Susceptibility assessment of shallow landslides triggered by rainfall in tropical basins and mountainous terrains

Natural Hazards - This study presents the analyses and results of the implementation of the SHALSTAB model to study landslides caused by rainfall that occurred on September 21, 1990, in a basin of...     

降雨型滑坡危险性区划方法

降雨诱发的滑坡等地质灾害分布广、危害大,开展地质灾害危险性区划是减轻地质灾害损失的有效途径之一。以湖南省为例,根据地质灾害调查成果,选取3 412处滑坡,分析了区域降雨型滑坡的发育特点和分布规律,建立了危险性区划指标体系,利用不确定性推理中的确定性系数法,对滑坡与工程地质岩组、坡度、坡向、植被和年均降水量5个评价因子进行了相关性分析,建立了Logistic多元回归模型;采用不规则网格单元划分方法,形成了湖南省滑坡灾害危险性区划图。     

Real-time estimation of hazard for landslides triggered by rainfall

 Landslide movements triggered by rainfall can be foreseen in real-time by modelling the relationship between rainfall amount and landslide occurrence. This paper deals with the problem of the reliability of the FLaIR (Forecasting of Landslides Induced by Rainfalls) model when applied to forecasting landslide movements in the usual condition of poor historical information availability. In this case, the identification of the admissibility field for the model parameters, instead of a point estimation, leads to an improvement of the forecasting reliability. Moreover, this approach makes the model capable of taking into account information embodied in periods of heavy rain but without movement. The concepts of informative content and foreseeability of landslide movements are introduced and their duality is analyzed. The effectiveness of the estimation procedure described has been tested by application on two landslides located in southern Italy. Received: 15 October 1996 · Accepted: 25 June 1997     

Cost-sensitive rainfall thresholds for shallow landslides

The risk management of rainfall-induced landslides requires reliable rainfall thresholds to issue early warning alerts. The practical application of these thresholds often leads to misclassifications, either false negative or false positive, which induce costs for the society. Since missed-alarm (false negative) and false-alarm (false positive) cost may be significantly different, it is necessary to find an optimal threshold that accounts for and minimises such costs, tuning the false-alarm and missed-alarm rates. In this paper, we propose a new methodology to develop cost-sensitive rainfall thresholds, and we also analyse several factors that produce uncertainty, such as the accuracy of rainfall intensity values at landslide location, the time of occurrence, the minimum rainfall amount to define the non-triggering event, and the variability of cost scenarios. Starting from a detailed mapping of landslides that occurred during five large-scale rainfall events in the Italian Central Alps, we first developed rainfall threshold curves with a ROC-based approach by using both rain gauge and bias-adjusted weather radar data. Then, based on a reference cost scenario in which we quantified several cost items for both missed alarms and false alarms, we developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). Finally, we studied the sensitivity of cost items. The study confirms how important is the information regarding rainfall intensity at the landslide site for the development of rainfall thresholds. Although the use of bias-corrected radar strongly improves these values, a large uncertainty related to the exact time of landslide occurrence still remains, negatively affecting the analysis. Accounting for the different missed-alarm and false-alarm misclassification costs is important because different combinations of these costs make an increase or decrease of the rainfall thresholds convenient. In our reference cost scenario, the most convenient threshold is lower than ROC-based thresholds because it seeks to minimise the number of missed alarms, whereas the missed-alarm costs are almost seven times greater than false-alarm costs. However, for different cost scenarios, threshold may vary significantly, as much as half an order of magnitude.

