黄土区滑坡研究中地形因子的选取与适宜性分析

黄土高原是中国生态较为脆弱的地区,也是滑坡发育的地层之一。黄土滑坡发育是孕灾环境、致灾因子和承灾体等多种因素联合作用的结果,其中作为重要孕灾环境因素的地形因子的选取是黄土滑坡风险研究的基础。本文选取黄土滑坡灾害多发的甘谷县作为研究区,综合利用敏感性指数、确定性系数和相关系数方法进行地形因子在滑坡灾害研究中的适宜性分析,得出以下结论：基于确定性系数法、敏感性分析模型和相关系数法,最终筛选出适宜于本区域滑坡灾害评价的地形因子为：坡度、坡度变率、坡形和地表粗糙度;确定性系数法、敏感性分析模型都基于分析单一因子与滑坡之间的关系进行致灾因子选取,忽视地形因子之间的相关性。实验结果表明,研究区稳定性较差的区域与已发生滑坡灾害分布数量具有较好的对应关系,并深入分析了滑坡与地形因子分级范围的关系,发现地形因子分级范围对地质灾害风险研究具有重要的影响,是导致部分区域的差异性主要原因之一。实地调查发现,河网切割密度及人类工程活动也对研究区危险性具有重要的控制作用,是重要的地形因素。     

Landslide Susceptibility Assessment of the Youfang Catchment using Logistic Regression

A detailed landslide susceptibility map was produced in the Youfang catchment using logistic regression method with datasets developed for a geographic information system(GIS).Known as one of the most landslide-prone areas in China, the Youfang catchment of Longnan mountain region,which lies in the transitional area among QinghaiTibet Plateau, loess Plateau and Sichuan Basin, was selected as a representative case to evaluate the frequency and distribution of landslides.Statistical relationships for landslide susceptibility assessment were developed using landslide and landslide causative factor databases.Logistic regression(LR)was used to create the landslide susceptibility maps based on a series of available data sources: landslide inventory; distance to drainage systems, faults and roads; slope angle and aspect; topographic elevation and topographical wetness index, and land use.The quality of the landslide susceptibility map produced in this paper was validated and the result can be used fordesigning protective and mitigation measures against landslide hazards.The landslide susceptibility map is expected to provide a fundamental tool for landslide hazards assessment and risk management in the Youfang catchment.     

基于信息量模型和数据标准化的滑坡易发性评价

本文以北川曲山-擂鼓片区为研究区,将坡度、坡向、高程、地层、距断层的距离、距水系的距离和距道路的距离作为该区域滑坡易发性评价因子。采用信息量模型计算了各项评价因子的信息量值,并运用4种标准化模型对信息量值进行标准化处理。各评价因子的权重由层次分析法（AHP）确定。在GIS中将权重值和各评价因子的标准化信息量值,进行叠加计算得到区域滑坡总信息量值,并基于自然断点法对其进行重分类,将研究区划分为极高易发区、高易发区、中易发区、低易发区和极低易发区5级易发区。将基于4种标准化模型和信息量模型得到的滑坡易发性评价结果进行了对比分析,结果表明：基于最值标准化信息量模型的滑坡易发性评价结果的ROC曲线下面积AUC值为0.807,高于其余模型的AUC值,说明最值标准化信息量模型的滑坡易发性评价效果最好。极高易发区面积占研究区面积的20.03%,离断层和水系较近,主要分布地层为寒武系、志留系和三迭系。研究结果可为区内滑坡风险评价和灾害防治提供参考。     

Centrifuge model test of an irrigation-induced loess landslide in the Heifangtai loess platform,Northwest China

The Heifangtai platform in Northwest China is famous for irrigation-induced loess landslides. This study conducted a centrifuge model test with reference to an irrigation-induced loess landslide that occurred in Heifangtai in 2011. The loess slope model was constructed by whittling a cubic loess block obtaining from the landslide site. The irrigation water was simulated by applying continuous infiltration from back of the slope. The deformation, earth pressure, and pore pressure were investigated during test by a series of transducers. For this particular study, the results showed that the failure processes were characterized by retrogressive landslides and cracks. The time dependent reductions of cohesion and internal friction angle at basal layer with increasing pore-water pressure were responsible for these failures. The foot part of slope is very important for slope instability and hazard prevention in the study area, where concentration of earth pressure and generation of high pore-water pressures would form before failures. The measurements of earth pressure and pore-water pressure might be effective for early warning in the study area.     

