The influence of rainstorm pattern on shallow landslide

In this study, the influence of the rainstorm pattern on shallow landslide is examined. The physically-based shallow landslide model is used to conduct this examination with considering four representative rainstorm patterns including uniform, advanced, central, and delayed rainstorms. The results show that in spite of the rainfall duration and the rainfall pattern, the rainstorm with less than the minimum landslide-triggering rainfall amount will not trigger landslide. However, for the rainstorm with greater than the minimum landslide-triggering rainfall amount, the occurrence of landslide significantly depends not only on the rainfall duration but also on the rainfall pattern. Among the four representative rainstorm patterns, the delayed rainstorm has the greatest rainfall duration threshold for landslide occurrence, followed by the central rainstorm, and then the uniform rainstorm. In addition, for each rainstorm pattern, the corresponding rainfall duration threshold for landslide occurrence decreases with the increase of rainfall amount, and seems to be constant for large rainfall amount.     

Influences of soil water characteristic curve on rainfall-induced shallow landslides

The analysis of slope instability induced by rainfall was usually performed using the main drying curve as the measurement of the main wetting curve is a more time-consuming and costly task. In this study, the influences of the main drying and wetting curves on rainfall-induced shallow landslides are examined. Three designed scenarios and a real case scenario are used to conduct this examination. The prediction of shallow landslide occurrence is related to the main drying and wetting curves due to the strong relation between groundwater pressure head and hysteresis effect. The main wetting curve may have a less minimum landslide-triggering rainfall amount and a less rainfall duration threshold for landslide occurrence than the drying wetting curve. For safety’s sake, an underestimation of shallow landslide occurrence may be produced by the commonly used main drying curve. In addition, besides the shallow landslide occurrence, the failure depth and the time to failure are also influenced by the main drying and wetting curves. The hysteresis effect should be taken into account for assessing rainfall-induced shallow landslides.     

The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

Effects of degree of saturation on shallow landslides triggered by rainfall

The empirical rainfall threshold concept and the physical-based model are two commonly used approaches for the assessment of shallow landslides triggered by rainfall. To investigate in detail the rainfall-triggered shallow landslides, many physical-based models coupling the infinite slope stability analysis with the rainfall infiltration modeling in variably saturated soil were developed. However, in those physical-based shallow landslide models, the unit weight and the unsaturated shear strength were assumed constant rather than depending on the degree of saturation. In this study, the effects of the unit weight and the unsaturated shear strength as function of degree of saturation on rainfall-triggered shallow landslides are examined. Several designed scenarios and a real case scenario are used to conduct the examinations. The results show that not only the occurrence of shallow landslides but also the failure depth and the time to failure could be misassessed if the influences of degree of saturation on the unit weight and the unsaturated shear strength are neglected.     

Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region,Garhwal Himalayas,India

Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ^?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.     

降雨类型对浅层滑坡稳定性的影响

在降雨与浅层滑坡稳定性关系的研究中, 目前的研究往往忽略了降雨类型的影响.因此, 选取4种具有代表性的降雨类型: 均匀型、递增型、递减型以及峰值型为对象, 基于Rosso提出的降雨强度与地下水关系模型, 构建考虑降雨类型的浅层滑坡地下水位高度随降雨时间的变化关系, 研究不同降雨类型对浅层滑坡地下水位变化的影响.进而, 结合无限边坡理论, 建立浅层滑坡的稳定性计算模型, 研究不同降雨类型对浅层滑坡稳定性的影响.研究结果表明: 降雨类型对浅层滑坡稳定性的影响是明显的, 递增型降雨作用下的浅层滑坡安全系数最小, 其次是均匀型降雨, 再次是峰值型降雨, 最大的是递减型降雨; 同时在确定浅层滑坡临界降雨量和进行区域浅层滑坡易发性研究时降雨类型的影响不容忽视.      

