层面倾角对顺层岩质滑坡贡献率研究

顺层岩质滑坡作为滑坡的一种类型,在国内很多省份均有较高的发生频率,造成了较大的经济损失及不良的社会影响。为了研究顺层岩质滑坡发育的规律,依据笔者参与并成功治理的国内81处顺层岩质滑坡建立数据库,利用贡献率法将不同层面倾角区间的顺层岩质滑坡的各种相互关系进行定量化分析,以研究不同层面倾角区间的顺层岩质滑坡的相关性。结果表明,层面倾角为10°～25°的坡体,对顺层岩质滑坡贡献率程度最高;层面倾角为25°～35°的坡体,对顺层岩质滑坡贡献率程度中等;层面倾角为大于35°及小于10°的坡体,对顺层岩质滑坡贡献率程度最低。所得分析结论与实际情况吻合较好,能很好地为以后国内顺层岩质滑坡的研究及治理提供借鉴参考     

地形坡度对鄂渝地区水库型堆积层滑坡贡献率研究

堆积层滑坡是库区常见的滑坡类型之一,而地形坡度是滑坡发育的重要内因,研究地形坡度与堆积层滑坡发生概率之间的关系对水库型堆积层滑坡的危险性评价具有重要意义。以三峡库区及丹江口库区的139处堆积层滑坡为例,首先,将滑坡地形坡度以每隔5划分为一个区间,总共分为7个区间; 在此基础上,采用贡献率方法,定量研究了地形坡度分别对滑坡数量、面积、体积的贡献率; 最后,通过迭加统计,得到了不同坡度区间对滑坡发生的综合贡献率。结果表明, 15～25的地形坡度对水库型堆积层滑坡的贡献率最高, 10～15及25～30的地形坡度对水库型堆积层滑坡的贡献率中等,小于10及大于30的地形坡度对水库型堆积层滑坡的贡献率最小。研究结果可为具有类似地质背景的水库型堆积层滑坡危险性评估及防治规划提供参考依据。     

基于贡献率权重法的区域滑坡影响因子敏感性分析

滑坡影响因子是区域滑坡危险性评价的基础,而因子的敏感性直接反应评价过程中权重大小,因此因子敏感性的精度将影响着评价结果的精度。本文以平昌县滑坡灾害为例,选取坡度、地层、高差、高程、坡形五个因子作为滑坡灾害的敏感性分析因子,采用贡献率权重法对研究区滑坡灾害影响因子的内部敏感性及因子间敏感性进行分析,该评价方法结构简单,不受地域限制,能客观的反应出各评价因子间以及因子内对地质灾害的敏感性。分析结果显示:选取的5个指标敏感性大小依次为:坡形坡度地层高差高程;在各评价指标内部中,坡度10°~30°、侏罗系下统蓬莱镇组上段地层、高差4.94~12.36 m、高程300~800 m、凸形与直线形坡是滑坡发生的高敏感区间。     

三峡水库区云阳-巫山段斜坡高差因素对滑坡发育的贡献率研究

三峡水库区滑坡发育与多种因素相关。这些影响因素可以归纳为两大类：外部因子和内部因子。其中斜坡相对高差是滑坡发育的必要内部条件之一，对斜坡的发育有着重要的影响。文章借助于GIS技术，采用贡献率法重点研究斜坡高差对研究区滑坡发育的贡献。通过对研究区内已有的205个滑坡样本点进行细致剖析，结果表明相对高差在500～1000m的斜坡对滑坡贡献率最高，是滑坡发育的主要高差区间；400m、1100～1300m斜坡贡献率中等，是滑坡发育的次要高差区间；100～300m、1400～1700m斜坡的贡献率较低，是滑坡发育相对较弱的高差区间。文章运用贡献率法定量地分析了三峡水库区滑坡发育与斜坡相对高差之间的关系。所得研究结果与实际情况吻合较好，为库区以后的规划建设提供了有力的依据。     

大别造山带岳西县斜坡变形破坏演化模式

岳西县自然斜坡在地球内、外动力共同作用下,容易变形并遭到破坏,造成人员伤亡和财产损失,严重制约了当地的经济发展。通过系统的工程地质调查和浅表生改造理论分析,查明了岳西县斜坡变形破坏特征及其成因,并探讨了其演化模式。结果表明,岳西县不同岩组的抗风化能力和力学特性存在差异,斜坡发生地质灾害的机理也不相同。根据斜坡结构特征,岳西县滑坡分为全风化层滑坡、强风化层滑坡和顺层岩质滑坡：全风化层滑坡的滑面位于全风化层中或全风化层与强风化层的分界线处;强风化层滑坡的滑面主要发育于强风化层与中风化层的分界线处;顺层岩质滑坡主要发育于片麻岩发育的顺向坡中。根据变形破坏方式,岳西县崩塌可分为滑移式崩塌、倾倒式崩塌和坠落式崩塌：滑移式崩塌主要由一组缓倾坡外结构面和另一组陡倾(坡外或者坡内)结构面控制;倾倒式崩塌主要由一组陡倾坡内结构面和另一组近水平发育的结构面控制;坠落式崩塌主要由一组结构面陡倾或近直立发育的结构面控制。岳西县滑坡多发育于风化壳厚度较大、岩体较松散、结构面强度低的地区;崩塌多发育于斜坡高陡、岩质风化程度低、结构面发育的地区。研究成果对岳西县乃至整个大别山地区地质灾害的研究及防治工作具有一定的借...     

