High resolution paleoenvironmental and chronological investigations of Norse landnám at Tasiusaq, Eastern Settlement, Greenland     

Kevin J. Edwards  J. Edward Schofield 《Quaternary Research》2008,69(1):1-15

High-resolution paleoenvironmental data from a peat profile with a small pollen source area are used to reconstruct the impacts of landnám on vegetation and soils at a Norse farm complex (∅2 at Tasiusaq) comprising two farms in the Eastern Settlement of Greenland. Analyses include the AMS ¹⁴C dating of plant macrofossil samples and the use of Bayesian radiocarbon calibration to construct improved age-depth models for Norse cultural horizons. The onset of a regional landnám may be indicated by the clearance of Betula pubescens woodland immediately prior to local settlement. The latter is dated to AD 950-1020 (2σ) and is characterised by possible burning of Betula glandulosa scrub to provide grassland pasture for domestic stock. Clearance and grazing resulted in accelerated levels of soil erosion at a westerly farm. This was followed by an easterly migration of settlement and agriculture. Site constraints prevent an assessment of the demise of the easterly farm, but pressures of overgrazing and land degradation may have been the major factors responsible for the abandonment of the earlier farm.  相似文献   

A New Probability of Detection Model for Updating Crack Distribution of Offshore Structures     

李典庆  张圣坤  唐文勇 《中国海洋工程》2003,17(3)

1 .IntroductionNondestructiveinspection (NDI)isveryimportantforensuringthereliabilityofoffshorestructuresintheirservicelives (Lauraetal.,1 996 ) .Itiswellknownthatdetectionofflawsinvolvesconsider ablestatisticaluncertainties.Asaresult,theprobabilityofdetection (POD)forallflawsofagivensizehasbeenusedintheliteraturetodefinethecapabilityofaparticularNDItechniqueinagivenen vironment.SincethedataofPODusuallyscatterlargely ,itisdifficulttodeterminewhichmodelfitstheavailabledatabest.Thismodelun…  相似文献   

An assessment of Greenland walrus populations     

Witting  Lars; Born  Erik W. 《ICES Journal of Marine Science》2005,62(2):266-284

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Variation in the catchability of yellow perch (Perca flavescens) in the fisheries of Lake Erie using a Bayesian error-in-variable approach     

Jiao  Yan; Reid  Kevin; Nudds  Tom 《ICES Journal of Marine Science》2006,63(9):1695-1704

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The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle-slip problem   总被引：4，自引：1，他引：3  

Maria Clara de Lacy  Mirko Reguzzoni  Fernando Sansò  Giovanna Venuti 《Journal of Geodesy》2008,82(9):527-542

This paper deals with the problem of detecting and correcting cycle-slips in Global Navigation Satellite System (GNSS) phase data by exploiting the Bayesian theory. The method is here applied to undifferenced observations, because repairing cycle-slips already at this stage could be a useful pre-processing tool, especially for a network of permanent GNSS stations. If a dual frequency receiver is available, the cycle-slips can be easily detected by combining two phase observations or phase and range observations from a single satellite to a single receiver. These combinations, expressed in a distance unit form, are completely free from the geometry and depend only on the ionospheric effect, on the electronic biases and on the initial integer ambiguities; since these terms are expected to be smooth in time, at least in a short period, a cycle-slip in one or both the two carriers can be modelled as a discontinuity in a polynomial regression. The proposed method consists in applying the Bayesian theory to compute the marginal posterior distribution of the discontinuity epoch and to detect it as a maximum a posteriori (MAP) in a very accurate way. Concerning the cycle-slip correction, a couple of simultaneous integer slips in the two carriers is chosen by maximazing the conditional posterior distribution of the discontinuity amplitude given the detected epoch. Numerical experiments on simulated and real data show that the discontinuities with an amplitude 2 or 3 times larger than the noise standard deviation are successfully identified. This means that the Bayesian approach is able to detect and correct cycle-slips using undifferenced GNSS observations even if the slip occurs by one cycle. A comparison with the scientific software BERNESE 5.0 confirms the good performance of the proposed method, especially when data sampled at high frequency (e.g. every 1 s or every 5 s) are available.  相似文献   

