向斜构造煤层开采地表移动规律研究

现行的地表移动预计方法，都是建立在开采工作面主断面为线性分布的基础上，因此，对于非线性分布煤层的预计将会产生较大的误差。本文以随机介质理论为基础，利用曲线积分的方法建立了地表移动与变形预计公式，并且利用数值积分法和叠加原理解算地表移动与变形值，扩大了地表移动预计理论的应用范围，同时也大大提高了预计值的精度     

Integration of hyperspectral and LiDAR data for mapping small water bodies

Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.     

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

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.     

The Coarse-Grained Lacustrine Slope Apron Deposits in the Moliqing Area, Yitong Basin, Northeast China

Overlapping gravity accumulation bodies were formed on the northwestern steep slope of the Shuangyang Formation in the Moliqing fault depression of northeast China. This study analyzed in detail the spatial distribution of the lithofacies and lithofacies associations of these accumulation bodies based on more than 600 m of core sections, and summarized 12 major types of lithofacies and three types of lithofacies associations: (1) the proximal zone consists of gravelly debris flows dominated by alluvial channel conglomerates; (2) the middle zone is dominated by various gravity flow deposits and traction flow deposits; and (3) the distal zone is dominated by mudstones with intercalations of sandy debris and turbidites. Combining with the grain size cumulative probability curves analysis, we determined the transformation of debris flows to sandy debris flows and to turbidity currents in the slope zone of the basin margin, and further proposed a lacustrine slope apron model that is characterized by (1) an inconstant multiple source (line source), (2) an alternation of gravity flow deposits and traction flow deposits dominated by periodical changes in a source flood flow system, and (3) the transformation of sandy debris flow deposits into distal turbidity current deposits. This sedimentary model may be applicable to other fault depressions for predicting reservoir distribution.     

广州白云堡豪苑观光塔滑坡的形成与防治研究

以往常有两种误区：(1)认为单斜岩层边坡只要坡脚处岩层不被切断，就不会破坏；(2)植树绿化和排水设施的设置总是对边坡的稳定性有利的。文章通过野外调查和力学模型分析了坡脚处岩层未被切断的白云堡豪苑观光塔处单斜岩层滑坡的形成机制，认为该滑坡属于顺层边坡溃屈型的板裂破坏——溃屈破坏，分析了滑坡的稳定性及剩余滑动力。分析表明，人工开挖后边坡的防治方法和措施不当对该滑坡的产生起了非常关键性的作用，其中盲目的植树绿化和排水沟设置成了边坡不稳定的主要诱导因素。由此可见，边坡(滑坡)防治措施的选择对其稳定性具有非常重要的意义。最后，提出切中要害的滑坡防治方案。     

水对土质边坡的稳定性影响分析

首先论述了地下水对边坡稳定性的影响因素,水对土质边坡的影响作用,接着推导出了考虑水作用影响的边坡安全系数计算公式,最后指出应用动态的观点来研究边坡体内的地下水作用.     

海底缓坡场地地震侧移数值分析方法

地震动使海底倾斜土层软化、液化并产生永久变形和位移。基于有限元理论,提出一种海底缓坡场地地震引起水平侧移的数值计算方法,将波浪荷载简化为恒定压力荷载和初始孔压,采用二维有效应力动力有限元分析方法进行液化分析,同时由模量软化理论得到土层在地震动各时段的模量,通过非线性静力方法计算软化、液化引起的水平侧移。由算例分析了土层坡度、液化层及上覆非液化层厚度、波浪荷载等因素对侧移的影响,通过对比分析表明了该方法的有效性,可为近海工程场地地震地质灾害评价提供参考数据。     

Slump debris flows in the Akovolwo Mountains area of Benue State,Nigeria

In September 1979, rain-induced complex landslides occurred in two separate localities along the slopes of the Akovolwo Mountains near Jato-Aka in the Kwande Local Government area of Benue State, Nigeria.The two movements developed on bedrock slopes covered by a veneer of colluvium and (or) residuum no more than 1.5 to 2m deep. Each started as a slump and graduated into a debris flow. The slump, extending downhill a short distance away from the head scarp, had been reconstituted into a debris flow as the initial movement (sliding movement) of the soil mass caused remoulding of the saturated moving mass into viscous debris-laden mud. The resulting mass moved partly along a pre-existing mountain stream channel and partly along a fresh channel it cleared in the savanna forest. At the break of slope, the mass of boulders was dumped and a trail of smaller fragments littered the channels towards the Katsina-Ala River.     

水及开挖卸荷对岩质边坡稳定性影响分析

水及开挖卸荷是影响节理裂隙岩质边坡稳定性的重要因素。分析研究了水对节理裂隙岩质边坡的力学及物理化学作用机理。应用弹塑性力学及断裂力学的相关理论,分析讨论了裂隙面的压剪起裂破坏机理;提出了由于开挖卸荷而引起裂纹扩展的作用机理。