基于物理力学机制的滑坡数值预报模式: 综述、挑战与机遇

滑坡预测预报是地质灾害防治领域长期以来备受关注的前沿科学问题。当前的研究框架专注于滑坡的变形行为特征与外动力因素, 面临着普适性不强与预报精准度不高的双重瓶颈问题。基于目前研究现状, 系统梳理了滑带流变力学行为与强度弱化效应的内涵, 阐述了滑坡渐进破坏演化机制, 总结了滑坡预测预报模型所包含的类型, 并介绍了其中的典型模型, 指出当前研究主要存在如下问题: ①滑坡演化物理力学模型尚需扩展; ②预测预报模型未能充分结合滑坡演化过程和物理力学模型; ③物理力学模型预测与多场监测数据间的兼容性问题未能实际解决。针对上述问题, 阐述了基于物理力学过程的滑坡预测预报所面临的挑战, 并立足多学科融合与交叉, 提出了开展滑坡预测预报研究的新思路。新思路要求从滑坡滑带介质特性与流变力学行为出发, 建立滑坡演化过程物理力学模型, 紧密结合实时多场监测数据, 建立滑坡数值预报模式, 实现滑坡物理力学过程实时动态更新, 以期实现理论与技术的突破。      

新铺下二台滑坡变形机制及中长期预报模型

以奉节新铺下二台滑坡为例, 基于GPS位移监测数据、裂缝数据、降雨量及库水位等多源数据, 总结分析了大型古滑坡的复活规律, 引入滑坡中长期预报模型, 实现了以季度或月份为时间单位的跨水文年滑坡位移预测, 并通过岩土体蠕变压缩模型, 验证了推移式滑坡后缘裂缝形成机理。结果表明: ①降雨是下二台滑坡变形的主导因素, 滑坡变形使得滑体产生裂缝并成为降雨入渗通道, 加剧了岩体破碎与软弱层软化, 降低了滑坡稳定性, 集中持续降雨可使滑坡失稳破坏; ②通过模型预测值与地表监测数据的比较, 将年降雨量作为滑坡中长期预报模型中的主控因素具有实际可操作性且有助于提高滑坡中长预报精度; ③推移式滑坡后缘裂缝由滑坡推移式位移和岩土体压缩形成, 引入蠕变压缩模型计算的裂缝宽度并和监测数据的比较说明, 蠕变压缩模型非常适合该类边坡, 同时应用岩土体蠕变压缩模型反推得到岩土体平均变形模量, 判断岩体破碎程度, 可以为滑坡稳定性分析及后续工程治理提供参考。      

基于多因子及泰勒级数的滑坡变形预测模型研究

将滑坡的变形看作时间、月降雨量、气温的函数,使用泰勒级数建立它们的函数关系,并将泰勒级数展开至二次项,建立卡尔曼滤波模型,用于滑坡变形的预测预报。实例计算表明,卡尔曼滤波模型的拟合效果和预测效果良好,可用于土质滑坡变形的短期预测预报。     

参数调整对气象预测的B-P网络模型性能的影响

为了探索ＢＰ网络的参数调整特性,进行了参数α、β的选取对ＢＰ算法的收敛速度和模型的稳定性的影响研究。通过ＢＰ网络用于气象预测建模的参数调整个例分析表明：参数α、β的取值对ＢＰ模型的稳定性无显著影响,但参数值的调整尤其是β值的调整对建模的收敛速度有明显的影响。     

阶跃型位移特征滑坡时间预测预报研究

滑坡时间预测预报目前主要以滑坡最终破坏的时间为目标函数,但对于变形特征为阶跃型的滑坡却难以准确地预测其
破坏时间。为此,提出以位移作为此类滑坡时间预报的目标函数。将滑坡位移分解为蠕变位移和波动位移,采用二次移动平均法
分别提取,然后采用多项式拟合和灰色GM(1,1)模型分别对蠕变位移和波动位移进行预测,最后将两部分预测位移相加得到滑坡
预测的总位移。以典型阶跃型位移特征滑坡———三峡库区八字门滑坡为例,运用其位移监测数据进行验证,并对多模型预测结果
进行对比分析,结果表明,该位移预测模型预测精度良好,能较好地预测阶跃型位移特征滑坡位移。      

