Search Results (8)

On 21 May 2021, an Mw 6.1 earthquake occurred in Yangbi County, Dali Bai Autonomous Prefecture, Yunnan Province, with the epicenter located in an unmapped blind fault approximately 7 km west of the Weixi-Qiaohou fault (WQF) on the southeastern margin of the Qinghai–Tibetan Plateau. While numerous studies have been conducted to map the coseismic slip distribution by using the Global Navigation Satellite System (GNSS), Interferometric Synthetic Aperture Radar (InSAR) and seismic data as well as their combinations, the understanding of deformation characteristics during the postseismic stage remains limited, mostly due to the long revisiting time interval and large uncertainty of most SAR satellites. In this study, we refined coseismic slip and afterslip distributions with nonlinear inversions for both fault geometry and relaxation time. First, we determined the fault geometry and coseismic slip distribution of this earthquake by joint inversion for coseismic offsets in the line-of-sight (LOS) direction of both Sentinel-1A/B ascending and descending track images and GNSS data. Then, the descending track time series of Sentinel-1 were further fitted using nonlinear least squares to extract the coseismic and postseismic deformations. Finally, we obtained the refined coseismic slip and afterslip distributions and investigated the spatiotemporal evolution of fault slip by comparing the afterslip with aftershocks. The refined coseismic moment magnitude, which was of Mw 6.05, was smaller than Mw 6.1 or larger, which was inferred from our joint inversion and previous studies, indicating a significant reduction in early postseismic deformation. In contrast, the afterslip following the mainshock lasted for about six months and was equivalent to a moment release of an Mw 5.8 earthquake. These findings not only offer a novel approach to extracting postseismic deformation from noisy InSAR time series but also provide valuable insights into fault slip mechanisms associated with the Yangbi earthquake, enhancing our understanding of seismic processes. Full article

The Sichuan-Yunnan block is a tectonically active region in China, with frequent large earthquakes occurring in and around it. Despite most earthquakes being concentrated along boundary faults, intraplate faults also have the potential to generate damaging earthquakes. Remote sensing makes it possible to identify these potential earthquake source faults. During an active fault investigation in the Liangshan area, a distinct lithological boundary named Caimashui fault was found. The geometric distribution and kinematic parameter of the fault is crucial for assessing seismic hazards and understanding the deformation pattern within the Sichuan-Yunnan block. The Caimashui fault is mapped with remote sensing interpretation, a field survey, and UAV measurement. Through trenching and Quaternary dating, the Late Quaternary active characteristics of the fault are studied. The fault is a Holocene active dextral strike-slip fault with a reverse component, exhibiting a dextral strike-slip rate of ~0.70 ± 0.11 mm/a. Paleoseismic investigation shows that the last surface rupture event of the Caimashui fault occurred later than 4150 ± 30a BP, with a magnitude of M ≥ 7.0. The fault may act as a secondary splitting fault, absorbing the deformation caused by various sinistral strike-slip rates of the boundary faults and the potential energy from the counterclockwise rotation of the Central Yunnan micro-block. Full article

Earthquake-triggered landslides (ETLs) feature large quantities, extensive distributions, and enormous losses to human lives and critical infrastructures. Near-real spatial prediction of ETLs can rapidly predict the locations of coseismic landslides just after a violent earthquake and is a vital technical support for emergency response. However, near-real prediction of ETLs has always been a great challenge with relatively low accuracy. This work proposes an ensemble prediction model of EnPr by integrating machine learning tree models and a deep learning convolutional neural network. EnPr exhibits relatively strong prediction and generalization performance and achieves relatively accurate prediction of ETLs. Six great seismic events occurring from 2008 to 2022 on the southeastern margin of the Tibetan Plateau are selected to conduct ETL prediction. In a chronological order, the 2008 M_s 8.0 Wenchuan, 2010 M_s 7.1 Yushu, 2013 M_s 7.0 Lushan, and 2014 M_s 6.5 Ludian earthquakes are employed for model training and learning. The 2017 M_s 7.0 Jiuzhaigou and 2022 M_s 6.1 Lushan earthquakes are adopted for ETL prediction. The prediction accuracy merits of ACC and AUC attain 91.28% and 0.85, respectively, for the Jiuzhaigou earthquake. The values of ACC and AUC achieve 93.78% and 0.88, respectively, for the Lushan earthquake. The proposed EnPr algorithm outperforms the algorithms of XGBoost, random forest (RF), extremely randomized trees (ET), convolutional neural network (CNN), and Transformer. Moreover, this work reveals that seismic intensity, high and steep relief, pre-seismic fault tectonics, and pre-earthquake road construction have played significant roles in coseismic landslide occurrence and distribution. The EnPr model uses globally accessible open datasets and can therefore be used worldwide for new large seismic events in the future. Full article

