A cross-border regional earthquake early warning system: PRESTo@CE<Superscript>3</Superscript>RN

Since 2002 the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS) in Udine (Italy), the Agencija Republike Slovenije za Okolje (ARSO) in Ljubljana (Slovenia) and the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) in Vienna (Austria), are collecting, analyzing, archiving and exchanging seismic data in real time, initially in the framework of the EU Interreg IIIa Italia-Austria project “Trans-national seismological networks in the South-Eastern Alps”. As outcome of the successful cooperation, in the 2013 OGS, ARSO and ZAMG decided to officially merge their seismic monitoring efforts into the “Central and Eastern European Earthquake Research Network—CE³RN”. This work reports the results of a nine-month real-time test of the earthquake early warning (EEW) algorithm probabilistic and evolutionary early warning system carried out at the CE³RN. The study allowed identifying the actions to be implemented in order to let the CE³RN become in the next future an efficient cross-border EEW system.     

Integrated smart robot with earthquake early warning system for automated inspection and emergency response

Natural Hazards - Earthquakes as a natural hazard have caused substantial economic losses and human life loss in many countries. Taiwan, which is located on the western Circum-Pacific seismic belt,...     

基于WEBGIS和实时降雨信息的区域地质灾害预警预报系统

基于WEBGIS平台,根据浙江省地质灾害大调查和补充调查资料,结合浙江省气象台提供的雨季实时降雨量与降雨量预测信息,建立了浙江省突发性地质灾害预警预报系统。该系统目的在于：（1）建立浙江省突发性地质灾害信息库管理系统,实现对突发性地质灾害点分布和灾情信息的图形和数据一体化管理;（2）建立基于网络或其它通讯方式的滑坡（泥石流）灾害实时预警预报系统,实现与气象部门的连接,根据雨季的实时降雨预报和雨量资料,对浙江省滑坡（泥石流）灾害发生的空间范围进行实时发布。该系统核心是地质灾害预警预报模块,而模块是在区域地质灾害空间预测的基础上,结合实时的气象动态信息,研究在不同地质环境和不同气象条件下地质灾害体发生的规律,以提高区域地质灾害的预报精度。2004年的5月底到7月初的雨季中进行了试运行,该系统的预测情况与地质灾害的实际发生情况吻合性较好,表明预测方法和模型是基本可行的,且可操作性强。     

降雨诱发区域性滑坡预报预警方法研究

论文以四川省雅安市雨城区为研究区,将逻辑回归模型引入区域降雨型滑坡预警预报,建立了同时考虑降雨强度和降雨过程的降雨临界值表达式.在滑坡危险性区划的基础上,研究提出了区域降雨型滑坡预警预报指标,包括临界值降雨指数R和滑坡发生指数L,并利用20台自动遥测雨量计和地质灾害群测群防网络,采用历史记录雨量和预报雨量,建立了区域降雨型滑坡预报预警体系.     

A regional real-time debris-flow warning system for the District of North Vancouver, Canada

Engineered (structural) debris-flow mitigation for all creeks with elements at risk and subject to debris flows is often outside of the financial capability of the regulating government, and heavy task-specific taxation may be politically undesirable. Structural debris-flow mitigation may only be achieved over long (decadal scale) time periods. Where immediate structural mitigation is cost-prohibitive, an interim solution can be identified to manage residual risk. This can be achieved by implementing a debris-flow warning system that enables residents to reduce their personal risk for loss of life through timely evacuation. This paper describes Canada??s first real-time debris-flow warning system which has been operated for 2 years for the District of North Vancouver. The system was developed based on discriminant function analyses of 20 hydrometric input variables consisting of antecedent rainfall and storm rainfall intensities for a total of 63 storms. Of these 27 resulted in shallow landslides and subsequent debris flows, while 36 storms were sampled that did not reportedly result in debris flows. The discriminant function analysis identified as the three most significant variables: the 4-week antecedent rainfall, the 2-day antecedent rainfall, and the 48-h rainfall intensity during the landslide-triggering storm. Discriminant functions were developed and tested for robustness against a nearby rain gauge dataset. The resulting classification functions provide a measure for the likelihood of debris-flow initiation. Several system complexities were added to render the classification functions into a usable and defensible warning system. This involved the addition of various functionality criteria such as not skipping warning levels, providing sufficient warning time before debris flows would occur, and hourly adjustment of actual rainfall vs. predicted rainfall since predicted rainfall is not error-free. After numerous iterations that involved warning threshold and cancelation refinements and further model calibrations, an optimal solution was found that best matches the actual debris-flow data record. Back-calculation of the model??s 21-year record confirmed that 76% of all debris flows would have occurred during warning or severe warning levels. Adding the past 2 years of system operation, this percentage increases marginally to 77%. With respect to the District of North Vancouver boundaries, all debris flows occur during Warning and Severe Warnings emphasizing the validity of the system to the area for which it was intended. To operate the system, real-time rainfall data are obtained from a rain gauge in the District of North Vancouver. Antecedent rainfall is automatically calculated as a sliding time window for the 4-week and 2-day periods every hour. The predicted 48-h storm rainfall data are provided by the Geophysical Disaster Computational Fluid Dynamics Centre at the Earth and Ocean Science Department at the University of British Columbia and is updated every hour as rainfall is recorded during a given storm. The warning system differentiates five different stages: no watch, watch level 1 (the warning level is unlikely to be reached), watch level 2 (the warning level is likely to be reached), warning, and severe warning. The debris-flow warning system has operated from October 1, 2009 to April 30, 2010 and October 1, 2010 and April 30, 2011. Fortunately, we were able to evaluate model performance because the exact times of debris flows during November 2009 and January 2010 were recorded. In both cases, the debris flows did not only occur during the warning level but coincided with peaks in the warning graphs. Furthermore, four debris flows occurred during a warning period in November 2009 in the Metro Vancouver watershed though their exact time of day is unknown. The warning level was reached 13 times, and in four of these cases, debris flows were recorded in the study area. One debris flow was recorded during watch II level. There was no severe warning during the 2 years of operation. The current warning level during the wet season (October to April) is accessible via District of North Vancouver??s homepage (www.dnv.org) and by automated telephone message during the rainy season.     