滑坡频度-降雨量的分形关系

降雨-滑坡关系是对降雨引发的滑坡进行预报的一个重要基础。本文根据中国浙江省1990～2003年期间有明确日期和坐标记录的1414个滑坡数据和基本覆盖浙江全部陆地区域的1257个雨量站记录的日降雨量数据,研究了滑坡频度-降雨关系。研究结果表明,降雨引发滑坡的频度与降雨量之间遵循分形的幂指数关系,并且在两个尺度的降雨量范围内具有不同的标度指数。按照幂指数关系拟合的两条滑坡累计频度-降雨关系线交点(拐点)处的降雨量(Rin)指出了引发75%左右滑坡的累计降雨阀值的上边界(以THCR表示)。对1d、4d、6d和11d这4个累计降雨时段的研究表明,引发75%左右滑坡的累计降雨阀值分别为205mm(1d)、273mm(4d)、294mm(6d)、315mm(11d)。     

Rainfall-induced landslides in Hulu Kelang area, Malaysia

Hulu Kelang is known as one of the most landslide-prone areas in Malaysia. The area has been constantly hit by landslide hazards since 1990s. This paper provides an insight into the mechanism of rainfall-induced landslide in the Hulu Kelang area. Rainfall patterns prior to the occurrences of five selected case studies were first analyzed. The results showed that daily rainfall information is insufficient for predicting landslides in the area. Rainfalls of longer durations, i.e., 3–30 days prior to the landslides should be incorporated into the prediction model. Numerical simulations on a selected case study demonstrated that both matric suction and factor of safety decreased steadily over time until they reached the lowest values on the day of landslide occurrence. Redistribution of infiltrated rainwater in the soil mass could be a reason for the slow response of failure mechanism to rainfall. Based on 21 rainfall-induced landslides that had occurred in the area, three rainfall thresholds were developed as attempts to predict the occurrence of rainfall-induced landslide. The rainfall intensity–duration threshold developed based on the local rainfall conditions provided a reasonably good prediction to the landslide occurrence. The cumulative 3- versus 30-day antecedent precipitation index threshold chart was capable of giving the most reliable prediction with the limiting threshold line for major landslide yielded a reliability of 97.6 %.     

Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy)

Researchers have long attempted to determine the amount of rainfall needed to trigger slope failures, yet relatively little progress has been reported on the effects of climate change on landslide initiation. Indeed, some relationships between landslides and climate change have been highlighted, but sign and magnitude of this correlation remain uncertain and influenced by the spatial and temporal horizon considered. This work makes use of statistically adjusted high-resolution regional climate model simulations, to study the expected changes of landslides frequency in the eastern Esino river basin (Central Italy). Simulated rainfall was used in comparison with rainfall thresholds for landslide occurrence derived by two observation-based statistical models (1) the cumulative event rainfall–rainfall duration model, and (2) the Bayesian probabilistic model. Results show an overall increase in projected landslide occurrence over the twenty-first century. This is especially confirmed in the high-emission scenario representative concentration pathway 8.5, where according to the first model, the events above rainfall thresholds frequency shift from ~?0.025 to ~?0.05 in the mountainous sector of the study area. Moreover, Bayesian analysis revealed the possible occurrence of landslide-triggering rainfall with a magnitude never occurred over the historical period. Landslides frequency change signal presents also considerable seasonal patterns, with summer displaying the steepest positive trend coupled to the highest inter-model spread. The methodological chain here proposed aims at representing a flexible tool for future landslide-hazard assessment, applicable over different areas and time horizons (e.g., short-term climate projections or seasonal forecasts).     

The rainfall intensity–duration control of shallow landslides and debris flows: an update

A global database of 2,626 rainfall events that have resulted in shallow landslides and debris flows was compiled through a thorough literature search. The rainfall and landslide information was used to update the dependency of the minimum level of rainfall duration and intensity likely to result in shallow landslides and debris flows established by Nel Caine in 1980. The rainfall intensity–duration (ID) values were plotted in logarithmic coordinates, and it was established that with increased rainfall duration, the minimum average intensity likely to trigger shallow slope failures decreases linearly, in the range of durations from 10 min to 35 days. The minimum ID for the possible initiation of shallow landslides and debris flows was determined. The threshold curve was obtained from the rainfall data using an objective statistical technique. To cope with differences in the intensity and duration of rainfall likely to result in shallow slope failures in different climatic regions, the rainfall information was normalized to the mean annual precipitation and the rainy-day normal. Climate information was obtained from the global climate dataset compiled by the Climate Research Unit of the East Anglia University. The obtained global ID thresholds are significantly lower than the threshold proposed by Caine (Geogr Ann A 62:23–27, 1980), and lower than other global thresholds proposed in the literature. The new global ID thresholds can be used in a worldwide operational landslide warning system based on global precipitation measurements where local and regional thresholds are not available..     

