A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping
多发区域滑坡事件的预测细胞模型：对滑坡易发性制图的意义
Geomorphology, Volume 295, 15 October 2017, Pages 480-488
M.J. Crozier
Abstract:Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock.
The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity for many events.
The overall ability to predict the impact of these events and consequently the development of effective mitigation measures is limited by the ability to predict the travel path, storm centre, and intensity range within the cell structure of extreme weather systems.
Early warning system for shallow landslides using rainfall threshold and slope stability analysis
基于降雨阈值与边坡稳定性分析的浅层滑坡早期预警系统
Geoscience Frontiers, In press, corrected proof, Available online 31 October 2017
Shruti Naidu, K.S. Sajinkumar, Thomas Oommen, V.J. Anuja, C. Muraleedharan
Abstract:A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent (x-variable) vs. daily rainfall (y-variable) provided the best fit to the data with a threshold equation of y = 80.7–0.1981x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is ∼20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model (PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety (FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.
Landslide characteristics and spatial distribution in the Rwenzori Mountains, Uganda
乌干达Rwenzori山区滑坡特征及空间分布
Journal of African Earth Sciences, Volume 134, October 2017, Pages 917-930
Liesbet Jacobs, Olivier Dewitte, Jean Poesen, Jan Maes, Matthieu Kervyn
Abstract:In many landslide-prone regions, data on landslide characteristics remain poor or inexistent. This is also the case for the Rwenzori Mountains, located on the border of Uganda and the DR Congo. There, landslides frequently occur and cause fatalities and substantial damage to private property and infrastructure. In this paper, we present the results of a field inventory performed in three representative study areas covering 114 km2. A total of 371 landslides were mapped and analyzed for their geomorphological characteristics and their spatial distribution. The average landslide areas varied from less than 0.3 ha in the gneiss-dominated highlands to >1 ha in the rift alluvium of the lowlands. Large landslides (>1.5 ha) are well represented while smaller landslides (<1.5 ha) are underrepresented. The degrees of completeness of the field inventories are comparable to those of similar historical landslide inventories. The diversity of potential mass movements in the Rwenzori is large and depends on the dominant lithological and topographic conditions. A dominance of shallow translational soil slides in gneiss and of deep rotational soil slides in the rift alluvium is observed. Slope angle is the main controlling topographic factor for landslides with the highest landslide concentrations for slope angles above 25–30° in the highlands and 10–15° in the lowlands. The undercutting of slopes by rivers and excavations for construction are important preparatory factors. Rainfall-triggered landslides are the most common in the area, however in the zones of influence of the last two major earthquakes (1966: Mw = 6.6 and 1994: Mw = 6.2), 12 co-seismic landslides were also observed.
The role of observations in the inverse analysis of landslide propagation
观测在滑坡传播反演分析中的作用
Computers and Geotechnics, Volume 92, December 2017, Pages 11-21
Michele Calvello, Sabatino Cuomo, Pooyan Ghasemi
Abstract:Model calibration is usually based on trial-and-error procedures that, in turn, rely on expert judgment or previously acquired experiences for similar phenomena. Efficient and reliable procedures for model calibration of the propagation stage of landslides are still needed. This paper addresses this issue by proposing an inverse analysis procedure and applying it to the case history of a short run-out landslide triggered by a rising perched water table after a heavy rainfall. It focuses on the key role played by the field observations used to set up the inverse analysis, and evaluating the reliability of the numerical simulations. It also investigates the effect of different types of optimization parameters on the inverse analysis results, referring to a mixed-phase model or to a two-phase model for the propagating soil. Several sets of observations are used; all of them refer to the soil deposit thickness at the end of propagation, but differ in both location and number of the adopted values. The numerical analysis of the case history is performed through the academic “GeoFlow_SPH” model, and model calibration by inverse analysis is conducted using the “UCODE” software. The results obtained are discussed with the aim to provide practical criteria to identify the minimum amount of information required for a satisfactory model calibration.
