福建南安市地质灾害特征及防治对策

根据福建省南安市地质灾害调查和区划工作成果，总结该区地质灾害类型主要有滑坡、崩塌和泥石流，尤以滑坡和崩塌的危害性最大。全市共发现地质灾害140处，其中滑坡72处(含土质滑坡67处)，崩塌65处(土质崩塌55处)，泥石流3处。南安市地质灾害具有分布广、规模小、突发性强、危害性大等特点，其控制因素：包括地形地貌、岩土体性质、降雨和人类工程活动等。南安市属于低山丘陵地貌，其中低山山地占全市面积的50％，丘陵、台地占25％；花岗岩、凝灰岩分布面积广，其残积层厚度较大，约5～17m，岩性为残积砾(砂)质粘性土，是致灾的主要土体。98％的地质灾害与降雨有直接的关系，当过程雨量达到100mm时，滑坡开始产生；过程雨量大于200mm时，滑坡普遍发生。直接与人类工程活动有关的地质灾害共134处，占地质灾害总数的95％，坡脚开挖是引发地质灾害的主要因素，占调查总数的84．4％。论文还提出了地质灾害防治的相应对策。     

Landslide and debris flow initiated characteristics after typhoon Morakot in Taiwan

Typhoon Morakot brought extreme rainfall and initiated numerous landslides and debris flows in southern Taiwan in August of 2009. The purpose of this study is to identify the extreme rainfall-induced landslide frequency-area distribution in the Laonong River Basin in southern Taiwan and debris flow-initiated conditions under rainfall. Results of the analysis show that debris flows were initiated under high cumulative rainfall and long rainfall duration or high rainfall intensity. The relationship of mean rainfall intensity and duration threshold could reflect debris flow initiation characteristics under high rainfall intensity in short rainfall duration conditions. The relationship of cumulative rainfall and duration threshold could reflect debris flow initiation characteristics under high cumulative rainfall in long rainfall duration. Defining rainfall events by estimating rainfall parameters with different methodologies could reveal variations among intermittent rainfall events for the benefit of issuing debris flow warnings. The exponent of landslide frequency-area distribution induced by Typhoon Morakot is lower than that induced by the Chi-Chi earthquake. The lower exponent of landslide frequency-area distribution can be attributed to the transportation and deposition areas of debris flow that are included in the landslide area. Climate change induced high rainfall intensity and long duration of precipitation, for example, Typhoon Morakot brought increased frequency of debris flow and created difficulty in issuing warnings from rainfall monitoring.     

The mobility of long-runout landslides

Several issues relevant to the mobility of long-runout landslides are examined. A central idea developed in this paper is that the apparent coefficient of friction (ratio of the fall height to the runout distance) commonly used to describe landslide mobility is physically meaningless. It is proposed that the runout distance depends primarily on the volume and not on the fall height, which just adds scatter to the correlation. The negative correlation observed between the apparent coefficient of friction and the volume is just due to the fact that, on the gentle slopes on which landslides travel and come to rest, a large increase in runout distance due to a large volume corresponds to a small increase in the total fall height, hence to a decrease in the apparent coefficient of friction.

It is shown that the spreading of a fluid-absent, granular flow is not able to explain the large runout distances of landslides, and in particular does not allow the centre of mass to travel further than expected for a sliding block. This contrasts with the behaviour of natural landslides, for which the centre of mass is shown to travel much further than expected from a simple Coulomb model. The presence of an interstitial fluid which can partly or entirely support the load of particles allows the effective coefficient of solid friction to be reduced or even suppressed. Air is not efficient for fluidising large landslides and a loose debris cannot slide over a basal layer of entrapped and compressed air, as air would rapidly pass through the debris in the form of bubbles during batch sedimentation. Water is much more efficient as a fluidising medium due to its higher density and viscosity, and its incompressibility. As water is known to enhance the mobility of the saturated debris flows, it is proposed that water is also responsible for the long runout of landslides. This is consistent with the fact that the increase in runout with volume is similar for debris flows and landslides. Field evidence suggests that most landslides are unsaturated with water but not dry, even on Mars.

