Updating EWS rainfall thresholds for the triggering of landslides

In this paper, the updating of rainfall thresholds for landslide early warning systems (EWSs) is presented. Rainfall thresholds are widely used in regional-scale landslide EWSs, but the efficiency of those systems can decrease during the time, so a periodically updating should be required to keep their functionality. The updating of 12 of the 25 thresholds used in the EWS of Tuscany region (central Italy) is presented, and a comparison between performances of new and previous thresholds has been made to highlight the need of their periodical update. The updating has been carried out by collecting ca. 1200 new landslide reports (from 2010 to March 2013) and their respective rainfall data, collected by 332 rain gauges. The comparison has been made by the use of several statistical indexes and showed a marked increasing in the performances of the new thresholds with respect to previous ones.     

Implementation and integrated numerical modeling of a landslide early warning system: a pilot study in Colombia

Landslide early warning systems (EWS) are an important tool to reduce landslide risks, especially where the potential for structural protection measures is limited. However, design, implementation, and successful operation of a landslide EWS is complex and has not been achieved in many cases. Critical problems are uncertainties related to landslide triggering conditions, successful implementation of emergency protocols, and the response of the local population. We describe here the recent implementation of a landslide EWS for the Combeima valley in Colombia, a region particularly affected by landslide hazards. As in many other cases, an insufficient basis of data (rainfall, soil measurements, landslide event record) and related uncertainties represent a difficult complication. To be able to better assess the influence of the different EWS components, we developed a numerical model that simulates the EWS in a simplified yet integrated way. The results show that the expected landslide-induced losses depend nearly exponentially on the errors in precipitation measurements. Stochastic optimization furthermore suggests an increasing adjustment of the rainfall landslide-triggering threshold for an increasing observation error. These modeling studies are a first step toward a more generic and integrated approach that bears important potential for substantial improvements in design and operation of a landslide EWS.     

A Data Based Model to Predict Landslide Induced by Rainfall in Rio de Janeiro City

Landslide prediction is complex and involves many factors, such as geotechnical, geological, topographical, and even meteorological. This work presents a methodology by using a Data Mining approach in order to predict landslide occurrences induced by rainfall in Rio de Janeiro city. Landslide and rain data records from 1998 to 2001 were obtained from field technical reports and 30 automatic rain gauges, respectively. It was also collected data regarding soil parameters, including urban areas, forest, vulnerability, among others, and totalizing 46 soil variables. All the information was inserted into a Geographic Information Systems. Clustering (Dendrogram and k-means) and Statistical (Principal Component Analysis and Correlation) techniques were used to regionalize the rain data and select the rain gauges to be input on Artificial Neural Networks , which were used to replace the missing rain values. The landslide volume variable also presented missing values and it was completed by the k-Nearest Neighbor method. After data preparation, some models were built to predict landslide and rainfall using Data Mining techniques. The obtained model’s performance is also analyzed.     

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。     

Hydrometeorological thresholds for landslide initiation and forest operation shutdowns on the north coast of British Columbia

Debris flows and debris avalanches are the most widespread and hazardous types of landslides on the British Columbia north coast. Triggered by heavy rain, they pose risks to forestry workers in sparsely developed regions. The scarcity of long-term quality rain gauges and the lack of weather radar information create significant challenge in predicting the timing of landslides, which could be used to warn and, when necessary, evacuate forestry personnel. Traditional methods to relate rainfall antecedents and rainfall intensity to known landslide dates have proven to be unsatisfactory in this study due to extreme spatial variability of rainfall, enhanced by the orographic effect and the scarcity of rain gauges in a very large area. This has led to an integration of meteorological variables in a landslide advisory system that classifies three types of approaching storms by the 850-mbar wind speed and direction, the occurrence of subtropical moisture flow, and the existence of a warm layer characterized by high thickness values of the 500- to 1,000-mbar pressure levels. The storm classification was combined with a 4-week antecedent rainfall and the 24-h rainfall measured near or in the watershed where logging operations are taking place. This system, once implemented, is thought to reduce loss of life, injury, and economic losses associated with forestry works in the study area.     

