Spatio-temporal analysis and simulation on shallow rainfall-induced landslides in China using landslide susceptibility dynamics and rainfall I-D thresholds

An empirical simulation method to simulate the possible position of shallow rainfall-induced landslides in China has been developed. This study shows that such a simulation may be operated in real-time to highlight those areas that are highly prone to rainfall-induced landslides on the basis of the landslide susceptibility index and the rainfall intensity-duration (I-D) thresholds. First, the study on landslide susceptibility in China is introduced. The entire territory has been classified into five categories, among which high-susceptibility regions (Zone 4- ‘High’ and 5-‘Very high’) account for 4.15% of the total extension of China. Second, rainfall is considered as an external triggering factor that may induce landslide initiation. Real-time satellite-based TMPA 3B42 products may provide real rainfall spatial and temporal patterns, which may be used to derive rainfall duration time and intensity. By using a historical record of 60 significant past landslides, the rainfall I-D equation has been calibrated. The rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate the spatiotemporal distribution of rainfall-induced landslide hazards when rainfall events exceed the rainfall I-D thresholds, where the susceptibility category is ‘high’ or ‘very high’. This study shows a useful tool to be part of a systematic landslide simulation methodology, potentially providing useful information for a theoretical basis and practical guide for landslide prediction and mitigation throughout China.     

Controls of preferential orientation of earthquake- and rainfall-triggered landslides in Taiwan's orogenic mountain belt

Landsliding usually occurs on specific hillslope aspect, which may reflect the control of specific geo-environmental factors, triggering factors, or their interaction. To explore this notion, this study used island-wide landslide inventories of the Chi-Chi earthquake in 1999 (M_W = 7.6) and Typhoon Morakot in 2009 in Taiwan to investigate the preferential orientation of landslides and the controls of landslide triggers and geological settings. The results showed two patterns. The orientations of earthquake-triggered landslides were toward the aspect facing away from the epicenter in areas with peak ground acceleration (PGA) ≥ 0.6 g and landslide ratio ≥ 1%, suggesting that the orientations were controlled by seismic wave propagation. Rainfall-triggered landslides tended to occur on dip slopes, instead of the windward slopes, suggesting that geological settings were a more effective control of the mass wasting processes on hillslope scale than the rainfall condition. This study highlights the importance of the endogenic processes, namely seismic wave and geological settings, on the predesigned orientation of landslides triggered by either earthquake or rainfall, which can in turn improve our knowledge of landscape evolution and landslide prediction. © 2019 John Wiley & Sons, Ltd.     

基于降雨入渗的Newmark模型改进及地震滑坡危险性预测研究

滑坡是一种破坏性非常强的地质灾害,其中地震与降雨均为诱导滑坡发生的关键因素。从降雨期间发生地震的角度考虑,基于Green-Ampt降雨入渗模型对Newmark模型进行改进,推导两因素耦合作用下的边坡安全系数F_S。以云南省鲁甸县某一区域为例,分别开展无降雨、降雨无积水与降雨积水三种情况下的地震滑坡危险性预测及坡度与入渗深度因子对位移影响分析。通过比较上述三种情况,得到研究区域内的Newmark累积位移分布及危险性区划。结果表明：与未降雨情况相比,后两种情况下地震滑坡高危险程度区域面积占比计算区域随着降雨时间的增加从1%分别提高至9%、12%,滑坡低危险程度区域面积从51%分别降低至35%、33%;坡度值与入渗深度值越大,滑坡位移越大,危险性越高。Newmark改进模型充分考虑了降雨对地震滑坡产生的促进作用,能更好地反映出研究区每个场点相对的滑坡危险性,对滑坡危险性预测具有一定指导意义。     

基于人工边坡稳定性的降雨型滑坡预警预报模型设计与应用

由削坡建房遗留的人工边坡存在大量滑坡隐患问题,在降雨引发土质边坡自身动力变化分析条件下,以稳定性评价建模为基础,提出降雨型滑坡动力学预警预报模型。文中以广东省梅州市花岗岩地区为例,使用GIS技术构建了1 727个预警分析单元,并进行关键地质环境因子赋值及与气象站点数据关联;按坡高、坡度等参数,分别构建16个边坡失稳动力学预警模块,并根据降雨量变化,计算边坡稳定性系数,最终按其阈值确定风险等级并予以预警。本研究对于推动人工边坡诱发的滑坡地质灾害预警预报与预防均具有重要意义。     

Establishing a threshold for rainfall-induced landslides by a kinetic energy–duration relationship

