斜向坡变形破坏机制的数值模拟研究

本文讨论了斜向坡的旋转式变形和破坏机制，用有限元法计算了此种斜坡中的剩余下滑力的分布方式，并以此来解释在滑动过程中发生一定旋转的原因；论文还运用离散元法，模拟了此种滑坡的滑动过程。     

某滑坡区滑带土工程地质特性研究

本文论述了某滑坡滑带土的工程地质特性及其滑坡稳定性的影响，为滑坡的合理整治提供了依据。     

Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey

In the last decades, landslide hazard assessment has attracted many researchers' attention. A number of parameters are suggested to be responsible to quantitatively explain the mechanism of landslides; many of these parameters are very important and factual. However, some data types and models are site-specific and could not be applied to different locations. Furthermore, the data stored in continuous parameter maps are divided into a number of classes arbitrarily, depending on the vision of the expert. Basically, this division controls the result of bivariate analysis. Besides, the responsible portion of the parameter map controlling the mechanism is also weighted arbitrarily. Based on these two facts, the class boundaries put a prejudice on the produced susceptibility/hazard maps, which result in dependence on the knowledge of the user rather than being dependent on the data and the fact itself. The aim of this study is to refine the previously defined methods in a more data-dependent trend. To achieve this goal, two new concepts: seed cells and percentile maps are introduced. Seed cells are the zones that are considered to represent the best undisturbed morphological decision rules (conditions before landslide occurs) and would be achieved by adding a buffer zone to the crown and flank areas of the landslide. To quantitatively classify the input parameter maps, the data distributions of seed cells in the parameter maps are divided into a number of classes on the basis of their distribution's percentile break-points upon which the parameter maps are directly dependent on the seed cell distributions, hence to the data itself.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

Local Modeling模式及其在月径流预测中的应用

Local Modeling方法是一种动力系统预测方法，将其应用于河西内陆区黑河干流出山口莺落峡水文站月平均流量的中长期预测预报，取得了较为理想的成果。预测试验的结果表明，该预测模型有较高计算精度，尤其适用于非主汛期各月的月平均流量的预测；对于主汛期6～9月的月平均流量的预测，在考虑前期来水与预见期内降水的影响后，亦可获到较为理想的预测结果。可以认为，该方法的预报精度达到了水文情报预报规范的要求，Local Modeling方法的应用，将为西北干旱地区河川径流的中长期预报提供了一个新的途径。     

Landslide hazard in the Nebrodi Mountains (Northeastern Sicily)

The eastern sector of the Nebrodi Mountains (NE Sicily), a part of the Apenninic-Maghrebian orogenic chain, is characterized by an high landslide hazard. The village of S. Domenica Vittoria, which lies in the area, has been particularly affected by various landslide phenomena, with resulting damage to buildings and infrastructure.The rocks outcropping in the area belong to the Cretaceous Monte Soro Flysch; they consist of an alternation of argillaceous and calcareous beds at the base and argillaceous and quartzarenitic beds at the top. The lithotechnical characteristics of the formation and the steepness of the slopes in the area lead to an elevated instability, as testified by the widespread occurrence of sub-vertical arcuate cliffs (landslide scarps) and sub-horizontal areas (landslide terraces), typical of a landslide-controlled morphology. From a kinematics point of view, the observed phenomena can be referred to multiple rotational slides, flows, and complex landslides, often with a retrogressive development and enlargement. Triggering causes lie principally in the intense rainfalls that determine the decay of the geomechanical properties of the terrain and supply discontinuos groundwater circulation that is evident in seasonal springs. Human activity, such as the construction of roads and buildings on steep slopes and dispersal of water from supply systems and sewers has a significant impact as well.Due to the instability of the area, expansion of the village, which is already limited by the morphological conditions, is made difficult by the high hazard level, especially in the areas at higher elevations, where the principal landslide scarps are located, and even more on the rims of the scarps. Considering the high hazard level, S. Domenica Vittoria has been inserted by the National Geological Service among the sites in Sicily to be monitored by means of a GPS network. The survey carried out along the entire slope hosting the village has furnished the base for geological and geomorphological knowledge needed for the planning of the network, to identify the areas at landslide risk, where parts of the village lie, including the areas of expansion of the village, the main roads, and a portion of the Favoscuro river bed.     