区域地质灾害评价预警的递进分析理论与方法

根据多年丰富的区域地质灾害考察和综合研究实践,作者架构了区域地质灾害评价预警研究的理论体系和工作方法,主要包括:(1)开展区域地质灾害综合调查;(2)建立地质灾害信息系统,包括基于GIS的区域地质灾害空间数据库和分层图形库(GGIS);(3)研究区域地质灾害分布与地形(高程、高差、坡度)、水系、植被、工程地质岩组、地质构造形迹、斜坡类型、降雨量分布和地震活动等的统计关系,为评价因子选取、分级和权重确定提供依据;(4)筛选提取评价预警研究因子体系,建立地质灾害发育因子、基础因子、诱发因子和易损因子体系;(5)创建研究区域地质灾害"发育度"、"潜势度"、"危险度"和"危害度"(简称"四度")的概念模型和数学模型;(6)在满足一定精度比例尺数字化图上划分计算单元,分别计算研究区域地质灾害"发育度"、"潜势度"、"危险度"和"危害度";(7)根据计算结果和应用目的,把相同或相近级别的图斑合并,分别编制区域地质灾害"四度"区划图;(8)根据"四度"区划结果提出研究区的地质灾害防治规划、分级监测预警目标区和地质环境可持续开发利用对策;(9)对重点地段或地点专门编制地质灾害防治预案和政府-社会联动的应急反应机制.上述9个步骤构成区域地质灾害评价预警的时空递进分析理论与方法,简称"四度"递进分析法(AMFP).该方法在三峡库区(54175km2)和四川雅安(1067km2)进行了应用,结果是可信的.     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Hydrological extreme events pose an imminent risk to society and economics. In this paper, various aspects of hydrological hazards in Russia are analysed at different scales of risk assessment. It is shown that the number of hydrological and meteorological hazards in Russia has been growing every year. The frequency of economic losses associated with extreme low flow in this century has increased by factor five compared to the last decade of the previous century. With regard to floods, an interesting spatial patter can be observed. On the one hand, the number of floods in the Asian part of the country has increased, whereas on the other hand, the number and intensity of floods in estuarine areas in the European part of Russia have significantly reduced since the middle of the twentieth century, especially in the 2000s. This decrease can be attributed to runoff flooding in the mouths of regulated rivers, with an effective system of flood and ice jam protection. The analysis shows that there is an 8–12-year periodicity in the number of flood occurrences and that flood surges have intensified over the last 110 years, especially on the European territory of Russia. An integrated index that accounts for flood hazards and socio-economic vulnerability was calculated for each region of Russia. A classification of flood risk was also developed, taking into account more than 20 hydrological and social–economic characteristics. Based on these characteristics, hazard and vulnerability maps for entire Russia were generated which can be used for water management and the development of future water resources plans.     