Improved landslide susceptibility prediction for sustainable forest management in an altered climate
气候变化背景下持续森林管理的改进滑坡易发性预测
Engineering Geology, Volume 230, 29 November 2017, Pages 104-117
M.G. Barik, J.C. Adam, M.E. Barber, B. Muhunthan
Abstract:Landslide occurrences, which result in significant casualties, economic losses, and ecological impacts, have been increasing worldwide over the last few decades. Thus, it is crucial for future landslide susceptibility to be considered when making long-term plans for timber extraction. Two factors that are known to reduce soil strength and increase landslide susceptibility are clear cutting (due to reduced root contributions to soil strength) and degree of soil saturation. Therefore, as projected climate change is expected to result in storms with higher intensity precipitation in many mountainous regions, these areas are likely to become more susceptible to landslide activity resulting in potentially severe consequences to aquatic habitat due to increased sediment loads. There is a need to investigate potential management plans that simultaneously protect the economic viability of the forest industry and the ecosystem services of the forest. The primary objectives of this study are to explore the impact of timber harvesting on landslide susceptibility under climate change and to create high resolution (10 m) landslide susceptibility maps to inform land management decisions in an altered climate. The Distributed Hydrology Soil Vegetation Model (DHSVM), a physically-based hydrology model that has been improved to incorporate mass wasting and erosion processes, was used to assess the sensitivity of landslide susceptibility to timber extraction. To investigate the impacts of climate change on landslide susceptibility we applied downscaled output from two General Circulation Models (GCMs) with two greenhouse gas (GHG) emission scenarios, A1B and B1, for the year 2045. The areal extent classified with a high landslide susceptibility increased on average by 7.1% and 10.7% for the B1 and A1B GHG emissions scenarios, respectively. The landslide susceptibility maps produced in this study can enable forest managers to plan for climate change by identifying areas that are more prone to landslide activity under altered climate conditions. The methodologies developed herein can be used by forest managers around the world to better assess landslide potential.
Landslide detection using probability regression, a case study of Wenchuan, northwest of Chengdu
基于概率回归的滑坡探测---四川汶川实例研究
Applied Geography, Volume 89, December 2017, Pages 32-40
Fang Chen, Bo Yu, Chong Xu, Bin Li
Abstract:Landslides have become one of the dominant disasters all around the world. Reliable and efficient landslide mapping is playing a significant role in landslide studies. However, to the best of our knowledge, there is little research on detecting multiple landslides simultaneously from images to stimulate practical cases. In this work, we propose a regression model to detect landslides and investigate its applicability in practical cases. It synthesizes contextual, spectral and geometric features. Among the test images, F-measure of landslide detection has a range between 0.771 and 0.998, validating its robustness and high efficiency.
Distribution and failure modes of the landslides in Heitai terrace, China
中国黑台阶地滑坡分布及破坏模式
Engineering Geology, In press, corrected proof, Available online 20 September 2017
Dalei Peng, Qiang Xu, Fangzhou Liu, Yusen He, Xianlin Zhang
Abstract:Agricultural irrigation has increased the groundwater level in the Heitai terrace (part of the Heifangtai terrace) by 20 m over nearly five decades, which causes 3–5 landslides each year at the edge of the terrace. The Heitai terrace is of great interest in the study of loess-related landslides; but there is no unanimous agreement on the types of either the landslides in this study site or the loess-related slope failures in general. On the basis of aerial images (res. 5 cm), Digital Elevation Model (res. 10 cm), and field investigations, we analyzed the distribution and failure mode of the landslides in Heitai. The geological structure and characteristics of 69 landslides (vol. 5 × 103–6 × 106 m3) are studied. The preliminary results of groundwater recharge in the terrace and formation of the apparent spring lines on the slope surface are analyzed to better understand the failure modes. We divided the landslides in Heitai into two groups based on the location of the failure surface, i.e. loess landslide and loess-bedrock landslide, of which the development is governed by the angle between the principle direction of slope deformation and the dip of bedrock bedding. We further analyzed the failure mode of each type observed in Heitai, defined as follows: loess-bedrock planar slide, loess-bedrock irregular slide, loess flowslide, loess slide, and loess flow. The proposed types of loess-related landslide are to be incorporated in the Varnes classification (Varnes, 1978) in consideration of the engineering properties of loess, and to provide backward compatibility for Heitai and potentially other regions in the Loess Plateau of China.
