Establishing a threshold for rainfall-induced landslides by a kinetic energy–duration relationship

Many investigators have attempted to define the threshold of landslide failure, that is, the level of the selected climatic variable above which a rainfall-induced landslide occurs. Intensity–duration (I–d) relationships are the most common type of empirical thresholds proposed in the literature for predicting landslide occurrence induced by rainfall. Recent studies propose the use of the kinetic power per unit volume of rainfall (J m⁻² mm⁻¹) to quantify the threshold of landslides induced by rainfall. In this paper, the relationship between rainfall duration and kinetic power corresponding to landslides triggered by rain was used to propose a new approach to define the threshold for predicting landslide occurrence. In particular, for the first time, a kinetic power per unit volume of rainfall–duration relationship is proposed for defining the minimum threshold needed for landslide failure. This new method can be applied using commonly used relationship for estimating the kinetic power per unit volume of rainfall and a new equation based on the measured raindrop size distribution. The applicability of this last method was tested using the data of rainfall intensity, duration and median volume diameter for 51 landslides in Taiwan. For the 51 landslides, the comparison between the measured pairs' kinetic power–duration and all selected relationships demonstrated that the equation based on the measured raindrop size distribution is the best method to define the landslide occurrence threshold, as it is both a process-oriented approach and is characterized by the best statistical performance. This last method has also the advantage to allow the forecasting of landslide hazard before the end of the rainfall event, since the rainfall kinetic power threshold value can be exceeded for a time interval less than the event duration.     

Comparing threshold definition techniques for rainfall‐induced landslides: A national assessment using radar rainfall

Translational landslides and debris flows are often initiated during intense or prolonged rainfall. Empirical thresholds aim to classify the rain conditions that are commonly associated with landslide occurrence and therefore improve understating of these hazards and predictive ability. Objective techniques that are used to determine these thresholds are likely to be affected by the length of the rain record used, yet this is not routinely considered. Moreover, remotely sensed spatially continuous rainfall observations are under‐exploited. This study compares and evaluates the effect of rain record length on two objective threshold selection techniques in a national assessment of Scotland using weather radar data. Thresholds selected by ‘threat score’ are sensitive to rain record length whereas, in a first application to landslides, ‘optimal point’ (OP) thresholds prove relatively consistent. OP thresholds increase landslide detection and may therefore be applicable in early‐warning systems. Thresholds combining 1‐ and 12‐day antecedence variables best distinguish landslide initiation conditions and indicate that Scottish landslides may be initiated by lower rain accumulation and intensities than previously thought. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

A new method for spatio-temporal prediction of rainfall-induced landslide

1 Introduction The landslides influences on the human society have become an environment difficult problem not able to be neglected, and according to the priority of harms, harms of landslides are only smaller than those from earthquakes in all sorts of natural hazards[1]. Landslide is part of rock mass, soil mass or their compound mass slides downward along a certain slid- ing surface under the actions of inner and external dy- namics, and it is one severe instability phenomenon of rock and s…     

Analysing the Relationship Between Typhoon‐Triggered Landslides and Critical Rainfall Conditions

Many landslides are triggered by rainfall. Previous studies of the relationship between landslides and rainfall have concentrated on deriving minimum rainfall thresholds that are likely to trigger landslides. Though useful, these minimum thresholds derived from a log–log plot do not offer any measure of confidence in a landslide monitoring or warning system. This study presents a new and innovative method for incorporating rainfall into landslide modelling and prediction. The method involves three steps: compiling radar reflectivity data in a QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system during a typhoon (tropical hurricane) event, estimating rainfall from radar data and using rainfall intensity and rainfall duration as explanatory variables to develop a landslide logit model. Given the logit model, this paper discusses ways in which the model can be used for computing probabilities of landslide occurrence for a real‐time monitoring system or a warning system, and for delineating and mapping landslides. Copyright © 2007 John Wiley & Sons, Ltd.     

Predicting global landslide spatiotemporal distribution： Integrating landslide susceptibility zoning techniques and real-time satellite rainfall estimates

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of sufficient ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing a preliminary real-time prediction system to identify where rainfall-triggered landslides will occur is proposed by combining two necessary components： surface landslide susceptibility and a real-time space-based rainfall analysis system （http：//trmm.gsfc.nasa.gov）. First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics （digital elevation topography, slope, soil types, soil texture, land cover classification, etc.） using a GIS weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide hazards at areas with high susceptibility. A major outcome of this work is the availability for the first time of a global assessment of landslide hazards, which is only possible because of the utilization of global satellite remote sensing products. This preliminary system can be updated continuously using the new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and mitigation activities across the world.     