基于显式统计原理的地质灾害区域预警方法初步研究

区域预警是提高防灾减灾意识、有效减轻地质灾害造成损失的重要手段。地质灾害显式统计预警理论考虑了地质环境变化与降雨参数等多因素的耦合作用,克服了传统单一临界雨量判据方法的局限。笔者应用地质灾害显式统计预警的基本原理,以中国的东南区为例开展应用研究。选取岩土体类型、地形起伏等12个基础地质环境因素.通过确定性系数模型(CF)综合分析了地质灾害分布与地质环境基础因素的关系.选取地质灾害"潜势度"作为地质环境优劣的指标,并进行了定量计算。选取当日雨量和一个降雨过程的前期累计雨量作为降雨激发因素的指标.采用多元回归的统计分析方法,分析了地质环境因素、降雨激发因素的耦合作用与地质灾害发育情况之间的关系.建立了显式统计的地质灾害预警预报模型。以2006年5月18日台风"珍珠"登陆期间的实况预警情况对模型进行了应用校验。验证了显式统计预警原理及模型方法的可行性和实用性。     

Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides

A process chain for the definition and the performance assessment of an operational regional warning model for rainfall-induced landslides, based on rainfall thresholds, is proposed and tested in a landslide-prone area in the Campania region, southern Italy. A database of 96 shallow landslides triggered by rainfall in the period 2003–2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall threshold equations are defined applying a well-known frequentist method to all the reconstructed rainfall conditions responsible for the documented landslides in the area of analysis. Several thresholds at different exceedance probabilities (percentiles) are evaluated, and nine different percentile combinations are selected for the activation of three warning levels. Subsequently, for each combination, the issuing of warning levels is computed by comparing, over time, the measured rainfall with the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system, i.e. the one providing the best model performance in terms of success and error indicators, is selected employing the “event, duration matrix, performance” (EDuMaP) method.     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Crucial to most landslide early warning system (EWS) is the precise prediction of rainfall in space and time. Researchers are aware of the importance of the spatial variability of rainfall in landslide studies. Commonly, however, it is neglected by implementing simplified approaches (e.g. representative rain gauges for an entire area). With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on deterministic and geostatistical methods. With kriging usually being a labour-intensive, manual task, a simplified variogram modelling routine was applied for the automated processing of up-to-date point information data. Validation showed quite satisfactory results, yet it also revealed the drawbacks that are associated with univariate geostatistical interpolation techniques which solely rely on rain gauges (e.g. smoothing of data, difficulties in resolving small-scale, highly intermittent rainfall). In the perspective, the potential use of citizen scientific data is highlighted for the improvement of studies on landslide EWS.     

基于逻辑回归的四川青川县区域滑坡灾害预警模型

四川省青川县滑坡灾害群发,点多面广,区域滑坡灾害预警是有效防灾减灾的重要手段,预警模型是成功预警的核心。由于研究区滑坡诱发机理复杂、调查监测大数据及分析方法不足等原因,传统区域地质灾害预警模型存在预警精度有限、精细化不足等问题。文章在青川县地质灾害调查监测和降水监测成果集成整理与数据清洗基础上,构建了青川县区域滑坡灾害训练样本集,样本集包括地质环境、降雨等27个输入特征属性和1个输出特征属性,涵盖了青川县近9年（2010—2018年）全部样本,数量达1 826个（其中,正样本613个,负样本1 213个）。基于逻辑回归算法,对样本集进行5折交叉验证学习训练,采用贝叶斯优化算法进行模型优化,采用精确度、ROC曲线和AUC值等指标校验模型准确度和模型泛化能力。其中,ROC曲线也称为“受试者工作特征”曲线;AUC值表示ROC曲线下的面积。校验结果显示,基于逻辑回归算法的模型训练结果准确率和泛化能力均较好（准确率94.3%,AUC为0.980）。开展区域滑坡实际预警时,按训练样本特征属性格式,输入研究区各预警单元27个特征属性,调用预先学习训练好的模型,输出滑坡灾害发生概率,根据输出概率分段确定滑坡灾害预警等级。当输出概率P≥40%且P<60%时,发布黄色预警;当输出概率P≥60%且P<80%时,发布橙色预警;当输出概率P≥80%时,发布红色预警。     

A generalized geo-hazard warning system

An automated geo-hazard warning system is the need of the hour. It is integration of automation in hazard evaluation and warning communication. The primary objective of this paper is to explain a geo-hazard warning system based on Internet-resident concept and available cellular mobile infrastructure that makes use of geo-spatial data. The functionality of the system is modular in architecture having input, understanding, expert, output and warning modules. Thus, the system provides flexibility in integration between different types of hazard evaluation and communication systems leading to a generalized hazard warning system. The developed system has been validated for landslide hazard in Indian conditions. It has been realized through utilization of landslide causative factors, rainfall forecast from NASA??s TRMM (Tropical Rainfall Measuring Mission) and knowledge base of landslide hazard intensity map and invokes the warning as warranted. The system evaluated hazard commensurate with expert evaluation within 5?C6?% variability, and the warning message permeability has been found to be virtually instantaneous, with a maximum time lag recorded as 50?s, minimum of 10?s. So it could be concluded that a novel and stand-alone system for dynamic hazard warning has been developed and implemented. Such a handy system could be very useful in a densely populated country where people are unaware of the impending hazard.     

