Infinite Slope Stability Model Research Articles

A hydroclimatological approach to predicting regional landslide probability using Landlab

Abstract. We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

Improving the reliability of landslide susceptibility mapping through spatial uncertainty analysis: a case study of Al Hoceima, Northern Morocco

This paper aims at providing an answer as to whether generalization obtained with data-driven modelling can be used to gauge the plausibility of the physically based (PB) model’s prediction. Two statistical models namely; Weight of Evidence (WofE) and Logistic Regression (LR), and a PB model using the infinite slope assumptions were evaluated and compared with respect to their abilities to predict susceptible areas to shallow landslides at the 1:10.000 urban scale. Threshold-dependent performance metrics showed that the three methods produced statistically comparable results in terms of success and prediction rates. However, with the Area Under the receiver operator Curve (AUC), statistical models are more accurate (88.7 and 84.6% for LR and WofE, respectively) than the PB model (only 69.8%). Nevertheless, in such data-sparse situation, the usual approaches for validation, i.e. comparing observed with predicted data, are insufficient, formal uncertainty analysis (UA) is a means for evaluating the validity and reliability of the model. We then refitted the PB model using a stochastic modification of the infinite slope stability model input scheme using Monte Carlo (MC) method backed with sensitivity analysis (SA). For statistical models, we used an informal Student t-test for estimating the certainty of the predicted probability (PP) at each location. Both modelling outputs independently show a high validity; and whereas the level of confidence in LR and WofE models remained the same after performance re-evaluation, the accuracy of the PB model showed an improvement (AUC = 72%). This result is reasonable and provides a further validation of PB model. So, in urban slope analysis, where PB diagnostic is necessary, statistical and PB modelling may play equally supportive roles in landslide hazard assessment.

Are real-world shallow landslides reproducible by physically-based models? Four test cases in the Laternser valley, Vorarlberg (Austria)

In contrast to the complex nature of slope failures, physically-based slope stability models rely on simplified representations of landslide geometry. Depending on the modelling approach, landslide geometry is reduced to a slope-parallel layer of infinite length and width (e.g., the infinite slope stability model), a concatenation of rigid bodies (e.g., Janbu’s model), or a 3D representation of the slope failure (e.g., Hovland’s model). In this paper, the applicability of four slope stability models is tested at four shallow landslide sites where information on soil material and landslide geometry is available. Soil samples were collected in the field for conducting respective laboratory tests. Landslide geometry was extracted from pre- and post-event digital terrain models derived from airborne laser scanning. Results for fully saturated conditions suggest that a more complex representation of landslide geometry leads to increasingly stable conditions as predicted by the respective models. Using the maximum landslide depth and the median slope angle of the sliding surfaces, the infinite slope stability model correctly predicts slope failures for all test sites. Applying a 2D model for the slope failures, only two test sites are predicted to fail while the two other remain stable. Based on 3D models, none of the slope failures are predicted correctly. The differing results may be explained by the stabilizing effects of cohesion in shallower parts of the landslides. These parts are better represented in models which include a more detailed landslide geometry. Hence, comparing the results of the applied models, the infinite slope stability model generally yields a lower factor of safety due to the overestimation of landslide depth and volume. This simple approach is considered feasible for computing a regional overview of slope stability. For the local scale, more detailed studies including comprehensive material sampling and testing as well as regolith depth measurements are necessary.

A combined triggering-propagation modeling approach for the assessment of rainfall induced debris flow susceptibility

