基于I-D阈值的滑坡气象预警双指标模型

确定降雨阈值对于管控降雨型滑坡灾害风险具有重要意义。以浙江衢州市98处降雨型滑坡为例进行降雨阈值研究。在统计分析1970—2019年梅汛期间诱发滑坡降雨特征的基础上,首先对比分析I-D、E-D和E-I曲线建立的降雨阈值模型,然后基于I-D阈值建立以当日降雨量R₀和5 d有效降雨量R₅为预警指标的滑坡气象预警双指标模型,最后采用历史降雨和滑坡数据检验模型的合理性和可靠性。结果表明：(1)I-D模型对于降雨型滑坡的预测能力优于E-D和E-I模型;(2)按双指标模型反演衢州市历史50 a滑坡气象预警情况,红色、橙色和黄色预警的年均预警次数为1.5,3.2,9.3次,具有较高的合理性;20处验证滑坡点被双指标模型准确预警,其中15处为红色和橙色预警,此外模型成功预警了2014年全部8处降雨型滑坡;(3)用于检验模型预测能力的7处滞后性滑坡全部成功预警,其中3处橙色预警、3处黄色预警和1处蓝色预警。本研究提出的预警模型有助于衢州市滑坡气象预警发布,为政府部门开展风险评价和管理提供新思路与方法。     

降雨引发地质灾害的预报工作亟待规范

“地质灾害气象预报预警”和“地质灾害气象风险预警”内涵不清,以致人们可能被误导,认为通过气象（降雨）就可以预报滑坡、泥石流等地质灾害。 引发滑坡、泥石流的降雨量与地层岩性、断裂构造、地形地貌、植被土壤等地质环境因素密切相关,这些因素在空间上是变化的,在一个降雨区域的不同地方,降雨引发滑坡、泥石流的概率不同。     

基于LSTM＿TCN模型的降雨型滑坡时间概率预测及气象预警建模

如果滑坡发生时间信息不完备则会导致滑坡与降雨时序关系错误,以至于降雨阈值模型精度偏低。以重庆市万州区1995-2015年所发生的降雨型滑坡为研究对象,将区内严重缺失历史滑坡时间信息的恒合乡作为验证区,提出了一种基于长短时记忆网络(LSTM)融合时域卷积网络(TCN)的模型方法。该方法通过模拟降雨型滑坡发生时间与降雨量间的非线性关系,重建降雨型滑坡事件在某日发生的时间概率。将重建时间信息后的滑坡事件进行了验证与筛选,应用于累积有效降雨量-降雨历时曲线的合理划分,构建了滑坡气象预警模型。结果表明,本方法所预测滑坡时间概率平均值达到90.33%,高于人工神经网络(ANN)(71.17%)、LSTM(72.75%)和TCN(86.91%)的概率。利用预测概率高于90%的滑坡,将验证区18个时间信息扩充至201个。基于扩充时间信息后的滑坡数据所构建的气象预警模型比仅利用历史滑坡事件具有更合理的预警分级,在严重警告级别上有效预警率提升了42.86%。结果说明该方法可弥补野外调查中灾害数据时间信息不足的问题,为降雨型滑坡气象预警工作提供数据支撑,由此提高气象预警准确率。     

基于WebGIS云南滑坡灾害气象预警分析模型

针对云南主要由降雨引起的滑坡地质灾害现象,对云南近8年来的滑坡灾害数据和降雨量数据进行了分析,研究并设计了一种针对滑坡地质灾害发生的时空耦合预警分析模型。并在此基础上,通过与WebGIS技术的耦合,运用新一代的RIA技术Silverlight,基于MapGIS IGServer平台,在异步响应的网络中使用流程化的操作方式构建出云南省地质灾害气象预警系统。通过实例检验表明该滑坡地质灾害气象预警分析模型的应用,能够为相关部门提供更精确、及时的减灾防灾对策。     

强降雨过程对安化县、永顺县地质灾害气象预警预报工作的探讨

湘西北地区为湖南省地质灾害高易发区,多年以来一直是湖南省汛期地质灾害气象预警预报关注的重点地区。本文以2014年7月的一次强降雨过程分析为例,探讨安化、永顺两县降雨与地质灾害发生的关系,对已有的气象预警预报模型进行修正、完善,通过GIS平台网格化、调整参评因素权重、确定区域降雨引发地质灾害阈值等方法,达到湘西北地区地质灾害气象预警预报初步精细化的目标,并通过上述方法的探讨,对全省地质灾害气象预警预报精细化工作推进提供经验。     

