Assessing landslide characteristics in a changing climate in northern Taiwan

气候变化环境下的台湾北部滑坡特征评估  

CATENA, Volume 175, April 2019, Pages 263-277 

Chi-Wen Chen, Yu-Shiang Tung, Jun-Jih Liou, Hsin-Chi Li, Takashi Oguchi 

摘要：This study analyzed landslide characteristics under extreme precipitation with regard to present and future scenarios, in order to analyze the effects of climate change on landslide activities. For our study area, we selected two adjacent catchments in northern Taiwan: the Shihmen Reservoir catchment, an area with high-relief topography that is susceptible to landslides at present, and the Xindian River catchment, an area with gentle topography that is not prone to landslides at present. This study established empirical relationships between landslide-area characteristics and rainfall conditions according to rainfall-induced landslides during past typhoon events. The relationships were applied to estimate landslide-area characteristics caused by typhoon events for the base period (1979–2003) and the end of the 21st century (2075–2099) according to the climate change scenario of representative concentration pathways 8.5 (RCP8.5) and dynamical downscaling of rainfall data in Taiwan. We also analyzed rainfall amounts at different recurrence intervals from different rainfall durations for the two catchments. We found that the area with high-relief topography (the Shihmen Reservoir catchment) is relatively prone to landslides currently and that the cumulative rainfall is a key factor controlling landslide-area characteristics. On the other hand, the area with gentle topography (the Xindian River catchment) is less prone to landslides at present, and the rainfall intensity is a key factor controlling landslide-area characteristics. Under the effects of climate change in the near future, both landslide severity and landslide frequency will increase more in areas with gentle topography than in areas with high-relief topography, in response to the more frequent occurrence of a strong typhoon with higher rainfall intensity. 

Landslide susceptibility assessment using Frequency Ratio, a case study of northern Pakistan

基于频比的滑坡易发性评估：巴基斯坦北部实例研究  

The Egyptian Journal of Remote Sensing and Space Science, Volume 22, Issue 1, April 2019, Pages 11-24 

摘要：Hawas Khan, Muhammad Shafique, Muhammad A. Khan, Mian A. Bacha, Chiara Calligaris 

The northern Pakistan is attributed with rough terrain, active seismicity, monsoon rains, and therefore hosts to variety of geohazards. Among the geohazards, landslides are the most frequent hazard with devastating impacts on economy and society. However, for most of the northern Pakistan, landslide susceptibility maps are not available which can be used for landslide hazard mitigation. This study aims to develop a remote sensing based landslide inventory, analysing their spatial distribution and develop the landslide susceptibility map. The area, selected for this study is comprised of Haramosh valley, Bagrote valley and some parts of Nagar valley, in the Central Karakoram National Park (CKNP) in Gilgit-Baltistan, northern Pakistan. The SPOT-5 satellite image was used to develop a landslide inventory which was subsequently verified in the field. The landslide causative factors of topographic attributes (slope and aspect), geology, landcover, distances from fault, road and streams were used to evaluate their influence on the spatial distribution of landslides. The study revealed that the distance to road, slope gradient has the significant influence on the spatial distribution of the landslides, followed by the geology. The derived results were used in the Frequency ratio technique to develop a landslide susceptibility map. The developed landslide susceptibility map can be utilized for landslide mitigation in the study area. 

Post-failure stage simulation of a landslide using the material point method

基于物质点方法的滑坡后破坏阶段模拟  

Engineering Geology, Volume 253, 10 April 2019, Pages 149-159 

Enrico Conte, Luigi Pugliese, Antonello Troncone 

摘要：Traditional numerical methods such as the finite element method are usually used to analyse the slope response in the pre-failure and failure stages under the assumption of small deformations. However, these methods are generally unsuitable for simulating the post-failure stage of landslides due to the occurrence of large deformations. The material point method (MPM) is a numerical technique capable to overcome this limitation. In the present study, MPM is used to carry out a two-dimensional analysis of the run-out process of the Senise landslide that occurred in Southern Italy, in 1986. Accuracy of the method is assessed by comparing the final geometry of the landslide observed just after the event and the magnitude of the measured displacements, to those provided by the numerical simulation. The calculation results match fairly well the observed ones when two slip surfaces detected by the inclinometers, are accounted for in the analysis. An additional improvement of simulation is achieved taking into account the presence of some buildings and retaining walls existing in that area. Kinematics of the landslide is also investigated. The results show that the Senise landslide was a translational slide moving along two planar slip surfaces located in thin layers of clayey silt. In addition, these results demonstrate that a suitable analysis of the post-failure stage can lead to a better understanding of the complex mechanical processes that characterise some landslides, and thereby help in establishing the most effective stabilization measures. 

Using CUDA to accelerate uncertainty propagation modelling for landslide susceptibility assessment

应用CUDA加快滑坡易发性评估的不确定性传播建模  

Environmental Modelling & Software, Volume 115, May 2019, Pages 176-186 

Ionut Sandric, Cristian Ionita, Zenaida Chitu, Marian Dardala, Felix Titus Furtuna 

摘要：The study is focused on modelling uncertainty propagation from GIS data sources and on assessing their influence on landslide susceptibility modelling. A complete set of tools was developed and written in C++ programming language, Python, and based on NVIDIA CUDA technology for terrain analysis. These tools are using Monte Carlo simulations to generate noise in elevation values and spatial delineation of landslides bodies. The uncertainty propagation is assessed using pixel based cumulative probabilities statistics at the pixel level. Thus, for each pixel, from the landslide susceptibility map, an estimation of landslide susceptibility uncertainty was obtained and spatially visualised. The results show that weight of evidence is a robust method and is not significantly influenced by small-scale variations in the primary topographic attributes. The toolbox and the source code are available under the MIT license. 

Characteristics of rain-induced landslides in the Indian Himalaya: A case study of the Mandakini Catchment during the 2013 flood

印度喜马拉雅地区降雨型滑坡特征：2013年洪水期间Mandakini Catchment实例研究  

Geomorphology, Volume 330, 1 April 2019, Pages 100-115 

Alok Bhardwaj, Robert J. Wasson, Alan D. Ziegler, Winston T. L. Chow, Yas Pal Sundriyal 

摘要：Landslides triggered by monsoon rainfall are a recurring hazard that lead to loss of life and cause enormous property and infrastructure damage in the Indian Himalaya. This study is focused on understanding the role of extreme rainfall and physical factors in causing landslides in the Indian Himalaya, particularly in the Mandakini Catchment where an enormous landslide and flood disaster occurred in June 2013 following a two-day extreme rainfall event. Results indicate that sub-daily extreme rainfall depths causing landslides vary with elevation across the catchment. Antecedent rainfall six days prior to the extreme rainfall event was found to have substantial depths that could have primed the area for landslides. Except for aspect of slopes, the causative factors including land use/land cover, lithology, elevation, slope, river network, distance to roads, and total extreme rainfall as a triggering factor were found to be statistically significant in causing landslides in the catchment. The final product of the study is a new landslide susceptibility map that better delineates the landslide prone regions in the disaster-prone Mandakini Catchment after the June 2013 extreme rainfall event. The Map was prepared using logistic regression that shows medium and high susceptibility zones at upper sections of the catchment as well as along the Mandakini River and its tributaries where major sacred shrines, tourist spots and human establishments are located.