Rainfall thresholds for shallow landsliding derived from pressure‐head monitoring: cases with permeable and impermeable bedrocks in Boso Peninsula,Japan

Rainfall thresholds for shallow landslide initiation were determined for hillslopes with two types of bedrock, permeable sandstone and impermeable mudstone, in the Boso Peninsula, Japan. The pressure‐head response to rainfall was monitored above a slip scarp due to earlier landslides. Multiple regression analysis estimated the rainfall thresholds for landsliding from the relation between the magnitude of the rainfall event and slope instability caused by the increased pressure heads. The thresholds were expressed as critical combinations of rainfall intensity and duration, incorporating the geotechnical properties of the hillslope materials and also the slope hydrological processes. The permeable sandstone hillslope has a greater critical rainfall and hence a longer recurrence interval than the impermeable mudstone hillslope. This implies a lower potential for landsliding in sandstone hillslopes, corresponding to lower landslide activity. Copyright © 2007 John Wiley & Sons, Ltd.     

基于人工边坡稳定性的降雨型滑坡预警预报模型设计与应用

由削坡建房遗留的人工边坡存在大量滑坡隐患问题,在降雨引发土质边坡自身动力变化分析条件下,以稳定性评价建模为基础,提出降雨型滑坡动力学预警预报模型。文中以广东省梅州市花岗岩地区为例,使用GIS技术构建了1 727个预警分析单元,并进行关键地质环境因子赋值及与气象站点数据关联;按坡高、坡度等参数,分别构建16个边坡失稳动力学预警模块,并根据降雨量变化,计算边坡稳定性系数,最终按其阈值确定风险等级并予以预警。本研究对于推动人工边坡诱发的滑坡地质灾害预警预报与预防均具有重要意义。     

Approaches for defining thresholds and return periods for rainfall‐triggered shallow landslides

Probabilistic thresholds for triggering shallow landslides by rainfall are developed using two approaches: a logistic regression model and Iverson's physically based model. Both approaches are applied to a 180 km² area in northern Italy. For the physically based model a Monte Carlo approach is used to obtain probabilities of slope failure associated with differing combinations of rainfall intensity and duration as well as differing topographic settings. For the logistic regression model hourly and daily rainfall data and split‐sample testing are used to explore the effect of antecedent rainfall on triggering thresholds. It is demonstrated that both the statistical and physically based models provide stochastic thresholds that express the probability of landslide triggering. The resulting thresholds are comparable, even though the two approaches are conceptually different. The physically based model also provides an estimate of the percentage of potentially unstable areas in which failure can be triggered with a certain probability. The return period of rainfall responsible for landslide triggering is studied by using a Gumbel scaling model of rainfall intensity–duration–frequency curves. It is demonstrated that antecedent rainfall must be taken into account in landslide forecasting, and a method is proposed to correct the rainfall return period by filtering the rainfall maxima with a fixed threshold of antecedent rainfall. This correction produces an increase of the return periods, especially for rainstorms of short duration. Copyright © 2009 John Wiley & Sons, Ltd.     

Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster

We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy. Through the embedding into a hierarchical Bayesian estimation framework, we can use the integrated nested Laplace approximation methodology to make inference and obtain the posterior estimates of spatially distributed covariate and random effects. Several mapping units are useful to partition a given study area in landslide prediction studies. These units hierarchically subdivide the geographic space from the highest grid-based resolution to the stronger morphodynamic-oriented slope units. Here we integrate both mapping units into a single hierarchical model, by treating the landslide triggering locations as a random point pattern. This approach diverges fundamentally from the unanimously used presence–absence structure for areal units since we focus on modeling the expected landslide count jointly within the two mapping units. Predicting this landslide intensity provides more detailed and complete information as compared to the classically used susceptibility mapping approach based on relative probabilities. To illustrate the model’s versatility, we compute absolute probability maps of landslide occurrences and check their predictive power over space. While the landslide community typically produces spatial predictive models for landslides only in the sense that covariates are spatially distributed, no actual spatial dependence has been explicitly integrated so far. Our novel approach features a spatial latent effect defined at the slope unit level, allowing us to assess the spatial influence that remains unexplained by the covariates in the model. For rainfall-induced landslides in regions where the raingauge network is not sufficient to capture the spatial distribution of the triggering precipitation event, this latent effect provides valuable imaging support on the unobserved rainfall pattern.     