Earthquake-triggered landslides affecting a UNESCO Natural Site: the 2017 Jiuzhaigou Earthquake in the World National Park,China

On August 8~(th), 2017, an Ms 7.0 magnitude earthquake occurred in Jiuzhaigou County, northern Sichuan Province, China. The Jiuzhaigou Valley World National Park was the most affected area due to the epicentre being located in the scenic area of the park. Understanding the distribution characteristics of landslides triggered by earthquakes to help protect the natural heritage sites in Jiuzhaigou Valley remains a scientific challenge. In this study, a relatively complete inventory of the coseismic landslides triggered by the earthquake was compiled through the interpretation of high-resolution images combined with a field investigation. The results indicate thatcoseismic landslides not only are concentrated in Rize Gulley, Danzu Gully and Zezhawa Gully in the study area but also occur in the front part of Shuzheng Gully along the road network(from the entrance of Jiuzhaigou Valley to Heye Village). The landslides predominantly occur on the east-and southeastfacing slopes in the study area, which is a result of the integrated action of the valley direction and fault movement direction. The back-slope effect and the slope structure caused the difference in coseismic landslide distribution within the three gullies(Danzu Gully, Rize Gully, and Zezhawa Gully) near the inferred fault. In addition, the topographic position index was used to analyse the impact of microlandforms on earthquake-triggered landslides by considering the effect of the slope angle. The study results reveal a higher concentration of landslides in the slope position class of the middle slope(30°-50°) in Jiuzhaigou Valley. These findings can provide scientific guidance for the protection of natural heritage sites and post-disaster reconstruction in Jiuzhaigou Valley.     

Numerical simulation on a tremendous debris flow caused by Typhoon Morakot in the Jiaopu Stream,Taiwan

In August 2009,Typhoon Morakot brought a large amount of rainfall with both high intensity and long duration to a vast area of Taiwan.Unfortunately,this resulted in a catastrophic landslide in Hsiaolin Village,Taiwan.Meanwhile,large amounts of landslides were formed in the Jiaopu Stream watershed near the southeast part of the Hsiaolin Village.The Hsiaolin Village access road（Provincial Highway No.21 and Bridge No.8） was completely destroyed by the landslide and consequent debris flow.The major scope of this study is to apply a debris flow model to simulate the disaster caused by the debris flow that occurred in the Jiaopu Stream during Typhoon Morakot.According to the interviews with local residents,this study applied the destruction time of Bridge No.8 and Chen＇s house to verify the numerical debris flow model.By the spatial rainfall distributions information,the numerical simulations of the debris flow are conducted in two stages.In the first stage（before the landslide-dam failure）,the elevation of the debris flow and the corresponding potential damages toward residential properties were investigated.In the second stage（after the landslidedam failure）,comparisons of simulation results between the longitudinal and cross profiles of the Jiaopu Stream were performed using topographic maps and satellite imagery.In summary,applications of the adopted numerical debris flow model have shown positive impact on supporting better understanding of the occurrence and movement of debris flow processes.     

Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.     