Many investigators have attempted to define the threshold of landslide failure, that is, the level of the selected climatic variable above which a rainfall-induced landslide occurs. Intensity–duration (I–d) relationships are the most common type of empirical thresholds proposed in the literature for predicting landslide occurrence induced by rainfall. Recent studies propose the use of the kinetic power per unit volume of rainfall (J m⁻² mm⁻¹) to quantify the threshold of landslides induced by rainfall. In this paper, the relationship between rainfall duration and kinetic power corresponding to landslides triggered by rain was used to propose a new approach to define the threshold for predicting landslide occurrence. In particular, for the first time, a kinetic power per unit volume of rainfall–duration relationship is proposed for defining the minimum threshold needed for landslide failure. This new method can be applied using commonly used relationship for estimating the kinetic power per unit volume of rainfall and a new equation based on the measured raindrop size distribution. The applicability of this last method was tested using the data of rainfall intensity, duration and median volume diameter for 51 landslides in Taiwan. For the 51 landslides, the comparison between the measured pairs' kinetic power–duration and all selected relationships demonstrated that the equation based on the measured raindrop size distribution is the best method to define the landslide occurrence threshold, as it is both a process-oriented approach and is characterized by the best statistical performance. This last method has also the advantage to allow the forecasting of landslide hazard before the end of the rainfall event, since the rainfall kinetic power threshold value can be exceeded for a time interval less than the event duration.     

Analysing the Relationship Between Typhoon‐Triggered Landslides and Critical Rainfall Conditions

Many landslides are triggered by rainfall. Previous studies of the relationship between landslides and rainfall have concentrated on deriving minimum rainfall thresholds that are likely to trigger landslides. Though useful, these minimum thresholds derived from a log–log plot do not offer any measure of confidence in a landslide monitoring or warning system. This study presents a new and innovative method for incorporating rainfall into landslide modelling and prediction. The method involves three steps: compiling radar reflectivity data in a QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system during a typhoon (tropical hurricane) event, estimating rainfall from radar data and using rainfall intensity and rainfall duration as explanatory variables to develop a landslide logit model. Given the logit model, this paper discusses ways in which the model can be used for computing probabilities of landslide occurrence for a real‐time monitoring system or a warning system, and for delineating and mapping landslides. Copyright © 2007 John Wiley & Sons, Ltd.     

On the seismic regime network method

In this paper, based on the previous study of practical use of seismic regime windows and seismic regime belts, the problem of establishing a “seismic regime network” consisting of “windows” and “belts” is further posed and discussed according to the observed fact that many “windows” and “belts” make responses to one earthquake. For the convenience of usage, the “seismic regime network” is divided into two classes, the first class and the second one. The former can be used in tendency prediction for long-term seismic activity in a large area, the latter used in short-term prediction in a small area. In this paper, after briefly discussing the physical significance of “seismic regime network”, it is pointed out that this simple and easily used method can be used to observe and extract seismic precursory information from a large area before a great earthquake, thus it can provide a reliable basis for the analysis and judgement of seismic regime tendency in time and space. No doult, this method is of certain practical significance. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,13, 161–169, 1991. The English version of this paper is improved by Prof. Shaoxie Xu.     

基于加卸载响应比理论的降雨型滑坡预警研究

在建立边坡远程实时监测系统并获得变形与降雨量连续监测数据的基础上,运用加卸载响应比理论的基本原理,提出以一用为加卸载周期、将日降雨量及其变化作为边坡的加卸载参数、相应的日平均变形速率及其变化值为加卸载响应参数,建立了基于加卸栽响应比的降雨型滑坡短周期预警模型。以某公路边坡为例,运用加卸载响应比预测模型对边坡的2个监测点进行了加卸载响应比计算,发现2个点的加卸载响应比时序曲线与其稳定性动态演化规律相吻合。研究结果表明,可以运用该模型进行降雨型滑坡短周期预测预警。     

山西大宁县典型滑坡体地貌特征与降雨和强震关系

山西大宁县位于山西省吕梁山南端，境内沟壑纵横，具有独特的黄土高原地形地貌特征。在该地区进行地质灾害调查，以查明灾害分布、形成原因和隐患情况。应用地貌学的有关原理，结合遥感影像解译，在义亭河的支流河谷两岸0.3 km²（575 m×526 m）范围内发现并确认了2个大型和2个中型滑坡体。滑坡体均为基岩与上方的黄土沉积层整体滑下，滑坡体沿河流流动的方向发生一定程度的扭转，滑面近于直立，滑动方向与河流流向一致，没有形成堰塞湖。对滑坡体与周围地貌特征，以及河道被改动的方向特征研究认为：①4个滑坡体是在不同的地质时期形成；②其中1个滑坡体明显受到一条断裂的影响；③其它3个滑坡体，可能是在河流侵蚀搬运作用加强，导致的"重力塌陷"，及河流流向作用牵引的动力学作用下，经过较漫长的时间形成；④在距离该地区约60 km的洪洞地震、临汾地震，以及距离该地区230余公里的华县地震，这三次8级地震过程中，地震应力可能加剧了滑坡体的发生或滑动；⑤未来该滑坡体，仍然可能在非常规的外界条件下，如强降雨或地震应力等的影响下，出现加速滑动的可能。     

analyses on the triggering facrors of large quantities of landslides in the upper reaches of the minjiang river,sichuan province

