Experimental analysis and modelling of shallow landslides

The paper presents the results of some experimental tests reproducing the triggering mechanism of a special kind of shallow landslides induced by rainfalls (soil slip) in a physical 1-g model. The experimental data have been employed to verify the capability of a simplified stability model to describe the phenomenon and to back-analyse its occurrence in a case history (Pizzo d’Alvano, Campania Region 1998). The method enables a direct correlation between the safety factor of a slope and rainfall intensity, as well as antecedent rainfalls.     

Transient modeling of regional rainfall-triggered shallow landslides

This study investigates the transient modeling of regional rainfall-triggered shallow landslides in unsaturated soil using the Richards equation. To model shallow landslides within a distributed regional-scale framework, infinite slope stability analysis coupled with the hydrological model with consideration of the fluctuation of time-dependent pore water pressure and the soil–water characteristic curve proposed by van Genuchten was developed. The validity of the proposed model is established through several test problems by comparing the numerical results with the analytical solutions. A new procedure to set up wide-range shallow landslide analysis and to integrate regional distribution variations for input data such as geology, groundwater level, hydrogeological characteristics, and rainfall intensity and duration was presented. The results obtained demonstrate that the computed distribution of the safety factor is consistent with the distribution of actual landslides. In addition, the fluctuation of pore water pressure in unsaturated soil dominates the stability of landslides during typhoons accompanied by heavy rainfall. The findings observed in this study are a fundamental contribution to environmental effects for landslides in areas with higher occurrence and vulnerability to extreme precipitation.     

Physical and numerical modelling of shallow landslides

Physical modelling is an extremely useful tool for the study of the triggering process of shallow landslides. For this reason, in this work, numerous laboratory tests have been performed using a specific flume test apparatus. A wide range of initial soil conditions (i.e. porosity and water content) has been investigated to analyze the induced effect on failure time and mode, even simulating the presence of preferential flow directions within the soil. Different tests have been performed also reproducing, on a laboratory scale, the landslide event occurred on October 1, 2009, in the area where the testing material was sampled (i.e. Giampilieri, north-eastern Sicily, Italy). Furthermore, the experimental results have been employed to verify the capability of shallow landslide instability prediction (SLIP), a simplified stability model for the prediction of shallow landslide occurrence, to reproduce the triggering process.     

Soil depth reconstruction for the assessment of the susceptibility to shallow landslides in fine-grained slopes

This paper proposes a methodology aimed at reconstructing the maximum thickness mobilized by shallow landslides in fine-grained soils with the aid of geological and geotechnical analyses. The methodology, implemented within a geographic information system (GIS) environment, is composed of two stages for map reconstruction and two stages for map validation. The first stage of map reconstruction is aimed at individuating the soil thickness on the basis of only topographical and geological analyses; the second stage improves the previously obtained map with the aid of morphological and geotechnical analyses that provide a thickness map usable for shallow landslide susceptibility assessment. This map is validated with the aid of both in situ investigations (stage I), and geotechnical models able to back-analyse shallow precipitation-induced landslides over a wide area (stage II). An application of the proposed methodology is provided for a test area of the Calabria region (southern Italy) that is representative of the Catanzaro Strait, where widely diffused shallow landslides in fine-grained soils systematically occur. The results highlight the usefulness and reliability of the geotechnical models when implemented with the aid of a database representative of fine-grained soils while a secondary role is played by in situ investigations that in the test site have been performed only in a few representative and accessible areas.     

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.     

Modelling of shallow landslides with machine learning algorithms

This paper introduces three machine learning(ML)algorithms,the‘ensemble'Random Forest(RF),the‘ensemble'Gradient Boosted Regression Tree(GBRT)and the Multi Layer Perceptron neural network(MLP)and applies them to the spatial modelling of shallow landslides near Kvam in Norway.In the development of the ML models,a total of 11 significant landslide controlling factors were selected.The controlling factors relate to the geomorphology,geology,geo-environment and anthropogenic effects:slope angle,aspect,plan curvature,profile curvature,flow accumulation,flow direction,distance to rivers,water content,saturation,rainfall and distance to roads.It is observed that slope angle was the most significant controlling factor in the ML analyses.The performance of the three ML models was evaluated quantitatively based on the Receiver Operating Characteristic(ROC)analysis.The results show that the‘ensemble'GBRT machine learning model yielded the most promising results for the spatial prediction of shallow landslides,with a 95%probability of landslide detection and 87%prediction efficiency.     

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.     

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.     

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.

     

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.     

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.     

