Impact of rainstorm-triggered landslides on high turbidity in a mountain reservoir

Typhoon-triggered landslides deliver huge amounts of sediment to the upstream channel of the Shihmen Reservoir in northern Taiwan. Observation data regarding landsliding, sediment discharge and water turbidity following five major typhoon events from 1985 to 2006 demonstrated that each time water turbidity in the reservoir area rapidly increased up to ten-fold from the river catchment drainage, and the weight of landslide debris exceeded total sediment discharge five-fold. The fact that huge amounts of landslide debris still remained on upstream slopes and water turbidity suddenly increased in the reservoir area but not in upstream channel implied that the increasing water turbidity in the Shihmen Reservoir was indirectly related to the large landslides occurring in the upstream catchment. The main cause of high turbidity in the reservoir area was that, during a typhoon event, high water discharge flowing into the reservoir scoured the fine fraction sediment at the bottom of the reservoir and formed hyperpycanl flow with high turbidity, which then ascended to contaminate the reservoir surface water.     

Landslide influence on turbidity and total solids in Cubat?o do Norte River, Santa Catarina, Brazil

The rainfall events that occurred in the Cubat?o do Norte River watershed, Santa Catarina State, Brazil, in 2008, were characterized by both high intensities and amounts and triggered landslides in this watershed. The objective of the present study was to analyze the influence of landslides on the turbidity and the total solid concentration (TS) in this river using turbidity, TS, and river discharge data obtained from March 23, 2008, to June 11, 2010. The comparison between turbidity and discharge patterns implies that the landslide process was not continuous and increased the turbidity intermittently and irregularly. The sediment yield during the landslide occurrence was approximately five times higher than without the landslide, even though the discharges were similar. The turbidity/discharge relationship during the landslide occurrence was markedly different from that before and after the occurrence. The correlation coefficients between turbidity and TS showed that the landslide significantly changed the sediment yield in this watershed. The result indicates that sediment yield estimations at the watershed level should be treated more carefully when landslides occur.     

水动力型滑坡形成运动机理与防控减灾技术

水动力型滑坡是指在冰川融雪、降雨、水位变动、地表径流及地下水活动等水动力因素驱动下而发生的斜坡岩土体失稳灾害。西南地区是水动力型滑坡尤其是库区滑坡的高发区,其失稳破坏直接威胁到人类的生命财产和基础设施的安全,且有可能造成深远的次生灾害,提升水动力型滑坡灾害的监测预警、综合防控与应急处置水平极为迫切。水动力型滑坡易发于松散堆积层、破碎岩体、软岩以及含有软弱夹层的斜坡等地层,地质环境、水文活动以及人类活动干扰等因素的长期作用在水动力型滑坡的孕育过程中起着关键作用。斜坡在各种不利因素的持续交替作用下,逐渐产生变形破坏,稳定性不断降低并趋于极限失稳状态,最终在短期水文条件的改变下而导致整体失稳破坏。斜坡失稳后的滑坡动力过程非常复杂,尤其是特大型高位滑坡,在运动过程中可能会产生强烈的冲击破碎和沿程侵蚀铲刮现象,导致滑坡运动性态的改变和堆积方量的增大,水的存在会加剧滑坡沿程侵蚀铲刮作用以及导致运动性态向流态化转变而造成更远的运动距离和更广的致灾范围。水动力型滑坡是一个复杂的系统性问题,不同地质结构和水动力条件的滑坡变形破坏过程存在很大差异,远距离非接触式滑坡早期识别与监测技术以及基于人工智能和大数据且具备自主学习的滑坡预报预警方法是未来重要发展方向。水动力型滑坡防治涉及到工程建设、经济民生、社会等多方面因素,需要综合运用工程措施和非工程措施。在未来水利水电工程建设过程中,应重视库区滑坡的危害性,复建设施的修建应尽可能远离库区滑坡影响区。     

Identification of landslide susceptible villages around Kalsubai region,Western Ghats of Maharashtra using geospatial techniques

Heavy rainfall triggered landslides are on the rise along the Western Ghats making it a matter of priority to identify landslide-prone areas well in advance. The present effort is aimed at identifying landslide susceptible villages (LSV) around the Kalsubai region of Deccan volcanic province (DVP), Maharashtra, India from 8 weighted landslide parameters- rainfall, slope, lithology, land use and land cover (LULC), soil properties, relative relief, aspect and lineament. These parameters were combined with advanced remote sensing (RS) data and processed in geographical information system (GIS) as well as in image processing software, which are an integral part of geospatial techniques. Out of the total 59 villages, the study identified 9 villages are situated in very high, 13 in high, 12 in moderate, 11 in low and 14 in very low risk zones. Our data reveals incessant heavy rains and steep slopes are the dominant factors in triggering landslides, exacerbated by anthropogenic activity prevalent in the study area. The spatial and non-spatial database created will help to take effective steps in preventing and/or mitigating landslide disasters in the study area. The methodology can be applied to identify other landslide prone areas in a cost effective way.     

