2018年9月8日墨江地震及周边地区构造应力场特征分析   总被引：1，自引：0，他引：1       下载免费PDF全文

李泽潇  万永革  崔华伟  李振月  胡晓辉  黄骥超  靳志同 《地球物理学报》2020,63(4):1431-1443

2018年9月8日,云南省墨江县发生MS5.9地震并伴随一系列余震,探究该地震周围的应力场对于理解该地震的发生机制和后续地震的发展趋势具有着重要的参考意义.本研究收集了震源及其邻区中前人研究和Global CMT所给出的震源机制资料,对该地区进行了构造应力场反演,并同时利用反演得到的应力张量模拟墨江地区的震源机制解表现.结果表明:(1)在应力轴整体分布上,自西向东σ1轴(压轴)从NNE-SSW向逐渐转向NNW-SSE向,σ3轴(张轴)从WWN-EES向逐渐转向WWS-EEN向,张轴呈弧形分布,压轴呈放射状分布.(2)在应力轴倾伏角上,研究区域内的压应力轴和张应力轴倾伏角都比较小,即两轴均接近水平.(3)R值分布大体是在东南部相较于西北部大,结合当地地质背景分析得到,物质逃逸自西北向东南呈逐渐变缓的趋势.(4)利用反演得到的应力张量和应力状态计算墨江地震震源区的相对剪应力和相对正应力大小.由此推测,墨江地震恰好发生在相对剪切应力值和相对正应力正值最大的节面上.从而可以确定墨江地震的发震节面的基本参数:走向216.32°,倾角86.91°,滑动角0.27°,相对剪应力值0.9,相对正应力值0.3.本研究为此次墨江地震的发震背景和地震动力学研究提供了基础性资料.  相似文献   

Estimation of the 3D correlation structure of an alluvial aquifer from surface-based multi-frequency ground-penetrating radar reflection data     

Zhiwei Xu  James Irving  Kyle Lindsay  John Bradford  Peimin Zhu  Klaus Holliger 《Geophysical Prospecting》2020,68(2):678-689

Knowledge about the stochastic nature of heterogeneity in subsurface hydraulic properties is critical for aquifer characterization and the corresponding prediction of groundwater flow and contaminant transport. Whereas the vertical correlation structure of the heterogeneity is often well constrained by borehole information, the lateral correlation structure is generally unknown because the spacing between boreholes is too large to allow for its meaningful inference. There is, however, evidence to suggest that information on the lateral correlation structure may be extracted from the correlation statistics of the subsurface reflectivity structure imaged by surface-based ground-penetrating radar measurements. To date, case studies involving this approach have been limited to 2D profiles acquired at a single antenna centre frequency in areas with limited complementary information. As a result, the practical reliability of this methodology has been difficult to assess. Here, we extend previous work to 3D and consider reflection ground-penetrating radar data acquired using two antenna centre frequencies at the extensively explored and well-constrained Boise Hydrogeophysical Research Site. We find that the results obtained using the two ground-penetrating radar frequencies are consistent with each other, as well as with information from a number of other studies at the Boise Hydrogeophysical Research Site. In addition, contrary to previous 2D work, our results indicate that the surface-based reflection ground-penetrating radar data are not only sensitive to the aspect ratio of the underlying heterogeneity, but also, albeit to a lesser extent, to the so-called Hurst number, which is a key parameter characterizing the local variability of the fine-scale structure.  相似文献   

Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre-stack seismic data     

Mattia Aleardi 《Geophysical Prospecting》2020,68(9):2738-2761

Markov chain Monte Carlo algorithms are commonly employed for accurate uncertainty appraisals in non-linear inverse problems. The downside of these algorithms is the considerable number of samples needed to achieve reliable posterior estimations, especially in high-dimensional model spaces. To overcome this issue, the Hamiltonian Monte Carlo algorithm has recently been introduced to solve geophysical inversions. Different from classical Markov chain Monte Carlo algorithms, this approach exploits the derivative information of the target posterior probability density to guide the sampling of the model space. However, its main downside is the computational cost for the derivative computation (i.e. the computation of the Jacobian matrix around each sampled model). Possible strategies to mitigate this issue are the reduction of the dimensionality of the model space and/or the use of efficient methods to compute the gradient of the target density. Here we focus the attention to the estimation of elastic properties (P-, S-wave velocities and density) from pre-stack data through a non-linear amplitude versus angle inversion in which the Hamiltonian Monte Carlo algorithm is used to sample the posterior probability. To decrease the computational cost of the inversion procedure, we employ the discrete cosine transform to reparametrize the model space, and we train a convolutional neural network to predict the Jacobian matrix around each sampled model. The training data set for the network is also parametrized in the discrete cosine transform space, thus allowing for a reduction of the number of parameters to be optimized during the learning phase. Once trained the network can be used to compute the Jacobian matrix associated with each sampled model in real time. The outcomes of the proposed approach are compared and validated with the predictions of Hamiltonian Monte Carlo inversions in which a quite computationally expensive, but accurate finite-difference scheme is used to compute the Jacobian matrix and with those obtained by replacing the Jacobian with a matrix operator derived from a linear approximation of the Zoeppritz equations. Synthetic and field inversion experiments demonstrate that the proposed approach dramatically reduces the cost of the Hamiltonian Monte Carlo inversion while preserving an accurate and efficient sampling of the posterior probability.  相似文献   

The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil     

《International Journal of Applied Earth Observation and Geoinformation》2020

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 10⁶ m²), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.  相似文献   

