秦皇岛市工程场地地面运动峰值加速度预测

工程场地地面运动峰值加速度是强震区城市发展规划、抗震防灾的重要依据,也是工程建筑抗震设计的基本参数。本文在研究秦皇岛市区域地震地质环境和地震活动规律的基础上,确定了区域潜在震源区及相应的地震活动性参数。将该市工程场地划分为规则网格,采用地震危险性分析的概率方法,计算出各场地在各不同年限内所遭受到的不同地震危险性概率水平。最后,编制出了供一般工业与民用建筑设计使用的,按50年10％给定概率水平的秦皇岛市地面运动加速度预测图。     

GIS-based evaluation on the fault motion-induced coseismic landslides

Earthquake-induced potential landslides are commonly estimated using landslide susceptibility maps. Nevertheless, the fault location is not identified and the ground motion caused by it is unavailable in the map. Thus, potential coseismic landslides for a specific fault motion-induced earthquake could not be predicted using the map. It is meaningful to incorporate the fault location and ground motion characteristics into the landslide predication model. A new method for a specific fault motion-induced coseismic landslide prediction model using GIS (Geographic Information System) is proposed herein. Location of mountain ridges, slope gradients over 45 o , PVGA (Peak Vertical Ground Accelerations) exceeded 0.15 g, and PHGA (Peak Horizontal Ground Accelerations) exceeded 0.25 g of slope units were representing locations that initiated landslides during the 1999 Chi-Chi earthquake in Taiwan. These coseismic landslide characteristics were used to identify areas where landslides occurred during Meishan fault motion-induced strong ground motions in Chiayi County in Taiwan. The strong ground motion (over 8 Gal in the database, 1 Gal = 0.01 m/s 2 , and 1 g = 981 Gal) characteristics were evaluated by the fault length, site distance to the fault, and topography, and their attenuation relations are presented in GIS. The results of the analysis show that coseismic landslide areas could be identified promptly using GIS. The earthquake intensity and focus depth have visible effects on ground motion. The shallower the focus depth, the larger the magnitude increase of the landslides. The GIS-based landslide predication method is valuable combining the geomorphic characteristics and ground motion attenuation relationships for a potential region landslide hazard assessment and in disaster mitigation planning.     

Characteristics of clustering debris flows in Wenchuan earthquake zone

Clustering debris-flow events, namely many debris flows simultaneously triggered by a regional rainstorm in a large-scale mountainous area, occurred in four regions of Wenchuan earthquake stricken areas in 2008 and 2010. The characteristics of the clustering debris flows are examined with regard to triggering rainfall, formation process, and relationship with the earthquake by field survey and remote sensing interpretation. It is found that the clustering events occurred nearly at the same time with the local peak rainstorms, and the rainfall intensity-duration bottom limit line for clustering debris flows is higher than the worldwide line. It means that more rainfall is needed for the occurrence of the clustering debris flows. Four kinds of major formation processes for these debris flows are summarized： tributary-dominated, mainstream- dominated, transformation from slope failures, and mobilization or liquefaction of landslide. The four regions has a spatial correlation with the strong- quake-influenced zone with the peak ground acceleration = 0.2 g and the seismic intensity 〉 X.     

基于贝叶斯优化机器学习超参数的滑坡易发性评价

利用机器学习模型进行滑坡易发性评价时, 不同的超参数设置往往会导致评价结果的不同。采用贝叶斯算法对4种常见机器学习模型(逻辑回归LR、支持向量机SVM、人工神经网络ANN和随机森林RF)的超参数进行了优化, 探索了该算法对滑坡易发性机器学习模型的优化效果。以湘中地区4县(安化县、新华县、桃江县和桃源县)滑坡易发性评价为例说明该算法的可行性与适用性。基于滑坡历史编录, 确定研究区内1 017个滑坡点, 并选定15个滑坡影响因子, 以此构建滑坡易发性模型的训练集和测试集。利用贝叶斯优化算法对4种机器学习模型的主要超参数进行了优化, 依据优化后的超参数建立了4种优化模型, 并使用AUC值等指标来比较其预测能力。结果表明: 经超参数优化后的4种机器学习模型预测性能均有所提高, 且基于贝叶斯优化的随机森林模型表现最好。      