滑坡预警判据初步研究--以三峡库区为例

在三峡库区典型地段滑坡灾害调查评价和统计分析的基础上,结合典型滑坡变形发展的阶段性变形现象、标志和临界诱发因素分析,初步提出3个层次的滑坡预警预报判据27条,包括:(1)滑坡空间预测识别判据11条,主要用于滑坡或潜在危岩体空间识别和危险性区划,是滑坡空间预测的基本判据;(2)滑坡状态判据7条,主要用于滑坡单体稳定性评价的亚临界-临界状态预警判据,是滑坡状态预警判据系统的重要组成部分;(3)滑坡临界时间预报判据9条,主要用于单体滑坡剧烈变形或临滑预报,是滑坡时间预报研究的关键判据.     

关键影响因子作用下三峡库区堆积层滑坡分布规律及变形破坏响应特征

三峡库区崩滑地质灾害频发,堆积层滑坡是最常见的滑坡类型。在分析三峡库区145处库岸堆积层滑坡资料基础上,选取地形地貌、地质岩性和斜坡构造作为控制因素、降水和库水波动作为主要诱发因素,探究堆积层滑坡在上述关键影响因子下的分布发育规律及变形破坏响应特征,阐明内在机理,结果表明:(1)受区域地质构造和基岩地层岩性显著控制,滑坡发育频次和规模沿长江存在显著空间差异性;(2)砂页岩夹煤层岩组(SC)和泥灰岩与砂泥岩互层岩组(MSM)对库区堆积层滑坡危害最大,软岩、“软-硬”互层二元结构和水-岩(土)相互作用是主导滑坡发育的主要影响因素;(3)大多数滑坡涉水,主要发育在10°~30°斜坡上,前缘高程集中在100~175 m,受库水波动影响严重,岸别和斜坡结构对堆积层滑坡发育没有明显控制作用;(4)库区滑坡主要由降雨-库水下降联合诱发滑体前缘滑移-拉裂,引发牵引式滑坡,降雨与库水波动各自对滑体的影响格局和程度存在明显差异。以期研究成果为有针对性的库区滑坡总体防治提供一定的科学指导。     

Spatial distribution of landslides induced by the 2004 Mid-Niigata prefecture earthquake,Japan

On October 23, 2004, an earthquake with a moment magnitude of 6.8 occurred in the Chuetsu area of Niigata prefecture in Japan. This earthquake is known as the 2004 Mid-Niigata prefecture earthquake; the event was followed by severe aftershocks and caused many types of landslides such as surficial slides, shallow slides, and deep slides. A large number of landslides occurred in the upland village of Yamakoshi, destroying the entire village; in addition, a huge number of houses collapsed in Kawaguchi town. This study investigates the correlations between each type of landslide and the bedding plane orientation and dip, and other geomorphologic conditions. The landslide occurrence ratio (LOR) is used as an index to determine the correlation between the 2004 Mid-Niigata prefecture earthquake-induced landslides and the slope angle, slope aspect, rock type, and bedding plane orientation and dip. This work also proposes a methodology to determine the geometric alignment between the topography and the orientation of geological bedding planes. The method provides an efficient means of estimating the topography/bedding plane relationship over large areas.     

基于SBAS-InSAR技术的白鹤滩水电站库岸潜在滑坡变形分析

库岸潜在滑坡变形分析是保障国家水利水电设施安全运行的重要环节,针对仅利用单一轨道SAR数据对库岸潜在滑坡变形监测不准确的问题,采用SBAS-InSAR技术,联合升降轨Sentinel-1 SAR数据构建研究区2019年7月至2021年7月的雷达视线方向形变时间序列,并结合无人机野外调查,分析白鹤滩水电站库岸典型潜在滑坡的变形特征。结果表明：（1）受蓄水因素影响,白鹤滩水电站库岸潜在滑坡形变平均增速达10 mm/a以上,库岸稳定性受到破坏;（2）蓄水量变化是当前库岸滑坡发育的关键性诱因,在蓄水和降雨等因素共同作用下,白鹤滩水电站库岸潜在滑坡存在失稳风险;（3）升降轨SAR数据结合的方式能有效克服单一轨道导致的几何畸变等问题,使水电站库岸潜在滑坡变形监测更加准确、全面。研究结果有助于了解库区蓄水对库岸潜在滑坡变形趋势的影响,可为区域尺度防灾应急管理提供科学支持。     

Landslide susceptibility mapping using GIS and weighted overlay method: a case study from North Jordan

Road instability along the Jerash–Amman highway was assessed using the weighted overlay method in Geographic Information System environment. The landslide susceptibility map was developed from nine contributing parameters. The map of landslide susceptibility was classified into five zones: very low (very stable), low (stable), moderate (moderately stable), high (unstable), and very high (highly unstable). The very high susceptibility and high susceptibility zones covered 15.14% and 31.81% of the study area, respectively. The main factors that made most parts of study area prone to landslides include excessive drainage channels, road cuts, and unfavorable rock strata such as marl and friable sandstone intercalated with clay and highly fractured limestone. Fracture zones are a major player in land instability. The moderate and high susceptibility zones are the most common in urban (e.g., Salhoub and Gaza camp) and agricultural areas. About 34% of the urban areas and 28.82% of the agricultural areas are characterized by the high susceptibility zone. Twenty percent of the Jerash–Amman highway length and 58% of the overall highway length are located in the very high susceptibility zone. The landslide susceptibility map was validated by the recorded landslides. More than 80 of the inventoried landslides are in unstable zones, which indicate that the selected causative factors are relevant and the model performs properly.     

三峡库区滑坡空间发育规律及其关键影响因子

三峡库区涉水滑坡众多,目前库岸滑坡空间发育规律及其影响因素尚不明确.收集三峡大坝至库尾江津长江两岸593处滑坡相关资料,选取地层岩性、斜坡结构、高程与坡度作为滑坡关键控制因素及库水作用这一诱发因素.沿三峡大坝追溯至库尾,根据不同影响因子把干流库岸进行分段研究,统计滑坡在各影响因子中的分布特征,分析其分布规律及内在机理,可得以下结论:（1）受不同岩组的工程地质性质差异,干流库岸稳定性差异较大,造成滑坡在空间分布上呈显著区域差异性与分带性特征;（2）在同一岩组的左、右两岸或上下游段滑坡发育密度呈明显局部差异性,其主要受斜坡结构影响,顺向坡中发育密度明显高于横向坡与逆向坡;（3）由于地形地貌条件及库水作用影响,滑坡后缘高程与坡度由库首至库尾逐渐降低,而前缘主要集中于100~175 m,滑坡复活变形的最主要诱发因素为库水位升降作用,当水位作用于滑坡中前部时影响效果最明显,影响时效随着滑坡逐年变形应力调整后逐渐减弱.研究结果为三峡库区滑坡防治提供了一定依据.      

Using an extreme learning machine to predict the displacement of step-like landslides in relation to controlling factors

In the evolution of landslides, besides the geological conditions, displacement depends on the variation of the controlling factors. Due to the periodic fluctuation of the reservoir water level and the precipitation, the shape of cumulative displacement-time curves of the colluvial landslides in the Three Gorges Reservoir follows a step function. The Baijiabao landslide in the Three Gorges region was selected as a case study. By analysing the response relationship between the landslide deformation, the rainfall, the reservoir water level and the groundwater level, an extreme learning machine was proposed in order to establish the landslide displacement prediction model in relation to controlling factors. The result demonstrated that the curves of the predicted and measured values were very similar, with a correlation coefficient of 0.984. They showed a distinctive step-like deformation characteristic, which underlined the role of the influencing factors in the displacement of the landslide. In relation to controlling factors, the proposed extreme learning machine (ELM) model showed a great ability to predict the Baijiabao landslide and is thus an effective displacement prediction method for colluvial landslides with step-like deformation in the Three Gorges Reservoir region.     