重大滑坡预测预报研究进展与展望

我国是世界上滑坡灾害最严重的国家之一, 重大滑坡灾害严重威胁人民生命财产安全和国家重大战略实施。滑坡精准预测预报是防灾减灾的前提, 也是亟待突破的世界性科学难题。以重大滑坡预测预报为目标, 聚焦滑坡演化过程与物理力学机制核心科学问题, 凝炼了滑坡启滑关联机制、滑坡启滑物理力学机制、滑坡过程预测预报理论3个关键科学问题, 提出了如下研究思路: 以系统论、控制论和信息论为指导, 依托大型野外试验场, 采用现场原型试验与多场关联监测、大型物理模型试验、多场耦合模拟等技术手段, 以滑坡孕育过程为基础, 提出了重大滑坡的启滑分类; 揭示锁固解锁型、静态液化型和动水驱动型滑坡启滑物理力学机制, 建立相应的启滑判据; 构建重大滑坡数值预报模式与实时预报平台, 创立基于物理力学过程的滑坡预测预报理论。通过实施, 可奠定上述3类滑坡预测预报的地质、力学与物理基础, 引领重大滑坡预测预报研究, 保障国家重大战略的顺利实施, 契合国家防灾减灾重大需求。      

灾情的B－P网络评估新模型

提出用人工神经网络Ｂ－Ｐ模型进行灾情评估的新方法，该方法将灾情的划分等级作为训练样本集，以指标的各级标准值作为样本的输入特征值，建立多参数的Ｂ－Ｐ网络灾情评估模型。该模型用于５１个灾情个例评估结果表明Ｂ－Ｐ网络用于灾情评估具有一定的科学性和实用性。     

因子和样本优化及最优预报方程模型

为了选择与预报量有密切关系的因子和有代表性的样本,分别采用投影寻踪回归（ＰＰＲ）和ＢＰ神经网络对因子和样本进行优选。实例分析表明：优选出的样本保留了全部样本的大部分信息;用优选出的因子建模可达到与用全部因子建模相近的拟合和预报效果。     

基于地球多传感器网络信息的潜在滑坡判识模型

潜在滑坡的判识是滑坡预测预报中的关键问题,潜在滑坡早期判识能够有效减少灾害的发生。基于滑坡灾害诱发的各种影响因素,利用地球多源时空信息和多传感器网络,遥感监测潜在滑坡体,利用监测设备获取滑坡岩性、坡体结构、地貌形态、活动迹象等关键控制信息,从中选取滑坡灾害诱发的主要控制要素作为判识指标,建立基于多源信息的潜在滑坡多因素判识模型;特别是根据滑坡的成灾规律,分析潜在滑坡孕育过程中地貌形态改变、成灾条件变化与滑坡发生的临滑诱发条件,建立基于不同信息源的滑坡控制因素判识模型。最后,通过汶川地震灾区垮梁子滑坡体实例分析,验证潜在滑坡综合判识模型并进行优化,从而为滑坡灾害的早期判识预测提供依据。     

变质岩区大型高位滑坡的变形监测预报研究北大核心CSCD

以某变质岩区大型高位滑坡变形监测成果为基础,开展既有变形特征分析和变形发展分析。结果表明,CEEMDAN-PSR-KELM-ARIMA模型在滑坡变形预测中具有较强的适用性,所得预测结果的相对误差均值范围为2.00%~2.03%,其方差值也较小,具有较优的预测精度及稳定性;预报等级属于Ⅲ级-橙色预报,为较危险状态;滑坡变形速率具减小趋势,但累积变形仍会进一步增加。     

Dynamic assessment of rainfall-induced shallow landslide hazard

The assessment of rainfall-induced shallow landslide hazards is a significant issue in the Three Gorges Reservoir area in China due to the rapid development of land in the past two decades. In this study, a probabilistic analysis method that combines TRIGRS and the point-estimate method for evaluating the hazards of shallow landslides have been proposed under the condition of rainfall over a large area. TRIGRS provides the transient infiltration model to analyze the pore water pressure during a rainfall. The point-estimate method is used to analyze the uncertainty of the soil parameters, which is performed in the geographic information system (GIS). In this paper, we use this method to evaluate the hazards of shallow landslides in Badong County, Three Gorges Reservoir, under two different types of rainfall intensity, and the results are compared with the field investigation. The results showed that the distribution of the hazard map is consistent with the observed landslides. To some extent, the distribution of the hazard map reflects the spatial and temporal distribution of the shallow landslide caused by rainfall.     

