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991.
992.
在济南南部下寒武统朱砂洞组丁家庄段硅质白云岩中,发育地震引起的硅质触变脉、硅质触变沉陷构造和触变楔等软沉积变形构造。从同一地震触变沉陷构造中,采得一组灰黑色燧石样品。使用英国VG354同位素质谱仪和同位素质谱分析方法,测得每个样品的 147Sm/144Nd 和 143Nd/144Nd 同位素值。采用Sm-Nd 等时线法,对燧石进行了测年。获得燧石的成岩年龄为530.8±6.1 Ma,由于软燧石(硅胶体)成岩至少经历了0.1 Ma的时间,所以,地震沉积事件发生在530.7±6.1 Ma,属早寒武世早期。由于测年结果与沧浪铺阶的下界年龄接近,山东朱砂洞组丁家庄段无化石且河南省标准地层剖面中的整个朱砂洞组属沧浪铺阶,这暗示济南地区朱砂洞组丁家庄段属沧浪铺阶。本次测年得到了鲁西地区第1个下寒武统的同位素年龄值,这对确定该地区早寒武世地震沉积事件发生的时间具有参考价值和意义,也为深入研究鲁西地区寒武纪地层提供了新资料。  相似文献   
993.
994.
Titanomagnetite–melt partitioning of Mg, Mn, Al, Ti, Sc, V, Co, Ni, Cu, Zn, Ga, Zr, Nb, Mo, Hf and Ta was investigated experimentally as a function of oxygen fugacity (fO2) and temperature (T) in an andesitic–dacitic bulk-chemical compositional range. In these bulk systems, at constant T, there are strong increases in the titanomagnetite–melt partitioning of the divalent cations (Mg2+, Mn2+, Co2+, Ni2+, Zn2+) and Cu2+/Cu+ with increasing fO2 between 0.2 and 3.7 log units above the fayalite–magnetite–quartz buffer. This is attributed to a coupling between magnetite crystallisation and melt composition. Although melt structure has been invoked to explain the patterns of mineral–melt partitioning of divalent cations, a more rigorous justification of magnetite–melt partitioning can be derived from thermodynamic principles, which accounts for much of the supposed influence ascribed to melt structure. The presence of magnetite-rich spinel in equilibrium with melt over a range of fO2 implies a reciprocal relationship between a(Fe2+O) and a(Fe3+O1.5) in the melt. We show that this relationship accounts for the observed dependence of titanomagnetite–melt partitioning of divalent cations with fO2 in magnetite-rich spinel. As a result of this, titanomagnetite–melt partitioning of divalent cations is indirectly sensitive to changes in fO2 in silicic, but less so in mafic bulk systems.  相似文献   
995.
Of the natural hazards in Turkey, landslides are the second most devastating in terms of socio-economic losses, with the majority of landslides occurring in the Eastern Black Sea Region. The aim of this study is to use a statistical approach to carry out a landslide susceptibility assessment in one area at great risk from landslides: the Sera River Basin located in the Eastern Black Sea Region. This paper applies a multivariate statistical approach in the form of a logistics regression model to explore the probability distribution of future landslides in the region. The model attempts to find the best fitting function to describe the relationship between the dependent variable, here the presence or absence of landslides in a region and a set of independent parameters contributing to the occurrence of landslides. The dependent variable (0 for the absence of landslides and 1 for the presence of landslides) was generated using landslide data retrieved from an existing database and expert opinion. The database has information on a few landslides in the region, but is not extensive or complete, and thus unlike those normally used for research. Slope, angle, relief, the natural drainage network (including distance to rivers and the watershed index) and lithology were used as independent parameters in this study. The effect of each parameter was assessed using the corresponding coefficient in the logistic regression function. The results showed that the natural drainage network plays a significant role in determining landslide occurrence and distribution. Landslide susceptibility was evaluated using a predicted map of probability. Zones with high and medium susceptibility to landslides make up 38.8 % of the study area and are located mostly south of the Sera River Basin and along streams.  相似文献   
996.
Natural Hazards - We perform numerical simulations to assess how coastal tsunami hazard from submarine mass failures (SMFs) is affected by slide kinematics and rheology. Two types of two-layer SMF...  相似文献   
997.