Analysis of the stability and seismic behavior of the geosynthetic-reinforced embankments under earthquake

The stability and seismic behavior of geosynthetic-reinforced embankments during the earthquake is not well known.In this paper,the damage types of embankments were summarized,and the seismic stability of reinforced embankment were analyzed through an earthquake damage investigation in the Wenchuan earthquake region.Then,large-scale shaking table model tests were performed on the geosynthetic-reinforced embankment.The results show that the damage level of the reinforced embankment was almost less than that of the unreinforced embankment.The peak seismic earth pressure was nonlinear along the height of the embankment,the largest peak seismic earth pressure was roughly in the middle of the embankment slope.The peak ground accelerations(PGA)amplification factor first showed an increasing pattern and then a decreasing pattern with the increase of elevation,but there was a final increasing trend along the height of the reinforced embankment.The results can help to establish the proper design of the reinforcement embankments under earthquake conditions.     

基于GeoKSCloud的地震影响场分析云服务研究——以福建省为例

地震发生后处于不同地震烈度区域的地物受灾程度不同。快速准确地获取地震影响或波及范围内地震烈度空间分布,是震后应急救援的重要依据和主要参数。依托云计算技术,以云服务方式构建地震烈度速报系统,提供可扩展、可配置、开放透明的地震影响场分析应用服务,将是我国烈度速报系统研究开发与应用中的一项新技术和发展趋势。本文依托研究小组自主研发的地理知识云服务系统GeoKSCloud,以福建省为研究区域,在提出适用于福建省地震烈度衰减关系与地震动峰值加速度场地校正方法的基础上,开展了地震影响场分析云服务系统的设计与实现工作,分析了地震影响场分析云服务的运行机制和服务组合工作流;实现了地震烈度衰减关系计算方法、场地放大因子校正方法、网格点场地类别属性获取、网格点沿地震衰减长短轴方向的坐标变换等相关原子服务的云服务封装,以及支撑数据云存储、网络地理信息系统的云服务门户的开发与集成;最后,以1604年发生在泉州近海7.5级大地震为震例,在云服务门户进行了全省范围内所有等间距网格点地震峰值加速度(基岩PGA和地表PGA)的计算、插值,并进行计算结果与实际调查数据的对比分析。结果表明,因充分考虑了具体场地的放大效应,构建的地震影响场分析云服务,不仅较传统单凭地震烈度衰减关系确定地震动峰值加速度方法更加精细化,而且提供的服务与传统的网络服务相比具有可扩展、可配置、开放透明等明显优势,可为我国烈度速报系统研究与应用提供一个共性技术与支撑服务平台,创新地震烈度速报的运营模式。     

Seismic responses of the steel-strip reinforced soil retaining wall with full-height rigid facing from shaking table test

To investigate the seismic response of the steel-strip reinforced soil retaining wall with fullheight rigid facing in terms of the acceleration in the backfill, dynamic earth pressure in the backfill, the displacements on the facing and the dynamic reinforcement strain distribution under different peak acceleration, a large 1-g shaking table test was performed on a reduced-scale reinforced-earth retaining wall model. It was observed that the acceleration response in non-strip region is greater than that in potential fracture region which is similar with the stability region under small earthquake, while the acceleration response in potential fracture region is greater than that in stability region in middle-upper of the wall under moderately strong earthquakes. The potential failure model of the rigid wall is rotating around the wall toe. It also was discovered that the Fourier spectra produced by the inputting white noises after seismic wave presents double peaks, rather than original single peak, and the frequency of the second peak trends to increase with increasing the PGA (peak ground amplitude) of the excitation which is greater than 0.4 g. Additionally, the non-liner distribution of strip strain along the strips was observed, and the distribution trend was not constant in different row. Soil pressure peak value in stability region is larger than that in potential fracture region. The wall was effective under 0.1 g-0.3 g seismic wave according to the analyses of the facing displacement and relative density. Also, it was discovered that the potential failure surface is corresponds to that in design code, but the area is larger. The results from the study can provide guidance for a more rational design of reinforced earth retaining walls with full-height rigid facing in the earthquake zone.     