     

浅层滑坡诱发沟谷泥石流的地形和降雨条件

2011年贵州省望谟县打易镇的大范围浅层滑坡诱发的沟谷泥石流提供了研究这类泥石流地形和降雨条件的机会。在地质条件一致和小区域内的降雨条件基本一致的情况下,地形条件就是这些泥石流暴发与否的唯一决定因素。对比一些重要的地形因素与泥石流暴发的关系,得出了由流域面积、沟床纵比降和25°~45°山坡坡度面积比组成的泥石流综合地形因子T。在地形因子T的基础上,研究获得了由前期降雨量、1 h降雨强度、年平均降雨量等组成的降雨因子R。由地形因子T和降雨因子R获得的临界条件P可以判断该区域的泥石流暴发。由于研究工作部分基于泥石流的形成机理,研究成果还可用于其他区域的泥石流形成预测,为泥石流的预测预报提供了一个较好的方法。     

Spatially distributed rainfall thresholds for the initiation of shallow landslides

The evaluation of the combined influence of rainfall patterns (in terms of mean intensity and duration) and the geomorphological and mechanical characteristics of hillslopes on their stability conditions is a major goal in the assessment of the shallow landslide triggering processes. Geographic Information Systems (GIS) represent an important tool to develop models that combine hydrological and geomechanical analyses for the evaluation of slope stability, as they allow to combine information concerning rainfall characteristics with topographic and mechanical properties of the slopes over wide areas. In this paper, a GIS-based code is developed to determine physically based intensity/duration rainfall thresholds at the local scale. Given the rainfall duration and the local geometric, hydrological and mechanical characteristics of the slopes, the code evaluates the spatial distribution of the minimum rainfall intensity that triggers shallow landslides and debris flows over a given area. The key feature of the code is the capability of evaluating the time t _p required to reach the peak pore pressure head on the failure surface and computing the corresponding critical intensity/duration thresholds based on post-event peak pore pressures. The reliability of the model is tested using a set of one-dimensional analyses, comparing the physically based thresholds obtained for three different slopes with some empirical rainfall thresholds. In a log–log scale, the thresholds provided by the model decrease linearly with increased rainfall duration and they are bracketed by the empirical thresholds considered. Finally, an example of application to a study area of the Umbria region in central Italy is presented, describing the capability of the model of providing site-specific thresholds for different rainfall scenarios.     

Laboratory tests with interferometric optical fibre sensors to monitor shallow landslides triggered by rainfalls

Optical fibre–based sensors have now established their place in the field of geohazard monitoring due to their sensitivity to strain and temperature changes. Progressive development in the technology leads to the availability of novel, accurate and durable sensors at a relatively limited cost. This creates room for original monitoring applications that have been, so far, impeded by the shortcomings of conventional monitoring tools. In this work, we explore the applicability of an interferometric optical fibre sensor as a vibration sensing tool at laboratory scale. We tested the ability of the sensor to identify precursors of instability in a downscaled model of a rainfall-induced landslide composed of granular material. We carried out four experimental tests which involved different sensor deployments and soil mixtures. The recorded signals were processed by means of a time–frequency analysis and we identified two frequency-domain parameters—the spectral centroid and band power—that could provide information on the development of instability. Their ratio yielded a unique parameter through which a precursory stage could be outlined by defining a threshold value based on the data collected at the beginning of the experiment. In our lab tests, precursors of instability were detected 2–3 min before a crack was observed at the surface. This may upscale to a lead time of about 20–30 min or more in the field, classifying our monitoring approach in between an alarm and a warning system. The work presented here can be considered a first promising step towards an innovative monitoring system and shows the potential of optical fibre sensing as a shallow landslide monitoring technique, encouraging further testing, especially in real-case studies.

     

Spatio-temporal estimation of shallow landslide hazard triggered by rainfall using a three-dimensional model

A shallow landslide triggered by rainfall can be forecast in real-time by modeling the relationship between rainfall infiltration and decrease of slope stability. This paper describes a promising approach that combines an improved three-dimensional slope stability model with an approximate method based on the Green and Ampt model, to estimate the time–space distribution of shallow landslide hazards. Once a forecast of rainfall intensity and slope stability-related data, e.g., terrain and geology data, are acquired, this approach is shown to have the ability to estimate the variation of slope stability of a wide natural area during rainfall and to identify the location of potential failure surfaces. The effectiveness of the estimation procedures described has been tested by comparison with a one-dimensional method and by application to a landslide-prone area in Japan.     

