储层条件下波速的变化规律及其影响因素的实验研究

为了在模拟储层的温度压力条件下,更精确地测定大庆砂岩样品在干燥、饱水和饱油等不同情况下的纵、横波速及其变化规律,首先对由于岩石的非完全弹性而引起的隐伏效应、滞后效应等因素对波速测量的影响进行了分析,提出了相应的改进方法以提高测试的精度．实验结果表明,波速随压力的增大以对数形式增加,随温度的升高呈线性减小．通过实测数据的分析和计算,提出了压力影响系数和温度影响系数,且认为它们与岩性参数有关．     

影响辽东半岛热带气旋运动、强度和影响的特征

利用1971～2000年常规资料和热带气旋年鉴资料,对30年来影响辽东半岛及黄渤海域热带气旋运动、强度和影响的一般特征进行分析。结果表明：热带气旋活动有着明显的年际变化;热带气旋源地不同,对研究区域的影响程度不同;热带气旋在自南向北的移动过程中,强度和移动速度变化显著;热带气旋移动路径和灾害天气分布也存在较大差异。     

因子分析法在密鲴生殖力研究中的应用

应用因子分析法研究密鲴繁殖力与诸因素的关系。六个变量是体长、体重、成熟系数、绝对怀卵量和相对怀卵量。29个样本、经正交变换得到3个因子:绝对繁殖因子、相对繁殖因子和成熟因子。     

Characterization of groundwater contamination using factor analysis

 The effluent contamination of groundwater at two industrial sites at Visakhapatnam, India, was studied using factor analysis. Thirty groundwater samples near a zinc smelter plant and 19 from the polymers plant were analyzed for specific conductance, chloride, bicarbonate, sulfate, calcium, magnesium, sodium, and potassium. The data were subjected to R-mode factor analysis and the factor scores transferred to areal maps. While magnesium and sulfate are the dominant contaminants at the zinc site, sodium, chloride, and bicarbonate from the effluent are affecting groundwater in the polymers area. Contour maps for each factor suggest the areal extension of the contaminants. Received: 1 March 1995 · Accepted: 18 September 1995     

Evaluation of the processes affecting vertical water chemistry in an alluvial aquifer of Mankyeong Watershed, Korea, using multivariate statistical analyses

Vertical variations of redox chemistry and groundwater quality were investigated in an alluvial aquifer beneath an agricultural area, in which deep groundwaters are free of NO₃, Fe, and Mn problems that are frequently encountered during the development of alluvial groundwaters. This study was performed to identify and evaluate vertical chemical processes attenuating these chemical species in the study area. For this study, the processes affecting groundwater chemistry were identified by factor analysis (FA) and the groundwater samples collected from six multilevel samplers were hierarchically classified into three different redox zones by cluster analysis (CA) based on the similarity of geochemical features. FA results indicated three major factors affecting the overall water chemistry: agricultural activities (factor 1), redox reactions (factor 2), and remnant seawater (factor 3). The groundwater quality in the study area was revealed to be controlled by a series of different redox reactions, resulting in different redox zones as a function of depth. It was also revealed that the low Fe and Mn levels in the groundwater of the deeper part are associated with sulfate reduction, which led to precipitation of Fe as iron sulfide and adsorption of Mn on it.     

Spatially and temporally distributed modeling of landslide susceptibility

Mapping of landslide susceptibility in forested watersheds is important for management decisions. In forested watersheds, especially in mountainous areas, the spatial distribution of relevant parameters for landslide prediction is often unavailable. This paper presents a GIS-based modeling approach that includes representation of the uncertainty and variability inherent in parameters. In this approach, grid-based tools are used to integrate the Soil Moisture Routing (SMR) model and infinite slope model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds by combining climate data, a digital elevation model, soil, and land use data. The infinite slope model is used for slope stability analysis and determining the factor of safety for a slope. Monte Carlo simulation is used to incorporate the variability of input parameters and account for uncertainties associated with the evaluation of landslide susceptibility. This integrated approach of dynamic slope stability analysis was applied to the 72-km² Pete King watershed located in the Clearwater National Forest in north-central Idaho, USA, where landslides have occurred. A 30-year simulation was performed beginning with the existing vegetation covers that represented the watershed during the landslide year. Comparison of the GIS-based approach with existing models (FSmet and SHALSTAB) showed better precision of landslides based on the ratio of correctly identified landslides to susceptible areas. Analysis of landslide susceptibility showed that (1) the proportion of susceptible and non-susceptible cells changes spatially and temporally, (2) changed cells were a function of effective precipitation and soil storage amount, and (3) cell stability increased over time especially for clear-cut areas as root strength increased and vegetation transitioned to regenerated forest. Our modeling results showed that landslide susceptibility is strongly influenced by natural processes and human activities in space and time; while results from simulated outputs show the potential for decision-making in effective forest planning by using various management scenarios and controlling factors that influence landslide susceptibility. Such a process-based tool could be used to deal with real-dynamic systems to help decision-makers to answer complex landslide susceptibility questions.     

A Method Combining Numerical Analysis and Limit Equilibrium Theory to Determine Potential Slip Surfaces in Soil Slopes

This paper describes a precise method combining numerical analysis and limit equilibrium theory to determine potential slip surfaces in soil slopes. In this method, the direction of the critical slip surface at any point in a slope is determined using the Coulomb’s strength principle and the extremum principle based on the ratio of the shear strength to the shear stress at that point. The ratio, which is considered as an analysis index, can be computed once the stress field of the soil slope is obtained. Th...     

辽宁中部城市群夏季大气能见度的观测研究

利用2009年6—8月辽宁中部4个城市的观测资料,分析了辽宁中部城市群夏季的季、月、日能见度分布,并探讨了能见度的日变化特征及其影响因子。结果表明:辽宁中部城市群内各城市夏季大气能见度月际变化趋势基本一致,天气系统和大气环境比较均一,具有明显的区域性特征;各城市大气能见度日变化呈明显的单周期谷、峰形分布,06时前后能见度最差,15—16时最好;大气细粒子、水汽和风速都对城市群能见度有一定的影响,其中,大气细粒子是主要影响因子;城市群夏季的低能见度时次,仅有一小部分是由轻雾引发的,而大部分则是由霾天气造成的。     

Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (>  80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more robustly.