Fuzzy-support vector machine geotechnical risk analysis method based on Bayesian network

Machine learning method has been widely used in various geotechnical engineering risk analysis in recent years. However, the overfitting problem often occurs due to the small number of samples obtained in history. This paper proposes the FuzzySVM(support vector machine) geotechnical engineering risk analysis method based on the Bayesian network. The proposed method utilizes the fuzzy set theory to build a Bayesian network to reflect prior knowledge, and utilizes the SVM to build a Bayesian network to reflect historical samples. Then a Bayesian network for evaluation is built in Bayesian estimation method by combining prior knowledge with historical samples. Taking seismic damage evaluation of slopes as an example, the steps of the method are stated in detail. The proposed method is used to evaluate the seismic damage of 96 slopes along roads in the area affected by the Wenchuan earthquake. The evaluation results show that the method can solve the overfitting problem, which often occurs if the machine learning methods are used to evaluate risk of geotechnical engineering, and the performance of the method is much better than that of the previous machine learning methods. Moreover,the proposed method can also effectively evaluate various geotechnical engineering risks in the absence of some influencing factors.     

Application of Hilbert-Huang Transform to the Analysis of the Landslides Triggered by the Wenchuan Earthquake

A steep rock hill with two side slopes located at DK30+256 of National Road 213 was used as a prototype for analysis. The full process from initial deformation to sliding of the slope during ground shaking was simulated by using a new Continuum-based Discrete Element Method. During the earthquake, when shaking amplitudes were lower,the stress concentration points firstly appeared at the top of the slip mass, and then some tension failure points appeared, followed by shear failure points. At the same time, both the instantaneous frequencies of accelerations in the bedrock and that in the slip mass basically stayed in two different ranges. The energy transmittance coefficients of the sliding surface also stayed in a high range. As the ground shaking lasted,the number of failure points gradually increased until landslide occurrence. The instantaneous frequencies of accelerations in the slip mass and the energy transmittance coefficients of sliding surface gradually decreased, and both finally converged to a lower range. And then, the reasons triggering landslides are analysis in the joint time-frequency domain using Hilbert-Huang Transform, as follows: the differences of distribution and dissipation of the earthquake energy and the inconsistency of movements between the slip mass and the bedrock were the two major influence factors.     

考虑地震危险性的倾倒变形边坡风险定量分析

风险分析与评估是解决边坡固有不确定性的重要工具, 但同时考虑外在荷载和内在岩土力学参数的不确定性, 对边坡进行系统定量风险分析的研究较少。以西藏扎拉水电站厂后倾倒变形边坡为例, 基于场地地震峰值加速度概率密度函数和不同地震峰值加速度下边坡失稳概率拟合函数, 采用数值积分计算了边坡在设计基准期的失稳概率, 并采用离散元方法对边坡失稳后的影响范围进行了数值模拟, 在此基础上进行了承灾体易损性分析及定量风险计算, 最后采用ALARP准则进行了风险评价。研究表明, 考虑地震危险性条件下, 扎拉水电站厂后倾倒变形边坡在50 a设计基准期内失稳概率为0.061 9;边坡对水电站地面厂房存在较大威胁, 相应财产风险为5 482万元; 根据ALARP准则, 边坡风险处于不可接受区, 需采取措施防范或规避风险。研究成果对于边坡治理工程决策及风险管理具有指导意义。      

GIS-based earthquake-triggered landslide hazard zoning using contributing weight model