Regolith thickness modeling using a GIS approach for landslide distribution analysis,NW Himalayas

Regolith thickness is considered as a contributing factor for the occurrence of landslides. Although, mostly it is ignored because of complex nature and as it requires more time and resources for investigation. This study aimed to appraise the role of regolith thickness on landslide distribution in the Muzaffarabad and surrounding areas, NW Himalayas. For this purpose regolith thickness samples were evenly collected from all the lithological units at representative sites within different slope and elevation classes in the field. Topographic attributes (slope, aspect, drainage, Topographic Wetness Index, elevation and curvature) were derived from the Digital Elevation Model (DEM) (12.5 m resolution). ArcGIS Model Builder was used to develop the regolith thickness model. Stepwise regression technique was used to explore the spatial variation of regolith thickness using topographic attributes and lithological units. The derived model explains about 88% regolith thickness variation. The model was validated and shows good agreement (70%) between observed and predicted values. Subsequently, the derived regolith model was used to understand the relationship between regolith thickness and landslide distribution. The analysis shows that most of the landslides were located within 1–5 m regolith thickness. However, landslide concentration is highest within 5–10 m regolith thickness, which shows that regolith thickness played a significant role for the occurrence of landslide in the studied area.     

Spatial Variability of Mass Movements in the Satluj Valley,Himachal Pradesh during 1990～2006

Satluj Valley is known to have a history of landslides and related mass movement activities since the geological times. Geological and geomorphological settings combined with anthropogenic activities constitute a propensity towards slope failure. During the last two decades,the area witnessed substantial increase in athropogenic pressure,mainly due to the exploitation of hydropower potential,changing landuse pattern and population growth. In addition,a shift of the climatic patterns in the form of larger area falling under the influence of rains was observed. These natural as well as anthropogenic changes in the area have resulted in increased spatial coverage of landslide in the area. This paper documents these changes during 1990～2006.     

GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model(IOE), the support vector machine model(SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70%(125) of the landslides which was optimized by 10-fold crossvalidation being used for training purpose and the remaining 30%(54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index(NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic(ROC) curves and three statistical indexes involving positive predictive rate(PPR), negative predictive rate(NPR) and accuracy(ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model.Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.     

Seismogenic fault and topography control on the spatial patterns of landslides triggered by the 2017 Jiuzhaigou earthquake

Jiuzhaigou National Park, located in northwest plateau of Sichuan Province, is a UNESCO World Heritage Site, and one of the most popular scenic areas in China. On August 8, 2017, a Mw 6.5 earthquake occurred 5 km to the west of a major scenic area, causing 25 deaths and injuring 525, and the Park was seriously affected. The objective of this study was to explore the controls of seismogenic fault and topographic factors on the spatial patterns of these landslides. Immediately after the main shock, field survey, remote-sensing investigations, and statistical and spatial analysis were undertaken. At least 2212 earthquake-triggered landslides were identified, covering a total area of 11.8 km~2. Thesewere mainly shallow landslides and rock falls. Results demonstrated that landslides exhibited a close spatial correlation with seismogenic faults. More than 85% of the landslides occurred at 2200 to 3700 m elevations. The largest quantity of landslides was recorded in places with local topographic reliefs ranging from 200 to 500 m. Slopes in the range of ~20°-50° are the most susceptible to failure. Landslides occurred mostly on slopes facing east-northeast(ENE), east(E), east-southeast(ESE), and southeast(SE), which were nearly vertical to the orientation of the seismogenic fault slip. The back-slope direction and thin ridge amplification effects were documented. These results provide insights on the control of the spatial pattern of earthquake-triggered landslides modified by the synergetic effect of seismogenic faults and topography.     

Landslide distribution and sliding mode control along the Anninghe fault zone at the eastern edge of the Tibetan Plateau