The Three Rivers Lateral Collision Zone (TRLCZ), situated at the southeastern margin of the Tibetan Plateau, is a crucial frontier where materials from the plateau flow southeastward. This study extensively investigated the hydrochemical characteristics and origin of helium and carbon isotopes in 73 thermal springs within the TRLCZ. The analysis revealed dominant processes, including carbonate and silicate interactions, resulting in elevated concentrations of HCO₃⁻ and Na⁺. The impact of Ca/Mg-rich minerals, particularly dolomite, influenced the cation composition. Additionally, gypsum dissolution, notably in the Lancangjiang Fault and Weixi–Qiaohou Fault, was highlighted through Ca/SO₄ ratios. The positive correlation between SO₄²⁻ and Cl⁻ indicated dilution by shallow cold water, explaining the lower SO₄²⁻ content in the Jingshajiang–Zhongdian Fault and Nujiang Fault compared to the Weixi–Qiaohou Fault and Lancangjiang Fault. The circulation depth of thermal spring water varied, with the northern Weixi–Qiaohou Fault exhibiting the shallowest circulation depth (~3 km), while the Jingshajiang–Zhongdian Fault and southern segments of the Nujiang Fault displayed deeper depths—ranging from 4 to 7 km. A positive correlation between the circulation depth and fault activity was also observed. The Rc/Ra ratios of free gas samples, predominantly indicating crustal origin, varied from 0.01 Ra to 0.53 Ra. Elevated Rc/Ra ratios in the research area suggested potential minor additions of mantle helium through faults and fractures. Crustal limestone was identified as the primary source of CO₂-rich samples, with δ¹³C_CO2 values ranging from −1.6‰ to −7.2‰, while trace amounts of mantle CO₂ were found. The spatial distribution of the H₂ concentration, CO₂ concentration, He concentration, and mantle He proportions in gases indicated that higher values of He concentration and mantle He% always occur near sampling points with deeper circulation depths. However, no similar correlation was observed for H₂ and CO₂. Most earthquakes of magnitude 5 or greater occurred near the regions with high values of mantle source He release, highlighting the critical role of mantle fluids in the occurrence of earthquakes in the region. In this study, a fluid circulation model was developed to describe the process of fluid (water and gas) circulation migration and earthquake generation in the TRLCZ. Full article

The northeastern margin of the Tibetan Plateau (NE Tibetan Plateau) exhibits active geological structures and has experienced multiple strong earthquakes, with M ≥ 7, throughout history. Particularly noteworthy is the 1920 M8¹/₂ earthquake in the Haiyuan region that occurred a century ago and is documented as one of the deadliest earthquakes. Consequently, analyzing seismic risks in the northeastern margin of the Tibetan Plateau holds significant importance. The b value, a crucial parameter for seismic activity, plays a pivotal role in seismic hazard analyses. This study calculates the spatial b values in this region based on earthquake catalogs since 1970. The study area encompasses several major active faults, and due to variations in b values across different fault types, traditional grid-search methods may introduce significant errors in calculating the spatial b value within complex fault systems. To address this, we employed the hierarchical space–time point–process (HIST-PPM) method proposed by Ogata. This method avoids partitioning earthquake samples, optimizes parameters using Akaike’s Bayesian Information Criterion (ABIC) with entropy maximization, and theoretically allows for a higher spatial resolution and more accurate b value calculations. The results indicate a high spatial heterogeneity in b values within the study area. The northwestern and southeastern regions exhibit higher b values. Along the Haiyuan fault zone, the central rupture zone of the Haiyuan earthquake has relatively higher b values than other regions of this fault zone, which is possibly related to the sufficient release of stress during the main rupture of the Haiyuan earthquake. The b values vary from high in the west to low in the east along the Zhongwei fault. On the West Qinling fault zone, the epicenter of the recent Minxian–Zhangxian earthquake is associated with a low b value. In general, regions with low b values correspond well to areas with moderate–strong seismic events in the past 50 years. The spatial differences in b values may reflect variances in seismic hazards among fault zones and regions within the same fault zone. Full article