Spatial association between landslides and environmental factors over Guizhou Karst Plateau,China

Guizhou Karst Plateau is located at the center of the karst region in Asia, where landslides are a typical disaster. Affected by the local karst environment, the landslides in this region have their own characteristics. In this study, 3975 landslide records from inventories of the Guizhou karst plateau are studied. The geographical detector method is used to detect the dominant casual factor and predominant multi-factor combinations for the local landslides. The results show that landslides are prone to areas on slopes between 10° and 35°, of clay rock, in close proximity to gullies, and especially in areas of moderate vegetation, dryland, and mild rocky desertification. Continuous precipitation over 10 days has a great effect on landslide occurrence. Compared with the individual factors, the impact of two-factor interaction has greater explanatory power for landslide volume. The volume of earthquake-induced landslides is predominantly controlled by the interactions of faults and slopes, while that of humaninduced landslides is affected by the interactions of land cover and hydrological conditions. For rainfallinduced landslides, the dominant interactions vary in different regions. In the central karst basin, the interactions between faults and precipitation can explain over 90% of the variations in landslide volumes. In the southern hilly karst region, the interactions between lithology and slope can explain over 71% of the variations in landslide volume and those between fault and land-use can explain 50% of the variations of the landslide volumes in the northeastern mountainous karst region.     

Investigation and Assessment of Landslides and Debris Flows in Sichuan Province of China by Remote Sensing Technique

Taking TM images, ETM images, SPOT images, aerial photos and other remote sensing data as fundamental sources, this research makes a thorough investigation on landslides and debris flows in Sichuan Province, China, using the method of manual interpretation and taking topography maps as references after the processes of terrain correction, spectral matching, and image mosaic. And then, the spatial characteristics of landslides and debris flows in the year of 2005 are assessed and made into figures. The environmental factors which induce landslides and debris flows such as slope, vegetation coverage, lithology, rainfall and so on are obtained by GIS spatial analysis method. Finally, the relationships of landslides or debris flows with some environmental factors are analyzed based on the grade of each environmental factor. The results indicate： 1） The landslides and debris flows are mainly in the eastern and southern area of Sichuan Province, however, there are few landslides and debris flows in the western particularly the northwestern Sichuan. 2） The landslides and debris flows of Sichuan Province are mostly located in the regions with small slope degree. The occurring rate of debris flow reduces with the increase of the vegetation coverage degree, but the vegetation coverage degree has little to do with the occurrence of landslide. The more rainfall a place has, the easier the landslides and debris flows take place.     

基于SBAS-InSAR的矿区采空区潜在滑坡综合识别方法

针对位于山区且受大量采空区影响的边坡,利用传统测量方法监测耗费人力、物力且光学遥感难以定量识别其是否为潜在滑坡的问题,本文提出一种融合研究区小基线集（SBAS-InSAR）地表监测数据、坡度及坡向的识别方法。通过SBAS-InSAR技术获得研究区地表雷达视线（LOS）方向形变速率,将其转化为垂直方向形变速率,并根据研究区DEM建立坡度及坡向分析图,根据不同山体的坡度、坡向找到易发生滑坡的区域,融入该区域垂直方向的时序形变速率,对其进行滑坡识别。实验表明：卡房镇周边受采空区的影响较大,多数区域垂直方向年形变速率大于10 mm/a;通过本文方法对研究区潜在滑坡进行识别,发现在研究区的21处历史滑坡点中,有16处被识别为潜在滑坡,5处未被识别但也位于发生形变的区域内,表明本文方法对潜在滑坡的识别精度高,具有可行性。该研究为识别采空附近的潜在滑坡提供了一种新的思路,可以有效识别采空区附近山体边坡是否处于潜在的、不明显的滑动状态,对滑坡灾害具有预警作用。     

Landslide data mosaicking based on an airborne laser point cloud and multi-beam sonar images

Landslides are one of the most disastrous geological hazards in southwestern China. Once a landslide becomes unstable, it threatens the lives and safety of local residents. However, empirical studies on landslides have predominantly focused on landslides that occur on land. To this end, we aim to investigate ashore and underwater landslide data synchronously. This study proposes an optimized mosaicking method for ashore and underwater landslide data. This method fuses an airborne laser point cloud with multi-beam depth sounder images.Owing to their relatively high efficiency and large coverage area, airborne laser measurement systems are suitable for emergency investigations of landslides.Based on the airborne laser point cloud, the traversal of the point with the lowest elevation value in the point set can be used to perform rapid extraction of the crude channel boundaries. Further meticulous extraction of the channel boundaries is then implemented using the probability mean value optimization method. In addition, synthesis of the integrated ashore and underwater landslide data angle is realized using the spatial guide line between the channel boundaries and the underwater multibeam sonar images. A landslide located on the right bank of the middle reaches of the Yalong River is selected as a case study to demonstrate that the proposed method has higher precision thantraditional methods. The experimental results show that the mosaicking method in this study can meet the basic needs of landslide modeling and provide a basis for qualitative and quantitative analysis and stability prediction of landslides.     