Influence of saturation on rainfall generated landslides in shale along Murree-Kohala road,Pakistan

On August 10, 2010 a series of landslides of more than 90,000 m³ occurred along the Muree-Kohala road in the northern area of Pakistan. A study was undertaken to evaluate the likely impacts of percent saturation and bulk density on mobilized shear strength along the basal rupture surface of the landslide. A series of unconfined compression test and unconsolidated undrained triaxial tests were performed on remolded samples of different densities with varied percentages of saturation. The results of these tests suggest that soil cohesion and friction decreases with increasing saturation. The tests also showed that the shear strength parameters tend to increase with increasing dry density; however, all the samples exhibited a noticeable loss of shear strength with increasing degree of saturation, independent of soil density.Limit equilibrium slope stability analyses were performed along the most probable failure planes, based on shear strength parameters corresponding to degrees of saturation, which varied between 30% to about 100%. This resulted in drop of factor of safety from FS = 1.64 down to 0.51 as the degree of saturation approaches unity.These results suggest that the causative factor in triggering the landslide along Murree-Kohala was the partial saturation of the zone that developed the basal rupture plane. As rain infiltrated the slope, the bulk unit weight of the soil increased, while the shear strength along the developing plane of rupture decreased sufficiently to concentrate shear strain when the material became more than 60% saturation (FS < 1.0).     

Effects of soil heterogeneity on susceptibility of shallow landslides

Uncertainties in parameters of landslide susceptibility models often hinder them from providing accurate spatial and temporal predictions of landslide occurrences. Substantial contribution to the uncertainties in landslide assessment originates from spatially variable geotechnical and hydrological parameters. These input parameters may often vary significantly through space, even within the same geological deposit, and there is a need to quantify the effects of the uncertainties in these parameters. This study addresses this issue with a new three-dimensional probabilistic landslide susceptibility model. The spatial variability of the model parameters is modeled with the random field approach and coupled with the Monte Carlo method to propagate uncertainties from the model parameters to landslide predictions (i.e., factor of safety). The resulting uncertainties in landslide predictions allow the effects of spatial variability in the input parameters to be quantified. The performance of the proposed model in capturing the effect of spatial variability and predicting landslide occurrence has been compared with a conventional physical-based landslide susceptibility model that does not account for three-dimensional effects on slope stability. The results indicate that the proposed model has better performance in landslide prediction with higher accuracy and precision than the conventional model. The novelty of this study is illustrating the effects of the soil heterogeneity on the susceptibility of shallow landslides, which was made possible by the development of a three-dimensional slope stability model that was coupled with random field model and the Monte Carlo method.

     

Hydrological regimes in different slope environments and implications on rainfall thresholds triggering shallow landslides

Natural Hazards - Assessing hazard of rainfall-induced shallow landslides represents a challenge for the risk management of urbanized areas for which the setting up of early warning systems, based...     

Examination of influences of rainfall patterns on shallow landslides due to dissipation of matric suction

The influences of rainfall patterns on shallow landslides due to the dissipation of matric suction are examined in this study. Four representative rainfall patterns including the uniform, advanced, intermediated, and delayed rainfalls are adopted. The results show that not only the occurrence of shallow landslides but also the failure depth and the time of failure are affected by the rainfall pattern. The different rainfall patterns seem to have the same minimum landslide-triggering rainfall amount. There is a rainfall duration threshold for landslide occurrence for a rainfall event with larger than the minimum landslide-triggering rainfall amount. For each rainfall pattern, the rainfall duration threshold for landslide occurrence decreases to constant with the increase of rainfall amount. The uniform rainfall has the least rainfall duration threshold for landslide occurrence, followed by the advanced rainfall, and then the intermediated rainfall. For each rainfall pattern, the failure depths and the times of failure from the same amount of rainfall with different durations could be largely different. In addition, the differences of the failure depths and the times of failure between various rainfall patterns with the same amount and duration of rainfall could be also significant. The failure depth and the time of failure, as compared with the occurrence of shallow landslides, are more sensitive to the rainfall condition. In other words, in comparison with the evaluation of the occurrence of shallow landslides, it needs more accurate rainfall prediction to achieve reliable estimations of the failure depth and the time of failure.     