Rainfall-induced shallow slides can evolve into debris flows that move rapidly downstream with devastating consequences. Mapping the susceptibility to debris flow is an important aid for risk mitigation. We propose a novel practical approach to derive debris flow inundation maps useful for susceptibility assessment, that is based on the integrated use of DEM-based spatially-distributed hydrological and slope stability models with debris flow propagation models. More specifically, the TRIGRS infiltration and infinite slope stability model and the FLO-2D model for the simulation of the related debris flow propagation and deposition are combined. An empirical instability-to-debris flow triggering threshold calibrated on the basis of observed events, is applied to link the two models and to accomplish the task of determining the amount of unstable mass that develops as a debris flow. Calibration of the proposed methodology is carried out based on real data of the debris flow event occurred on 1 October 2009, in the Peloritani mountains area (Italy). Model performance, assessed by receiver-operating-characteristics (ROC) indexes, evidences fairly good reproduction of the observed event. Comparison with the performance of the traditional debris flow modeling procedure, in which sediment and water hydrographs are inputed as lumped at selected points on top of the streams, is also performed, in order to assess quantitatively the limitations of such commonly applied approach. Results show that the proposed method, besides of being more process-consistent than the traditional hydrograph-based approach, can potentially provide a more accurate simulation of debris-flow phenomena, in terms of spatial patterns of erosion and deposition as well on the quantification of mobilized volumes and depths, avoiding overestimation of debris flow triggering volume and, thus, of maximum inundation flow depths.

A Potential Headward Retreat Landslide Site at Munnar, Kerala

ABSTRACT A potential head ward retreat landslide area was identified in Munnar, a hill station in Western Ghats of Kerala, India. This imminent landslide was suspected to be formed in three different stages viz., evolution of plateau region, upliftment of the plateau region and the consequent slope modification which ultimately facilitated landslide occurrence. Geophysical study through vertical electrical sounding reveals that more than 11 m thick soil is still left in an overhanging position in the crown portion of the land-slide and the thickness continues to the top of that ridge. In the event of high rainfall, the land can fail as there is no toe support, and the slope angle is >40º. This area is adjacent to a college building and in the event of any further landslide, the consequence will be high. Slope stability analysis using one-dimensional infinite slope stability model reveals that the entire area occupied by the college and the adjacent areas are unstable even in dry conditions. Rainfall threshold analysis shows that the landslide occurred due to very high amount of a 5-day antecedent rainfall rather than a daily rainfall during the monsoon. All these point towards a pressing requirement of landslide management practices in this area. This study also attempts to suggest a few management practices to minimize the effect of landslides.

Does parameterization influence the performance of slope stability model results? A case study in Rio de Janeiro, Brazil

We produce factor of safety (FOS) and slope failure susceptibility index (SFSI) maps for a 4.4-km2 study area in Rio de Janeiro, Brazil, in order to explore the sensitivity of the geotechnical and geohydraulic parameterization on the model outcomes. Thereby, we consider parameter spaces instead of combinations of discrete values. SFSI is defined as the fraction of tested parameter combinations within a given space yielding FOS <1. We repeat our physically based calculations for various parameter spaces, employing the infinite slope stability model and the sliding surface model of the software r.slope.stability for testing the geotechnical parameters and the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) for testing the geohydraulic parameters. Whilst the results vary considerably in terms of their conservativeness, the ability to reproduce the spatial patterns of the observed landslide release areas is relatively insensitive to the variation of the parameterization as long as there is sufficient pattern in the results. We conclude that landslide susceptibility maps yielded by catchment-scale physically based models should not be interpreted in absolute terms and suggest that efforts to develop better strategies for dealing with the uncertainties in the spatial variation of the key parameters should be given priority in future slope stability modelling efforts.

Soil moisture causes dynamic adjustments to root reinforcement that reduce slope stability