Interpretation of radon anomalies in seismotectonic and tectonic-gravitational settings: the south-eastern Crati graben (Northern Calabria, Italy)

The study area is located in the south-eastern part of the Crati valley (Northern Calabria, Italy), which is a graben bordered by N–S trending normal faults and crossed by NW–SE normal left-lateral faults. Numerous severe crustal earthquakes have affected the area in historical time. Present-day seismic activity is mainly related to the N–S faults located along the eastern border of the graben. In this area, much seismically induced deep-seated deformation has also been recognised.In the present paper, radon concentrations in soil gas have been measured and compared with (a) lithology, (b) Quaternary faults, (c) historical and instrumental seismicity, and (d) deep-seated deformation.The results highlight the following:

(a) There is no evidence of a strong correlation between lithology and the radon anomalies.

(b) A clear correlation between the N–S geometry of radon anomalies and the orientation of main fault systems has been recognised, except in the southernmost part of the area, where the radon concentrations are strongly affected by the superposition of the N–S and the NW–SE fault systems.

(c) Epicentral zones of instrumental and historical earthquakes correspond to the highest values of radon concentrations, probably indicating recent activated fault segments. In particular, high radon values occur in the zones struck by earthquakes in 1835, 1854, and 1870.

(d) Deep-seated gravitational deformation generally coincides with zones characterised by low radon concentrations.

In the studied area, the anisotropic distribution of radon concentrations is congruent with the presence of neotectonic features and deep-seated gravitational phenomena. The method used in this study could profitably contribute towards either seismic risk or deep-seated gravitational deformation analyses.     

A size classification for debris flows

A 10-fold classification for debris flow size is proposed based on total volume, peak discharge and area inundated by debris. Size classes can be used for regional overview studies where detailed site investigations are either unnecessary, too costly or where the highest hazard and risk creeks need to be identified for further study. They are also useful to compare the regional impact between affected areas and the effects of rainstorms, and they allow lay-people to obtain an understanding of debris flow magnitude and consequences. Finally, different size classes allow the estimation of travel times to points of interest based on empirically derived equations. It is proposed that agencies concerned with debris flows should establish a documentation of debris flow size according to this classification, which serves as a data base for hazard and risk planning.     

Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides

This study evaluates the susceptibility of landslides in the Lai Chau province of Vietnam using Geographic Information System (GIS) and remote sensing data to focus on the relationship between tectonic fractures and landslides. Landslide locations were identified from aerial photographs and field surveys. Topographic, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image-processing techniques. A scheme of the tectonic fracturing of crust in the Lai Chau region was established. Lai Chau was identified as a region with many crustal fractures, where the grade of tectonic fracture is closely related to landslide occurrence. The influencing factors of landslide occurrence were: distance from a tectonic fracture, slope, aspect, curvature, soil, and vegetative land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability–frequency ratio model. The results of the analysis were verified using landslide location data and showed 83.47% prediction accuracy. That emphasized a strong relationship between the susceptibility map and the existing landslide location data. The results of this study can form a basis stable development and land use planning for the region.     

The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide-susceptibility map of its near vicinity

Landslides are common natural hazards in the seismically active North Anatolian Fault Zone of Turkey. Although seismic activity, heavy rainfall, channel incisions, and anthropogenic effects are commonly the main triggers of landslides, on March 17, 2005, a catastrophic large landslide in Sivas, northeastern of Turkey, the Kuzulu landslide, was triggered by snowmelt without any other precursor. The initial failure of the Kuzulu landslide was rotational. Following the rotational failure, the earth material in the zone of accumulation exhibited an extremely rapid flow caused by steep gradient and high water content. The Agnus Creek valley, where Kuzulu village is located, was filled by the earth-flow material and a landslide dam was formed on the upper part of Agnus Creek. The distance from the toe of the rotational failure down to the toe of the earth flow measured more than 1800 m, with about 12.5 million m³ of displaced earth material. The velocity of the Kuzulu landslide was extremely fast, approximately 6 m/s. The main purposes of this study are to describe the mechanism and the factors conditioning the Kuzulu landslide, to present its environmental impacts, and to produce landslide-susceptibility maps of the Kuzulu landslide area and its near vicinity. For this purpose, a detailed landslide inventory map was prepared and geology, slope, aspect, elevation, topographic-wetness index and stream-power index were considered as conditioning factors. During the susceptibility analyses, the conditional probability approach was used and a landslide-susceptibility map was produced. The landslide-susceptibility map will help decision makers in site selection and the site-planning process. The map may also be accepted as a basis for landslide risk-management studies to be applied in the study area.