Earthquake-triggered landslides have aroused widespread attention because of their tremendous ability to harm people's lives and properties.The best way to avoid and mitigate their damage is to develop landslide hazard maps and make them available to the public in advance of an earthquake.Future construction can then be built according to the level of hazard and existing structures can be retrofit as necessary.During recent years various approaches have been made to develop landslide hazard maps using statistical analysis or physical models.However,these methods have limitations.This study introduces a new GIS-based approach,using the contributing weight model,to evaluate the hazard of seismically-induced landslides.In this study,the city and surrounding area of Dujiangyan was selected as the research area because of its moderate-high seismic activity.The parameters incorporated into the model that related to the probability of landslide occurrence were:slope gradient,slope aspect,geomorphology,lithology,base level,surface roughness,earthquake intensity,fault proximity,drainage proximity,and road proximity.The parameters were converted into raster data format with a resolution of 25×25m2 pixels.Analysis of the GIS correlations shows that the highest earthquake-induced landslide hazard areas are mainly in the hills and in some of the moderately steep mountainous areas of central Dujiangyan.The highest hazard zone covers an area of 11.1% of the study area,and the density distribution of seismically-induced landslides was 3.025/km2 from the 2008 Wenchuan earthquake.The moderately hazardous areas are mainly distributed within the moderately steep mountainous regions of the northern and southeastern parts of the study area and the hills of the northeastern part;covering 32.0% of the study area and with a density distribution of 2.123/km2 resulting from the Wenchuan earthquake.The lowest hazard areas are mainly distributed in the topographically flat plain in the northeastern part and some of the relatively gently slopes in the moderately steep mountainous areas of the northern part of Dujiangyan and the surrounding area.The lowest hazard areas cover 56.9% of the study area and exhibited landslide densities of 0.941/km2 and less from the Wenchuan earthquake.The quality of the hazard map was validated using a comparison with the distribution of landslides that were cataloged as occurring from the Wenchuan earthquake.43.1% of the study area consists of high and moderate hazardous zones,and these regions include 83.5% of landslides caused by the Wenchuan earthquake.The successful analysis shows that the contributing weight model can be effective for earthquake-triggered landslide hazard appraisal.The model's results can provide the basis for risk management and regional planning is.     

Analysing post-earthquake landslide susceptibility using multi-temporal landslide inventories——a case study in Miansi Town of China

The earthquake that occurred on May 12, 2008, in Wenchuan County aroused a great deal of research on co-seismic landslide susceptibility assessment, but there is still a lack of an evaluation method that considers the activity state of the landslide itself. Therefore, this paper establishes a new susceptibility evaluation model that superimposes the active landslide state based on previous susceptibility evaluation models. Based on a multi-phase landslide database, the probabilistic approach was used to evaluate landslide susceptibility in the Miansi town over many years. We chose the elevation, slope, aspect, and distance from the channel as trigger factors and then used the probability comprehensive discrimination method to calculate the probability of landslide occurrence. Then, the susceptibility results of each period were calculated by superposition with the activity rate. The results show that between 2008 and 2014, the proportion of areas with low landslide susceptibility in the study area was the largest, and the proportionof areas with the highest susceptibility was minimal. The landslide area with highest susceptibility gradually decreased from 2014 to 2017. However, in 2017, 15.06% of the area was still with high susceptibility, and relevant disaster prevention and reduction measures should be taken in these areas. The larger area under the receiver operating characteristic curve(AUC) indicates that the results of the landslide susceptibility assessment in this study are more objective and reliable than those of previous models. The difference in the AUC values over many years shows that the accuracy of the evaluation results of this model is not constant, and a greater number of landslides or higher landslide activity corresponds to a higher accuracy of the evaluation results.     

Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas.The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability.Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone,with similar topographical and geological conditions.The two earthquakes are both featured by thrust fault and similar seismic mechanism.This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake.Six influencing parameters were taken into consideration: distance from the seismic fault,slope gradient,lithology,distance from drainage,elevation and Peak Ground Acceleration(PGA).The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan,Baoxing and Tianquan counties.The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work.The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area.The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.     