滑坡灾害预测预报信息共享平台

 滑坡是最常见的一种地质灾害,其主要诱因是降雨。滑坡灾害多发生在雨量充沛地域或洪水季节。南京市受自然环境和地质环境的影响,滑坡是其最主要的地质灾害类型之一,为了有效地预测滑坡的发生情况并最大限度地减少滑坡灾害为南京带来的损失,本文在已有的南京市地质灾害易发区等研究的成果上,结合南京市历史滑坡数据、气象资料和地质灾害预测数学模型构建了南京市滑坡灾害预测方法并确定了南京市滑坡灾害预测预报技术流程。在该预测方法和技术流程的基础上,本文同时应用了数据库技术、ArcGIS Server技术、AJAX远程调用技术、网页局部刷新技术和地图缓存技术等,融合地理信息系统功能与滑坡灾害预测预报业务功能,开发了南京市滑坡灾害预测预报信息共享平台。该平台可以对滑坡灾害基础数据和实时气象数据动态、科学地管理,结合南京市实时降雨数据可实现滑坡灾害预测预报并将灾害信息实时在线发布,同时提供对滑坡灾害信息的查询、检索、统计分析等功能,最终通过该信息共享平台,为南京市滑坡灾害的防灾减灾提供决策支持,为其他需要建立滑坡灾害预测信息共享平台的城市提供参考。     

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。      

湖南省沅麻盆地红层地区滑坡专业监测初探——以怀化辰溪大水田窝棚溪滑坡为例

湖南沅麻盆地红层地区是我省地质灾害高易发区,多年来一直是我省地质灾害气象风险预警重点关注区域。本文以怀化市辰溪县大水田乡窝棚溪滑坡专业监测点为例,初探沅麻盆地红层地区滑坡专业监测方法。通过分析强降雨过程各监测因子数据变化情况,分析判定已布设各监测设备的监测效果,对后期沅麻盆地红层区域地质灾害监测手段和方法提出建议,同时希望能对影响滑坡的降雨量、孔隙水压力、土壤含水率,地表位移及深部位移等因素和滑坡气象预警指标体系建立有一定的指导意义。     

降雨型黄土滑坡预警研究现状综述

黄土滑坡是一类典型的地质灾害,但目前并没有针对这类滑坡的区域性预警模型。介绍了黄土滑坡的分类和滑带特征研究现状,讨论了降雨型滑坡的两类预警模型:降雨型滑坡临界雨量模型,包括区域统计概率预警和临界雨量阈值预警;物理预警模型,主要为通过建立力学稳定性分析和降雨入渗模型耦合得到的预警模型。分析了降雨或地下水作用下土体含水量变化对滑坡稳定性的影响研究和黄土滑坡的预警研究现状,最后根据前人研究现状讨论了现有预警模型的特点并提出了未来降雨型黄土滑坡预警可能的发展方向。      

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。     

Probability Prediction Model for Landslide Occurrences in Xi’an,Shaanxi Province,China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall （IR） and antecedent effective rainfall （AER）. Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.     

基于修正Green-Ampt模型的降雨诱发区域浅层斜坡失稳灾害分析

由于具有类似的工程地质和水文地质条件, 在高度相关的降雨作用下, 同一个区域中的降雨诱发浅层斜坡失稳灾害常成群出现。在区域尺度预测浅层斜坡失稳灾害对滑坡灾害的防灾减灾工作具有重要的意义。为此, 提出了一种基于力学原理的降雨诱发浅层斜坡失稳灾害预测新模型RARIL。该模型采用修正Green-Ampt模型进行降雨入渗分析, 采用无限体边坡模型进行安全系数计算, 利用可靠度原理考虑区域斜坡稳定性分析中的参数不确定性。该模型具有可考虑降雨诱发浅层斜坡的失稳力学机理、可考虑区域内斜坡土体参数不确定性, 以及计算效率高、易于在GIS平台上实现等优点。案例分析表明, RARIL模型较为准确地预测了2010年8月12日11∶00至2010年8月14日9∶00期间强降雨在四川省汶川县映秀镇附近的303省道K0-K20段沿线区域引发的滑坡灾害, 研究结果证明RARIL模型在预测降雨诱发区域斜坡失稳灾害方面有很好的应用前景。      

泰安市地质灾害预警预报系统研究

主要介绍了泰安市地质灾害气象风险预警与指挥系统。系统开发的主要目的是为了更好的与泰安市地质灾害防治工作相结合,通过对气象因素及地质灾害资料的分析和研究,基于地质灾害气象预警模型,采用先进的GIS技术能实现对地质灾害易发风险性区域预警,能直观地了解到各部分区域的地质灾害易发风险性,为各级政府防灾减灾提供科学的技术支撑。     