Numerical modeling of rainstorm-induced shallow landslides in saturated and unsaturated soils

For the assessment of shallow landslides triggered by rainfall, the physically based model coupling the infinite slope stability analysis with the hydrological modeling in nearly saturated soil has commonly been used due to its simplicity. However, in that model the rainfall infiltration in unsaturated soil could not be reliably simulated because a linear diffusion-type Richards’ equation rather than the complete Richards’ equation was used. In addition, the effect of matric suction on the shear strength of soil was not actually considered. Therefore, except the shallow landslide in saturated soil due to groundwater table rise, the shallow landslide induced by the loss in unsaturated shear strength due to the dissipation of matric suction could not be reliably assessed. In this study, a physically based model capable of assessing shallow landslides in variably saturated soils is developed by adopting the complete Richards’ equation with the effect of slope angle in the rainfall infiltration modeling and using the extended Mohr–Coulomb failure criterion to describe the unsaturated shear strength in the soil failure modeling. The influence of rainfall intensity and duration on shallow landslide is investigated using the developed model. The result shows that the rainfall intensity and duration seem to have similar influence on shallow landslides respectively triggered by the increase of positive pore water pressure in saturated soil and induced by the dissipation of matric suction in unsaturated soil. The rainfall duration threshold decreases with the increase in rainfall intensity, but remains constant for large rainfall intensity.     

Early warning of rainfall-induced shallow landslides and debris flows in the USA

The state of knowledge and resources available to issue alerts of precipitation-induced landslides vary across the USA. Federal and state agencies currently issue warnings of the potential for shallow, rapidly moving landslides and debris flows in a few areas along the Pacific coast and for areas affected by Atlantic hurricanes. However, these agencies generally lack resources needed to provide continuous support or to expand services to other areas. Precipitation thresholds that form the basis of landslide warning systems now exist for a few areas of the USA, but the threshold rainfall amounts and durations vary over three orders of magnitude nationwide and over an order of magnitude across small geographic areas such as a county. Antecedent moisture conditions also have a significant effect, particularly in areas that have distinct wet and dry seasons. Early warnings of shallow landslides that include specific information about affected areas, probability of landslide occurrence, and expected timing are technically feasible as illustrated by a case study from the Seattle, WA area. The four-level warning scheme (Null, Outlook, Watch, Warning) defined for Seattle is based on observed or predicted exceedance of a cumulative precipitation threshold and a rainfall intensity–duration threshold combined with real-time monitoring of soil moisture. Based on analysis of historical data, threshold performance varies according to precipitation characteristics, and threshold exceedance corresponds to a given probability of landslide occurrence. Experience in Seattle during December 2004 and January 2005 illustrates some of the challenges of providing landslide early warning on the USA West Coast.     

Erratum to: Early warning of rainfall-induced shallow landslides and debris flows in the USA

The state of knowledge and resources available to issue alerts of precipitation-induced landslides vary across the USA. Federal and state agencies currently issue warnings of the potential for shallow, rapidly moving landslides and debris flows in a few areas along the Pacific coast and for areas affected by Atlantic hurricanes. However, these agencies generally lack resources needed to provide continuous support or to expand services to other areas. Precipitation thresholds that form the basis of landslide warning systems now exist for a few areas of the USA, but the threshold rainfall amounts and durations vary over three orders of magnitude nationwide and over an order of magnitude across small geographic areas such as a county. Antecedent moisture conditions also have a significant effect, particularly in areas that have distinct wet and dry seasons. Early warnings of shallow landslides that include specific information about affected areas, probability of landslide occurrence, and expected timing are technically feasible as illustrated by a case study from the Seattle, WA area. The four-level warning scheme (Null, Outlook, Watch, Warning) defined for Seattle is based on observed or predicted exceedance of a cumulative precipitation threshold and a rainfall intensity–duration threshold combined with real-time monitoring of soil moisture. Based on analysis of historical data, threshold performance varies according to precipitation characteristics, and threshold exceedance corresponds to a given probability of landslide occurrence. Experience in Seattle during December 2004 and January 2005 illustrates some of the challenges of providing landslide early warning on the USA West Coast.     