Comparison of the velocity of well-documented landslides with that predicted by fluid-absent, granular models shows that these models predict landslides that are much faster and less responsive to topography than natural ones. The relatively low velocities of landslides suggest that energy dissipation is dominated by a velocity-dependent stress and that the coefficient of solid friction is very low. This is consistent with the physics of fluidised or partly fluidised debris and suggests that landslide velocity may be controlled by local slope and flow thickness rather than by the initial fall height. In the absence of a supply of fluid at the base, fluidisation requires a net downward flux of sediment, implying some deposition at the base of landslides, which may thus progressively run out of material. In such a model, the spreading of the portion of a landslide beyond a certain distance would primarily depend on the volume passing this distance and not on the total volume of the landslide. Landslide deposits may therefore have self-similar shapes, in which the area covered beyond a certain distance is a constant function of the volume beyond that distance. It is shown that the shape of some well-documented landslide deposits is in reasonable agreement with this prediction. One consequence is that, as recently proposed for debris flows, assessment of hazards related to landslides should be based on the correlation between the volume and the area covered by the deposit, rather than on the apparent coefficient of friction.     

Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County,China

Landslides are a significant hazard in many parts of the world and represent an important geohazard in China. Rainfall is the primary triggering agent for landslides and often used for prediction slope failures. However, the relationship between rainfall and landslide occurrences is very complex. Great efforts have been made on the study of regional rainfall-induced landslide forecasting models in recent years; still, there is no commonly accepted method for rainfall-induced landslide prediction. In this paper, the quantitative antecedent soil water status (ASWS) model is applied to investigate the influence of daily and antecedent rainfall on the triggering of landslides and debris flows. The study area is Wudu County in Gansu Province, an area which exhibits frequent landslide occurrences. The results demonstrate a significant influence of high intensity rainfall events on landslide triggering. Still, antecedent rainfall conditions are very important and once a threshold of approximately 20 mm is exceeded, landslides and debris flows can occur even without additional rainfall. The study presented could also facilitate the implementation of a regional forecasting scheme once additional validation has been carried out.     

Relationships between natural terrain landslide magnitudes and triggering rainfall based on a large landslide inventory in Hong Kong

Rain-induced landslides are recognized as one of the most catastrophic hazards on hilly terrains. To develop strategies for landslide risk assessment and management, it is necessary to estimate not only the rainfall threshold for the initiation of landslides, but also the likely magnitudes of landslides triggered by a storm of a given intensity. In this study, the frequency distributions of both open hillside landslides and channelized debris flows in Hong Kong are established on the basis of the Enhanced Natural Terrain Landslide Inventory (ENTLI) with 19,763 records in Hong Kong up to 2013. The landslide magnitudes are measured in terms of the number, scar area, volume, or density of landslides. The mean values of the scar areas and volumes are 55.2 m² and 102.0 m³, respectively, for the open hillside landslides and 91.3 m² and 166.5 m³, respectively, for the channelized debris flows. Empirical correlations between the numbers, scar areas, and volumes of hillside landslides or channelized debris flows and the maximum rolling rainfall intensities of different periods have been derived. The maximum rolling 4- to 24-h rainfall amounts provide better predictions compared with those with the maximum rolling 1-h rainfall. Maximum rolling rainfall intensity-duration thresholds identifying the likely rainfall conditions that yield natural terrain landslides or debris flows of different magnitudes are also proposed. The initiation rainfall thresholds are identified as 75, 90, 100, 120, 150, 180, and 200 mm for the maximum rolling 1-, 2-, 4-, 6-, 8-, 12-, and 24-h rainfall, respectively.     

5.12震源区牛眠沟暴雨滑坡泥石流预测模型

牛眠沟研究区位于2008-05-12汶川大地震线性震源的南端,受强烈地震力作用,区内山体遭受严重破坏,发生多处滑坡和泥石流灾害。根据已建立的暴雨滑坡、泥石流预测概念模型,暴雨滑坡、泥石流预测可视为判断滑坡形成的地质环境和确定触发滑坡的降雨特征。查明研究区地质环境及灾害特征,确定了产生滑坡、泥石流的必要地质环境因子,以数字滑坡技术获取这些因子数据,代入模型,即可评价研究区各处、各沟谷发生滑坡、泥石流的危险程度;与相似地质环境及气候条件进行类比,确定研究区触发滑坡、泥石流的降雨特征及降雨量阈值后,最终建立暴雨滑坡、泥石流预测模型。据此模型进行研究区暴雨滑坡、泥石流预测,实地验证表明滑坡、泥石流发生位置的准确率>90%。     