支持向量机与Newmark模型结合的地震滑坡易发性评估研究

Newmark位移模型是研究地震滑坡易发性的经典模型,机器学习方法支持向量机模型也越来越多的应用到滑坡易发性评估研究。本文将Newmark位移模型与支持向量机模型相结合,建立基于物理机理的地震滑坡易发性评估模型并应用于2008年汶川地震重灾区汶川县。从震后遥感影像目视解译出汶川县1900处地震诱发滑坡,并将其随机划分为70%的训练数据集和30%的验证数据集。选择地形起伏度、坡度、地形曲率、与构造断裂带距离、与水系距离、与道路距离6个因子与Newmark位移值共同作为地震滑坡易发性影响因素。利用ROC曲线和模型不确定性等指标对模型结果进行评估,并与二元统计模型频率比和多元统计模型Logistic回归的结果进行对比。结果表明：与频率比和Logistic回归模型相比,支持向量机模型的正确率最高,训练集和验证集ROC曲线下的面积分别为0.876和0.851。将模型应用于绘制汶川县地震滑坡易发性图,结果显示滑坡易发性图与实际的滑坡点位分布一致性较高,有80.4%的滑坡位于极高和高易发区。这说明支持向量机与Newmark位移方法结合建立的地震滑坡易发性评估模型有较高的预测价值,可以为滑坡风险评估和管理提供依据。     

Post-earthquake Rainfall-triggered Slope Stability Analysis in the Lushan Area

The "4.20" Lushan earthquake in Sichuan province, China has induced a large amount of geological hazards and produced abundant loose materials which are prone to post-earthquake rainfalltriggered landslides. A detailed landslide inventory was acquired through post-earthquake emergent field investigation and high resolution remote sensing interpretation. The rainfall analysis was conducted using historical rainfall records during the period from 1951 to 2010. Results indicate that the average annual rainfall distribution is heterogeneous and the largest average annual rainfall occurs in Yucheng district. The Stability Index MAPping(SINMAP)model was adopted to assess and analyze the postearthquake slope stability under different rainfall scenarios(light rainfall, moderate rainfall, heavy rainfall, and rainstorm). The model parameters were calibrated to reflect the significant influence of strong earthquakes on geological settings. The slope stability maps triggered by different rainfall scenarios wereproduced at a regional scale. The effect of different rainfall conditions on the slope stability is discussed.The expanding trend of the unstable area was quantitatively assessed with the different critical rainfall intensity. They provide a new insight into the spatial distribution and characteristics of postearthquake rainfall-triggered landslides in the Lushan seismic area. An increase of rainfall intensity results in a significant increase of unstable area. The heterogeneous distribution of slope instability is strongly correlated with the distribution of earthquake intensity in spite of different rainfall conditions. The results suggest that the both seismic intensity and rainfall are two crucial factors for postearthquake slope stability. This study provides important references for landslide prevention and mitigation in the Lushan area after earthquake.     

四川省滑坡灾害气象预警模型建立与验证

四川省滑坡灾害严重,特别是2008年之后,灾情显著加剧,如何预防滑坡灾害是保护人民生命财产安全的有效途径。滑坡灾害的预警模型研究是滑坡灾害预防领域的核心课题。本文对四川省滑坡灾害危险性进行了评价,并开展了滑坡灾害气象风险预警模型研究。①以确定性系数的方法量化坡度、地形起伏度、水文地质岩性、植被覆盖度、地震烈度和年均降雨量因子,建立逻辑回归模型,定量地进行四川省滑坡灾害危险性区划,并对结果进行验证。结果表明,四川省滑坡灾害高危险性区域成“Y”字型分布,此外川中、川东北地区滑坡灾害危险性也非常高,这与四川省滑坡灾害的空间分布情况相符。②在前期滑坡灾害与降雨量统计分析、滑坡灾害危险性评价的基础上,以滑坡灾害危险性评价为静态因子,日降雨量数据为动态因子,通过逻辑回归模型的结果,确定以当日降雨量概率化值、滑坡灾害危险性值、前一日降雨概率化值、前两日降雨概率化值、前三日降雨概率化值为临灾模型影响因子,各因子对预警结果影响程度按上述顺序递减,建立了地质-气象耦合的临灾气象预警模型。通过检验区数据对模型的检验表明,该预警模型能成功预警80%以上的滑坡灾害;通过滑坡灾害群发个例检验发现,该预警模型与四川省现用模型相比,预警区域明显减小,空报率和漏报率显著降低。     