岸坡消落带岩体劣化的新生型滑坡(崩塌)隐患演化模式研究

三峡库区岸坡消落带是库岸边坡稳定性的敏感地带。库区内多次发生的地质灾害均与消落带的岩体劣化有关。随着时间的推移消落带的岩体劣化情况日益加剧,新生型滑坡不断涌现。本文通过实地调查与室内分析,系统总结了三峡库区秭归至巴东段岸坡消落带岩体劣化的类型以及新生型滑坡隐患的演化模式。研究表明,区内消落带岩性主要以碳酸盐岩类和碎屑岩类为主,碳酸盐岩类劣化类型主要有溶蚀(潜蚀)、裂缝显化与扩张和机械侵蚀,碎屑岩类的劣化类型主要有松动(剥落)、冲蚀(磨蚀)、结构面崩解块裂和软硬相间侵蚀,其中以松动/剥落型最为发育。在此基础上结合结构面发育特征、岸坡结构、岩性及结构和边界特征,厘定了不同岸坡消落带岩体劣化演化形成新生型滑坡隐患点的模式,碳酸岩盐类岸坡主要以基座碎裂压溃型、基座掏空倾倒型、顺向滑移型为主;碎屑岩类岸坡主要以软硬相间坍(崩)塌型、视倾向楔形滑动型、顺向滑移型及逆向倾倒型为主。研究结果可为三峡库区地质灾害监测预警及防治提供技术支撑。     

三峡库区香溪河段典型滑坡变形特征分析

本文从坡形采集入手,对三峡库区香溪河段蓄水后发生变形的滑坡进行归纳统计。统计表明,近水库岸坡为凸形的滑坡更容易发生变形。对香溪河段典型滑坡进行了长期地表位移监测,获得八字门滑坡和白家包滑坡的变形曲线为台阶状,耿家坪滑坡的变形曲线为脉动形。近库水微地貌为凸岸,滑体物质为老滑坡堆积物的滑坡变形曲线为台阶状,变形具积累性;近库水微地貌为凹岸,滑体物质为崩塌堆积物的滑坡变形曲线为脉动形,变形具“弹性”。     

基于GIS的贵州省滑坡灾害危险性评价

中国是受滑坡危害最严重的国家之一,滑坡的突发性和泛生性严重威胁到社会发展及人类生活。从宏观上研究滑坡灾害分布规律并进行危险性评价,对防灾减灾具有战略性指导意义。贡献率是统计学中常用指标,指某因素增长量占总增长量的比重。本文引入贡献率法以定量分析各因素与滑坡的关系,参考国内滑坡危险性评价研究,选取7个指标:地层岩性、断层、河流、道路、NDVI(归一化植被指数)、坡度、坡高。本文以贵州省为例,运用ArcGIS、Yaahp、SAGA等软件平台来评价滑坡危险性。结果显示:(1)侏罗纪地层、断层250m内、河流400m内、道路1km内、NDVI小于0.3、坡度15°~25°、坡高低于50m范围内对贵州省滑坡发育最有利;(2)贵州省滑坡灾害高危险区主要分布于六盘水市、遵义市西北部和铜仁市西部,低危险区主要分布于铜仁市东部和黔东南苗族侗族自治州东部。研究结果表明该方法能够定量且客观地描述滑坡分布规律及评价危险性,且具有可移植性。     

三峡地区新构造活动与滑坡分布关系

三峡库区广泛发育有“层状”地貌，是地壳大面积隆升的产物。现今构造应力场的方向总体表现为NNE—NE向，主压应力场并不水平，其仰角约为30°。新构造应力场控制地壳不均衡隆升结果造成坡体演化阶段不同，并控制滑坡的时空分布，奉节以东地区坡体处于变形破坏初期阶段，滑坡与崩塌共存，坡体陡高，滑带倾角大，重力背斜变形构造多见；奉节以西地区坡体处于变形破坏的中后期阶段，以滑坡发育为主要特征，坡体平缓，滑带倾角平缓，重力背斜变形构造少见；新构造应力场控制水平运动对滑坡的滑动方向、滑坡的破坏强度主要体现为构造应力场与自重应力场的叠加机制。     