Three hypogenic caves within the Naica mine of Mexico (Cueva de los CristalesCLC, Ojo de la ReinaOR, and Cueva de las VelasCLV) host spectacular gypsum crystals up to 11 m in length. These caves are close to another shallow cave of the area (Cueva de las EspadasCLE), with which they cover a 160 m-deep vertical section of the local drainage basin. Similar to other hypogenic caves, all these caves lack a direct connection with the land surface and should be unrelated with climate.A record of multi-technique fluid inclusion data and pollen spectra from cave and mine gypsum indicates surprisingly that climatic changes occurring at Naica could have controlled fluid composition in these caves, and hence crystal growth. Microthermometry and LA-ICP-Mass Spectrometry of fluid inclusions indicate that the shallow, chemically peculiar, saline fluid (up to 7.7 eq. wt.%NaCl) of CLE could have formed from evaporation, during a dry and hot climatic period. The fluid of the deep caves was instead of low salinity (~ 3.5 eq. wt.% NaCl) and chemically homogeneous, and was poorly affected by evaporation. We propose that mixing of these two fluids, generated at different depths of the Naica drainage basin, determined the stable supersaturation conditions for the gigantic gypsum crystals to grow. Fluid mixing was controlled by the hydraulic communication between CLE and the other deep caves, and must have taken place during cycles of warm-dry and fresh-wet climatic periods, which are known to have occurred in the region. Pollen grains from a 35 ka-old gypsum crystal of CLC corresponds to a fairly homogenous catchment basin made of a mixed broadleaf wet forest, which suggests precipitation during a fresh-wet climatic period and confirms our interpretation of the fluid inclusion data.The unusual combination of geological and geochemical factors of Naica suggests that other hypogenic caves found elsewhere may not host similar crystals. However, this work shows that fluid inclusions and pollen spectra represent a useful tool for cave studies in general, and if used in future studies might be essential to unravel the mechanisms of hypogenic deposition.  相似文献   
998.
999.
Airborne light detection and ranging (LiDAR) bathymetry appears to be a useful technology for bed topography mapping of non‐navigable areas, offering high data density and a high acquisition rate. However, few studies have focused on continental waters, in particular, on very shallow waters (<2 m) where it is difficult to extract the surface and bottom positions that are typically mixed in the green LiDAR signal. This paper proposes two new processing methods for depth extraction based on the use of different LiDAR signals [green, near‐infrared (NIR), Raman] of the SHOALS‐1000T sensor. They have been tested on a very shallow coastal area (Golfe du Morbihan, France) as an analogy to very shallow rivers. The first method is based on a combination of mathematical and heuristic methods using the green and the NIR LiDAR signals to cross validate the information delivered by each signal. The second method extracts water depths from the Raman signal using statistical methods such as principal components analysis (PCA) and classification and regression tree (CART) analysis. The obtained results are then compared to the reference depths, and the performances of the different methods, as well as their advantages/disadvantages are evaluated. The green/NIR method supplies 42% more points compared to the operator process, with an equivalent mean error (?4·2 cm verusu ?4·5 cm) and a smaller standard deviation (25·3 cm verusu 33·5 cm). The Raman processing method provides very scattered results (standard deviation of 40·3 cm) with the lowest mean error (?3·1 cm) and 40% more points. The minimum detectable depth is also improved by the two presented methods, being around 1 m for the green/NIR approach and 0·5 m for the statistical approach, compared to 1·5 m for the data processed by the operator. Despite its ability to measure other parameters like water temperature, the Raman method needed a large amount of reference data to provide reliable depth measurements, as opposed to the green/NIR method. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   
1000.
We discuss a geographic information system (GIS)‐based methodology for rock slope instability assessment based on geometrical relationships between topographic slopes and structural discontinuities in rocks. The methodology involves (a) regionalization of point observations of orientations (azimuth and dip) of structural discontinuities in rocks in order to generate a digital structural model (DStM), (b) testing the kinematical possibility of specific modes of rock slope failures by integrating DStMs and digital elevation model (DEM)‐derived slope and aspect data and (c) computation of stability scenarios with respect to identified rock slope failure modes. We tested the methodology in an area of 90 km2 in Darjeeling Himalaya (India) and in a small portion (9 km2) within this area with higher density of field structural orientation data. The results of the study show better classification of rock slope instability in the smaller area with respect to known occurrences of deep‐seated rockslides than with respect to shallow translational rockslides, implying that structural control is more important for deep‐seated rockslides than for shallow translational rockslides. Results of scenario‐based analysis show that, in rock slopes classified to be unstable, stress‐induced rock slope instability tends to increase with increasing level of water saturation. The study demonstrates the usefulness of spatially distributed data of orientations of structural discontinuities in rocks for medium‐ to small‐scale classification of rock slope instability in mountainous terrains. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   
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