Estimation of rainfall thresholds for shallow landslides in the Sierra Madre Oriental,northeastern Mexico

Landslides induced by prolonged rainfalls are frequent mass movements along the northeastern portion of the Sierra Madre Oriental in Mexico, causing significant damage to infrastructure. In this work, we have studied the connection between rainfall and landslides in the Santa Rosa Canyon, a catchment located in the northeastern Mexico. A landslide database triggered by major storms and hurricanes that have hit the region over the past 30 years was analyzed. A total of 92 rainfall events in the Santa Rosa Canyon were studied to determine the amount of precipitation needed to trigger shallow landslides. For each event the duration(D, in hours) and the cumulated rainfall event(E, in mm) were determined by using historical rainfall data from weather stations located near the study area. We have proposed an ED threshold for rainfall-induced landslides with durations 0.5 D 120 hours to address the conditions that trigger these events in the study area. On analyzing the obtained threshold, it has been established that almost 60 mm of a daily rainfall accumulation is required to trigger shallow landslides in the study area. This estimation is consistent with other calculations made for areas close to the Santa Rosa Canyon. Finally, we validated the predictive capability of the threshold with a different set of rainfall data that did not result in landslides performing a straightforward receiver operating characteristic analysis. A good approach was obtained, especially for rainfall events with daily measurements. Results could be used as input information in the design of a landslide early warning system for the northeastern Mexico, and replicated for other landslide prone areas in the region.     

Landslide and basin self-organized criticality in the Lushan Hot Spring area

Defining a basin under a critical state(or a self-organized criticality) that has the potential to initiate landslides,debris flows,and subsequent sediment disasters,is a key issue for disaster prevention.The Lushan Hot Spring area in Nantou County,Taiwan,suffered serious sediment disasters after typhoons Sinlaku and Jangmi in 2008,and following Typhoon Morakot in 2009.The basin’s internal slope instability after the typhoons brought rain was examined using the landslide frequency-area distribution.The critical state indices attributed to landslide frequency-area distribution are discussed and the marginally unstable characteristics of the study area indicated.The landslides were interpreted from Spot 5 images before and after disastrous events.The results of the analysis show that the power-law landslide frequency-area curves in the basin for different rainfall-induced events tend to coincide with a single line.The temporal trend of the rainfallinduced landslide frequency-area distribution shows 1/f noise and scale invariance.A trend exists for landslide frequency-area distribution in log-log space for larger landslides controlled by the historical maximum accumulated rainfall brought by typhoons.The unstable state of the basin,including landslides,breached dams,and debris flows,are parts of the basin’s self-organizing processes.The critical state of landslide frequency-area distribution could be estimated by a critical exponent of 1.0.The distribution could be used for future estimation of the potential landslide magnitude for disaster mitigation and to identify the current state of a basin for management.     

Reflection of typhoon morakot �� the challenge of compound disaster simulation

Climate change has altered locally single-type disasters to large-scale compound disasters because of increasing intensity and frequency of extreme rainfall events. The compound disasters can combine small-scale floods, debris flows, shallow landslides, deep-seated landslides, and landslide lakes into a large-scale single disaster event. Although simulation models and evaluation tools are available for single-type disasters, no single model is well developed for compound disasters due to the difficulty of handling the interrelationship between two successive single-type disasters. This study proposes a structure for linking available single-type simulation models to evaluate compound disasters and provides a useful tool of decision making for warning and planning of disaster reduction.     

泰安市崩塌、滑坡、泥石流发育特征及防治对策浅析

泰安市地处鲁中山区,地形地质条件较复杂,是山东省崩塌、滑坡、泥石流地质灾害的多发区,在强降雨条件下,地质灾害频繁发生,制约了当地社会经济的发展.本文通过对研究区崩塌、滑坡、泥石流发育现状、地质灾害特征进行统计分析,从地貌特征、岩土体特征、地质构造、降水、植被、人类工程活动等方面,深入阐述了崩塌、滑坡、泥石流与地质环境条...     

Preliminary studies on the dynamic prediction method of rainfall-triggered landslide

Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorologicalgeotechnical early warning system GRAPES-LFM(GRAPES: Global and Regional Assimilation and Pr Ediction System; LFM: Landslide Forecast Model),basing on the GRAPES model and the landslide predicting model TRIGRS(Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides.This integrated system is evaluated in Dehua County,Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP(National Centers for Environmental Prediction) FNL(Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety(FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides.