浅析已运营高速公路高边坡安全风险防控工作研究

山区高速公路建设中涉及了大量的边坡工程问题,建立一套基于山区高速公路地质环境条件、边坡工程特点及交通运营要求的高边坡安全风险检评系统,并结合边坡工程监测,有利于开展已运营高速公路高边坡安全风险防控工作,保障高速公路安全运营。     

矿山工程中滑坡地质灾害特征及成因分析

滑坡地质灾害在矿山工程建设过程中具有严重的破坏性,加剧水土流失、减弱了水分涵养功能、降低了生物多样性等一系列生态环境问题,对周围土壤、空气造成影响。本文通过对某矿山工程边坡的基本特征、成因分析、稳定性影响因素和破坏模式进行分析评价,提出针对性的矿山工程边坡滑坡防治建议,为该工程区域的防灾减灾提出科学依据,对保护当地人民生命和财产安全具有重要意义。     

泥石流与滑坡

P书82侧侧旧3193,集成地质、力学伯息和监测数据的滑坡动态模型=伪1腼ielandsliding 11Kdd诫th int铭rationof~toring info忱nation阴d~抽nie inforrnation/朱建军,丁晓利…//测绘学报一20()3,32(1)一261一266 先假设边坡滑坡体为刚体,建立边坡滑坡的动态模型,由此建立卡尔受滤波的系统方程.边坡的力学状态通过卡尔受涟波与边坡变形观侧的数据联系起来了.模型的不确定性(模型误差)是通过建立的虚拟观侧方程来考虑的.与已有的方法不同的是,所建立的方法不仅利用包含在观测中的统计信息,而且能利用边坡滑坡的有关力学状态和地质条件所提供的…     

基于二元逻辑回归模型的新疆果子沟滑坡风险区划

新疆果子沟区域是我国与中亚地区社会、经济、文化交流的重要通道以及我国石油、天然气等能源资源安全大通道,沿途滑坡灾害频发,威胁人类安全、影响社会、经济发展,但该区域针对滑坡灾害的研究程度较低,需借助滑坡灾害易发性分析与风险等级评估结果指导防灾减灾。本文基于GF-1号卫星影像数据进行滑坡解译,选取地层岩性、断层密度、坡度、坡向、地表高程、植被指数等6个评估因子,探讨运用GIS、RS技术及统计分析模型进行滑坡灾害易发性分析与建模。基于频率比法分析各因子敏感性,利用二元Logistic回归模型进行灾害易发性分析,将研究区滑坡灾害风险分为极低、低、中、高、极高五个等级。将模型计算结果与历史滑坡信息进行比较,并借助ROC Curve检验模型准确性,AUC为0.844,表明模型预测结果具有较高准确性,因此建立的分析模型可以满足新疆果子沟区域滑坡灾害分析与评估应用,研究成果可为研究区重大线型工程保护、边坡加固提供辅助决策支持。     

贝岭镇米贝村边坡稳定问题及滑坡治理方法分析

边坡稳定性问题是治理地质灾害的重要内容,不稳定的基岩和土壤坡度严重影响了地质灾害的预防和管理,难以建立灾害管理体系。为了处理这种现象,技术部门在施工过程中需要着眼于边坡滑坡问题,对事故现场的地质情况进行全面调查,制订科学合理的处理方案。本文对贝岭镇米贝村边坡稳定问题及滑坡治理方法进行了分析,希望能为业界同行提供参考。     

区域滑坡灾害风险评价方法研究

回顾了滑坡灾害风险评价研究进展,指出了现有评价方法的不足。然后提出了基于土地利用类型的滑坡灾害易损性评价方法,建立了针对滑坡灾害的防灾减灾能力评价指标体系,并给出了具体评价方法。最后提出了基于G IS的区域滑坡灾害风险评价流程以及滑坡灾害风险等级确定方法。     

降雨型浅层滑坡的变形预测模型

滑坡是边坡被某些诱发因素激发失稳产生滑动的一种地质现象。它是地质灾害的主要类型,尤其以降雨滑坡数量最多,其中浅层滑坡分布最广。通过对降雨型浅层滑坡的变形进行分析,建立了基于功能原理的滑坡一维运动方程,并结合太沙基固结原理,研究滑坡运动过程中孔隙水压力的消散,揭示了滑坡从运动-停止的动力演化过程,构建了降雨型浅层滑坡的位移预测模型,并以都江堰塔子坪滑坡为例进行分析,通过mathmatic给出了滑坡运动的速率、位移与降雨量的量化关系式。     