An epidemiological approach to determining the risk of road damage due to landslides

Disruption of segments of roads can have a significant impact on the vulnerability of the entire network. Natural disasters are frequent causes of disruptions of this kind. This article focuses on determining the risk of road disruptions due to landslides. Our approach is based on methodology widely used in the field of epidemiology. We had available data on the location of the landslides, the road network and a list of the disrupted road segments. With the use of a 2 × 2 table, we determined the relationship between landslide data and road segment disruptions and derived the risk coefficient based on the number of landslides in the vicinity of the road and its length. The result is a disruption risk map with risk coefficients ranging from 0 to 47.94. In order to distinguish the most risky segments, we calculated a threshold of 12.40 with the use of a risk breakdown in a group of segments without damage. Nineteen percentage (402 km) of the road network in the Zlín region (Czech Republic), where the methodology was applied, is located beyond this threshold. The benefits of this approach stem from its speed and potential to define the most risky areas on which a detailed geomorphologic analysis can be focused.     

近30年滑坡研究文献图谱可视化分析

以中国知网CNKI数据库收录的17680篇（1992—2021年）中文滑坡文献和Web of Science 核心数据库收录的11350篇（2016—2021年）外文滑坡文献为研究对象,利用文献计量学和知识图谱可视化技术,基于提取的中外文文献关键词信息分析了中国滑坡研究的发展历程、中国学者对国际滑坡研究的贡献,并对比了中外文滑坡研究热点的异同。结果表明：（1）稳定性一直是中国滑坡研究的重点,且随着滑坡研究的方法、对象、诱发因素、防灾减灾需求等方面的发展而不断延续拓展;（2）滑坡灾害研究具有明显的时代特色,具有明确发生时间的重大滑坡事件一般都会成为一段时间内的研究热点;（3）中国在国际滑坡研究领域占有绝对优势,发文量占总发文量的23.34%,发文量排名前4位的研究机构均来自中国;（4）在全球气候变化背景下,边坡稳定性、重大突发性滑坡灾害、高速远程链式危害、古滑坡复活,基于大量地面调查、遥感、监测、勘测数据的机器学习和深度学习开展的风险隐患识别、预警模型和判据研究,包括海底滑坡在内的海洋地质灾害可能成为未来的研究热点。研究结果较客观地展现了中国滑坡研究的发展脉络和国内外滑坡研究的热点和趋势,以期有助于我国滑坡灾害研究与防治科技的进步。     

Indigenous knowledge and the desertification debate: problematising expert knowledge in North Africa

In Morocco the crisis narrative of desertification has been invoked for decades to facilitate and justify policy and legal changes that have systematically disadvantaged pastoralists and damaged the environment. The existing data from southern Morocco, however, do not support the claims of widespread desertification due to overgrazing or other pastoral activities. Furthermore, many anti-desertification and range improvement projects in southern Morocco have not succeeded. In an effort to rethink desertification and range ecology in Morocco, this paper presents an overview of the indigenous knowledge of range ecology among the Aarib, a group of camel pastoralists in southern Morocco, and compares it to the “expert” knowledge of Moroccan range managers. It suggests that this expert knowledge is based on questionable evidence and that it has been privileged over local knowledge primarily for political, economic and administrative reasons. The discrepancies between expert and indigenous knowledges of range ecology presented here underscore the need to reconsider range ecology in Morocco, taking indigenous ecological knowledge into account. Doing so may point the way to more successful development and conservation projects which are more environmentally appropriate and socially just. Not doing so will likely exacerbate environmental degradation in the region.     

基于CiteSpace的浅层滑坡文献计量分析

基于Web of Science数据库,以1999—2019年检索所得1240篇浅层滑坡期刊论文为样本,利用CiteSpace对该领域内国家/机构、学科/期刊和高频关键词进行文献计量和可视化分析,结果表明：浅层滑坡研究的国际合作非常普遍,意大利在浅层滑坡研究中占据核心地位,意大利国家研究委员和中国科学院两家机构在该领域发挥重要作用,GEOMORPHOLOGY和LANDSLIDES杂志为浅层滑坡研究代表性期刊。复合模型算法为浅层滑坡研究领域近期的热点主题。     

Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach

To prepare a landslide susceptibility map is essential to identify hazardous regions, construct appropriate mitigation facilities, and plan emergency measures for a region prone to landslides triggered by rainfall. The conventional mapping methods require much information about past landslides records and contributing terrace and rainfall. They also rely heavily on the quantity and quality of accessible information and subjectively of the map builder. This paper contributes to a systematic and quantitative assessment of mapping landslide hazards over a region. Geographical Information System is implemented to retrieve relevant parameters from data layers, including the spatial distribution of transient fluid pressures, which is estimated using the TRIGRS program. The factor of safety of each pixel in the study region is calculated analytically. Monte Carlo simulation of random variables is conducted to process the estimation of fluid pressure and factor of safety for multiple times. The failure probability of each pixel is thus estimated. These procedures of mapping landslide potential are demonstrated in a case history. The analysis results reveal a positive correlation between landslide probability and accumulated rainfall. This approach gives simulation results compared to field records. The location and size of actual landslide are well predicted. An explanation for some of the inconsistencies is also provided to emphasize the importance of site information on the accuracy of mapping results.     

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.