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。     

Modeling landslide recurrence in Seattle, Washington, USA

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.     

Suggestion of a method for landslide early warning using the change in the volumetric water content gradient due to rainfall infiltration

An early warning system can be an effective measure to reduce the damage caused by landslides by facilitating the timely evacuation of residents from a landslide-prone area. Early detection of landslide triggering across a broad range of natural terrain types can be accomplished by monitoring rainfall and the physical property changes of soils in real time or near-real time. This study involved the installation of a real-time monitoring system to observe physical property changes in soils in a valley during rainfall events. This monitoring included the measurement of volumetric water content, which was compared with the results of laboratory flume tests to identify landslide indicators in the soils. The response of volumetric water content to rainfall events is more immediate than that of pore-water pressure, and volumetric water content retains its maximum value for some time before slope failure. Therefore, an alternative method for landslide monitoring can be based on the observation of volumetric water content and its changes over time at shallow soil depths. Although no landslide occurred, the field monitoring results showed a directly proportional relationship between the effective cumulative rainfall and the gradient of volumetric water content per unit time (t/t _max). This preliminary study thus related slope failure to the volumetric water content gradient as a function of rainfall. Laboratory results showed that a high amount of rainfall and a high gradient of volumetric water content could induce slope failure. Based on these results, it is possible to suggest a threshold value of the volumetric water content gradient demarcating the conditions for slope stability and slope failure. This threshold can thus serve as the basis of an early warning system for landslides considering both rainfall and soil properties.     

Frequency–volume relation and prediction of rainfall-induced landslides

Rainfall-induced landslides constitute a major public concern in Hong Kong. This paper investigates two aspects of critical importance to landslide hazard and risk assessment and management: magnitude–cumulative frequency relationship for landslides, and relationship between rainfall and the occurrence of landslides. The results indicated that landslides with a failure volume of not less than 4 m³ have a cumulative frequency–size distribution with a power-law dependence on volume of failure. Analysis of rainfall/landslides showed that the 12-hour rolling rainfall is most important in predicting the number of landslides. Failure volume dependency in the relationships between rainfall and the number of landslides is also presented. However, with an increase in failure volume of landslides, the most important rainfall variable may vary from rainfall of short duration (12-h rolling rainfall) to that of relatively long duration (24-h rolling rainfall).     

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.     

Comparison of statistical methods and multi-time validation for the determination of the shallow landslide rainfall thresholds

Shallow landslides are unforeseeable phenomena often resulting in critical conditions in terms of people’s safety and damage. The main purpose of this paper is the comparison of different statistical methods used to determine the rainfall thresholds for the shallow landslide occurrence. Rainfall data over a 46-year period were collected for one rain gauge located in a test area of northwest Italy (Riviera Spezzina; RS). In the RS, intense rainfalls often induce shallow landslides causing damage and sometimes casualties. The rainfall events occurred in the 1967–2006 period were classified as events inducing shallow landslides (SLEs_1967–2006) and events that did not trigger shallow landslides (NSLEs_1967–2006). Thresholds for various percentiles of SLEs_1967–2006 were computed by identifying the lower limit above which shallow landslides occurred. Another set of thresholds, corresponding to different probabilities of occurrence, was determined using SLEs_1967–2006 and NSLEs_1967–2006. The least-squares linear fit (LSF) and the quantile regression (QR) techniques were employed in the former approach, while the logistic regression (LR) was applied in the latter. The thresholds were validated with the same data used for their definition and with the data recorded in the 2008–2014 period. Contingency tables were created and contingencies and skill scores were computed. The 10% probability threshold obtained using the LR method is characterized by the best values of at least two skill scores for both periods considered; therefore, it may be considered the “best” threshold for the RS. The results of this work can help the choice of the best statistical method to determine the shallow landslide rainfall thresholds.     

Early warning system for shallow landslides using rainfall threshold and slope stability analysis

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent (x-variable) vs. daily rainfall (y-variable) provided the best fit to the data with a threshold equation of y = 80.7–0.1981x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is ∼20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model (PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety (FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.