AbstractIn steep soil‐mantled landscapes, the initiation of shallow landslides is strongly controlled by the distribution of vegetation, whose roots reinforce the soil. The magnitude of root reinforcement depends on the number, diameter distribution, orientation and the mechanical properties of roots that cross potential failure planes. Understanding how these properties vary in space and time in forests remains a significant challenge. Here we test the hypothesis that spatio‐temporal variations in root reinforcement along a hillslope occur as a function of topographic soil moisture gradients. To test this hypothesis we compared root reinforcement measurements from relatively dry, divergent noses to relatively wet, convergent hollows in the southern Appalachian Mountains, North Carolina, USA. Our initial results showed that root reinforcement decreased in areas of higher soil moisture because the tensile strength of roots decreased. A post hoc laboratory experiment further demonstrated that root tensile strength decreased as root moisture content increased. This effect is consistent with other experiments on stem woods showing that increased water content in the cell wall decreases tensile strength. Our experimental data demonstrated that roots can adjust to changes in the external root moisture conditions within hours, suggesting that root moisture content will change over the timescale of large storm events (hours–days). We assessed the effects of the dynamic changes in root tensile strength to the magnitude of apparent cohesion within the infinite slope stability model. Slopes can be considerably less stable when precipitation‐driven increases in saturated soil depth both increase pore pressures and decrease root reinforcement. Copyright © 2016 John Wiley &amp; Sons, Ltd.

기후변화 시나리오를 이용한 광역 사면안정 해석(2): 결과분석

This study aims to assess the slope stability variation of Jeonbuk drainage areas by RCM model outputs based on A1B climate change scenario and infinite slope stability model based on the previous research by Choi et al.(2013). For a large-scale slope stability analysis, we developed a GIS-based database regarding topographic, geologic and forestry parameters and also calculated daily maximum rainfall for the study period(1971~2100). Then, we assess slope stability variation of the 20 sub-catchments of Jeonbuk under the climate change scenario. The results show that the areal-average value of safety factor was estimated at 1.36(moderately stable) in spite of annual rainfall increase in the future. In addition, 7 sub-catchments became worse and 5 sub-catchments became better than the present period(1971~2000) in terms of safety factor in the future.

Probabilistic slope stability analysis considering the variability of hydraulic conductivity under rainfall infiltration–redistribution conditions

Many soil parameters are highly variable, especially saturated hydraulic conductivity, which is bound to significantly influence the stability of unsaturated soil slopes that are subjected to rainfall infiltration and redistribution. A random variable model is used to characterize the variability of saturated hydraulic conductivity. Random number sequences of saturated hydraulic conductivity are generated following a lognormal distribution using the Monte Carlo Simulation method. Then the closed form of the limit state function is established, based on the combination of the extension of the Green-Ampt model and the infinite slope stability model. The suggested probabilistic method can calculate the time-dependent failure probability of the slope during a process of rainfall infiltration and redistribution. For a hypothetical slope that is subjected to steady-state rainfall infiltration, a series of parameter analyses are conducted and the results indicate that there exists a critical rainfall duration. At different stages of rainwater infiltration–redistribution, the trends between the failure probability of the soil slope and the coefficient of variation of the saturated hydraulic conductivity have a different form. The coefficient of variation of the saturated hydraulic conductivity does not affect the failure time of the slope that is most likely to occur. This paper figures out why some landslides occur after a rainfall event from the perspective of rainwater redistribution, and the corresponding lag times generally depend on the duration of antecedent rainfall. It is very risky to adopt mean safety factors to assess their stabilities for rainfall-induced landslides when the variability of the hydraulic conductivity is considered.

Comparative analysis of SHALSTAB and SINMAP for landslide susceptibility mapping in the Cunha River basin, southern Brazil

The Shallow Landsliding Stability Model (SHALSTAB) and Stability Index Mapping (SINMAP) models have been applied to various landslide management and research studies. Both models combine a hydrological model with an infinite slope stability model for predicting landslide occurrence. The objectives of the present study were to apply these two models to the Cunha River basin, Santa Catarina State, southern Brazil, where many landslides occurred in November 2008, and perform a comparative analysis of their results. Soil samples were collected to determine the input parameters. The models were calibrated with a landslide scar inventory, and rainfall data were obtained from three rain gauges. A comparison of their results obtained from the models was undertaken with the success and error index. Based on the maps of stability and instability areas for the study basin, the models performed well. Since the initial equations of both models are not particularly different, their results are similar. Locations with steep slopes, as well as areas with concave relief that tend to have larger contribution areas and moisture, have lower stability indexes. SHALSTAB classified only ~13 % of the total area of the Cunha River basin as unstable, while SINMAP classified ~30 % as unstable. The analysis of maps based on the results of the two models shows that if SHALSTAB is correctly calibrated, based on hydrological parameters, its results could be more accurate than SINMAP in the prediction of landslide areas. Although SINMAP showed better calibration of the landslide scars, its classification over the basin results in an overestimation of stability areas. The conclusion is that SHALSTAB is more suitable than SINMAP for the prediction of landslides in the Cunha River basin, Brazil.