基于WEB的浙江省降雨型滑坡预警预报系统

滑坡发生的最主要诱发因素是降雨.基于浙江省淳安、磐安、庆元和永嘉4个县的历史滑坡资料, 在研究降雨量、降雨强度和降雨过程与滑坡灾害的空间分布、时间上的对应关系, 建立起滑坡灾害时空分布与降雨过程的统计关系, 确定区域性滑坡的临界降雨量和降雨强度阀值的基础上, 开发出了降雨型滑坡预警预报系统, 其中采用临界降雨量模型和有效降雨量模型来进行预警预报.系统留给浙江省气象台一个传送数据的接口, 气象台将每天按时上传降雨数据, 数据保存在后台数据库MicrosoftSQLServer中.建成的系统能够自动获取数据库中的数据生成时间与降雨量实时曲线, 当降雨量达到降雨强度阀值时, 触发MAPGIS图件, 在Internet上发布区域预警预报信息, 并提供预警措施.      

Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin

Prolonged and high intensity rainfall often saturates urban drainage systems and generates urban pluvial flooding, resulting in hazardous flash floods. The city most affected by urban flooding in Colombia (South America) is Barranquilla since lacks a proper storm water drainage system. Heavy rainfall produces flash floods to quickly become torrential streams that flow down the streets endangering pedestrians. This research describes a low-cost early warning system (EWS) to detect in real time the hazard level of a stream in an ungauged basin. The EWS indicates whether it is safe or not for pedestrians to cross a flooded street, based on certain criteria used to assess the hazard level of the torrent. A hydrological and hydraulic model calculates the flow, velocity and water level in all cross sections along the stream. The model uses only real-time measurements of rain gauges and topographic survey data to determine the hazard level. Finally, a wireless sensor network sends the alert to a web platform and warns the community in real time.

     

Evaluation of rain gauge network in arid regions using geostatistical approach: case study in northern Oman

A geostatistical approach based on ordinary kriging is presented for the evaluation and the augmentation of an existing rain gauge network. The evaluation is based on estimating the percentage of the area that achieves a targeted level of acceptable accuracy. The variances of kriging estimation erros at un-gauged locations were assumed to be normally distributed. Kriging estimation erros with a probability that equals to or exceeds a given threshold value of acceptance probability were assumed to have satisfactory accuracies. The percentage of the area that achieved the targeted probability of acceptance is delineated and used to judge the overall performance of the existing rain gauge network. A study area in northern Oman located in Sohar governorate is selected as the pilot case. The area has 34 rain gauges and it is characterized by a terrain surface that varies from coastal plain to mountains. For a threshold value of 0.85, and 0.90 of acceptance probability, the existing network achieved area of acceptable probability of 88.71 and 77.72 %, respectively. For a success criterion of 80 %, the existing rain gauge network indicated acceptable performance for acceptance probability threshold of 0.85 and inadequate performance is noticed in the case of probability threshold of 0.90, which necessitated further network augmentation. A sequential algorithm for ranking and prioritization of the existing rain gauges is used to classify the existing rain gauges into base and non-base rain gauges. The base rain gauge network for mean annual rainfall comprised about 29 of the existing rain gauges. The identified non-base rain gauges were sequentially relocated to achieve higher levels of percentage of area with acceptable accuracy. The percentage of area with acceptable accuracy increased from 88.71 % for the original rain gauge network to about 94.51 % for the augmented network by adding four rain gages at probability acceptance threshold of 0.85. It also increased from 77.72 % for the existing network to 90.50 % for the augmented rain gauge network at acceptance threshold of 0.9.     

Rainfall thresholds for the possible landslide occurrence in Sicily (Southern Italy) based on the automatic reconstruction of rainfall events

Review of the literature on the reconstruction of the rainfall responsible for slope failures reveals that criteria for the identification of rainfall events are lacking or somewhat subjective. To overcome this problem, we developed an algorithm for the objective and reproducible reconstruction of rainfall events and of rainfall conditions responsible for landslides. The algorithm consists of three distinct modules for (i) the reconstruction of distinct rainfall events, in terms of duration (D, in h) and cumulated event rainfall (E, in mm), (ii) the identification of multiple ED rainfall conditions responsible for the documented landslides, and (iii) the definition of critical rainfall thresholds for possible landslide occurrences. The algorithm uses pre-defined parameters to account for different seasonal and climatic settings. We applied the algorithm in Sicily, southern Italy, using rainfall measurements obtained from a network of 169 rain gauges, and information on 229 rainfall-induced landslides occurred between July 2002 and December 2012. The algorithm identified 29,270 rainfall events and reconstructed 472 ED rainfall conditions as possible triggers of the observed landslides. The algorithm exploited the multiple rainfall conditions to define objective and reproducible empirical rainfall thresholds for the possible initiation of landslide in Sicily. The calculated thresholds may be implemented in an operational early warning system for shallow landslide forecasting.     

