The largest karst cave discovered in a tunnel during motorway construction in Slovenia’s Classical Karst (Kras)

Karst researchers of the Karst Research Institute ZRC SAZU are regularly consulted during the planning of Slovenia’s motorways and invited to observe and monitor construction in the karst areas. More than 350 caves have been discovered in the course of building 60 km of new motorways over the past decade. Access to the most important caves is preserved by concrete tubes closed with metal covers at the roadside. The largest cave system in a tunnel, named LC-S647, is almost entirely preserved. The protection of this cave will serve as a good example for the preservation of natural heritage in the future. Construction work for the motorway uncovered a high degree of karstification. In particular, the discovery of this cave in the Kastelec tunnel LC-S647 showed the existence of a major cave system in the geological and speleological past. A number of unconnected passages have also been found. Caves discovered during highway construction have brought new knowledge about the cavernosity and the geological history of this part of the karst.     

Landslide susceptibility mapping for a landslide-prone area (Findikli,NE of Turkey) by likelihood-frequency ratio and weighted linear combination models

Landslides are very common natural problems in the Black Sea Region of Turkey due to the steep topography, improper use of land cover and adverse climatic conditions for landslides. In the western part of region, many studies have been carried out especially in the last decade for landslide susceptibility mapping using different evaluation methods such as deterministic approach, landslide distribution, qualitative, statistical and distribution-free analyses. The purpose of this study is to produce landslide susceptibility maps of a landslide-prone area (Findikli district, Rize) located at the eastern part of the Black Sea Region of Turkey by likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model and to compare the results obtained. For this purpose, landslide inventory map of the area were prepared for the years of 1983 and 1995 by detailed field surveys and aerial-photography studies. Slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. The differences between the susceptibility maps derived by the LRM and the WLC models are relatively minor when broad-based classifications are taken into account. However, the WLC map showed more details but the other map produced by LRM model produced weak results. The reason for this result is considered to be the fact that the majority of pixels in the LRM map have high values than the WLC-derived susceptibility map. In order to validate the two susceptibility maps, both of them were compared with the landslide inventory map. Although the landslides do not exist in the very high susceptibility class of the both maps, 79% of the landslides fall into the high and very high susceptibility zones of the WLC map while this is 49% for the LRM map. This shows that the WLC model exhibited higher performance than the LRM model.     

Greening as strategic development in industrial change - Why companies participate in eco-networks

Networking between companies and other regional key actors has grown into a widespread instrument for economic development since the 1990s. Participatory networks have formed the concept for many activities of Local Agenda 21. Simultaneously, economic geography has focused on network theories to explain innovation in and the economic success of regions.This article focuses on the reasons why individual actors participate in environmentally oriented information networks. The questions approached are: Does the concept of learning within networks influence a firm’s development? How do the participants interact with each other? What effects do the networks have on their environment (arenas)?The changing arenas of a firm are analysed with regard to environmental concerns. These changes need to be anticipated for reliable strategies. To gain information and knowledge about current behaviour and activities, the functions of networks as learning platforms are discussed. Drawing upon arguments from different network theories, the motivations of participating in a network are threefold: actor and firm oriented, network internal (inter-firm), and network external. From these, a generic target cube of network motivations and actions is set up.The concept is reviewed by examining 12 ‘regional environmental information-oriented corporation networks’ (RUN) in the Greater Munich Area. The empirical material reveals that this type of network does not provide a guarantee for significant improvements in a firm’s environmental behaviour. However, participants learn about best practices while pursuing explicit or implicit aims as to influence their arenas.     

Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

广州地区深基坑支护形式研究

介绍了广州地区基坑支护近年来的主要类型及其适用范围,并在分析选型各影响因素的基础上,总结出设计选型的要点。     

陕西白河县月儿潭绿松石与次生磷钙铝矾研究

对陕西省白河县月儿潭风化严重的绿松石样品进行了岩石薄片观察、化学成分测试、X射线粉晶衍射和红外吸收光谱分析等研究.结果表明,绿松石风化分解由天蓝色退色成黄绿色,最后变成白色,结构也由致密细腻变得松散多孔,主要原因是发生了硫酸根对磷酸根的交代作用,最终的交代产物主要是磷钙铝矾.     

GPS变形监测平差计算及不确定度分析

全球定位系统（GPS）是一种全天候、高精度的连续定位系统,它以速度快、方法灵活多样、操作简便等优势被广泛应用于工程测量和变形监测中。结合水厂铁矿GPS边坡变形监测实例,对GPS监测网的星历预报、基线向量平差计算、网平差计算、结果及残差不确定度进行了细致分析研究,以验证GPS技术在边坡变形监测中的可靠性和精度。     

Re-Os同位素对峨眉山大火成岩省成因制约的探讨

峨眉山大火成岩省（ELIP）主要由玄武岩、玄武质火山碎屑岩及少量的苦橄岩（包括越南的科马提岩）、长英质岩石以及层状岩体和岩墙组成,其物质来源直接关系到其成因是否与地幔柱活动有关。Re-Os同位素体系是地核、地幔和地壳物质的最佳示踪剂。前人对ELIP内的Re-Os同位素研究表明,低Ti玄武岩的Os含量为0．006×10^-9-0．40010^-9,^187Os／^188Os初始值为0．1371～1．403,并提出其与地幔柱活动有关;而高Ti玄武岩的Os含量为0．00410^-9～0．56010^-9,^187Os／^188Os初始值为0．1271～5．19,认为起源于大陆岩石圈地幔或地幔柱上升过程中受到大量岩石圈地幔“混染”（xu JF et al．,2007）;科马提岩的0s含量为1．2410^-9～7．0010^-9,^187Os／^188Os初始值为0．1251～0．1261,苦橄岩的Os含量为0．3210^-9～2．32910^-9,^187Os／^188Os初始值为0．1233～0．1266,指示苦橄岩和科马提岩均来自亏损地幔源区（Hanski et al．,2004;陈雷等,2007）。本文利用Os含量最低、^187Os／^188Os最高的高Ti玄武岩作为地壳端员,用铁质陨石、原始上地幔（PUM）和亏损地幔（DMM）作为地核和各种地幔端员,分别做二元混合计算,结果显示绝大多数玄武岩和所有苦橄岩及科马提岩均落在地壳和DMM混合曲线附近,并且邻区特提斯洋地幔岩与DMM具有相近的Os含量和^187Os／^188Os组成,据此推测峨眉山火成岩的形成与特提斯洋的活动有关,主要受控于地壳和亏损地幔的相互作用。     

基于AGA的SVM需水预测模型研究

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.