Estimation of rainfall thresholds triggering shallow landslides for an operational warning system implementation

The Piemonte regional warning system service, managed by the Environmental Protection Agency of Piemonte (“ARPA Piemonte” as official Italian acronym), is based on an advanced meteo-hydrological automatic monitoring system, and it is integrated with forecasting activities of severe weather-related natural hazards. At present, a meteo-hydrological chain is operated to provide flood forecasting on the main river pattern. The development of a forecasting tool for shallow landslides triggered by heavy rainfall is presented. Due to the difficulties in modelling shallow landslides triggering in a large and complex area like the Piemonte region, an empirical model is developed on the basis of the correlation between rainfall and previous landslides in historical documents. The research focuses on establishing rainfall thresholds for landslides triggering, differentiating the critical rainfall values through a geological characterisation of the different territories. The period from 1990 to 2002 is considered. A total number of 160 landslides with hourly information and time of triggering are used to calibrate the system. As a first outcome, two different zones have been identified: (1) zones in alpine environments, principally characterised by a bedrock composed of metamorphic rocks, igneous rocks, dolostones or limestones that require high values of critical rainfall and (2) zones in hilly environments, principally characterised by sedimentary bedrock that require low values of critical rainfall. Verification has been performed on a total number of 429 landslides with known date of occurrence. The results show a good agreement with the model with no missed alarms and a very low number of false alarms, thus suggesting an effective operational implementation.     

SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins

Landslides are a main cause of human and economic losses worldwide. For this reason, landslide hazard assessment and the capacity to predict this phenomenon have been topics of great interest within the scientific community for the implementation of early warning systems. Although several models have been proposed to forecast shallow landslides triggered by rainfall, few models have incorporated geotechnical factors into a complete hydrological model of a basin that can simulate the storage and movement of rainwater through the soil profile. These basin and full hydrological models have adopted a physically based approach. This paper develops a conceptual and physically based model called open and distributed hydrological simulation and landslides—SHIA_Landslide (Simulación HIdrológica Abierta, or SHIA, in Spanish)—that is supported by geotechnical and hydrological features occurring on a basin-wide scale in tropical and mountainous terrains. SHIA_Landslide is an original and significant contribution that offers a new perspective with which to analyse shallow landslide processes by incorporating a comprehensive distributed hydrological tank model that includes water storage in the soil coupled with a classical analysis of infinite slope stability under saturated conditions. SHIA_Landslide can be distinguished by the following: (i) its capacity to capture surface topography and effects concerning the subsurface flow; (ii) its use of digital terrain model (DTM) to establish the relationships among cells, geomorphological parameters, slope angle, direction, etc.; (iii) its continuous simulation of rainfall data over long periods and event simulations of specific storms; (iv) its consideration of the effects of horizontal and vertical flow; and (vi) its inclusion of a hydrologically complete water process that allows for hydrological calibration. SHIA_Landslide can be combined with real-time rainfall data and implemented in early warning systems.     

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.     

Effects of soil-engineering properties on the failure mode of shallow landslides

Some landslides mobilize into flows, while others slide and deposit material immediately down slope. An index based on initial dry density and fine-grained content of soil predicted failure mode of 96 landslide initiation sites in Oregon and Colorado with 79% accuracy. These material properties can be used to identify potential sources for debris flows and for slides. Field data suggest that loose soils can evolve from dense soils that dilate upon shearing. The method presented herein to predict failure mode is most applicable for shallow (depth <5?m), well-graded soils (coefficient of uniformity >8), with few to moderate fines (fine-grained content <18%), and with liquid limits <40.