Tibetan Plateau is known as the roof of the world. Due to the continuous uplift of the Tibetan Plateau, many active fault zones are present. These active fault zones such as the Anninghe fault zone have a significant influence on the formation of special geomorphology and the distribution of geological hazards at the eastern edge of the Tibetan Plateau. The Anninghe fault zone is a key part of the Y-shaped fault pattern in the Sichuan-Yunnan block of China. In this paper, high-resolution topographic data, multitemporal remote sensing images, numerical calculations, seismic records, and comprehensive field investigations were employed to study the landslide distribution along the active part of the Anninghe. The influence of active faults on the lithology, rock mass structures and slope stress fields were also studied. The results show that the faults within the Anninghe fault zone have damaged the structure and integrity of the slope rock mass, reduced the mechanical strength of the rock mass and controlled the slope failure modes. The faults have also controlled the stress field, the distribution of the plastic strain zone and the maximum shear strain zone of the slope, thus have promoted the formation and evolution of landslides. We find that the studied landslides are linearly distributed along the Anninghe fault zone, and more than 80% of these landslides are within 2-3 km of the fault rupture zone. Moreover, the Anninghe fault zone provides abundant substance for landslides or debris flows. This paper presents four types of sliding mode control of the Anninghe fault zone, e.g., constituting the whole landslide body, controlling the lateral boundary of the landslide, controlling the crown of the landslide, and constituting the toe of the landslide. The results presented merit close attention as a valuable reference source for local infrastructure planning and engineering projects.     

Spatial Variability of Mass Movements in the Satluj Valley,Himachal Pradesh during 1990～2006

Satluj Valley is known to have a history of landslides and related mass movement activities since the geological times.Geological and geomorphological settings combined with anthropogenic activities constitute a propensity towards slope failure.During the last two decades.the area witnessed substantial increase in athropogenic pressure,mainly due to the exploitation of hydropower potential,changing landuse pattern and population growth.In addition,a shift of the climatic Datterns in the form of larger area falling under the influence of rains was observed.These natural as well as anthropogenic changes in the area have resulted in increased spatial coverage of landslide in the area.This paper documents these changes during 1990～2006.     

Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.     

风振影响下乔木坡地暴雨型浅层滑坡演化机制

强对流或台风等极端天气下乔木坡地发生浅层滑坡灾害往往是暴雨和强风共同作用的结果。以皖南山区一处暴雨型浅层滑坡——畈章组滑坡为例, 通过现场调查和气象资料的分析表明, 除暴雨外风荷载也有可能促进滑坡的启动。为揭示该滑坡启动与破坏后这一完整运动过程的演化机制, 首先基于无限斜坡模型分析了实际降雨条件下的滑坡稳定性, 然后对取自于滑坡体内乔木根系周围和滑动面附近的两种土样利用DPRI型环剪仪, 分别开展了不排水循环剪切试验和自然排水残余剪切试验。结果表明: ①降雨入渗引起滑动面孔隙水压力的上升, 并导致稳定性的降低是畈章组滑坡启动的直接原因; ②乔木根系周围的饱和土在风振作用产生的动剪切荷载下易形成高的超孔隙水压力, 并导致浅表层的局部失稳滑动, 增加了畈章组滑坡整体破坏的可能性; ③滑动面土体的残余强度具有强烈的"正速率效应", 从而控制了畈章组滑坡启动后不会表现出高速远程的运动特征, 与现场调查结论一致。研究结果可以为暴雨协同风振作用下富乔木坡地浅层滑坡的预警预报研究提供参考。      

降雨与开挖作用下黄土滑坡失稳过程分析: 以关中地区长武县杨厂村老庙滑坡为例

降雨入渗和人工开挖是诱发黄土滑坡的重要因素, 为了研究在这2种诱因作用下关中地区黄土滑坡失稳过程及其对稳定性的影响, 以陕西省长武县杨厂村老庙滑坡为研究对象, 通过现场调查、地质测绘和钻孔勘探, 查明了该滑坡变形特征, 定性分析了滑坡变形演变过程; 基于滑坡变形前15 d内日降雨量实测值, 采用有限元软件, 对坡脚开挖后连续降雨作用下滑坡形成过程进行了仿真模拟; 基于强度折减法对该滑坡稳定性变化规律进行了研究。结果表明: ①关中地区特殊的地层结构是滑坡变形的内因, 降雨是最主要的诱发因素; ②滑坡失稳演化过程表现为: 坡体处于蠕滑状态, 坡脚开挖后, 坡体前缘失稳, 牵引中后缘坡体向下错动而产生张拉裂缝, 在降雨作用下, 雨水沿裂缝渗入坡体深部, 滑坡中部岩土体浸水后抗剪强度降低, 从而导致黄土层与红黏土层接触面饱水形成贯通滑带, 诱发深层滑坡; ③滑坡开挖后较初始状态, 稳定性系数降幅为0.102, 此后受连续降雨影响, 稳定性系数在前10 d以平均0.010/d的速率缓慢下降, 第10~13 d以0.034/d的速率快速下降至最低, 第13 d以后开始回升。研究结果可以为该类滑坡防治提供有效依据。      