Over the past geological and historical period, tens of thousands of landslides occurred in the upper reaches of the Minjiang River, an area which is characterized by alpine valleys and has been densely populated over the past several hundreds of years. Discussing the triggering factor of these landslides is of great significance to geological hazard mitigation and prevention in this region. In this paper, we focus on four aspects of regional rainfall, shape features of landslide slopes, the corresponding relationship between landslide area and earthquake magnitude, and the recurring features of the reconstructed palaeoearthquake record at Diexi. Compared with those in Nepal, both mean seasonal rainfall accumulation and mean daily rainfall for the past 30 years are too low to reach the threshold values triggering landslides in the upper reaches of the Minjiang River. Secondly, landslides in the study area are usually absent of inner gorges(canyon topography)on the hillslope toes, which are confirmed in previous studies as typical features of landslides triggered by storms. Thirdly, wide distribution of the landslides in the study area supports our notion of earthquake-triggering because the landslides triggered by storms commonly distribute locally. Fourthly, periodicity analysis of the reconstructed palaeoearthquake record at Diexi provides a few cycles of twenty to thirty years, possibly corresponding to the earthquakes of magnitudes>5.0 or 5.5 which are believed to have caused soft-sediment deformation in the study area. In contrast, like the 2008 M_S8.0 Wenchuan earthquake, the average recurrence interval of the large earthquakes in the study area is 2.6ka. They caused tens of thousands of landslides and provided more coarse silt particles for the nearby lake sediments at least in 330 years for each time. This is consistent with exponential increase of earthquake magnitude from large to medium and of the landslide area with the increased earthquake magnitude. To sum up, we suggest that tens of thousands of landslides in the upper reaches of the Minjiang River were most likely triggered by earthquakes instead of storms. This preliminary viewpoint needs further examination in the future.     

Distribution of Landslides in Baoshan City, Yunnan Province, China

Using Google Earth software as a platform, this study has established an integrated database of both old and new landslides in Baoshan City, Yunnan Province, China, and analyzed their development characteristics together with distribution rules, respectively. Based on the results, a total of 2 427 landslides occurred in the study area, including 2 144 new landslides and 283 old landslides, with a total area of about 104.8 km². The new landslides are mostly in small-scales with an area less than 10 000 m², while the area of individual old landslide is mostly larger than 10 000 m². By analyzing the relationship between the two types of landslides and eight impact factors (i.e., elevation, slope angle, slope aspect, slope position, lithology, fault, regional Peak Ground Acceleration (PGA), and average annual rainfall), the different individual influencing factors, distribution regularities and mechanisms of the two types of landslides are revealed. In detail, the main influencing factors of new landslides are elevation, slope angle, slope aspect, slope position, lithology, regional PGA and average annual rainfall, while the influencing factors of old landslides are mainly elevation, slope angle, and lithology. This study provides basic data and support for landslide assessment and further disaster reduction in Baoshan City. Besides, it also provides new constraints in deeply understanding the effect of different topographic and geological conditions, historical earthquakes, rainfall and other factors on the occurrence mechanisms of both new landslides and old landslides.     