大型滑坡坝溃决对下游河谷坡岸的影响分析——以白格滑坡下游50km内的河谷边坡为例

堰塞湖的泄流会对下游河谷边坡造成严重的冲刷,对下游居民的生产生活及基础设施的安全造成威胁.为了研究堰塞湖泄流对下游河谷边坡的影响,选取了具有足够代表性的金沙江白格滑坡下游一定范围(50 km)的河谷边坡为代表区域,将遥感信息提取技术、GIS技术与空间分析等方法相结合,定量地研究了堰塞湖泄流对河谷边坡的影响;并综合考虑了...     

河北省宽城县某滑坡特征与稳定性评价

位于河北省宽城县某拟建铁路将穿越一老滑坡体,体积约77×104 m3,并在滑坡前缘以路堑方式穿过,因开挖施工导致老滑坡复活.在现场地质调查基础上,阐明了滑坡所在的地质环境条件和发育特征,系统分析了老滑坡的形成原因和复活机理,即老滑坡是受附近断层影响,岩体完整性较差,而前缘河流冲刷和回漩旁蚀降低了边坡的整体稳定性,在暴雨或地震诱发下形成,而修建铁路的路堑开挖则是导致前缘抗滑段失效而复活的主要原因.在现场试验和室内试验成果基础上,分别对沿现滑面和古滑面在不同工况下的稳定性进行计算,并系统分析了铁路路堑边坡开挖对滑坡稳定性的影响程度,并对滑坡治理提出了措施建议.     

基于时序遥感影像的黄土滑坡形变与河流水位关系研究——以天水市清泉村滑坡为例北大核心CSCD

河流对岸坡的侵蚀作用是滑坡失稳的重要因素之一,特别是在中国黄土地区。因此,探讨河流水位的季节性变化对黄土边坡稳定性的影响规律,对早期黄土滑坡灾害预警具有重要作用。论文以甘肃省天水市清泉村滑坡为例,分析5年内沿岸边坡形变速率与季节性水位变化之间的关系。基于SBAS-InSAR技术获取滑坡时序形变信息,借助MNDWI与DEM获取边坡底部时序水位信息,并结合GPM降雨数据进行相关性分析,研究发现随着降雨增多、河流水位的上涨,清泉村滑坡的形变速率明显增大,在夏季时滑坡形变量增长较快,并且边坡形变相较于水位季节变化具有一定的滞后性;经相关性分析,得出水位与滑坡形变的相关性系数为0.46,降雨与滑坡形变的相关性系数为0.39,表明清泉村滑坡的形变速率与水位变化更相关。因此,河流的季节性变化对滑坡形变速率具有一定影响,进而造成河流对沿岸滑坡的侵蚀作用呈现出季节性变化。研究揭示的黄土滑坡与河流水位的季节性变化关系,对揭示河岸边坡的演化过程、滑坡识别与灾害防治具有重要意义。     

金沙江水电站工程区典型单体滑坡风险评价探讨

在对金沙江流域内的部分大型水电站工程区内的滑坡分析基础上,以两个滑坡为例,针对水电站工程区讨论了单体滑坡的风险评价方法。选取滑坡稳定性,规模和可能造成的涌浪高度3个指标进行危险性评价;并且定性地将大坝的易损性确定为高、中、低三个等级。在此基础上,对研究区的牛滚函滑坡和东岳庙滑坡进行了危险性分析和易损性评价,得出这两个单体滑坡的风险分析结果：牛滚函滑坡为低度风险,东岳庙滑坡为中度风险。研究成果为水电站工程区滑坡减灾防灾与风险管理提供了科学依据。     

HP-2型滑坡遥测系统

以自行研制的恒流式静态应变仪(中国专利号:88212764.0)为主机的HP-2型滑坡遥测系统,用作测值远传和分散设点集中遥测数据。本系统配接PC-1500A或IBM PC/XT计算机,可构成滑坡监测系统;它既能控制多点巡回检测、定点检测和通道号显示,亦可控制应变仪作半桥或全桥测量,又能控制采样时间等。1987—1990年运行结果表明,本遥测系统相当稳定可靠。     