An Integrated Multi-Level Early Warning Method for Rainfall-Induced Shallow Landslides

Rainfall-induced landslides have occurred frequently in Southwestern China since the Wenchuan earthquake,resulting in massive loss of people''s life and property. Fortunately,landslide early-warning is one of the most important tools for landslide hazard prevention and mitigation. However, the accumulation of historical data of the landslides induced by rainfall is limited in many remote mountain areas and the stability of the slope is easily affected by human engineering activities and environmental changes, leading to difficulties to accurately realize early warning of landslide hazards by statistical methods. The proposed warning method is divided into rainfall warning component and deformation warning component because the deformation induced by rainfall has the characteristic of hysteretic nature. Rainfall, tilted angle and crack width are chosen as monitoring indexes. Rainfall grade level that contains rainfall intensity and duration information is graded according to the variation of the safety factor calculated by 3-D finite difference numerical simulation method, and then is applied using the strength reduction method and unascertained information theory to obtain the deformation grade level of several monitored points. Finally, based on the system reliability theory, we establish a comprehensive landslide warning level method that provides four early warning levels to reflect the safety factor reductions during and post rainfall events. The application of this method at a landslide site yield generally satisfactory results and provide a new method for performing multi-index and multi-level landslide early warnings.     

Applying Probability Determination to Refine Landslide-triggering Rainfall Thresholds Using an Empirical “Antecedent Daily Rainfall Model”

—Rainfall-triggered landslides constitute a serious hazard and an important geomorphic process in many parts of the world. Attempts have been made at various scales in a number of countries to investigate triggering conditions in order to identify patterns in behaviour and, ultimately, to define or calculate landslide-triggering rainfall thresholds. This study was carried out in three landslide-prone regions in the North Island of New Zealand. Regional landslide-triggering rainfall thresholds were calculated using an empirical “Antecedent Daily Rainfall Model.” In this model, first introduced by, triggering rainfall conditions are represented by a combination of rainfall occurring in a period before the event (antecedent rainfall) and rainfall on the day of the event. A physically-based decay coefficient is derived for each region from the recessional behaviour of storm hydrographs and is used to produce an index for antecedent rainfall. Statistical techniques are employed to obtain the thresholds which best separate the rainfall conditions associated with landslide occurrence from those of non-occurrence or a given probability of occurrence.The resultant regional models are able to represent the probability of occurrence of landsliding events on the basis of rainfall conditions. The calculated thresholds show regional differences in susceptibility of a given landscape to landslide-triggering rainfall. These differences relate to both the landslide database and the difference of existing physical conditions between the regions.     

Quantifying rainfall controls on catchment‐scale landslide erosion in Taiwan

Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (M_W = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling catchment‐scale shallow landslide occurrence and sediment yield as a function of rainfall return period

A model‐based method is proposed for improving upon existing threshold relationships which define the rainfall conditions for triggering shallow landslides but do not allow the magnitude of landsliding (i.e. the number of landslides) to be determined. The SHETRAN catchment‐scale shallow landslide model is used to quantify the magnitude of landsliding as a function of rainfall return period, for focus sites of 180 and 45 km² in the Italian Southern Alps and the central Spanish Pyrenees. Rainfall events with intensities of different return period are generated for a range of durations (1‐day to 5‐day) and applied to the model to give the number of landslides triggered and the resulting sediment yield for each event. For a given event duration, simulated numbers of landslides become progressively less sensitive to return period as return period increases. Similarly, for an event of given return period, landslide magnitude becomes less sensitive to event duration as duration increases. The temporal distribution of rainfall within an event is shown to have a significant impact on the number of landslides and the timing of their occurrence. The contribution of shallow landsliding to catchment sediment yield is similarly quantified as a function of the rainfall characteristics. Rainfall intensity–duration curves are presented which define different levels of landsliding magnitude and which advance our predictive capability beyond, but are generally consistent with, published threshold curves. The magnitude curves are relevant to the development of guidelines for landslide hazard assessment and forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

降雨和地震耦合作用对滑坡稳定性的影响——以甘肃西和Ⅲ号滑坡为例

以甘肃省西和县西山Ⅲ号滑坡为例分析了地震与降雨耦合作用对滑坡稳定性的影响。采用GEOSTUDIO软件对其进行了天然及地震降雨耦合作用两种条件下的数值模拟。通过计算结果对比可知,西山Ⅲ号滑坡在天然状态下处于稳定状态;地震降雨耦合作用对西山Ⅲ号滑坡的稳定会起到很强的削弱作用,滑坡将处于失稳状态。在此处采用的计算条件下,相同降雨量下地震与不同降雨强度的耦合作用显示,降雨强度越小雨水入渗相对越多,地震作用下超孔隙水压力影响区域越大,滑坡越不稳定。     