2010年玉树地震库仑应力变化对2016年杂多地震的影响及区域危险性评估

在以往研究的基础上，利用弹性位错理论和岩石圈分层粘弹性模型，进一步分析2010年玉树地震同震及震后应力变化对2016年杂多地震的影响，讨论玉树地震和杂多地震对研究区主要活动断裂的应力影响及未来地震危险性。结果表明，玉树地震同震库仑应力使杂多地震震中位置应力升高1.476 kPa。2010年玉树地震至2016年杂多地震的6 a内，震后粘弹性松弛作用使研究区域库仑应力增强区域应力持续集中，并使应力影区进一步释放应力，杂多地震位于玉树地震导致的库仑应力增强区域。2016年杂多地震发生时，其震中位置应力升高3.902 kPa。采用多组不同模型参数的研究结果均显示，玉树地震对杂多地震孕育起促进作用。2016年杂多地震同震破裂仅影响震中周边小范围区域的应力状态，在杂多断裂带西北端出现应力高值区域。2010年玉树地震同震及震后作用使甘孜-玉树断裂的叶诺卡-结隆段、巴塘乡-洛须段、当江段、巴塘乡断裂中段及五道梁-曲麻莱断裂称多段应力明显升高。甘孜-玉树断裂西北段的叶诺卡-结隆段、巴塘乡-相古段地震空区的地震危险性较高。     

Laboratory investigations of earthquake- and landslide-induced composite surges

Seismic surges and landslides are both major secondary mountain hazards during an earthquake. This paper investigates earthquake- and landslide-induced composite surges through large-scale shaking table water tank model experiments. A series of tests were conducted for various initial water depths, peak ground accelerations, slide impact velocities, and slide volumes. Based on the results of the tests, the effects of these parameters on the maximum wave heights of the earthquake- and landslide-induced composite surges were analyzed. An amplification coefficient of seismic surges was defined, and the prediction equation for the amplification coefficient was developed through non-dimensional multiple linear regression analysis. Then, an empirical equation for the maximum wave heights of the composite surges was developed based on the amplification coefficient and Demirel’s method. This equation provides a calculation method for earthquake- and landslide-induced composite surge waves.     

汶川Ms8.0地震前的地面运动排列熵变化

将排列熵理论引入地震学领域，采用四川地震台网22个地震台的数据，每小时计算一个垂直分量排列熵值，研究汶川M_S8.0地震前地面运动排列熵的时空变化特征，试图提取与地震的孕育和发生有关的信息。结果显示，震前22 h内，震中附近形成一个排列熵高值区，这个高值区与位于龙门山断裂系北侧的高值区显示出此消彼长的态势；震中东侧的低值区在南北方向拉伸运移，并在震中东北侧向西北方向分叉凸出，汶川地震就发生在新的高值区和低值区陡变部位。结合其他学者的研究结果认为,这些现象很可能与汶川地震的发生有关联。基于地面运动排列熵的时空变化特征推测，这次地震不仅是巴颜喀拉块体与四川盆地对抗的结果，处于龙门山断裂系北侧的鄂尔多斯块体的运动也参与了此次地震的孕育和发生。     

九寨沟MS7.0地震强地震动模拟及参数敏感性分析

对2017年九寨沟M_S7.0地震进行强地面运动模拟,应用复合震源模型建立特定圆形子震分布的断层破裂运动学模型,对地震矩、应力降、破裂速度、子断层尺寸和震源深度等参数进行敏感性分析,得到一组合理的震源参数,然后基于复合震源模型计算得到该地区地震动,最后与观测的峰值加速度(PGA)、反应谱和PGA的空间分布特征进行对比。结果表明,该模型整体上可以再现各台站地震动强度特征,验证了复合震源模型计算强地面运动的有效性,同时敏感性规律也为复合震源模型计算缺乏强震记录区域的地震动参数的变化区间提供了依据。