Extreme rainfall events: evaluation with different instruments and measurement reliability

With regard to extreme events, it is well documented that an intensity of about 1 mm/min already represents an extreme intensity. Under alpine conditions, a precipitation event with an intensity of 3 mm/min has occurred. Therefore, the rain gauges in this region have to be able to measure in this and even in higher intensity ranges. This study deals with basic automated tipping-bucket rain (TBR) gauge and Bulk precipitation samplers, which are able to hold more than 95 % of the cumulative rainfall, that are verified within the space of the week without losses during the extreme events and with minimal evaporation loss. Bulk samplers collected more rainfall than TBR gauges in 110 of 221 extreme events analysed over the past 10 years. In 17 extreme events, an underestimation greater than 10 % was evaluated. The objective was to single out the counting errors associated with TBR gauge, during extreme events, so as to help the understanding of the measured differences between instruments in the field. We want to determine whether the automated precipitation gauge can provide a reliable and precise measurement of precipitation with particular interest regarding heavy and extreme events.     

三种JDZ型翻斗式雨量计性能比对实验研究

在我国,JDZ系列翻斗式雨量计已广泛用于降雨量的观测。为了掌握JDZ系列雨量计测量降雨的精度和可靠性,以三种JDZ型翻斗式雨量计(JDZ02、JDZ05和JDZ10)为研究对象,基于一套智能化的雨量计率定系统开展室内性能比对实验。结果表明:(1)以小雨强0.4mm·min^-1作为零误差参考雨强,JDZ02在小于2mm·min^-1时的误差在-4%以内,JDZ05在小于4mm·min^-1时的误差在-4%以内,JDZ10在小于6mm·min^-1时的误差在-4%以内。(2)在雨强-总误差的拟合关系中,二次多项式拟合的效果最好,线性拟合的效果次之,幂函数拟合的效果最差,故建议采用雨强-误差的二次多项式关系订正JDZ系列雨量计监测的降雨数据。(3)左右翻斗水量过程线可以精细刻画翻斗内水量动态变化,判断出翻斗式雨量计的翻斗左右平衡性能,并可计算出翻斗式雨量计动态率定过程中的误差变化。     

National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data

China is one of the countries where landslides caused the most fatalities in the last decades.The threat that landslide disasters pose to people might even be greater in the future,due to climate change and the increasing urbanization of mountainous areas.A reliable national-scale rainfall induced landslide suscep-tibility model is therefore of great relevance in order to identify regions more and less prone to landslid-ing as well as to develop suitable risk mitigating strategies.However,relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area.The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China.In this context,it is aimed to explore the benefit of mixed effects mod-elling to counterbalance associated bias propagations.Six influencing factors including lithology,slope,soil moisture index,mean annual precipitation,land use and geological environment regions were selected based on an initial exploratory data analysis.Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information:Set 1(disregards the presence of incomplete landslide information),Set 2(excludes factors related to the incompleteness of landslide data),Set 3(accounts for factors related to the incompleteness via random effects).The vari-able sets were then introduced in a generalized additive model(GAM:Set 1 and Set 2)and a generalized additive mixed effect model(GAMM:Set 3)to establish three national-scale statistical landslide suscep-tibility models:models 1,2 and 3.The models were evaluated using the area under the receiver operating characteristics curve(AUROC)given by spatially explicit and non-spatial cross-validation.The spatial pre-diction pattern produced by the models were also investigated.The results show that the landslide inven-tory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models.The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9.However,although Model 1 reached the highest AUROCs within non-spatial cross-validation(median of 0.9),it was not associated with the most plausible representation of landslide susceptibility.The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias.The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility.However,a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data(e.g.,the Kuenlun Mountains in the northern Tibetan Plateau).The non-linear mixed-effects model(Model 3)reduced the impact of these biases best by introducing bias-describing variables as random effects.Among the three models,Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive perfor-mance(median AUROC of spatial cross validation 0.84)compared to the other two models(median AUROCs of 0.81 and 0.79,respectively).We conclude that ignoring landslide inventory-based incomplete-ness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.     

Rainfall thresholds for rainfall-induced landslides in Slovenia

In Slovenia, rainfall-induced landslides lead to considerable damages, even causing human losses. In order to reduce the impact of this kind of landslide, several researchers analyzed rainfall-induced landslides in this country, but to date, no rainfall thresholds have been developed for a landslide warning system at national scale. In this paper, the definition of rainfall thresholds for rainfall-induced landslides in Slovenia is presented. The thresholds have been calculated by collecting approximately 900 landslide data and the relative rainfall amounts, which have been collected from 41 rain gauges. To define the thresholds, an existing procedure characterized by a high degree of objectiveness has been used. This approach is based on a software that was developed for a test site with very different characteristics (Tuscany, central Italy). At first, a single national threshold has been defined; subsequently, the country was divided into four zones, on the basis of the major river basins. The effectiveness of the thresholds has been verified by the use of several statistical parameters and it resulted in quite good performances, even if with some uncertainties, probably due to the quality of the available data. Besides the setting of a threshold system, usable for civil protection purposes at national scale, an additional outcome of this work was the possibility of applying, with good results, a methodology defined for another region, therefore testing its degree of exportability in different settings.     

Rainfall induced debris flows in pyroclastic deposits, Campania (southern Italy)

A combination of empirical and physically based hydrological models has been used to analyze historical data on rainfall and debris-flow occurrence in western Campania, to examine the correlation between rainfall and debris-flow events.

Rainfall data from major storms recorded in recent decades in western Campania were compiled, including daily series from several rain gauges located inside landslide areas, supplemented by hourly rainfall data from some of the principal storms.

A two-phase approach is proposed. During phase 1, soil moisture levels have been modelled as the hydrological balance between precipitation and evapotranspiration, on a daily scale, using the method of Thornthwaite [Geograph. Rev. 38 (1948) 55].

Phase 2 is related to the accumulation of surplus moisture from intense rainfall, leading to the development of positive pore pressures. These interactions take place on an hourly time scale by the “leaky barrel” (LB) model described by Wilson and Wiezoreck [Env. Eng. Geoscience, 1 (1995) 11]. In combination with hourly rainfall records, the LB model has been used to compare hydrological effects of different storms. The critical level of retained rain water has been fixed by the timing of debris-flow activity, related to recorded storm events.

New rainfall intensity–duration thresholds for debris-flow initiation in western Campania are proposed. These thresholds are related to individual rain gauge and assume a previously satisfied field capacity condition. The new thresholds are somewhat higher than those plotted by previous authors, but are thought to be more accurate and thus need less conservatism.     

Rainfall patterns for shallow landsliding in perialpine Slovenia

This paper presents two types of analysis: an antecedent rainfall analysis based on daily rainfall and an intensity-duration analysis of rainfall events based on hourly data in perialpine Slovenia in the ?kofjelo?ko Cerkljansko hills. For this purpose, eight rainfall events that are known to have caused landslides in the period from 1990 to 2010 were studied. Over the observed period, approximately 400 records of landslides were collected. Rainfall data were obtained from three rain gauges. The daily rainfall from the 30 days before landslide events was investigated based on the type of landslides and their geo-environmental setting, the dates of confirmed landslide activity and different consecutive rainfall periods. The analysis revealed that the rainfall events triggering slope failure can be divided into two groups according to the different antecedent periods. The first group of landslides typically occurred after short-duration rainstorms with high intensity, when the daily rainfall exceeded the antecedent rainfall. The second group comprises the rainfall events with a longer antecedent period of at least 7 days. A comparison of the plotted peak and mean intensities indicates that the rainfall patterns that govern slope failure are similar but do not necessarily reflect the rainfall intensity at the time of shallow landslides in the Dav?a or Poljane areas, where the majority of the landslides occurred. Because of several limitations, the suggested threshold cannot be compared and evaluated with other thresholds.     

Analysis of rainfall preceding debris flows on the Smědavská hora Mt., Jizerské hory Mts., Czech Republic

In August 2010, extreme rainfall affected the north of the Czech Republic and caused regional floods and landslides. Three torrential debris flows originated in the Jizerské hory Mts., close to Bílý Potok on the north slope of the Smědavská hora Mt. The rainfall situation which triggered the debris flow was analyzed and compared with the rainfall situation in 1958 when a debris flow occurred in the same area. The rainfall data were obtained from rain gauges of the Czech Hydrometeorological Institute. Four rain gauges were chosen close to the Smědavská hora Mt. with data of daily amounts from 1983 to 2013 and 10-min intensity or hourly amounts from the specific period. The data from 1958 were available from three different rain gauges (only daily amounts). The data series were not complete so linear regression was applied to interpolate them. A number of analyses were carried out including daily rainfall, 2-day/3-day moving values, antecedent precipitation index (API) of 5/10/30 days, 10-min intensity, and hourly amounts, and the trigger factor of the debris flow in the study area was also investigated. It was determined that for the triggering of debris flows, both high API values as well as high-intensity short-duration rainfall is needed. It was documented that in cases of solely high API indices or high-intensity short-duration rainfalls, no debris flows were initiated.     