A comparison of logistic regression-based models of susceptibility to landslides in western Colorado,USA

The Paonia-McClure Pass area of Colorado has been recognized as a region highly susceptible to mass movement. Because of the dynamic nature of this landscape, accurate methods are needed to predict susceptibility to movement of these slopes. The area was evaluated by coupling a geographic information system (GIS) with logistic regression methods to assess susceptibility to landslides. We mapped 735 shallow landslides in the area. Seventeen factors, as predictor variables of landslides, were mapped from aerial photographs, available public data archives, ETM + satellite data, published literature, and frequent field surveys. A logistic regression model was run using landslides as the dependent factor and landslide-causing factors as independent factors (covariates). Landslide data were sampled from the landslide masses, landslide scarps, center of mass of the landslides, and center of scarp of the landslides, and an equal amount of data were collected from areas void of discernible mass movement. Models of susceptibility to landslides for each sampling technique were developed first. Second, landslides were classified as debris flows, debris slides, rock slides, and soil slides and then models of susceptibility to landslides were created for each type of landslide. The prediction accuracies of each model were compared using the Receiver Operating Characteristic (ROC) curve technique. The model, using samples from landslide scarps, has the highest prediction accuracy (85 %), and the model, using samples from landslide mass centers, has the lowest prediction accuracy (83 %) among the models developed from the four techniques of data sampling. Likewise, the model developed for debris slides has the highest prediction accuracy (92 %), and the model developed for soil slides has the lowest prediction accuracy (83 %) among the four types of landslides. Furthermore, prediction from a model developed by combining the four models of the four types of landslides (86 %) is better than the prediction from a model developed by using all landslides together (85 %).     

GIS支持下CF与Logistic回归模型耦合的九寨沟景区滑坡易发性评价

2017年8月8日九寨沟M_S7.0地震诱发了数以千计的崩滑体,产生的大量松散固体碎屑在降雨作用下极易启动转化为新的滑坡或泥石流形成次生灾害,因此对九寨沟景区进行滑坡易发性评价尤为必要。基于震前、震后高精度遥感影像对比分析结合现场调查,共获取1047处滑坡,总面积为3.88 km2。在分析滑坡发育分布与影响因素关系的基础上,本文选取了构造因子、地形因子、地质因子及其他因子等9个指标,采用确定性系数(CF)模型、逻辑回归(Logistic)模型以及两种模型耦合分析进行滑坡易发性评价。研究结果表明,坡度、坡向、高程和地层岩性是影响滑坡分布的主要因子;研究区被划分为低易发区(60.72%)、中度易发区(24.18%)、高易发区(9.89%)和极高易发区(5.21%),高-极高易发区基本沿沟谷分布,面积为99 km2,其中熊猫海、老虎海周边均为滑坡极高易发区;采用耦合模型比单一模型评价结果更加合理,其结果可作为景区滑坡防治和分段分时开放的参考依据。     

Hazard Zoning for Landslides Connected to Torrential Floods in the Jerte Valley (Spain) by using GIS Techniques

The Jerte Valley is anortheast-southwest tending graben located in the mountainous region of west central Spain (Spanish Central System). Mass movements have been a predominant shaping process on the Valley slopes during the Quaternary. Present day activity is characterized as either `first-time failure' (shallow debris slides and debris flows) or `reactivations' of pre-existing landslides deposits.A delineation of landslide hazard zoningwithin the Valley has been carried out by using the detailed documentation of a particular event (a debris slide and a sequel torrential flood, which occurred on the Jubaguerra stream gorge), and GIS techniques. The procedure has had four stages, which are: (1) the elaboration of a susceptibility map (spatial prediction) of landslides; (2) the elaboration of a map of `restricted susceptibility' in the particular case of slopes that are connected to streams and torrents (gorges); (3) the elaboration of a digital model which relates the altitude to the occurrence probability of those particular precipitation conditions which characterized the Jubaguerra event and (4) the combination of the probability model with the `restricted susceptibility map', to establish `critical zones' or areas which are more prone to the occurrence of phenomena that have same typology as this one.     

Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models,Serra do Mar,Brazil

The hillslopes of the Serra do Mar, a system of escarpments and mountains that extend more than 1500 km along the southern and southeastern Brazilian coast, are regularly affected by heavy rainfall that generates widespread mass movements, causing large numbers of casualties and economic losses. This paper evaluates the efficiency of susceptibility mapping for shallow translational landslides in one basin in the Serra do Mar, using the physically based landslide susceptibility models SHALSTAB and TRIGRS. Two groups of scenarios were simulated using different geotechnical and hydrological soil parameters, and for each group of scenarios (A and B), three subgroups were created using soil thickness values of 1, 2, and 3 m. Simulation results were compared to the locations of 356 landslide scars from the 1985 event. The susceptibility maps for scenarios A1, A2, and A3 were similar between the models regarding the spatial distribution of susceptibility classes. Changes in soil cohesion and specific weight parameters caused changes in the area of predicted instability in the B scenarios. Both models were effective in predicting areas susceptible to shallow landslides through comparison of areas predicted to be unstable and locations of mapped landslides. Such models can be used to reduce costs or to define potentially unstable areas in regions like the Serra do Mar where field data are costly and difficult to obtain.     

An empirical model for landslide travel distance prediction in Wenchuan earthquake area

Sliding mass of landslides highly endangered the area along travel path, especially landslides with long travel distance. It is necessary to develop an effective prediction model for preliminarily evaluating landslide travel distance so as to improve disaster prevention and relocation. This paper collected 54 landslides with 347–4,170 m travel distance triggered by the 2008 Wenchuan earthquake to discuss the effectiveness of various influential factors on landslide travel distance and obtained an empirical model for its prediction. The results revealed that rock type, sliding source volume, and slope transition angle were the predominant factors on landslide travel distance. The validity of proposed model was verified by the satisfactory agreement between observations and predictions. Therefore, this model might be practically applicable in Wenchuan earthquake area and other similar geomorphological and geological regions.     

Effectiveness of visually analyzing LiDAR DTM derivatives for earth and debris slide inventory mapping for statistical susceptibility modeling

Landslide inventories are the most important data source for landslide process, susceptibility, hazard, and risk analyses. The objective of this study was to identify an effective method for mapping a landslide inventory for a large study area (19,186 km²) from Light Detection and Ranging (LiDAR) digital terrain model (DTM) derivatives. This inventory should in particular be optimized for statistical susceptibility modeling of earth and debris slides. We compared the mapping of a representative set of landslide bodies with polygons (earth and debris slides, earth flows, complex landslides, and areas with slides) and a substantially complete set of earth and debris slide main scarps with points by visual interpretation of LiDAR DTM derivatives. The effectiveness of the two mapping methods was estimated by evaluating the requirements on an inventory used for statistical susceptibility modeling and their fulfillment by our mapped inventories. The resulting landslide inventories improved the knowledge on landslide events in the study area and outlined the heterogeneity of the study area with respect to landslide susceptibility. The obtained effectiveness estimate demonstrated that none of our mapped inventories are perfect for statistical landslide susceptibility modeling. However, opposed to mapping polygons, mapping earth and debris slides with a point in the main scarp were most effective for statistical susceptibility modeling within large study areas. Therefore, earth and debris slides were mapped with points in the main scarp in entire Lower Austria. The advantages, drawbacks, and effectiveness of landslide mapping on the basis of LiDAR DTM derivatives compared to other imagery and techniques were discussed.     

