middle Pleistocene (∼160 ka B.P.) has lower As content (7.3 μg/g) due to the Yellow River as the primary provenance. Accordingly, the provenance of basin As forced by tectonic uplift and Yellow River evolution determines the background As of aquifer sediments. After deposition, sediment As content decays over time, with higher decay rates in coarse-grained sands than fine-grained. Overall, both provenance formation and sediment age, representing initial and dynamic states of solid phase As, jointly determine the As content of aquifer sediments. More solid phase As provided by younger sediments from the proximal orogenic provenance and reducing conditions due to frequent river–lake transitions, jointly lead to higher As concentrations in shallow groundwater. The study highlights the potential for using a combined analysis of the tectonic movement-surface processes-environment system to improve understanding of geogenic high As groundwater over global large sedimentary basins in the proximity of young orogenic belts.