基于时相变化的晴空条件下Himawari-8 AHI火点检测     

鄢俊洁  瞿建华  冉茂农  张芳芳 《遥感学报》2020,24(5):571-577

Himawari-8静止气象卫星具有高空间分辨率、高观测频次和高时效特点,对于火点检测具有很强优势。对Himawari-8卫星的3.9μm和11.2μm两通道亮温进行了连续时相变化研究,得出两通道的亮温在时间上的变化差值稳定且规律明显。根据两通道的亮温时相特征,考虑白天可见光对3.9μm通道的影响,并结合火点产生时引起的亮温变化特征,提出了适用于晴空条件下改进的火点检测算法。在多处进行了此算法的实验,例如2018-11-27 T 16:40(UTC时)河北张家口市桥东区一化工厂附近发生的严重爆炸起火事件以及2019-02-28澳大利亚西南部发生的火灾事件,均快速有效的检测到了火点。实验表明,改进的火点检测算法能很好的进行火点检测,并能解决晨昏交界、冰雪下垫面、常规火源点、太阳耀光等火点检测的难题。  相似文献   

Sentinel-2卫星落叶松林龄信息反演   总被引：1，自引：0，他引：1  

唐少飞  田庆久  徐凯健  徐念旭  岳继博 《遥感学报》2020,24(12):1511-1524

林龄结构信息能够有效反映区域森林群落不同生长阶段的固碳能力，对于评估森林生态系统的健康状况具有重要意义。本研究以中国温带典型优势树种落叶松林为研究对象，分别选择其芽萌动期、展叶期和落叶期时段的Sentinel-2影像，采用多元线性回归（MLR）、随机森林（RF）、支持向量机回归（SVR）、前馈反向传播神经网络（BP）以及多元自适应回归样条（MARS）等5种方法依次构建落叶松林龄反演模型。通过相关性分析首先确定最佳遥感反演物候期，并在此基础上根据相关性差异筛选出5个最优特征变量用于模型反演，分别为冠层含水量（CWC），归一化水体指数（NDWI），叶面积指数（LAI），光合有效辐射吸收率（FAPAR）和植被覆盖度（FVC）。研究结果表明，展叶期为落叶松林最佳遥感反演物候期。除植被衰减指数（PSRI）以及落叶期的NDVI、RVI外，落叶松林龄与各指标之间均呈负相关关系，其中与冠层含水量（CWC）的相关性最高，pearson相关系数达到-0.74（p<0.01）。此外，不同模型反演结果表明，随机森林模型（RF）为最佳落叶松林龄估测模型，其平均决定系数R²和平均均方根误差RMSE分别为0.89和2.91 a；多元线性回归模型（MLR）的林龄估测结果最差，其平均决定系数R²和平均均方根误差RMSE仅为0.57和5.69 a，非线性模型能更好的解释林龄与建模变量之间的关系。  相似文献   

基于 SRP 概念模型的祁连山地区生态脆弱性评价   总被引：1，自引：0，他引：1       下载免费PDF全文

刘佳茹  赵军  沈思民  赵彦军 《干旱区地理》2020,43(6):1573-1582

基于生态敏感性-生态恢复力-生态压力度（SRP）概念模型，从地形、气候、植被和社会经济 因子选取 8 个评价指标，利用遥感和 GIS 技术，采用主成分分析方法求取权重，对祁连山地区启动 水源涵养区生态环境保护和综合治理规划研究前后近 10 a 的生态脆弱性程度进行系统、定量地评 估，旨在揭示生态脆弱性的分布特征、时空演变及动因，为区域生态保护、资源利用和可持续发展 提供参考。结果表明：（1）从研究区生态脆弱性分布来看，祁连山地区主要以轻度和重度脆弱为 主，脆弱性程度从西北向东南地区逐渐减弱，西北地区植被覆盖度小，海拔高，生态环境较为恶劣 是导致脆弱性程度较高的原因；（2）祁连山地区 3 期生态脆弱程度呈逐渐下降趋势，综合指数分别 为 3.307、3.118 和 3.103；2005 年 生 态 脆 弱 性 较 高 ，极 度 脆 弱 面 积 为 28 610 km²，2010 年 下 降 为 11 723 km²，2015 年降低为 6 174 km²，极度脆弱面积逐渐减少；（3）从祁连山地区生态脆弱性演变动 因来看，8 个指标对生态脆弱性影响均较为显著，但在不同的时间影响程度各不相同，2005—2015 年 3 期数据中对生态脆弱性影响最大的均为植被指数，降水次之，地形因子影响最小。总体来看， 近年来祁连山地区生态脆弱性程度有所降低，但仍然需要加强保护力度，促进生态环境可持续 发展。  相似文献   

陕北地区退耕还林还草工程土壤保护效应的时空特征   总被引：1，自引：1，他引：0  

刘文超  刘纪远  匡文慧 《地理学报(英文版)》2020,30(3):401-422

This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade.  相似文献   

Coupling numerical simulation with remotely sensed information for the study of frozen soil dynamics     

HuiRan Gao  WanChang Zhang 《寒旱区科学》2020,12(6):404-417

The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil.  相似文献   

重力数据约束的二维地震层析成像在台湾海峡南部的应用     

王笋  闫培  刘善虎 《大地测量与地球动力学》2019,39(3):302-306

地震-重力联合反演可以降低多解性，针对大勘探范围内岩石波速-密度关系存在较大散布的问题，引入交叉梯度结构约束构建统一的目标函数是一种有效的解决方案。利用台湾海峡南部HX-13测线进行验证：由于火成岩侵入体的存在，部分区域难以拾取可靠的地震初至，常规的走时反演无法准确恢复基底面的形态。搜集研究区的船测重力资料，根据地震地质条件和数据特点设置合适的反演参数，实现基于物性和结构双重约束的重力-地震联合反演。由对反演结果的分析和解释可以看出，该方法可在很大程度上弥补地震数据不完备的缺陷，使反演过程稳定，并提高模型的可靠性。  相似文献