台风暴雨型滑坡降雨阈值曲线研究以福建地区为例

台风暴雨型滑坡具有群发性、规模小、爆发性强的特点,容易造成严重的人员伤亡和巨大的财产损失。本文应用极值理论分析,以极端降雨重现期的极大值作为标准并计算有效的降雨区间,通过统计分析,确定触发暴雨型滑坡的降雨阈值曲线。应用模型对福建地区台风暴雨型滑坡进行了分析,福建省3个灾害高发区为:南平三明地区、泉州地区和宁德地区。南平三明地区降雨阈值较高,但发生的滑坡数量较多,主要以3d的降雨为主;泉州地区小于3d的连续降雨和大于8d的连续降雨是触发该地滑坡的主要降雨区间;宁德地区对短期降雨较为敏感,滑坡主要由1d的降雨引起。比较分析研究表明,台风地区触发滑坡的降雨阈值要高于非台风地区。降雨型滑坡阈值主要受气候,地质和土壤厚度影响,气候因素为主控因素。     

基于层次分析法的水库蓄水后滑坡易发性评价

水库库区地形地质和水位地质条件复杂,蓄水后受降雨和库水位变动影响容易产生滑坡、崩塌等次生地质灾害,严重威胁水库安全运行和附近居民安全. 本文依托层次分析法,以某蓄水水库为研究对象,在充分收集其地形地质和水文条件资料的基础上,选取地形地貌、地层岩性、坡度、坡向、地灾点密度、地灾点面积、降雨、库水变动幅度和地震强度等9个致滑因子,构建评价矩阵和滑坡危险性计算评价方法. 依据评价成果划分4个滑坡危险性等级,借助MapGIS软件生成库区潜在滑坡危险性分区图. 该分区图与遥感解译的库区滑坡体分布点高度吻合,验证了评价模型的合理性.     

金沙江干热河谷区滑坡遥感解译研究

“三江”(即金沙江、澜沧江及怒江)地区自然条件恶劣,交通不便,解决该地区水电大开发地质灾害调查中一条切实可行的方法是利用遥感。论文分析了金沙江干热河谷气候环境和地形条件的特点及他们对滑坡解译产生的影响。通过研究这一地区的滑坡在多种遥感影像上的图斑特征配合实地考察,分析并列举了干扰滑坡识别的图斑,总结出该地区的古滑坡、活动滑坡和典型滑坡的识别特征。同时对该地区滑坡不发育,所占地质灾害比例低的现象进行了分析。指出当地气候、地形、构造特征、岩土类型对滑坡发育存在的影响。为该类型地区的遥感地质调查提供借鉴。     

基于逻辑回归–信息量的川藏交通廊道滑坡易发性评价

川藏交通廊道位于青藏高原中东部,是世界上隆升和地貌演化最快的区域之一。在内外动力耦合作用下,区内滑坡灾害极其发育,严重制约着公路、铁路和水电工程的规划建设。在区域地质资料收集和整理的基础上,选取岩性、坡度、坡向、坡形、地形起伏度、地形粗糙度、断裂密度和河流距离8个因素为评价因子,结合传统信息量和逻辑回归模型的优势,采用逻辑回归–信息量模型对研究区滑坡进行易发性评价。通过对评价因子的多重共线性和显著性检验,得到评价因子不存在多重共线性且均对滑坡发生具有显著影响。采用ROC曲线对评价结果进行检验,其AUC值为0.81,表明评价模型能很好地预测滑坡的发生。易发性评价结果表明:研究区高易发区主要集中龙门山断裂带、金沙江断裂带、澜沧江断裂带、怒江断裂带、边坝–洛隆断裂带等大型活动断裂带控制区,以及区内坡度陡峭、地形起伏度大的大型河流深切河谷的两岸;中易发区在区内分布广泛,主要分布在岸坡较陡、地形起伏度中等的大型河流支流的两岸。研究结果有利于加深对川藏交通廊道滑坡发育分布的认识,也可为研究区的工程规划建设和防灾减灾提供科学依据。     

Landslides in the Rumphi District of Northern Malawi: characteristics and mechanisms of generation

Landslides are a common phenomenon in all the regions of Malawi. A number of historical landslides have been documented and are summarized here. This paper examines the occurrence of landslides in the Rumphi District of Northern Malawi. The study is based on a detailed study of 98 landslides that occurred in 2003 at Ntchenachena and Chiweta areas in the Rumphi District. This paper examines factors that contributed to and caused these landslides. The paper suggests that landslides were triggered by 206 mm of rain received in 2 days. The high percentage of medium to fine sand and abrupt rise in pore pressure accelerated the process of liquefaction at Ntchenachena. Cleft water pressure at the point between regolith and soil mass caused a number of slides in the Chiweta areas. High slope angles, deep weathering of the basement and high annual total rainfall contributed to the slope instability. Human activities through cultivation on steep slope, slope remodeling, and deforestation significantly altered the conditions of the slopes, thereby increasing the degree of landslide hazard present in these areas.     