Landslide intelligent prediction using object-oriented method

Landslides are one of the most serious geological disasters in the world and happen quite frequently in the Three Gorges. Landslide prediction is a very important measure of landslide prevention and cure in the Three Gorges. Traditional methods lack in sufficiently mining the various complex information from a landslide system. They often need much manual intervention and possess poor intelligence and accuracy. An intelligent method proposed in this paper for landslide prediction based on an object-oriented method and knowledge driving is hopeful to solve the above problem. The method adopted Landsat ETM+ images, 1:50,000 geological map and 1:10,000 relief map in the Three Gorges as the data origins. It firstly produced the key factors influencing landslide development and used multi-resolution segmentation algorithm to segment the image objects based on the key landslide factors of engineering rock group, reservoir water fluctuation, slope structure and slope level. Secondly, the method chose some sample objects and adopted the decision tree algorithm C5.0 to mine the landslide forecast criteria according to the factor values of each sample object. Finally, under knowledge driving the method classified the image objects and realized landslide susceptibility analysis and intelligent prediction in the Three Gorges. The method proposed in this paper is object-oriented. Results of a real-world example show that: (1) the object-oriented method possesses much more compact knowledge representation, higher efficiency, more continuous classifying result and higher prediction accuracy compared with the pixel-oriented method; (2) it possesses the overall accuracy of 87.64% and kappa coefficient of 0.8305 and is more accurate than the other seven methods (such as the pixel-oriented methods of Parallelpiped, Minimum Distance, Maximum Likelihood, Mahalanobis Distance, K-means and Isodata and the object-oriented method of Nearest Neighbor); (3) about 46.97% landslides lie in the high susceptibility region, 24.24% landslides lie in the moderate susceptibility region, 27.27% landslides lie in the low susceptibility region and 1.52% landslides lie in the very low susceptibility region. Therefore the method can effectively realize landslide susceptibility analysis and provides a new idea for landslide intelligent and accurate prediction.     

大型高位堆积体滑坡稳定性分析与数值模拟

青藏高原边缘地带堆积体滑坡的发生与地质构造、强降雨、地震等作用密切相关,其中多数属于大型高位堆积体滑坡。为研究其发生机理与稳定性,以舟曲县江顶崖大型高位堆积体滑坡为研究对象,首先,从滑坡所处的地理位置、地质条件等出发,分析滑坡的概况与成因;其次,基于传统传递系数法划分滑坡计算模型,提出滑坡稳定性分析的变坡法;最后,采用Midas GTS NX软件对江顶崖滑坡自然工况下稳定性进行数值模拟分析,并与传统及改进算法结果进行对比。研究结果表明：(1)研究区的地形坡度、地层岩性条件以及活动断裂、历史强震作用是滑坡发生的内因,外因是连续强降雨作用使岩土体力学强度降低以及暴雨导致滑坡前缘的白龙江水位上涨、流速加快,冲刷坡脚导致前缘失稳,滑坡中后缘发生牵引式滑动;(2)运用传递系数法计算折线形滑坡稳定性时,滑面倾角变化值大于10°会导致结果出现较大误差,应用改进的“等分均匀变坡法”可以减小误差,以江顶崖滑坡为计算实例并结合数值模拟验证该方法的有效性;(3)自然工况下模拟发现,滑体的前缘主要表现为水平滑移,滑体的中后部局部主要表现为垂直下沉,而滑坡前缘则主要表现为隆起,因此,滑坡部分区域出现了较大的位移...     

Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster

We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy. Through the embedding into a hierarchical Bayesian estimation framework, we can use the integrated nested Laplace approximation methodology to make inference and obtain the posterior estimates of spatially distributed covariate and random effects. Several mapping units are useful to partition a given study area in landslide prediction studies. These units hierarchically subdivide the geographic space from the highest grid-based resolution to the stronger morphodynamic-oriented slope units. Here we integrate both mapping units into a single hierarchical model, by treating the landslide triggering locations as a random point pattern. This approach diverges fundamentally from the unanimously used presence–absence structure for areal units since we focus on modeling the expected landslide count jointly within the two mapping units. Predicting this landslide intensity provides more detailed and complete information as compared to the classically used susceptibility mapping approach based on relative probabilities. To illustrate the model’s versatility, we compute absolute probability maps of landslide occurrences and check their predictive power over space. While the landslide community typically produces spatial predictive models for landslides only in the sense that covariates are spatially distributed, no actual spatial dependence has been explicitly integrated so far. Our novel approach features a spatial latent effect defined at the slope unit level, allowing us to assess the spatial influence that remains unexplained by the covariates in the model. For rainfall-induced landslides in regions where the raingauge network is not sufficient to capture the spatial distribution of the triggering precipitation event, this latent effect provides valuable imaging support on the unobserved rainfall pattern.     

