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.     

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.     

The double solid reactant method: II. An application to the shallow groundwaters of the Porto Plain,Vulcano Island (Italy)

This paper presents an example of application of the double solid reactant method (DSRM) of Accornero and Marini (Environmental Geology, 2007a), an effective way for modeling the fate of several dissolved trace elements during water–rock interaction. The EQ3/6 software package was used for simulating the irreversible water–rock mass transfer accompanying the generation of the groundwaters of the Porto Plain shallow aquifer, starting from a degassed diluted crateric steam condensate. Reaction path modeling was performed in reaction progress mode and under closed-system conditions. The simulations assumed: (1) bulk dissolution (i.e., without any constraint on the kinetics of dissolution/precipitation reactions) of a single solid phase, a leucite-latitic glass, and (2) precipitation of amorphous silica, barite, alunite, jarosite, anhydrite, kaolinite, a solid mixture of smectites, fluorite, a solid mixture of hydroxides, illite-K, a solid mixture of saponites, a solid mixture of trigonal carbonates and a solid mixture of orthorhombic carbonates. Analytical concentrations of major chemical elements and several trace elements (Cr, Mn, Fe, Ni, Cu, Zn, As, Sr and Ba) in groundwaters were satisfactorily reproduced. In addition to these simulations, similar runs for a rhyolite, a latite and a trachyte permitted to calculate major oxide contents for the authigenic paragenesis which are comparable, to a first approximation, with the corresponding data measured for local altered rocks belonging to the silicic, advanced argillic and intermediate argillic alteration facies. The important role played by both the solid mixture of trigonal carbonates as sequestrator of Mn, Zn, Cu and Ni and the solid mixture of orthorhombic carbonates as scavenger of Sr and Ba is emphasized.

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.     

EPR investigation of the methyl radical,the hydrogen atom and carbon oxide radicals in Maxixe-type beryl

The EPR spectra of Maxixe-type beryl contain a large number of overlapping signals. The angular dependence of the 1:3:3:1 signal typical for the CH₃ radical shows that this radical is located at the center of the channel cavity with its symmetry axis parallel to the crystal c-axis and is rotating around this axis. Its EPR spectrum is axially symmetric with g _// = 2.00263, g _⊥ = 2.00249 and A_// = 2.288 mT, A_⊥ = 2.256 mT. These anisotropies have the opposite signs of those found for surface-adsorbed methyl radicals. Hydrogen atoms are located at position 2a at the center of the beryl cavity and the EPR parameters of the narrow doublet signal are A ₀ = 1,407 MHz and g = 2.00230. Another doublet signal, which is broader and has axial symmetry with g _// = 2.00265, g _⊥ = 2.00625 and A_// = 0.895 mT, A_⊥ = 0.885 mT, could come from a HCO₃ radical. One narrow and easily saturated signal with g _// = 2.00227 and g _⊥ = 2.00386 is interpreted to arise from a carbon monoxide radical in the beryl channel, oriented with its axis parallel to the crystal c-axis. Additional weak doublet lines, which have similar g values as the carbon monoxide radical, are created by nearby hydrogens. A powder spectrum with g _// = 2.0017 and g _⊥ = 2.0004 appears upon UV irradiation of the single crystal and is easily saturated. This spectrum is interpreted to arise from a carbon dioxide radical, which rotates around its symmetry axis.     

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.     

喜马拉雅山脉的地质地貌特征:来自SRTM数字高程模型和降水量数据的约束

利用GTOPO30和SRTM3数字高程(DEM)数据,提取了喜马拉雅山脉(造山带)的数字高程模型并对其进行了地质地貌的初步分析。从SRTM3数字高程数据提取出坡度数据,初步分析了喜马拉雅山脉坡度和高程的特征。数字高程和坡度图清楚地展现了喜马拉雅大型断裂带(构造边界)的空间分布特征。分析了中国气象局下属的西藏、青海、四川和云南4省区气象观测台站55年来的年平均降水量观测数据、喜马拉雅山脉南坡的年平均降水量数据、喜马拉雅DEM和裂变径迹数据,发现喜马拉雅山脉从东至西,年平均降水量逐渐减少,地形起伏逐渐变小,而高程渐次升高,与此同时剥蚀速率降低;从北至南,年平均降水量逐渐增加,地形起伏增大,高程快速降低,而剥蚀速率则急剧升高。这充分说明了喜马拉雅年平均降水量大的地区,地表剥蚀作用相对较强,年平均降水量小的地区,地表剥蚀作用则较弱,即:在喜马拉雅地区,长周期的地表剥蚀过程(可长达数个百万年时间尺度)和短周期(仅仅50年)的降水量观测是耦合的。     

Influence of Structural Non-Stationarity of Surface Roughness on Morphological Characterization and Mechanical Deformation of Rock Joints

Summary Structural non-stationarity of surface roughness affects accurate morphological characterization as well as mechanical behaviour of rock joints at the laboratory scale using samples with a size below the stationarity threshold. In this paper, the effect of structural non-stationarity of surface roughness is investigated by studying the scale dependence of surface roughness and mechanical behaviour of rock joints. The results show that the structural non-stationarity mainly affects the accurate characterization of the surface roughness of the fracture samples. It also controls the amount and location of the contact areas during shear tests, which in turn affects the mechanical properties and asperity degradation of the samples. It is concluded that for accurate determination of the morphological and mechanical properties of rock joints at laboratory and field scales, samples with size equal to or larger than the stationarity threshold are required. Author’s address: Nader Fardin, Rock Mechanics Group, Department of Mining Engineering, Faculty of Engineering, University of Tehran, P.O. Box: 11365/4563, Tehran, Iran     

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.