Slope stability analysis using a physically based model: a case study from A Luoi district in Thua Thien-Hue Province, Vietnam

A case study of slope stability mapping is presented for the A Luoi district situated in the mountainous western part of Thua Thien-Hue Province in Central Vietnam, where slope failures occur frequently and seriously affect local living conditions. The methodology is based on the infinite slope stability model, which calculates a safety factor as the ratio between shear strength and shear stress. The triggering mechanism for slope instability considered in the analysis is the maximum daily precipitation recorded in a 28-year period (1976–2003) taking into account runoff and infiltration predicted with a hydrological model. All necessary physical parameters are derived from topography, soil texture, and land use, in GIS-raster grid format with pixel size of 30 by 30 m. Results of the analysis are compared with a slope failure inventory map of 2001, showing that more than 86.9 % of the existing slope failures are well predicted by the physically based slope stability model. It can be concluded that the larger part of the study area is prone to landsliding. The resulting slope stability map is useful for further research and land-use planning, but for precise prediction of future slope failures, more effort is needed with respect to spatial variation of causative factors and analysis techniques.

Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems

Abstract. Real-time assessment of debris-flow hazard is fundamental for developing warning systems that can mitigate risk. A convenient method to assess the possible occurrence of a debris flow is to compare measured and forecasted rainfalls to critical rainfall threshold (CRT) curves. Empirical derivation of the CRT from the analysis of past events' rainfall characteristics is not possible when the database of observed debris flows is poor or when the environment changes with time. For debris flows and mud flows triggered by shallow landslides or debris avalanches, the above limitations may be overcome through the methodology presented. In this work the CRT curves are derived from mathematical and numerical simulations, based on the infinite-slope stability model in which slope instability is governed by the increase in groundwater pressure due to rainfall. The effect of rainfall infiltration on landside occurrence is modelled through a reduced form of the Richards equation. The range of rainfall durations for which the method can be correctly employed is investigated and an equation is derived for the lower limit of the range. A large number of calculations are performed combining different values of rainfall characteristics (intensity and duration of event rainfall and intensity of antecedent rainfall). For each combination of rainfall characteristics, the percentage of the basin that is unstable is computed. The obtained database is opportunely elaborated to derive CRT curves. The methodology is implemented and tested in a small basin of the Amalfi Coast (South Italy). The comparison among the obtained CRT curves and the observed rainfall amounts, in a playback period, gives a good agreement. Simulations are performed with different degree of detail in the soil parameters characterization. The comparison shows that the lack of knowledge about the spatial variability of the parameters may greatly affect the results. This problem is partially mitigated by the use of a Monte Carlo approach.

Spatially distributed three-dimensional slope stability modelling in a raster GIS