IFKIS-Hydro: an early warning and information system for floods and debris flows

IFKIS-Hydro is an information and warning system for hydrological hazards in small- and medium-scale catchments. The system collects data such as weather forecasts, precipitation measurements, water level gauges, discharge simulations and local observations of event-specific phenomena. In addition, IFKIS-Hydro incorporates a web-based information platform, which serves as a central hub for the submission and overview of data. Special emphasis is given to local information. This is accomplished particularly by human observers. In medium-scale catchments, discharge forecast models have an increasing importance in providing valuable information. IFKIS-Hydro was developed in several test regions in Switzerland and the first results of its application are available now. The system is constantly extended to additional regions and may become the standard for warning systems in smaller catchments in Switzerland.     

地质灾害区域预警原理与显式预警系统设计研究

通过总结分析国内外经验和新认识,文章把地质灾害区域预警原理初步划分为隐式统计预警、显式统计预警和动力预警三种类型.隐式统计预警是把地质环境因素的作用隐含在降雨参数中,仅仅考虑降雨参数建立模型的方法.显式统计预警是一种把地质环境因素变化与激发因素相迭加耦合而后建立判据模型的预警方法.动力预警是一种考虑地质体在降雨过程中自身动力变化过程而建立数学物理判据方程的方法,实质上是一种解析预警方法.本文以系统工程思想为指导,比较全面地架构了显式统计预警系统的设计方法,包括需求分析、问题表述、目标设定、设计原则、图层设计、系统建模、系统运算、预警等级确定、产品生成、产品会商、产品发布、预警校验、预警决策、应急行动、成本收益分析和系统完善升级等内容.这项设计研究为具体研发设计某个地区的预警系统提供了思想平台,为建立国家、省和市(县)分层级联动的地质灾害区域预警体系提供了技术路线.     

Rainfall thresholds for landslide early warning system in Nakhon Si Thammarat

Transient seepage in unsaturated soil slope is one of the significant triggering factors in rainfall-induced landslides. Rainfall infiltration leads to the decrease in stabilizing effect because of increased positive pore-water pressures. SEEP/W and SLOPE/W used in this study have been widely employed to describe frameworks for understanding transient seepage in soil slope, and to perform slope stability analyses, respectively. The study area is in Sichon District in Nakhon Si Thammarat Province, southern Thailand. A landslide there was investigated by modeling the process of rainfall infiltration under positive and negative pore-water pressures and their effects on slope stability. GIS (Geographic Information System) and geotechnical laboratory results were used as input parameters. The van Genuchten’s soil water characteristic curve and unsaturated permeability function were used to estimate surface infiltration rates. An average rainfall was derived from 30-year monthly rainfall data between 1981 and 2011 in this area reported by the Thailand Royal Irrigation Department. For transient condition, finite element analysis in SEEP/W was employed to model fluctuations in pore-water pressure during a rainfall, using the computed water infiltration rates as surface boundary conditions. SLOPE/W employing Bishop simplified method was then carried out to compute their factors of safety, and antecedent precipitation indices (API) calculated. Heterogeneous slope at the site became unstable at an average critical API (API_cr) of 380 mm, agreeing well with the actual value of 388 mm.     

Integration of a limit-equilibrium model into a landslide early warning system

Landslides are a significant hazard in many parts of the world and exhibit a high, and often underestimated, damage potential. Deploying landslide early warning systems is one risk management strategy that, amongst others, can be used to protect local communities. In geotechnical applications, slope stability models play an important role in predicting slope behaviour as a result of external influences; however, they are only rarely incorporated into landslide early warning systems. In this study, the physically based slope stability model CHASM (Combined Hydrology and Stability Model) was initially applied to a reactivated landslide in the Swabian Alb to assess stability conditions and was subsequently integrated into a prototype of a semi-automated landslide early warning system. The results of the CHASM application demonstrate that for several potential shear surfaces the Factor of Safety is relatively low, and subsequent rainfall events could cause instability. To integrate and automate CHASM within an early warning system, international geospatial standards were employed to ensure the interoperability of system components and the transferability of the implemented system as a whole. The CHASM algorithm is automatically run as a web processing service, utilising fixed, predetermined input data, and variable input data including hydrological monitoring data and quantitative rainfall forecasts. Once pre-defined modelling or monitoring thresholds are exceeded, a web notification service distributes SMS and email messages to relevant experts, who then determine whether to issue an early warning to local and regional stakeholders, as well as providing appropriate action advice. This study successfully demonstrated the potential of this new approach to landslide early warning. To move from demonstration to active issuance of early warnings demands the future acquisition of high-quality data on mechanical properties and distributed pore water pressure regimes.