“一带一路”地区滑坡灾害风险评估

"一带一路"倡议是中国参与全球治理的重要切入点,对"一带一路"地区滑坡灾害风险评估与区划,可为沿线国家和地区的防灾减灾提供依据。首先,选取坡度和地形起伏度两个指标,提取研究区滑坡灾害安全区域。其次,采用模糊层次分析法（FAHP）确定滑坡灾害风险评估体系并计算各因子综合权重,基于滑坡灾害风险评估模型定量评估"一带一路"地区滑坡灾害危险性、损失和风险。最后,运用滑坡灾害点和近百年"一带一路"地区滑坡灾害致死人数和经济损失空间分布分别验证评估的滑坡灾害危险性和损失。结果表明：（1）滑坡灾害安全区域主要分布在平原、盆地和沙漠等地区,仅有4.7%（56个）的滑坡灾害点分布在安全区域内,提取结果较为合理。（2）"一带一路"地区容易诱发滑坡灾害的条件为坡度介于25°~45°之间,地形起伏度大于900 m,距河网的距离小于500 m,多年平均降雨量介于400~800 mm,地震密度3×10^-4~2×10^-3个·km^-2之间,工程地质岩组为中等硬质岩体、软质岩和土质岩体。非安全区域中,滑坡灾害以中、低危险性为主,危险性评估结果精度AUC值为0.823。（3）"一带一路"地区容易造成潜在损失的滑坡灾害承灾体条件为：人口密度为80~160人·km^-2,公路线密度为0.2~0.9 km·km^-2,夜间灯光指数为20~60。非安全区域中,滑坡灾害潜在损失普遍较低,损失区划结果与近百年滑坡灾害致死人数和经济损失空间分布具有很好的一致性。（4）"一带一路"非安全区域,滑坡灾害极低、低、中等、高和极高风险区面积所占比例分别为44.7%、25.5%、15.3%、10.3%、4.2%,以极低和低风险为主。     

The use of surface monitoring data for the interpretation of landslide movement patterns

The Tessina landslide is a large, seasonally active slope failure located on the southern slopes of Mt. Teverone, in the Alpago valley of NE Italy, consisting of a complex system that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, threatens two villages and is hence subject to detailed monitoring, with high quality data being collected using piezometers, inclinometers, extensometers, and through the use of a highly innovative, automated Electronic Distance Measurement (EDM) system, which surveys the location of a large number of reflector targets once every 6 h. These systems form the basis of a warning system that protects the villages, but they also provide a very valuable insight into the patterns of movement of the landslide.In this paper, analysis is presented of the movement of the landslide, concentrating on the EDM dataset, which provides a remarkable record of surface displacement patterns. It is proposed that four distinct movement patterns can be established, which correspond closely to independently defined morphological assessments of the landslide complex. Any given block of material transitions through the four phases of movement as it progresses down the landslide, with the style of movement being controlled primarily by the groundwater conditions. The analysis is augmented with modelling of the landslide, undertaken using the Itasca FLAC code. The modelling suggests that different landslide patterns are observed for different parts of the landslide, primarily as a result of variations in the groundwater conditions. The model suggests that when a movement event occurs, displacements occur initially at the toe of the landslide, then retrogress upslope.     

基于信息量模型和机器学习方法的滑坡易发性评价研究——以四川理县为例

以阿坝藏族羌族自治州地质灾害频发的理县为研究区,从地形地貌、地质环境、水文条件和人类工程活动等方面选取11个影响因子,通过皮尔森相关系数研究各因子之间的相关性,从而构建滑坡易发性评价指标体系。利用信息量模型计算各影响因子的信息量值,从信息量模型得出的极低和低易发性分区中选取非滑坡样本,在此基础上将样本数据代入随机森林和径向基函数神经网络2种机器学习模型开展滑坡易发性评价,并通过接收灵敏度（Receiver Operating Characteristic,ROC）曲线进行精度验证。结果显示：随机森林模型预测出的高易发区单位面积内分布的滑坡点数量更为集中,在仅占6.666%的区域分布了74.026%的灾害点,评价结果优于径向基函数神经网络模型。ROC曲线中两模型AUC（Area Under Curve）值分别为0.893、0.874,说明随机森林模型具有更高的可靠性,比径向基函数神经网络在该区域地质灾害易发性评价中更具优势。     

论滑坡学

滑坡学可分为理论滑坡学和应用滑坡学．前者的分支有：滑坡发生学、滑坡运动学、滑坡组构学、滑坡形态学、滑坡断代－周期学、滑坡分类学、滑坡分布学、滑坡制图学、滑坡编目学和滑坡数据库系统等．应用滑坡学含滑坡研究方法论、技术手段和滑坡防御工程等．     

滑坡危险度区划研究述评

滑坡危险度区划是滑坡研究发展到一定深度所提出的新课题。到目前为止，我国既无统一的滑坡危险度评价理论体系，也无统一的滑坡危险度区划制图方法。因此，该项工作异常薄弱，这是造成预防不及时，措施不力，从而导致广泛、严重滑坡灾害的原因之一。滑坡危险度区划的主要目的是：①建立标准化评价体系；②滑坡信息库；③评价区域滑坡的危险性；④提供标准化危险度区划图件；⑤减灾防灾的决策依据。文章对此问题的研究动态评述基础上。提出了危险度区划的内涵和研究目标。     

Validation of landslide hazard models using a semantic engine on online news

The objective of this work is twofold: (i) automatically setting up a landslide inventory using a state-of-the art semantic engine based on data mining on online news and (ii) evaluating if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds.The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was automatically set up for the Tuscany region (23,000 km², Italy). Using a completely automated procedure, the inventory was compared with the outputs of the regional landslide early warning system and a good correspondence was found, e.g. 84% of the events reported in the news is correctly identified by the warning system.On the basis of the obtained results, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the Internet channel using an appropriate semantic engine dedicated to perform a monitoring of the Google News aggregator.Moreover, validation statistics can be used to evaluate the effectiveness of the predictive model and, if deemed necessary, an update of the rainfall thresholds could be performed to obtain an improvement of the forecasting effectiveness of the warning system.In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum or none human intervention.     

裂点发育及其对堰塞坝的稳定性影响

通过野外调查及试验对堰塞坝的稳定和裂点的发育进行研究,发现堰塞坝的稳定性主要取决于泄洪道内阶梯-深潭系统的发育程度SP和坝体上游洪峰的水流能量P.堰塞坝的保存与溃决情况采用保留的坝高比进行定量描述,对于洪峰流量小于30 m3/s山区河流,保留坝高比与SP呈线性相关;洪峰流量大于30 m3/s(＜ 30000m3/s)时,河道稳定所需的最小河床结构强度SP随着单宽水流能量P的增加而增大.堰塞坝泄洪道内不发育阶梯-深潭系统或发育程度较低的坝体,SP值小于稳定河床最小的阻力强度,将会发生下切、溯源冲刷并引起溃坝.保留的堰塞坝在泥沙淤积和水流的长期作用下会形成裂点,对河床下切起到控制作用,降低再次发生滑坡的风险.大型裂点能改变河床演变和河流地貌,连续堰塞坝形成的裂点能长期保存并形成优美的自然景观,创造良好的河流生态环境.     

Spatially and temporally distributed modeling of landslide susceptibility

Mapping of landslide susceptibility in forested watersheds is important for management decisions. In forested watersheds, especially in mountainous areas, the spatial distribution of relevant parameters for landslide prediction is often unavailable. This paper presents a GIS-based modeling approach that includes representation of the uncertainty and variability inherent in parameters. In this approach, grid-based tools are used to integrate the Soil Moisture Routing (SMR) model and infinite slope model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds by combining climate data, a digital elevation model, soil, and land use data. The infinite slope model is used for slope stability analysis and determining the factor of safety for a slope. Monte Carlo simulation is used to incorporate the variability of input parameters and account for uncertainties associated with the evaluation of landslide susceptibility. This integrated approach of dynamic slope stability analysis was applied to the 72-km² Pete King watershed located in the Clearwater National Forest in north-central Idaho, USA, where landslides have occurred. A 30-year simulation was performed beginning with the existing vegetation covers that represented the watershed during the landslide year. Comparison of the GIS-based approach with existing models (FSmet and SHALSTAB) showed better precision of landslides based on the ratio of correctly identified landslides to susceptible areas. Analysis of landslide susceptibility showed that (1) the proportion of susceptible and non-susceptible cells changes spatially and temporally, (2) changed cells were a function of effective precipitation and soil storage amount, and (3) cell stability increased over time especially for clear-cut areas as root strength increased and vegetation transitioned to regenerated forest. Our modeling results showed that landslide susceptibility is strongly influenced by natural processes and human activities in space and time; while results from simulated outputs show the potential for decision-making in effective forest planning by using various management scenarios and controlling factors that influence landslide susceptibility. Such a process-based tool could be used to deal with real-dynamic systems to help decision-makers to answer complex landslide susceptibility questions.