Comparison of the return period for landslide-triggering rainfall events in Japan based on standardization of the rainfall period

The intensity of rainfall events with potential to cause landslides has varying temporal characteristics. In this study, the time at which the 72-h accumulated rainfall reached its maximum was used to standardize the period of rainfall measurement. The proposed standardization of the rainfall period was used in conjunction with the return level of rainfall intensity, obtained from intensity–duration–frequency curves, to investigate rainfall intensity anomalies associated with 10 hazardous rainfall events that triggered numerous landslides at the regional scale in Japan. These landslides included shallow landslides in volcanic and non-volcanic areas, as well as deep-seated landslides. The rainfall events that triggered the shallow landslides were divided into two types: downpours that repeatedly reached close to the 100-year return level within approximately 3–4 h, and accumulated rainfall that reached close to 200–400 mm over longer time intervals but within 72 h. Lithological differences seemed unrelated to the differences between the two types of shallow-landslide-triggering rainfall; however, precipitation >1000 mm was necessary to trigger deep-seated landslides. Although the characteristics of the hyetographs differed markedly among the landslide-triggering rainfall events, all the landslides could have been triggered when the mean rainfall intensity reached the 100-year rainfall level during the standardized period. Thus, the landslide trigger can be evaluated indirectly based on the increase in the return level of the mean rainfall intensity, which could provide a means for estimating the time of landslide occurrence.     

Landslide susceptibility analysis based on citizen reports

Landslide susceptibility estimates are essential for reducing the risk posed by landslides to social and economic well-being. However, estimates of landslide susceptibility depend on reliable landslide inventories whose production requires extensive field or remote sensing efforts. Further, most inventories are not updated through time and thus may not capture the influence of changes in climate and/or land use. Inventories based on citizen reports of landslide occurrence, have the potential to overcome these limitations. Such an inventory can be produced from citizen reports to a 311-phone and online system, a nationwide database that updates real-time and records reported landslides location and timing. Whereas this landslide inventory is promising, it has not used for landslide susceptibility analyses and may be associated with spatial uncertainties and reporting biases. In this study we explore the use of 311-based landslide inventory for landslide susceptibility estimates in Pittsburgh, PA, USA, where landslide risk is among the highest in the nation. We compare the 311-based inventory to field-validated inventories through a multi-pronged approach that combines field validation of 311-reported landslides, probabilistic analysis of the association between landslides and the underlying topographic and geologic factors, and spatial filtering. Our results show that: (a) approximately 70% of the 311-reported landslides are associated with an identifiable landslide in the field; (b) the spatial uncertainty of the 311-reported landslides is 104 ± 25 m; (c) 311-reported landslides differ from other inventories in that they are primarily associated with proximity to roads, however, field-correction of 311-reported landslide locations rectifies this anomaly; (d) a simple spatial filter, scaled by the uncertainty in location as determined from a subset of the 311-data, can increase the consistency between the 311-reported inventory and field-validated inventories. These results suggest that 311-based landslide inventories can improve susceptibility estimates at a relatively low cost and high temporal resolution.     

Role of basin‐wide landslides in the formation of extensive alluvial gemstone deposits in Sri Lanka

The tectonically stable central highlands of Sri Lanka and its alluvial valleys are the source areas and sinks, respectively, for one of the most prolific Quaternary gemstone provinces in the world. However, the known ¹⁰Be/²⁶Al cosmogenic‐nuclide‐determined low natural (preanthropogenic) denudation rates of 2–11 mm kyr^?1, and resulting sediment fluxes, are grossly inadequate to deliver the vast throughputs of overburden required to concentrate the known gemstone deposits. Basin‐wide, unstable, slow‐moving channelized landslides and debris flows, aided by biotic factors, are the dominant mechanisms of mass‐wasting on hill‐slopes and bulk delivery of sediment to the alluvial valleys and fluvial networks. Channelization ensures modulated sediment transfer and run‐out during an erosional–depositional continuum. In a selected inventory of landslides, mobilized sediment volumes ranged from less than 1000 cubic metres to a maximum of ～800 000 cubic metres per event. Monsoonal rainfall (both cumulative seasonal and total daily thresholds) is the primary external factor, which interacts with colluvium thickness and steep slopes in triggering landslides. There are three to five ‘threshold’ rainfall events per year in the highlands that can be expected to generate landslides. They can occur under conditions of decreasing daily rainfall as the seasonal total rainfall increases. GIS databases show a very significant spatial overlap and direct causal linkage between several hundred landslide occurrences and the innumerable gem pits and mines in the catchments of the best known mining region of Sri Lanka. Landslide‐associated mass movements, besides providing significant numbers of gemstones to the alluvial valleys over time, are also a fundamental factor in the geomorphic evolution of the rugged central highland landscape. Rainfall‐driven landslide activity may be a natural geological response affecting erosional equilibrium in high‐relief tectonically stable terrains. Climatically forced base level changes will, over time, control sediment storage, removal or reworking in the valleys. Copyright © 2007 John Wiley & Sons, Ltd.     