基于小流域的地震扰动区降雨型滑坡泥石流危险性评价方法

地震扰动区存在大量震裂松散坡体,在持续或者密集的降雨条件下极易转化为滑坡灾害。同时,滑坡又会给泥石流提供大量松散固体物质,增加泥石流的危险性。因此,在震区,灾害通常以"链"的形式出现,比单一灾种危害性大。为了更有效地对地质灾害危险性进行评价,笔者将滑坡、泥石流作为灾害链,综合地加以分析和研究。选择5·12汶川大地震中受灾严重的都江堰市白沙河流域的17条泥石流沟作为研究区,建立滑坡-泥石流危险性评价耦合模型,研究24 h不同降雨量条件下小流域滑坡泥石流危险性的变化。耦合模型包括了坡体稳定性评价模型,水文模型及以泥石流规模、发生频率、流域面积、主沟长度、流域高差、切割密度、不稳定斜坡比为评价因子的泥石流危险性评价统计模型。研究结果表明:随着降雨量的增大,参与泥石流活动的松散物质方量持续增加,但当24 h降雨量超过200 mm后,泥石流沟的危险度等级不再发生变化;17条泥石流沟中4条为中危险度,12条为高危险度,1条为极高危险度。这说明研究区地质灾害问题相当严峻,在多雨季节存在泥石流群发的可能性,直接威胁到居住在泥石流沟附近的人民群众生命财产安全;因此,对于有直接危害对象的高危险度及其以上的泥石流沟,应该按照高等级设防标准进行工程治理及发布预警报。同时也说明,将滑坡、泥石流作为灾害链研究具必要性和可行性。     

低山丘陵区典型滑坡-泥石流链生灾害特征与成灾机理

2019年6月10—13日,龙川县发生持续强降雨,导致全县境内发生大量滑坡、泥石流灾害,贝岭镇米贝村是三个重灾区之一。本文以贝岭镇米贝村6号沟发生的滑坡-泥石流链生灾害为研究对象,在野外精细化调查测量基础上,结合数值模拟分析与计算,对链生灾害特征与成灾机理展开研究。研究发现:①6号沟内共发育7处浅层土质小型滑坡,仅3号滑坡体与部分6号滑坡体转化为泥石流,构成泥石流主要物源,其余滑坡未构成持续性影响;②持续降雨下渗,坡体由非饱和向饱和状态转变,坡表形成连续饱和区,孔隙水压力的增加与孔隙水的软化促使土体强度降低,加之坡体饱和自重的增大,斜坡发生浅表层失稳破坏;③降雨的持续下渗与支沟沟源“漏斗状”地形下的地表汇水快速增大滑坡松散堆积体内的含水率,促使其物理性质发生变化,在重力势能下呈流态状启动、运动转化为泥石流。降雨结构影响滑坡-泥石流链生过程,前期降雨引发滑坡、后期降雨启动形成泥石流,滑坡与泥石流的发生表现出阶段性特征。研究成果有助于指导当地政府进一步开展滑坡-泥石流链生灾害的防灾减灾工作,也为该地区未来区域预警研究工作提供理论支撑。     

陕西省宝鸡市地质灾害发育特征

根据近7年来陕西省宝鸡市12区县地质灾害详细调查资料,总结宝鸡地区地质灾害主要类型、空间分布规律、发育特征及其危害性。研究结果显示,宝鸡市地质灾害发育类型主要包括滑坡、崩塌、泥石流及不稳定斜坡等4类,总体发育特征具有群发性、突发性、周期性和链生性。其中,滑坡和崩塌数量多、危害大,泥石流相对发育较少,不稳定斜坡多与崩塌相伴生,大多发展为崩塌灾害。每年汛期在强降雨作用下,都可能诱发表层小型滑坡和崩塌,特别是城镇居民房前屋后的小型黄土滑坡和崩塌,以及山区公路切坡导致的残坡积层滑坡崩塌频繁发生,是宝鸡市地质灾害群测群防和减灾防灾关注的重点。     

Statistical Analysis of Landslide Events in Central America and their Run-out Distance

Statistical analyses of landslide deposits from similar areas provide information on dynamics and rheology, and are the basis for empirical relationships for the prediction of future events. In Central America landslides represent an important threat in both volcanic and non-volcanic areas. Data, mainly from 348 landslides in Nicaragua, and 19 in other Central American countries have been analyzed to describe landslide characteristics and to search for possible correlations and empirical relationships. The mobility of a landslide, expressed as the ratio between height of fall (H) and run-out distance (L) as a function of the volume and height of fall; and the relationship between the height of fall and run-out distance were studied for rock falls, slides, debris flows and debris avalanches. The data show differences in run-out distance and landslide mobility among different types of landslides and between debris flows in volcanic and non-volcanic areas. The new Central American data add to and seem consistent with data published from other regions. Studies combining field observations and empirical relationships with laboratory studies and numerical simulations will help in the development of more reliable empirical equations for the prediction of landslide run-out, with applications to hazard zonation and design of optimal risk mitigation measures.     

