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11.
As a part of the ANR-Forclim experiment, particle mass fluxes and sedimentation processes were investigated on the slope of Aquitanian margin of the Bay of Biscay, between the canyons of Cap-Breton and Cap-Ferret. Interface sediments were collected along a depth transect from 145 to 2000 m; simultaneously a mooring line was deployed at the deepest station (WH, 2000 m) with two traps (800 and 1700 m) for a 16-month period (June 2006–November 2007). 210Pb activities of settling particles and of interface sediments were determined to study transport processes of particles. Sediment and mass accumulation rates, calculated from excess 210Pb profiles in the sediment column, show the expected decreasing trend with depth, as usually observed on margins. Mean particulate mass fluxes at 800 and 1700-m depth at site WH are, respectively, 27 and 70 g m?2 a?1.The 210Pb budget points out events of temporary high lateral input of particles. The comparison of mass and 210Pb fluxes between the water column and the seabed indicates that lateral transport plays an important role in particle accumulation on the Aquitanian margin. Regarding the objectives of the ANR-Forclim program, which aims to improve significantly the interpretation of fossil foraminifera signals, as a proxy for hydrological changes in the North Atlantic ocean, these results highlight advection processes must be considered when interpreting fluxes of foraminifers on the Aquitanian margin.  相似文献   
12.
本文利用野外调查结果、二维地震反射剖面、钻井和测井数据建立了一条横穿库车河地区的南北向构造剖面,将库车冲断褶皱带划分为北部褶皱带、克依构造带、秋立塔格背斜带和亚肯背斜带。作者在库车冲断褶皱带北部发现了渐新世—中新世角度不整合,在库车南部亚肯背斜和东秋立塔格背斜顶部发现了构造生长地层,通过确定构造生长地层的底界,利用库车河地区古近系(下第三系)—第四系磁极柱,判断亚肯背斜和东秋立塔格背斜构造生长地层的沉积时代为5.2±0.2 Ma。上述结果暗示库车冲断褶皱带北部山前带的变形始于渐新世,并且经历了中新世、上新世的构造改造,南部秋立塔格背斜带和亚肯背斜带形成较晚,可能是上新世开始变形,而且变形活动持续至今,由此看来库车冲断褶皱带的变形时代由北向南变新。作者估算东秋立塔格背斜上新世以来(5.2±0.2 Ma)的构造变形量为7.5 km,变形速率为1.5 mm/a。  相似文献   
13.
For those working in the field of landslide prevention, the estimation of hazard levels and the consequent production of thematic maps are principal objectives. They are achieved through careful analytical studies of the characteristics of landslide prone areas, thus, providing useful information regarding possible future phenomena. Such maps represent a fundamental step in the drawing up of adequate measures of landslide hazard mitigation. However, for a complete estimation of landslide hazard, meant as the degree of probability that a landslide occurs in a given area, within a given space of time, detailed and uniformly distributed data regarding their incidence and causes are required. This information, while obtainable through laborious historical research, is usually partial, incomplete and uneven, and hence, unsatisfactory for zoning on a regional scale. In order to carry this out effectively, the utilization of spatial estimation of the relative levels of landslide hazard in the various areas was considered opportune. These areas were classified according to their levels of proneness to landslide activity without taking recurrence periods into account. Various techniques were developed in order to obtain upheaval numerical estimates. The method used in this study, which was applied in the area of Potenza, is based on techniques derived from artificial intelligence (Artificial Neural Network—ANN). This method requires the definition of appropriate thematic layers, which parameterize the area under study. These are recognized by means of specific analyses in a functional relationship to the event itself. The parameters adopted are: slope gradient, slope aspect, topographical index, topographical shape, elevation, land use and lithology.  相似文献   
14.
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