降雨输入不确定性对分布式流域水文模拟的影响研究——以武烈河流域为例

降雨输入对分布式流域水文模拟具有重要影响。针对流域降雨资料不完整的情况,以武烈河流域为例,基于反距离加权平均法对雨量站降雨资料进行插补延长,并结合SWAT模型研究了降雨输入不确定性对分布式流域水文模拟的影响。结果表明:不同降雨输入对流域平均降雨量的影响较小,但基于气象站资料的降雨数据在降雨空间差异显著的年份会明显低估面雨量,且在夏季汛期表现更为显著;不同降雨输入对分布式流域水文模拟的影响较大;在雨量站降雨资料不完整的情况下,通过对雨量站降雨数据进行插补延长,相对于直接利用气象站降雨资料,在一定程度上可以提高径流模拟精度,满足降雨资料欠缺流域分布式水文模拟的实际需求。     

A simplified method for predicting rainfall-induced mobility of active landslides

This paper deals with the landslides that are reactivated by a groundwater level increase owing to rainfall. These landslides are usually characterized by low displacement rate with deformations essentially concentrated within a narrow shear zone above which the unstable soil mass moves like a rigid body (i.e., with a horizontal displacement profile that is essentially constant with depth). In view of this evidence, a new method based on a simple sliding block model is proposed in the present study for a preliminary evaluation of landslide mobility. Unlike other existing methods that provide an evaluation of landslide mobility on the basis of groundwater level measurements, the present method directly relates landslide movements to rain recordings. This possibility constitutes a significant advantage from a practical viewpoint because it allows future displacement scenarios to be predicted from expected rainfall scenarios. In addition, the present method requires a limited number of parameters as input data, many of which can be obtained from conventional geotechnical tests. To evaluate the other parameters involved, an efficient calibration procedure is also proposed. Four case studies documented in the literature are analyzed to assess the capability of the present method to reproduce the main features of the slope response to rainfall. In all these case studies, both groundwater level variations and landslide displacements observed in field are well approximated by the method.     

Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds

Critical rainfall thresholds for landslides are powerful tools for preventing landslide hazard. The thresholds are commonly estimated empirically starting from rainfall events that triggered landslides in the past. The creation of the appropriate rainfall–landslide database is one of the main efforts in this approach. In fact, an accurate agreement between the landslide and rainfall information, in terms of location and timing, is essential in order to correctly estimate the rainfall–landslide relationships. A further issue is taking into account the average moisture conditions prior the triggering event, which reasonably may be crucial in determining the sufficient amount of precipitation. In this context, the aim of this paper is exploiting historical landslide and rainfall data in a spatial database for the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy. The hourly rainfall events that caused landslides occurred in the twentieth century were specifically identified and reconstructed. A procedure was proposed to automatically convert rain guages charts recorded on paper tape into digital format and then to provide the cumulative rainfall hyetograph in digital format. This procedure is based on a segmentation followed by signal recognition techniques which allow to digitalize and to recognize the hyetograph automatically. The role of rainfall prior to the landslide events was taken into account by including in the analysis the rainfall occurred 5, 15 and 30 days before each landslide. Finally, cumulated rainfall duration thresholds for different exceedance probability levels were determined. The obtained thresholds resulted in agreement with the regional curves proposed by other authors for the same area; antecedent rainfall turned out to be particularly important in triggering landslides.     

基于多类型雨量计的降雨特性分析

为提高对降雨特性的认识,选择常用的6种测雨设备（翻斗式SL3-1、JDZ05、RG-3,称重式Pluvio2,雨滴谱仪Parsivel2和非计数式JQH-1）,成对布设在南京水利科学研究院滁州水文实验基地的同一个实验场地,同步观测了2019年4月1日至8月31日为期5个月的降雨过程。比测分析得到:在中大雨条件下（日雨量≥ 10 mm）,SL3-1和JDZ05测的降雨总量能够满足4%误差控制要求,RG-3、Pluvio2和Parsivel2测的降雨量比JQH-1测值小4%;在小雨条件下（日雨量 < 10 mm）,翻斗式和称重式雨量计的测量值小于JQH-1测值的4%;SL3-1、RG-3、Pluvio2、Parsivel2测得雨强≤ 0.1 mm/min的频率大于75%,雨强≤ 0.2 mm/min条件下的雨量累积比重大于50%;Pluvio2和Parsivel2监测的降雨开始时间比SL3-1分别早0.5 h和2 h以上,而结束时间分别晚0.5 h和2 h以上。比测结果有助于研究人员选择合适的测量设备获取所关注的降雨特性。