黔西北地区地下水赋存规律及开发利用方向

黔西北地区地处乌蒙山区岩溶发育强烈,地下水系统小型多样、条件复杂,地下勘查找水及开发利用难度大。本文通过对三种不同岩溶流域类型区地下水赋存规律及岩溶发育的综合研究,提出了不同类型系统中勘查找水和开发利用的方向建议,对该类区中地下水资源勘查找水和开发利用工作有一定的指导意义。     

煤矿采区三维地震资料解释中的切片技术及其应用

长期以来,煤矿采区三维地震勘探资料解释的工作流程与二维地震勘探基本相同,三维地震资料相对二维地震资料所具有的许多解释方面的优越性未能有效发挥出来,人机联作的过程相对简单.在三维地震勘探获取的三维数据体基础上,可做进一步的运算和分析,提取速度、振幅、频率、相位等相关信息,并利用等时切片、层拉平切片、断层切片、面块切片、方差体、相干体等各种技术,有效解释小构造、小褶曲及岩性方面的信息.     

VLAN技术在福建省地震信息网络中的应用

本文介绍了如何在福建省地震信息网络中应用VLAN技术规划网络并进行有效的管理,减少广播风暴的发生,提高网络安全性。     

泥石流运动衰减动力学初步研究

我国公路泥石流病害严重，泥石流淤埋公路构建筑物是一类常见的公路泥石流病害类型。泥石流衰减动力学是防治泥石流淤埋病害的重要关键技术，也是泥石流运动学、动力学研究的核心问题之一。本文作者运用泥沙运动力学及流体力学原理，初步建立了泥石流固相颗粒和液相浆体的能量衰减条件，把泥石流衰减模式概化为两类，即能量抑制衰减和能量自由衰减；通过泥石流沉积模型试验，得到了不同粘度泥石流体的沉积扇变化形态，随着泥石流体粘度的增大，沉积扇边缘变陡、扩展范围变小、纵轴线长度减小等结论与实际情况吻合；初步建立了泥石流能量衰减速率计算方法。研究成果为防治公路泥石流病害奠定了基础。     

福建浦城－三都澳和崇安－石城成矿带铅同位素特征及其地质意义

对浦城－三都澳和崇安－石城成矿带钢金锡多金属矿床及相关岩体的铅同位素特征作了系统研究和对比。结果表明，两成矿带不同成矿期以及同一成矿期不同区段间的铅同位素组成存在很大差异。并就此探讨了在成矿作用和岩浆作用动力学机制等地质问题中的意义。     

变质反应的代数识别方法

在回顾变质矿物共生组合和变质反应图解分析法的基础上，论述了录求变质矿物组合之间、同一组合内矿物之间的平衡变质反应的代数方法，即矩阵高斯变换，线性回归分析、矩阵奇值分解。     

Development of a 3D GIS and its application to karst areas

There is a growing interest in modeling and analyzing karst phenomena in three dimensions. This paper integrates geology, groundwater hydrology, geographic information system (GIS), database management system (DBMS), visualization and data mining to study karst features in Huaibei, China. The 3D geo-objects retrieved from the karst area are analyzed and mapped into different abstract levels. The spatial relationships among the objects are constructed by a dual-linker. The shapes of the 3D objects and the topological models with attributes are stored and maintained in the DBMS. Spatial analysis was then used to integrate the data in the DBMS and the 3D model to form a virtual reality (VR) to provide analytical functions such as distribution analysis, correlation query, and probability assessment. The research successfully implements 3D modeling and analyses in the karst area, and meanwhile provides an efficient tool for government policy-makers to set out restrictions on water resource development in the area.     

New Prediction Models for Mean Particle Size in Rock Blast Fragmentation

The paper refers the reader to a blast data base developed in a previous study. The data base consists of blast design parameters, explosive parameters, modulus of elasticity and in situ block size. A hierarchical cluster analysis was used to separate the blast data into two different groups of similarity based on the intact rock stiffness. The group memberships were confirmed by the discriminant analysis. A part of this blast data was used to train a single-hidden layer back propagation neural network model to predict mean particle size resulting from blast fragmentation for each of the obtained similarity groups. The mean particle size was considered to be a function of seven independent parameters. An extensive analysis was performed to estimate the optimum value for the number of units for the hidden layer for each of the obtained similarity groups. The blast data that were not used for training were used to validate the trained neural network models. For the same two similarity groups, multivariate regression models were also developed to predict mean particle size. Capability of the developed neural network models as well as multivariate regression models was determined by comparing predictions with measured mean particle size values and predictions based on one of the most applied fragmentation prediction models appearing in the blasting literature. Prediction capability of the trained neural network models as well as multivariate regression models was found to be strong and better than the existing most applied fragmentation prediction model. Diversity of the blasts data used is one of the most important aspects of the developed models.     

Spatial and temporal changes in flooding and the affecting factors in China

Spatial and temporal changes in flood events in China are becoming increasingly important due to the rapid climate warming that is occurring. This study was conducted to consider changes in flood events and the factors affecting such changes. To accomplish this, China was divided into natural and social-economic flood regions: north China, northwest China, northeast China, southwest China, central China, east China, south China, and Taiwan, Hong Kong and Macau. Spatial and temporal changes in flood patterns were rebuilt during 1980?C2009, and Fast Fourier Transform Filtering was then employed to stimulate the changes in floods during this period. The factors affecting flooding were then analyzed quantitatively. The results showed that, based on the time series for China as a whole, flooding was more serious during 1990?C1999 than 1980?C1989 and 2000?C2009. However, in different regions, the trends in flooding differed greatly. Based on spatial changes, the areas hardest hit by floods were northeast China in the 1980s, northeast China, central China and east China in the 1990s, and central China after 2000. In China, the main flood-affecting factors were meteorological, ecological, population, water conservation facilities, and policy factors. However, the main affecting factors differed by region. Overall, the complex spatial and temporal features of flood variations and various affecting factors demand proper national and regional governmental action in the face of the changing flood patterns in China. The results of the present study provide valuable information to flood policymakers and flood disaster researchers.     

Regional differences in the relationship between climatic factors,vegetation, land surface conditions,and dust weather in China’s Beijing-Tianjin Sand Source Region

This paper analyzes the regional differences in dust weather and its relationship with climatic factors and vegetation cover, using data at 27 observation stations in the Beijing-Tianjin Sand Source Region from 1960 to 2007. There was a decreasing trend in dust weather in the southeast, which was correlated with wind and temperature. In contrast, in the northwest, the number of dusty days did not decrease and was significantly correlated with precipitation and vegetation cover. These results suggest that, in addition to the climate and underlying conditions, physical geographic conditions also influenced the frequency of dust weather.