Rio Muni盆地第四纪陆坡地震地貌学

基于Rio Muni盆地深水区1 400 km2的高分辨率三维地震资料,对第四纪陆坡开展地形、地貌单元的构型、成因及演化研究。主要取得3点结论:①依据海底坡度,研究区海底地形具有东西分带,南北分区的特点。②研究区发育水道（顺直水道和弯曲水道）、滑坡（陆坡滑坡和水道壁滑坡）及海底麻坑（孤立麻坑和条带状麻坑）3类典型地貌单元。上陆坡主要发育顺直水道,弯曲水道带发育在中-下陆坡。弯曲水道主要分布在南北2区,而顺直水道在南中北3区均有发育。水道的弯曲程度与海底坡度、重力流供给密切相关。③条带状海底麻坑主要分布在南北2区,孤立麻坑3区均发育。单一麻坑任意方向的剖面均具有“U”形或“V”形特征,其下方的气烟囱具有振幅增强,同相轴下拉特征。条带状麻坑分布在古水道上方或两侧的海底, 其走向剖面具有脊-槽相间地形特征。古水道和浅层气的逸散是形成条带状海底麻坑的主要因素。     

Landslide susceptibility mapping and factor effect analysis using frequency ratio in a catchment scale: a case study from Garuwa sub-basin,East Nepal

For assessing landslide susceptibility, the spatial distribution of landslides in the field is essential. The landslide inventory map is prepared on the basis of historical information of individual landslide events from different sources such as previously published reports, satellite imageries, aerial photographs and interview with local inhabitants. Then, the distribution of landslides in the study area is verified with field surveys. However, the selection of contributing factors for modelling landslide susceptibility is an inhibit task. The previous studies show that the factors are chosen as per availability of data. This paper documents the landslide susceptibility mapping in the Garuwa sub-basin, East Nepal using frequency ratio method. Nine different contributing factors are considered: slope aspect, slope angle, slope shape, relative relief, geology, distance from faults, land use, distance from drainage and annual rainfall. To analyse the effect of contributing factors, the landslide susceptibility index maps are generated four times using (a) topographical factors and geological factors, (b) topographical factors, geological factors and land use, (c) topographical factors, geological factors, land use and drainage and (d) all nine causative factors. By comparing with the pre-existing landslides, the fourth case (considering all nine causative factors) yields the best success rate accuracy, i.e. 81.19 %, which is then used to produce the final landslide susceptibility zonation map. Then, the final landslide susceptibility map is validated through chi-square test. The standard chi-square value with 3 degrees of freedom at the 0.001 significance level is 16.3, whereas the calculated chi-square value is 7,125.79. Since the calculated chi-square value is greater than the standard chi-square value, it can be concluded that the landslide susceptibility map is considered as statistically significant. Moreover, the results show that the predicted susceptibility levels are found to be in good agreement with the past landslide occurrences.     

Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling�CNarayanghat road section in Nepal Himalaya

Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling?CNarayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75?%) were randomly selected for building landslide susceptibility models, while the remaining 80 (25?%) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16?%. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57?% of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80?% accuracy (i.e. 89.15?% for IOE model, 89.10?% for LR model and 87.21?% for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling?CNarayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

Suitability analysis for topographic factors in loess landslide research: a case study of Gangu County,China

Loess Plateau is one of the ecologically fragile regions in China. It is one of the slippery strata of which landslides often developed. The formation and development of landslides are mainly affected by various natural environments, triggering factors, the vulnerability of landslide-bearing bodies, and topography has a controlling effect on landslides and determines landslide distribution. As important environmental elements, the selection and reclassification of topographic factors are the basis for loess landslide vulnerability map. In this study, our research suggests an effective workflow to select and analyze the topographic factors in the loess landslides. Nine hazard-formative environmental factors [e.g., slope, aspect, slope shape (SS), slope of slope (SOS), slope of aspect (SOA), surface amplitude (SA), surface roughness (SR), incision depth (ID) and elevation variation coefficient (EVC)] are prepared for landslide suitability analysis. The models of certainty factor, sensitivity index and correlation coefficient are combined to select and analyze the suitability of these factors. Four topographic factors (i.e., slope, SOS, SS and SR) were ultimately selected to carry out the landslide vulnerability mapping with other factors. Our results showed that most of the landslides were located in medium and high classes and accounting for 75.3%, and these places also coincided with higher economies and intense human activities. Our research also suggested that in situ measurements are necessary to determine how to reclassify these topographic factors and how many grades these topographic factors divided, which would further improve the reliability of landslide vulnerability map for the decision makers to deal with the possible future landslides in terms of safety and human activities.     

GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran,Iran)

The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

贡献权重模型在区域滑坡危险性评价中的应用

以攀枝花市米易县为研究区域,采用GIS技术,选取坡度、坡向、坡形、地层岩性和相对高差等5个指标作为评价因子,利用贡献权重模型对研究区的滑坡地质灾害进行危险性评价。评价结果经过检验符合实际情况:高危险度区占全区面积31.9%;中危险度区占全区面积52.6%;低危险度区占全区面积15.5%;高、中危险度区所包含的滑坡个数占到全区滑坡总数的95.9%。评价结果表明,GIS技术和贡献权重模型结合能够很好地为滑坡灾害危险性评价服务,可以解决过去危险性评价中效率低、精度差等问题,从而实现滑坡灾害评价的信息化和科学化。     

Application of frequency ratio,statistical index,and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning.     

基于逻辑回归–信息量的川藏交通廊道滑坡易发性评价

川藏交通廊道位于青藏高原中东部,是世界上隆升和地貌演化最快的区域之一。在内外动力耦合作用下,区内滑坡灾害极其发育,严重制约着公路、铁路和水电工程的规划建设。在区域地质资料收集和整理的基础上,选取岩性、坡度、坡向、坡形、地形起伏度、地形粗糙度、断裂密度和河流距离8个因素为评价因子,结合传统信息量和逻辑回归模型的优势,采用逻辑回归–信息量模型对研究区滑坡进行易发性评价。通过对评价因子的多重共线性和显著性检验,得到评价因子不存在多重共线性且均对滑坡发生具有显著影响。采用ROC曲线对评价结果进行检验,其AUC值为0.81,表明评价模型能很好地预测滑坡的发生。易发性评价结果表明:研究区高易发区主要集中龙门山断裂带、金沙江断裂带、澜沧江断裂带、怒江断裂带、边坝–洛隆断裂带等大型活动断裂带控制区,以及区内坡度陡峭、地形起伏度大的大型河流深切河谷的两岸;中易发区在区内分布广泛,主要分布在岸坡较陡、地形起伏度中等的大型河流支流的两岸。研究结果有利于加深对川藏交通廊道滑坡发育分布的认识,也可为研究区的工程规划建设和防灾减灾提供科学依据。     

基于三维非连续变形分析的巨石崩塌运动研究

巨石作为一种大体积、大质量的滚石,其崩塌失稳及高速、高能远程运动往往导致沿途建筑物和交通线路的毁灭性灾难。以西藏自治区G318国道K4580典型滑坡为工程背景,基于三维非连续变形分析（three-dimensional discontinuous deformation analysis,简称3D-DDA）方法研究巨石崩塌失稳及运动全过程的特征与现象。分别建立该边坡未滑坡、浅层滑坡后和深层滑坡后3种坡形的巨石崩塌3D-DDA数值模型。采用滚石运动横向偏移经验模型,验证3D-DDA巨石运动模拟的准确性。在此基础上,分析巨石崩塌失稳机制及破坏后沿3种不同坡形边坡的运动轨迹和动能演进等运动特征。结果表明,3D-DDA能够有效模拟巨石崩塌失稳、运动发展、剧烈冲击碰撞直至最终静止等整个动力学过程。巨石崩塌表现为滑动→倾倒?滑动→倾倒→翻转?下落的失稳模式转换;巨石运动表现为碰撞、弹跳、飞跃、滚动、滑动等多种运动形式以及横向偏移、侧向偏转等三维空间运动特征,经过道路并与高架桥发生碰撞,引发巨石灾害。不同坡面几何特征下的巨石运动偏移量、弹跳高度、运动至坡底碰撞时间、最终稳定时间等均随着未滑坡、浅层滑坡后、深层滑坡后3种坡形变化而减小。通过3D-DDA巨石崩塌运动分析,预测巨石运动全过程、影响范围、冲击能量、停积位置等,可为巨石防灾减灾对策或措施制定提供依据。     

基于R型因子分析法的滑坡发育影响因素分析

以陕西省岚皋县境内滑坡为研究对象,借助R型因子分析法,对滑坡发育的影响因素进行分析研究。结果表明:起主导作用的主项因素按照其影响作用的大小依次为滑坡前缘河流影响距、人类工程活动、地形地貌和控滑结构面; 影响较大的分项因素按照其影响作用的大小依次为滑坡体前缘河流影响距、开挖坡脚、原始斜坡坡向、控滑结构面倾向、耕地（占坡体百分比）和滑坡体碎石含量。结合影响滑坡发育的主项因素和分项因素,综合确定影响滑坡发育的主控因素按照其影响的作用大小依次为河流影响距、开挖坡脚、原始斜坡坡向、控滑结构面倾向。该问题的研究不仅可以为滑坡灾害的分析提供新的方法,而且对滑坡灾害的防灾减灾提供了一种新思路。