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias,NW Spain)

Given its geological and climatic conditions and its rugged orography, Asturias is one of the most landslide prone areas in the North of Spain. Most of the landslides occur during intense rainfall episodes. Thus, precipitation is considered the main triggering factor in the study area, reaching average annual values of 960 mm. Two main precipitation patterns are frequent: (i) long-lasting periods of moderate rainfall during autumn and winter and (ii) heavy short rainfall episodes during spring and early summer. In the present work, soil moisture conditions in the locations of 84 landslides are analysed during two rainfall episodes, which represent the most common precipitation patterns: October–November 2008 and June 2010. Empirical data allowed the definition of available water capacity percentages of 99–100% as critical soil moisture conditions for the landslide triggering. Intensity-duration rainfall thresholds were calculated for each episode, considering the periods with sustained high soil moisture levels before the occurrence of each analysed landslide event. For this purpose, data from daily water balance models and weather stations were used. An inverse relationship between the duration of the precipitation and its intensity, consistent with published intensity-duration thresholds, was observed, showing relevant seasonal differences.     

Analysis of the 2003 Varunawat Landslide,Uttarkashi, India using Earth Observation data

Mass movements such as landslides in mountainous terrains are natural degradation processes and one of the most important landscape-building factors. Varunawat Parbat overlooking Uttarkashi town witnessed a series of landslides on 23 September 2003 and the debris slides and rock falls continued for 2 weeks. This landslide complex was triggered due to the incessant rainfall prior to the event, and its occurrence led to the blockage of the pilgrim route to Gangotri (source of the Ganges river) and evacuation of thousands of people to safer places. Though there was no loss of lives due to timely evacuation, heavy losses to the property were reported. High-resolution stereoscopic earth observation data were acquired after the incidence to study the landslide in detail with emphasis on the cause of the landslide and mode of failure. Areas along the road and below the Varunawat foothill region are mapped for landslide risk. It was found that the foothill region of the Varunawat Parbat was highly disturbed by man-made activities and houses are dangerously located below steep slopes. The potential zones for landslides along with the existing active and old landslides are mapped. These areas are critical and their treatment with priority is required in order to minimise further landslide occurrences.     

浙江地区引发滑坡的降雨强度-历时关系

由于独特的地理位置,复杂的地质、地形和气候背景,浙江成为中国降雨型滑坡（土体和岩体滑动,也包括泥石流和崩塌等）最频发的地区之一。为评价浙江地区的滑坡灾害,本文对该地区1990年至2003年雨量站记录的降雨数据进行了详细分析,确定了引发土体滑坡-泥石流的降雨强度―历时下限。     

Landslide hazard and cascading effects following the extreme rainfall event on Madeira Island (February 2010)

Heavy rainfall on February 20, 2010, triggered numerous shallow rapid landslides across Madeira Island, a Portuguese archipelago in the North Atlantic. Two days after the extreme rainfall event, a field campaign was started which involved describing and mapping a variety of landslide types and the related losses at 120 different locations throughout the Island. Most of the failures started as debris slides or avalanches at high elevations and transformed into debris flows which rushed downslope into populated coastal areas. Over half of the mapped landslides were located in the central and southern area of the island. A further 1,257 landslide locations were revealed in these areas using remote sensing data which were then assembled in a spatial database. Due to anthropogenic influences caused by urban development and population expansion, the event demonstrated the increased vulnerability of the island??s infrastructure. In order to mitigate future losses, it is important to quantify the typical preparatory factors which contribute to rainfall-induced landslides. This increases our understanding of the hazards and associated risks. The analysis shows that based on their spatial frequency, distribution and in the context of the drainage system, three main factors contribute to the triggering of the landslides due to the heavy rainfall event in February 2010: the characteristic soil type, the land cover and the slope gradient. It can now be recognized that the distribution of landslides is highly dependent on the temporal and spatial distribution of these factors. Furthermore, the anthropogenic impact on the extent of the hazard becomes obvious due to poor settlement planning and drainage system modification.