We present a GRASS GIS implementation of a three-dimensional slope stability model capable of dealing with shallow and deep-seated slope failures, r.rotstab. It exploits a modified version of the revised Hovland method and evaluates the slope stability over a large number of randomly selected slip surfaces, ellipsoidal or truncated in shape. For each raster cell in the modelling domain, the factor of safety is taken from the most critical slip surface. This results in an overview of potentially unstable regions without showing the individual sliding areas. Furthermore, the model produces a susceptibility index for each cell, based on the proportion of slip surfaces with a low factor of safety. We test the model in the Collazzone area, Umbria, central Italy where detailed information on shallow and deep-seated landslides, morphology and lithology is available. The rate of true predictions (landslide plus non-landslide) ranges from 54.7 to 81.2% for shallow landslides and from 58.5 to 87.4% for deep-seated landslides, depending on the adjustment of the uncertain geotechnical parameters. In the same order, the rate of true landslide predictions decreases from 80.2 to 19.9% (shallow) and from 64.3 to 3.6% (deep-seated) so that an increase of the true landslide prediction rate can only be achieved at the cost of a significant increase of the false alarm rate. The results for shallow landslides are very similar to those yielded with the infinite slope stability model in terms of the minimum factor of safety, but differ substantially in terms of the spatial patterns. The evaluation of the landslide susceptibility index yields areas under the ROC curves of 0.68–0.70 (shallow landslides, r.rotstab), 0.61–0.65 (shallow landslides, infinite slope stability model) and 0.59–0.63 (deep-seated landslides). We conclude that the r.rotstab model outperforms the infinite slope stability model.

기후변화 시나리오를 이용한 광역 사면안정 해석(1): 방법론

본 연구에서는 기상청에서 제공하는 공간해상도 27km 지역규모의 A1B 시나리오 기반의 RCM 자료와 비집수면적 개념을 도입한 GIS기반의 무한사면안정모형을 이용하여 전라북도 수계를 대상으로 미래 기후변화에 따른 사면안정 변동성을 평가하였다. 우선, 미래의 사면안정성 변동성 평가를 위하여 RCM 자료는 공간적으로 유역단위에서 강우관측소 지점단위로, 시간적으로 월단위에서 일단위 자료로 다운스케일링을 수행하였다. 또한, 무한사면안정모형의 중요 매개변수인 습윤지수 산정을 위하여 비집수면적 개념을 도입하여 격자기반의 습윤지수 정보를 획득하였으며 범용수치지형도, 정밀토양도, 임상도를 이용하여 지형 지질 임상학적 매개변수을 추출하여 GIS기반의 무한사면안정모형을 구축하였다. 이상의 미래 강우입력자료와 무한사면안정모형을 이용하여 현재(1971~2000)대비 미래(2010~2100)에 대한 사면안정 변동성을 평가하였다. 본 논문은 2편으로 구성되어 있으며, 제1편에서는 기후변화 시나리오에 따른 사면안정 변동성 해석을 위한 RCM자료의 가공 및 무한사면안정모형의 구축 등 방법론을 제시한다. This study aims to assess the slope stability variation of Jeollabuk-do drainage areas by RCM model outputs based on A1B climate change scenario and infinite slope stability model based on the specific catchment area concept. For this objective, we downscaled RCM data in time and space: from watershed scale to rain gauge scale in space and from monthly data to daily data in time and also developed the GIS-based infinite slope stability model based on the concept of specific catchment area to calculate spatially-distributed wetness index. For model parameterization, topographic, geologic, forestry digital map were used and model parameters were set up in format of grid cells(<TEX>$90m{\times}90m$</TEX>). Finally, we applied the future daily rainfall data to the infinite slope stability model and then assess slope stability variation under the climate change scenario. This research consists of two papers: the first paper focuses on the methodologies of climate change scenario preparation and infinite slope stability model development.

Landslide susceptibility deterministic approach using geographic information systems: application to Breaza town, Romania

The study is a deterministic-based approach on landslide susceptibility. The purpose of the paper is to create quantitative susceptibility maps by joining the one-dimension infinite slope stability model with a raster-based GIS (ILWIS) and taking into account the spatial distribution of input parameters. A landslide-prone area, with relative homogeneous geology and geomorphology, located in the Subcarpathian sector of the Prahova River, Romania, was selected for the study. There are frequent problems caused by active landslides in the studied area, especially in years with heavy precipitation, often causing destruction of houses and roads situated on the slopes (1992, 1997, and 2005). Detailed surveys covering a 7-year period provided the necessary input data on slope parameters, hydrological components, and the geotechnical background. Two simulations were used: one on dry soil conditions and one on fully saturated soil conditions. A third test was based on the level of the groundwater table mapped in summer 2008. Detailed analyses were particularly focused on landslides to compare predicted results with actual results using field measurements. The model is very suitable for use in raster GIS because it can calculate slope instability on a pixel basis, each raster cell being considered individually. The drawback of the model is the highly detailed data of input parameters. Despite this disadvantage, in conclusion, the usefulness of slope stability models on a large-scale basis was emphasized under infinitely high failure plain conditions and lithological homogeneity.