汉江孤山水电站库首罗行滩滑坡稳定性分析及处理对策

罗行滩滑坡是汉江孤山水电站库首的重要滑坡之一,系发育在崩坡积土层中的堆积层滑坡,体积约70×104 m3,属中型滑坡。据野外调查,初步分析滑坡目前整体处于基本稳定状态。分现状、暴雨和水库蓄水等3种工况对滑坡进行稳定性计算,结果表明：在现状条件下,滑坡基本稳定;在暴雨工况和蓄水工况条件下两侧滑体稳定性较差,中段滑体稳定性较好,但两侧滑体若失稳对中段滑体稳定不利。滑坡失稳对工程危害较大,建议滑坡治理结合大坝围堰填筑用料采取清除措施。     

三峡树坪滑坡动力学的有限元模拟

三峡工程是迄今为止最大的水利工程,对库区滑坡灾害的监测和机制研究一直是重要的研究课题。本文利用Terra SAR-X的强度图进行相关计算,求解出2009年5月20日至8月5日期间三峡树坪滑坡的形变场。该形变场特征和树坪滑坡体的地形特征吻合甚好,位移大小、方向和三峡大学对滑坡体的野外观测结果基本吻合。以此高精度位移场为外部约束,结合野外观测资料对滑坡体介质力学性质进行分类并选取边界条件,利用有限元方法对滑坡活动进行动力学计算模拟。计算过程中对滑坡体的滑动面形状、因降雨引起材料参数变化和三峡水库水位等因素分别反演和调整,得出符合其变形和发展过程的滑坡动力学特征。发现软弱带的物性参数决定滑坡体总体滑动量,滑坡体的物性参数决定位移分布的峰值位置。在确定了滑坡动力学特征之后,进一步讨论降雨和库区水位下降对滑坡产生的贡献权重,得出降雨是树坪滑坡的决定因素。     

典型黄土丘陵区浅层黄土滑坡稳定性评价——以延安市志丹县为例

黄土丘陵地区地质环境脆弱,每到雨季极易诱发浅层黄土滑坡,对居民的生命和财产安全构成威胁也阻碍着当地经济的发展。对浅层滑坡进行稳定性评价,不仅有助于认识浅层滑坡的发生发展过程,而且对防灾减灾和地区规划建设具有十分重要的指导意义。本研究选择SINMAP模型作为评价浅层黄土滑坡的重要工具,评价了陕西省延安市志丹县黄土丘陵区浅层滑坡的稳定性,评价结果表明:1)研究区整体稳定性程度较高,在降雨量为8.6 mm、15 mm、25 mm、50 mm和100 mm时不稳定区域(包括极不稳定、不稳定和潜在不稳定)面积分别占研究区总面积的9.12%、18.93%、23.17%、30.94%和38.67%,不稳定区域的面积不超过整个研究区面积的一半,极不稳定区域的滑坡密度最大,其次为不稳定区域和潜在不稳定区域;2)随着降雨量的增大,潜在不稳定和不稳定区域的面积会逐渐扩大,极不稳定区始终位于坡度大且水流侵蚀强烈的地方,变化幅度小;3)浅层滑坡的稳定性很大程度上依赖于当地的地形条件:坡度分布为20°~51°,高程分布范围为1302~1606 m,在坡向上阴坡的发生数量多于阳坡,西向和西北向浅层滑坡最为发育;4)流域内的滑坡多属降雨诱发的山体滑坡,确定性模型SINMAP为预测这一类滑坡提供了强大的工具,不仅评估了现有的已发生的滑坡的稳定性,也预测了未来在不同降雨条件下可能发生滑坡的地区。分析结果可为预防和减轻滑坡灾害带来的损失,合理的城市规划和道路选址等提供参考。     

A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses

Bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation. A landslide inventory map was prepared using landslide locations identified from aerial photographs, field checks, and existing literature. Instability factors such as slope angle, soil type, soil erodibility, soil liquidity index, landcover pattern, precipitation, and proximity to stream, responsible for the occurrence of landslides, were imported as raster data layers in ArcGIS, and ranked using a numerical scale corresponding to the physical conditions of the region. In order to investigate the role of each instability factor in controlling the spatial distribution of landslides, both bivariate and multivariate models were used to analyze the digital dataset. The logistic regression approach was used in the multivariate model analysis. Both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method, and by comparing the maps with the known landslide locations. The multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area. The logistic regression model produced a landslide susceptibility map at a scale of 1:24,000 that classified susceptibility into four categories: low, moderate, high, and very high. The results also indicated that slope angle, proximity to stream, soil erodibility, and soil type were statistically significant in controlling the slope movement.