In the present study, seismic gaps were identified as periods with no occurrence of M ≥ 4.0 earthquake over dT ≥ 400 days. After examining all records in the Sichuan–Yunnan–Tibet–Qinghai junction area on the southeastern margin of the Tibetan Plateau in 1970–2022, a total of six M ≥ 4.0 seismic gaps were identified. Spatio-temporal images of the seismic gaps had similar characteristics and demonstrated spatial overlapping and statistical significance. The quiet periods of the six seismic gaps included 419–777 days (approximately 580 days on average). The semi-major-axis and semi-minor-axis lengths were in the 880–1050 km (approximately 987 km on average) and 500–570 km (about 533 km on average) ranges, respectively. Case analysis results revealed that the images of M ≥ 4.0 seismic gaps were of high significance in predicting M ≥ 6.7 strong earthquakes in the region, and they could be used as a predictive index on a time scale of about 1–0.5 years or less. Full article

Significant hydrogeochemical changes may occur prior- and post-earthquakes. The Xiaojiang fault zone (XJF), situated in a highly deformed area of the southeastern margin of the Tibetan Plateau, is one of the active seismic areas. In this study, major and trace elements, and hydrogen and oxygen isotopes of 28 sites in hot springs along the XJF were investigated from June 2015 to April 2019. The meteoric water acts as the primary water source of the hot spring in the XJF and recharged elevations ranged from 1.8 to 4.5 km. Most of the hot spring water in the study area was immature water and the water–rock reaction degree was weak. The temperature range was inferred from an equation based on the SiO₂ concentration and chemical geothermal modeling: 24.3~96.0 °C. The circulation depth for the springs was estimated from 0.45 to 4.04 km. We speculated the meteoric water firstly infiltrated underground and became heated by heat sources, and later circulated to the earth’s surface along the fault and fracture and finally constituted hot spring recharge. Additionally, a continuous monitoring was conducted every three days in the Xundian hot spring since April 2019, and in Panxi and Qujiang hot springs since June 2019. There were short-term (4–35 d) seismic precursor anomalies of the hydrochemical compositions prior to the Xundian M_L4.2, Dongchuan M_L4.2, and Shuangbai M_L5.1 earthquakes. The epicentral distance of anomalous sites ranged from 19.1 to 192.8 km. The anomalous amplitudes were all over 2 times the anomaly threshold. The concentrations of Na⁺, Cl⁻, and SO₄²⁻ are sensitive to the increase of stress in the XJF. Modeling on hydrology cycles of hot springs can provide a plausible physicochemical basis to explain geochemical anomalies in water and the hydrogeochemical anomaly may be useful in future earthquake prediction research of the study area. Full article

The Tibetan Plateau (TP) is one of the world’s most sensitive areas for climate change. Previous studies have revealed that air pollutants emitted from South and Southeast Asia can be transported to and have a negative impact on the TP. However, the majority of the investigators have focused on the pollutant transport processes from South Asian regions (i.e., India and Bangladesh) and parts of Southeast Asia, while the regions adjacent to the southeast fringe of the TP (i.e., Burma and the Sino-Burmese border) have been neglected. Here, fine particulate matter (PM_2.5) samples were collected during the period 11 March to 13 May 2018 at Gaomeigu, a high-altitude remote site in the southeastern margin of the TP. Characteristics, sources of PM_2.5, and the potential source regions for different chemical components were investigated. During the sampling time, PM_2.5 mass loadings ranged from 3.79 to 54.57 µg m⁻³, with an arithmetic mean concentration of 20.99 ± 9.80 µg m⁻³. In general, major peaks of organic carbon (OC) and elemental carbon (EC) always coincided with high loadings of K⁺ and NO₃⁻, which implies that common combustion sources caused these species’ concentrations to covary, while the daily variations of crustal elements showed different trends with the other chemical compositions, suggesting different source regions for crustal materials. Five source factors were identified as possible aerosol sources for PM_2.5 by positive matrix factorization (PMF). They are the mining industry (5.3%), characterized by heavy metal elements; secondary formation (18.8%), described by the high concentrations of NH₄⁺ and SO₄²⁻; traffic-related emissions (26.7%), dominated by carbonaceous species (especially soot-EC) and some metal elements; fugitive dust (15.2%), represented by crustal elements (Ti, Fe, and Mn), Ca²⁺, and Mg²⁺; and biomass burning (34.0%), which is typified by high concentrations of K⁺, NO₃⁻, char-EC, primary OC, and secondary OC. The concentration-weighted trajectory (CWT) analysis results showed that the northeast part of Burma is the potential source region for high concentrations of EC and NO₃⁻ due to biomass burning emissions, while the tourism industry surrounding Gaomeigu gave strong grid cell values of SO₄²⁻ as well as moderate values of EC and NO₃⁻. Moreover, the mining industry in the southwest direction of Gaomeigu has important impacts on the zinc concentrations. Full article