台风-非台风降雨型滑坡的多时段临界雨量值预测模型

统计确定临界降雨量是滑坡早期预警常用的方法。东南沿海地区台风暴雨不同于一般降雨, 常引发滑坡灾害, 从而威胁沿海地区人民生命财产安全。为了建立台风和非台风降雨型滑坡临界降雨量预测模型, 以浙江丽水市为例, 基于2010-2020年台风暴雨、非台风降雨诱发滑坡与降雨量的统计, 构建了丽水市滑坡发生概率和有效降雨量的关系, 提出了多时长临界降雨量预测模型, 并开展了台风和非台风降雨型滑坡预测模型结果的对比分析。结果表明, 非台风降雨与台风暴雨之间雨型和雨量差异是导致丽水市内2类降雨滑坡预测模型差异的主要原因; 以多时长预测模型确定的临界雨量值法和有效降雨天数更加符合丽水市降雨型滑坡的预测预报, 且预测精度相比于传统相关性分析法更高。研究成果对于开发区域降雨型滑坡预测模型具有理论意义, 对我国东南沿海地区汛期滑坡早期预警具有重要实际意义。      

Long-term activity of earthquake-induced landslides: A case study from Qionghai Lake Basin,Southwest of China

Earthquake-triggered landslides are a major geological hazard in the eastern Tibetan Plateau, and have prolonged impact on earth surface processes and fluvial system. To determine how long co-seismic landslides affect basins, a massive number of landslides existing in Qionghai Lake Basin were investigated for landslide distribution characteristics and geomorphological evidences, with further comparison and analysis using historic seismic analog method. The landslides found in Qionghai Lake Basin showed clear features of seismic triggering with strongly controlled by Zemuhe fault. These landslides are still active at present. Some new slides generally occur in ancient slope failure zones causing serious secondary hazards in recent years. In this study we strengthen the idea that the landslides triggered by the 185o Xichang earthquake （Ms7.5） have long term activity and prolonged impact on the mountain disasters with a period of more than 16o years. Our results support growing evidence that coseismic landslides have a prolonged effect on secondary disasters in a basin, and invite more careful consideration of the relationship between current basin condition and landslide history for a longer period.     

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Landslide susceptibility assessment using the certainty factor and analytic hierarchy process

A new approach combining the certainty factor (CF) and analytic hierarchy process (AHP) methods was proposed to assess landslide susceptibility in the Ziyang district, which is situated in the Qin-Ba Mountain region, China. Landslide inventory data were collected based on field investigations and remote sensing interpretations. A total of 791 landslides were identified. A total of 633 landslides were randomly selected from this data set as the training set, and the remaining landslides were used for validation as the test set. Nine factors, including the slope angle, slope aspect, slope curvature, lithology, distance to faults, distance to streams, precipitation, road network intensity degree and land use were chosen as the landslide causal factors for further susceptibility assessment. The weight of each factor and its subclass were calculated by AHP and CF methods. Landslide susceptibility was compared between the bivariate statistical method and the proposed CF-AHP method. The results indicate that the distance to streams, distance to faults and lithology are the most dominant causal factors associated with landslides. The susceptibility zonation was categorized into five classes of landslide susceptibility, i.e., very high, high, moderate, low and very low level. Lastly, the relative operating characteristics (ROC) curve was used to validate the accuracy of the new approach, and the result showed a satisfactory prediction rate of 78.3%, compared to 69.2% obtained with the landslide susceptibility index method. The results indicate that the CF-AHP combined method is more appropriate for assessing the landslide susceptibility in this area.     

Simulation of landslide run-out by considering frictional heating and thermal pressurization

Some of the remarkable characteristics of natural landslides, such as surprisingly long travel distances and high velocities, have been attributed to the mechanisms of frictional heating and thermal pressurization. In this work, this mechanism is combined with a depth-averaged model to simulate the long runout of landslides in the condition of deformation. Some important factors that influence frictional heating and thermal pressurization within the shear zone are further considered, including velocity profile and pressurization coefficient. In order to solve the coupled equations, a combined computational method based on the finite volume method and quadratic upwind interpolation for convective kinematics scheme is proposed. Several numerical tests are performed to demonstrate the feasibility of the computational scheme, the influence of thermal pressurization on landslide run-out, and the potential of the model to simulate an actual landslide.