霍西煤矿区地表滑坡灾害敏感性数值建模与等级划分

本文以山西省霍西煤矿区为研究区,利用遥感和GIS方法对滑坡灾害的敏感性进行了数值建模与定量评价。利用交叉检验方法构建了径向基核函数支持向量机滑坡敏感性评价模型,并基于拟合精度对模型进行了定量评价;对各评价因子在模型中的重要性进行对比分析;基于空间分辨率为30m的评价因子,通过径向基核函数支持向量机模型获得了霍西煤矿区滑坡敏感性指数值,并利用分位数法将霍西煤矿区的滑坡敏感性分为极高、高、中和低4个等级。结果表明：拟合精度建模阶段和验证阶段分别为87.22%和70.12%;与滑坡敏感性关系最密切的5个评价因子依次是岩性、距道路距离、坡向、高程和土地利用类型;极高和高敏感区域分布了93.49%的滑坡点,面积占总面积的50.99%,是比较合理的分级方案。本研究不仅可以为研究区人工边坡调查和煤矿资源合理开采提供借鉴,对相似矿区的相关工作也具有参考价值。     

基于栅格最大值法的县域综合地质灾害建模

四川省地形高低悬殊, 岩性构造发育, 各类地质灾害频发, 开展地质灾害易发性评价具有重要意义。崩塌、泥石流属于广义上的滑坡, 以四川省丹巴县为例, 从考虑不同滑坡类别的区域性地质灾害易发性出发综合考虑崩塌、滑坡、泥石流的空间概率分布。基于ArcGIS通过高精度数字高程模型共选取高程、坡度等10个地质灾害关键控制因素, 采用信息量模型对综合地质灾害进行了易发性评价。最终通过ArcGIS的单元统计(Cell Statistics)功能实现多个栅格图层最大值法合成综合易发性, 进一步利用受试者工作特征曲线(ROC)验证单种滑坡类别易发性模型的精度。按照自然断点法将研究区划分为极低、低、中、高、极高易发区, 高易发区和极高易发区主要集中分布在章谷镇、太平桥乡以及甲居镇等地。研究结果证明信息量模型能对单类地质灾害进行评价, 栅格最大值法是获取综合易发性的一种有效评价方法。      

Multitemporal UAV-based photogrammetry for landslide detection and monitoring in a large area:a case study in the Heifangtai terrace in the Loess Plateau of China

With high spatial resolution,on-demand-flying ability,and the capacity for obtaining threedimensional measurements,unmanned aerial vehicle(UAV) photogrammetry is widely used for detailed investigations of single landslides,but its effectiveness for landslide detection and monitoring in a large area needs to be investigated.The Heifangtai terrace in the Loess Plateau of China is a loess terrace that is extremely susceptible to irrigation-induced loess landslides.This paper used UAV-based photogrammetry for a series of highresolution images spanning over 30 months for landslide detection and monitoring of the terrace with an area of 32 km~2.Dense and evenly distributed ground control points were established and measured to ensure the high accuracy of the photogrammetry results.The structure-from-motion(Sf M) technique was used to convert overlapping images into orthographic images,3D point clouds,digital surface models(DSMs) and mesh models.Using multitemporal differential mesh models,landslide vertical movements and potential landslides were detected and monitored.The results indicate that a combination of UAV-based orthophotos and differential mesh models can be used for flexible and accurate detection and monitoring of potential loess landslides in a large area.     

Evaluating effectiveness of frequency ratio,fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district,India

Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics (ROC) curve, spatially agreed area approach and seed cell area index (SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.