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1.
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
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洋底板块运动是地球动力学和全球变化研究的重要内容.本文根据质量迁移与地球外部重力场变化的对应关系,利用不同时期测高资料推算的1995—2019全球海洋重力场变化结果,反演分析全球洋底板块运动特征.研究表明,板块汇聚边界、板块内无震海岭、海山群、断裂带等区域重力异常变化显著,而在板块离散边界无明显变化趋势;西南印度洋中脊、大西洋中脊、中印度洋中脊等地区重力异常垂直梯度变化显著,且在西太平洋俯冲带、部分海岭区域也存在明显变化,其空间分布与地形基本吻合.海洋重力场变化整体上准确反映了全球洋底板块构造运动.相较于重力异常变化反演结果,重力垂直梯度的变化能够更为准确地反映洋底板块运动特征,特别是在洋中脊区域,扩张速率越小,垂直重力梯度变化越显著.此外,详细讨论了测高海洋重力场不确定因素对洋底板块运动分析结果的影响,海面坡度改正是主要因素之一. 相似文献
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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
4.
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
5.
The simultaneous transfer of pore fluid and vapour was studied in the unsaturated shallow subsurface of a Plio-Pleistocene marine mudstone badland slope in southwestern Taiwan during the dry season using field monitoring data and numerical simulations. Data from field monitoring show mass-basis water contents of ~0.05 to ~0.10 that decrease towards the unsaturated ground surface and were invariant during the middle part of the dry season, except for daily fluctuations. In addition, the observed daily fluctuations in water content correlate with fluctuations in bedrock temperature, especially at depths of 2.5–5.0 cm. Periodic increases in water content occurred most notably during the day, when the bedrock temperature showed the greatest increase. Water contents then decreased to the previous state as bedrock temperature decreased during the night. Calculated vapour fluxes within the mudstone during the day increased up to 6 × 10−6–1 × 10−5 kg m−2 s−1, deriving a 0.01–0.02 increase in mass-basis water content at 2.5 cm depth for a 12-h period. This agrees with field monitoring data, suggesting that increases in water content occurred due to vapour intrusions into the bedrock. Pore water electrical conductivity (EC) showed periodic variations due to vapour intrusion, and gradually increased between the ground surface and depths of 2.5–5.0 cm. In contrast, pore water EC gradually decreased between 15 and 40 cm depth. Calculated water fluxes at depths of 2.5–40.0 cm varied from −4 × 10−6 to −2 × 10−9 kg m−2 s−1. These fluxes generated an increase in solute concentrations at the ground surface, with negative values of water flux indicating an upwards movement of water towards the surface. We show that the increase in solute content due to solute transfer from depth is highly dependent on variations in water flux with depth. © 2020 John Wiley & Sons, Ltd. 相似文献
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Time series of hydrogen and oxygen stable isotope ratios (δ2H and δ18O) in rivers can be used to quantify groundwater contributions to streamflow, and timescales of catchment storage. However, these isotope hydrology techniques rely on distinct spatial or temporal patterns of δ2H and δ18O within the hydrologic cycle. In New Zealand, lack of understanding of spatial and temporal patterns of δ2H and δ18O of river water hinders development of regional and national-scale hydrological models. We measured δ2H and δ18O monthly, together with river flow rates at 58 locations across New Zealand over a two-year period. Results show: (a) general patterns of decreasing δ2H and δ18O with increasing latitude were altered by New Zealand's major mountain ranges; δ2H and δ18O were distinctly lower in rivers fed from higher elevation catchments, and in eastern rain-shadow areas of both islands; (b) river water δ2H and δ18O values were partly controlled by local catchment characteristics (catchment slope, PET, catchment elevation, and upstream lake area) that influence evaporation processes; (c) regional differences in evaporation caused the slope of the river water line (i.e., the relationship between δ2H and δ18O in river water) for the (warmer) North Island to be lower than that of the (cooler, mountain-dominated) South Island; (d) δ2H seasonal offsets (i.e., the difference between seasonal peak and mean values) for individual sites ranged from 0.50‰ to 5.07‰. Peak values of δ18O and δ2H were in late summer, but values peaked 1 month later at the South Island sites, likely due to greater snow-melt contributions to streamflow. Strong spatial differences in river water δ2H and δ18O caused by orographic rainfall effects and evaporation may inform studies of water mixing across landscapes. Generally distinct seasonal isotope cycles, despite the large catchment sizes of rivers studied, are encouraging for transit time analysis applications. 相似文献
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面向数字孪生城市的智能化全息测绘 总被引:2,自引:0,他引:2
以大数据、物联网、人工智能、虚拟现实、云计算、智能驾驶等新技术为代表的信息化浪潮席卷全球,数字世界与物理世界正形成两大平行发展、相互作用的体系,数字孪生技术应运而生。随着物联网技术(IOT)的发展,数字孪生的理念被引入到智慧城市建设中来,深刻影响着城市规划、建设与治理。笔者所在单位面向数字孪生城市和自然资源统一监管对测绘地理信息的新需求,在全国开创性地开展了面向数字孪生城市的智能化全息测绘试点工作。本文结合上海市智能化全息测绘试点工作,从数字孪生城市、数字孪生城市对地理信息的新需求、智能化全息测绘关键技术及测绘成果等方面展开了论述,重点介绍了智能化全息测绘的技术体系和产品体系,以及在社会各领域的应用成果。 相似文献