Bayesian estimation of seismic hazard for two sites in Switzerland     

Erik Rüttener  Juan José Egozcue  Dieter Mayer-Rosa  Stephan Mueller 《Natural Hazards》1996,14(2-3):165-178

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.  相似文献   

Bayesian Spatial Modelling of Gamma Ray Count Data     

Daniela Leonte  David J. Nott 《Mathematical Geology》2006,38(2):135-154

Gamma ray logging is a method routinely employed by geophysicists and environmental engineers in site geology evaluations. Modelling of gamma ray data from individual boreholes assists in the local identification of major lithological changes; modelling these data from a network of boreholes assists with lithological mapping and spatial stratigraphic correlation. In this paper we employ Bayesian spatial partition models to analyse gamma ray data spatially. In particular, a spatial partition is defined via a Voronoi tessellation and the mean intensity is assumed constant in each cell of the partition. The number of vertices generating the tessellation as well as the locations of vertices are assumed unknown, and uncertainty about these quantities is described via a hierarchical prior distribution. We describe the advantages of the spatial partition modelling approach in the context of smoothing gamma ray count data and describe an implementation that may be extended to the fitting of a more general model than a constant mean within each cell of the partition. As an illustration of the methodology we consider a data set collected from a network of eight boreholes, which is part of a geophysical study to assist in mapping the lithology of a site. Gamma ray logs are linked with geological information from cores and the spatial analysis of log data assists with predicting the lithology at unsampled locations.  相似文献   

Seismic Hazard for Selected Sites in Greece: A Bayesian Estimate of Seismic Peak Ground Acceleration   总被引：1，自引：1，他引：1  

A. A. Lyubushin  T. M. Tsapanos  V. F. Pisarenko  G. Ch. Koravos 《Natural Hazards》2002,25(1):83-98

A procedure for estimating maximum values of seismic peak ground accelerationat the examined site and quantiles of its probabilistic distribution in a future timeinterval of a given length is considered. The input information for the method areseismic catalog and regression relation between peak seismic acceleration at a givenpoint and magnitude and distance from the site to epicenter (seismic attenuation law).The method is based on Bayesian approach, which simply accounts for influenceof uncertainties of seismic acceleration values. The main assumptions for the method are Poissonian character of seismic events flow and distribution law of Gutenberg-Richter's type. The method is applied to seismic hazard estimation in six selected sitesin Greece.  相似文献   

Identification of soil degradation during earthquake excitations by Bayesian inference     

Jianye Ching  Steven D. Glaser 《地震工程与结构动力学》2003,32(6):845-869

A Bayesian inference approach is introduced to identify soil degradation behaviours at four downhole array sites. The approach of inference is based on a parametric time‐varying infinite impulse response filter model. The approach is shown to be adaptive to the changes of filter parameters and noise amplitudes. Four sites, including the Lotung (Taiwan), Chiba (Japan), Garner Valley (California), and Treasure Island (California) sites with downhole seismic arrays are analysed. Our results show two major types of soil degradation behaviour: the well‐known strain‐dependent softening, and reduction in stiffness that is not instantaneously recoverable. It is also found that both types of soil degradation are more pronounced in sandy soils than in clayey soils. The mechanism for the second type of soil degradation is not yet clear to the authors and suggested to be further studied. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

Smoothing and Change Point Detection for Gamma Ray Count Data   总被引：1，自引：0，他引：1  

Daniela Leonte  David J. Nott  William T. M. Dunsmuir 《Mathematical Geology》2003,35(2):175-194

Gamma ray detectors are used to measure the natural radioactivity of rocks. For a number of boreholes drilled at a site the gamma ray detector is lowered into each borehole and counts of gamma ray emissions at different depths are recorded as the instrument is gradually raised to ground level. The profile of gamma counts can be informative about the geology at each location. The raw count data are highly variable, and in this paper we describe the use of adaptive smoothing techniques and change point models in order to identify changes in the geology based on the gamma logs. We formulate all our models for the data in the framework of the class of generalized linear models, and describe computational methods for Bayesian inference and model selection for generalized linear models that improve on existing techniques. Application is made to gamma ray data from the Castelreagh Waste Management Centre which served as a hazardous waste disposal facility for the Sydney region between March 1974 and August 1998. Understanding the geological structure of this site is important for further modelling the transport of pollutants beneath the waste disposal area.  相似文献