基于不同核函数的2010年玉树地震滑坡空间预测模型研究

基于统计学习理论与地理信息系统(GIS)技术的地震滑坡灾害空间预测是一个重要的研究方向,其可以对相似地震条件下地震滑坡的发生区域进行预测.2010年4月14日07时49分(北京时间),青海省玉树县发生了M_w6.9级大地震,作者基于高分辨率遥感影像解译与现场调查验证的方法,圈定了2036处本次地震诱发滑坡,这些滑坡大概分布在一个面积为1455.3 km²的矩形区域内.本文以该矩形区域为研究区,以GIS与支持向量机(SVM)模型为基础,开展基于不同核函数的地震滑坡空间预测模型研究.应用GIS技术建立玉树地震滑坡灾害及相关滑坡影响因子空间数据库,选择高程、坡度、坡向、斜坡曲率、坡位、水系、地层岩性、断裂、公路、归一化植被指数(NDVI)、同震地表破裂、地震动峰值加速度(PGA)共12个因子作为地震滑坡预测因子.以SVM模型为基础,基于线性核函数、多项式核函数、径向基核函数、S形核函数等4类核函数开展地震滑坡空间预测研究,分别建立了玉树地震滑坡危险性指数图、危险性分级图、预测结果图.4类核函数对应的模型正确率分别为79.87%,83.45%,84.16%,64.62%.基于不同的训练样本开展模型训练与讨论工作,表明径向基核函数是最适用于该地区的地震滑坡空间预测模型.本文为地震滑坡空间预测模型中核函数的科学选择提供了依据,也为地震区的滑坡防灾减灾工作提供了参考.     

Real-time mapping of earthquake-induced landslides

Rigid sliding block analysis is a common analytical procedure used to predict the potential for earthquake-induced landslides for natural slopes. Currently, predictive models provide the expected level of displacement as a function of the characteristics of the slope (e.g., geometry, strength, yield acceleration) and the characteristics of earthquake shaking (e.g., peak ground acceleration, peak ground velocity). These predictive models are used for developing seismic landslide hazard maps which identify zones with risk of earthquake-induced landslides. Alternatively, these models can be combined with Shakemaps to generate “near-real-time” Slidemaps which could be used, among others, as a tool in disaster management. Shakemaps (a publicly available free service of the United States Geological Survey, USGS) provide near-real-time ground motion conditions during the time of an earthquake event. The ground motion parameters provided by a Shakemap are very useful for the development of Slidemaps. By providing ground motion parameters from an actual earthquake event, Shakemaps also serve as a tool to decouple the uncertainty of the ground motion in sliding displacements prediction. Campania region in Italy is studied for assessing the applicability of using Shakemaps for regional landslide-risk assessment. This region is selected based on the availability of soil shear strength parameters and the proximity to the 1980 Irpina (M _w  = 6.9) Earthquake.     

汶川地震滑坡危险性评价——以武都区和文县为例

利用GIS技术详细研究汶川地震在甘肃省陇南市武都区和文县触发的滑坡地质灾害的分布规律及其与地震烈度、地形坡度、断层、高程、地层岩性的相关关系,采用基于GIS的加权信息量模型的崩塌滑坡危险性评价方法,对研究区的地震滑坡危险性进行学科分析。结果表明：极高危险区在高程上主要分布在集水高程区,高度危险区主要沿白水江、白龙江等主干河流两侧极高易发区的边界向两侧扩展,轻度和极轻度危险区面积占比较小,主要分布在低烈度、活动断裂不发育、人类活动微弱的高海拔地区,另外国道G215沿极高危险性区域分布明显;利用危险性等级分区结果统计人口公里格网数据,得到武都区和文县潜在影响人口,发现研究区约78万人将受到地震滑坡灾害的潜在影响。     

Quantifying rainfall controls on catchment‐scale landslide erosion in Taiwan

Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (M_W = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparison of the return period for landslide-triggering rainfall events in Japan based on standardization of the rainfall period

The intensity of rainfall events with potential to cause landslides has varying temporal characteristics. In this study, the time at which the 72-h accumulated rainfall reached its maximum was used to standardize the period of rainfall measurement. The proposed standardization of the rainfall period was used in conjunction with the return level of rainfall intensity, obtained from intensity–duration–frequency curves, to investigate rainfall intensity anomalies associated with 10 hazardous rainfall events that triggered numerous landslides at the regional scale in Japan. These landslides included shallow landslides in volcanic and non-volcanic areas, as well as deep-seated landslides. The rainfall events that triggered the shallow landslides were divided into two types: downpours that repeatedly reached close to the 100-year return level within approximately 3–4 h, and accumulated rainfall that reached close to 200–400 mm over longer time intervals but within 72 h. Lithological differences seemed unrelated to the differences between the two types of shallow-landslide-triggering rainfall; however, precipitation >1000 mm was necessary to trigger deep-seated landslides. Although the characteristics of the hyetographs differed markedly among the landslide-triggering rainfall events, all the landslides could have been triggered when the mean rainfall intensity reached the 100-year rainfall level during the standardized period. Thus, the landslide trigger can be evaluated indirectly based on the increase in the return level of the mean rainfall intensity, which could provide a means for estimating the time of landslide occurrence.