Landslides and increased debris-flow activity: A systematic comparison of six catchments in Switzerland

An increase in debris-flow frequency is expected in steep Alpine catchments after the occurrence of a large landslide, such as a rock avalanche. Herein we describe changes in debris-flow activity following increases in sediment availability due to landslides, or accelerated rock-glacier movement, for five catchments in the Swiss Alps, the Spreitgraben, Schipfenbach, Bondasca, Riascio, and Dorfbach catchments. Documentation on debris-flow activity is available from both before and after the landslide that generated the new sediment deposits. Data from nearby meteorological stations were used to explore possible changes in rainfall activity, and how the intensity and duration of rainfall events may have changed. In all cases there was a considerable increase in debris-flows frequency for one to eight years following the landslide. The annual number of days with debris-flow activity following the landslide was similar to that observed for the Illgraben catchment, where many such landslides occur annually. No clear change in precipitation totals preceding debris flows was apparent for the Riascio catchment, suggesting that the increase in frequency of debris flows is related to the increase in the amount of sediment that can be readily mobilized. In the two cases where rainfall data were available on an hourly basis, no systematic changes in the intensity or duration of rainfall related to debris-flow triggering were apparent, as shown by the close-clustering of storms on the intensity-duration plots. Following the sediment-generating event, an initial and sudden increase of the sediment yield was observed, followed by a decrease over time towards pre-disturbance values. The response of the catchments appears to be related to the amount of debris-flow activity prior to the landslide: sediment yield from catchments with frequent debris flows prior to the landslide activity did not increase as dramatically as in catchments where debris-flow activity was less common prior to the landslide. © 2018 John Wiley & Sons, Ltd.     

大型高位堆积体滑坡稳定性分析与数值模拟

青藏高原边缘地带堆积体滑坡的发生与地质构造、强降雨、地震等作用密切相关,其中多数属于大型高位堆积体滑坡。为研究其发生机理与稳定性,以舟曲县江顶崖大型高位堆积体滑坡为研究对象,首先,从滑坡所处的地理位置、地质条件等出发,分析滑坡的概况与成因;其次,基于传统传递系数法划分滑坡计算模型,提出滑坡稳定性分析的变坡法;最后,采用Midas GTS NX软件对江顶崖滑坡自然工况下稳定性进行数值模拟分析,并与传统及改进算法结果进行对比。研究结果表明：(1)研究区的地形坡度、地层岩性条件以及活动断裂、历史强震作用是滑坡发生的内因,外因是连续强降雨作用使岩土体力学强度降低以及暴雨导致滑坡前缘的白龙江水位上涨、流速加快,冲刷坡脚导致前缘失稳,滑坡中后缘发生牵引式滑动;(2)运用传递系数法计算折线形滑坡稳定性时,滑面倾角变化值大于10°会导致结果出现较大误差,应用改进的“等分均匀变坡法”可以减小误差,以江顶崖滑坡为计算实例并结合数值模拟验证该方法的有效性;(3)自然工况下模拟发现,滑体的前缘主要表现为水平滑移,滑体的中后部局部主要表现为垂直下沉,而滑坡前缘则主要表现为隆起,因此,滑坡部分区域出现了较大的位移...     

Rainfall characteristics for shallow landsliding in Seattle,Washington, USA

Shallow landsliding in the Seattle, Washington, area, has caused the occasional loss of human life and millions of dollars in damage to property. The effective management of the hazard requires an understanding of the rainfall conditions that result in landslides. We present an empirical approach to quantify the antecedent moisture conditions and rainstorm intensity and duration that have triggered shallow landsliding using 25 years of hourly rainfall data and a complementary record of landslide occurrence. Our approach combines a simple water balance to estimate the antecedent moisture conditions of hillslope materials and a rainfall intensity–duration threshold to identify periods when shallow landsliding can be expected. The water balance is calibrated with field‐monitoring data and combined with the rainfall intensity–duration threshold using a decision tree. Results are cast in terms of a hypothetical landslide warning system. Two widespread landslide events are correctly identified by the warning scheme; however, it is less accurate for more isolated landsliding. Copyright © 2005 John Wiley & Sons, Ltd.