Modeling the contribution of trees to shallow landslide development in a steep, forested watershed

The objective of this study was to identify the contribution of trees to shallow landslide development in a steep forested watershed using a deterministic modeling approach. Rainfall interception, tree root reinforcement, and tree surcharge were considered the main factors. A revised version of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability (TRIGRS) model was employed in the approach. Hydrological modifications included adding the processes of rainfall interception using an application of the Rutter model. The revised infinite slope stability model was also used to consider tree root reinforcement and tree surcharge. A comparative analysis was conducted with the results simulated by TRIGRS and the revised model to quantify the contribution of trees to landslide development. The Bonghwa site in South Korea, which was damaged by an extreme storm with 228mm of rainfall on July 24–25, 2008, was selected as the study site. Data related to the local topography, soil, and forest properties were measured in the field for use in the model simulations, although some data were taken from the literature or assumed by the authors on the basis of the site characteristics. The results showed the rainfall interception did not significantly affect the amount of rainfall reaching the soil surface, but it changed the temporal distribution of the rainfall intensity. Additionally, the rainfall interception was found to have little influence on infiltration from the simulation results of pore water pressure. The results of the simulated factor of safety indicated that root reinforcement and tree surcharge made significant contributions to the enhancement of slope stability. The simulation results were compared to the results from locations in which landslides occurred, indicating that the revised model estimated the landslide susceptibility over the entire study site well, while TRIGRS appeared to overestimate the risk of shallow landslides. In conclusion, trees appeared to make a significant mechanical contribution to shallow landslide development during a severe storm event in steep, forested watersheds. Efforts to revise the existing model improved its performance to assess the shallow landslide susceptibility of mountainous watersheds despite some limitations of the current study.

Landslide model performance in a high resolution small-scale landscape

The frequency and severity of shallow landslides in New Zealand threatens life and property, both on- and off-site. The physically-based shallow landslide model LAPSUS-LS is tested for its performance in simulating shallow landslide locations induced by a high intensity rain event in a small-scale landscape. Furthermore, the effect of high resolution digital elevation models on the performance was tested. The performance of the model was optimised by calibrating different parameter values. A satisfactory result was achieved with a high resolution (1m) DEM. Landslides, however, were generally predicted lower on the slope than mapped erosion scars. This discrepancy could be due to i) inaccuracies in the DEM or in other model input data such as soil strength properties; ii) relevant processes for this environmental context that are not included in the model; or iii) the limited validity of the infinite length assumption in the infinite slope stability model embedded in the LAPSUS-LS. The trade-off between a correct prediction of landslides versus stable cells becomes increasingly worse with coarser resolutions; and model performance decreases mainly due to altering slope characteristics. The optimal parameter combinations differ per resolution. In this environmental context the 1m resolution topography resembles actual topography most closely and landslide locations are better distinguished from stable areas than for coarser resolutions. More gain in model performance could be achieved by adding landslide process complexities and parameter heterogeneity of the catchment.

Role of Vegetation on Slope Stability under Transient Unsaturated Conditions

We examine the role of vegetation on the stability of shallow soils under unsaturated transient regime. Two main positive effects of the vegetation on slope stability are discussed: i) a geo-mechanical effect, i.e., the reinforcement of soil by plant roots; ii) a soil-hydrological effect, i.e., the soil suction regime affected by root water uptake. The root distribution is assessed by an eco-hydrological model, which predicts the root density as function of local climatic conditions in growing season and soil hydrological properties. The predicted root distribution is employed for assessing the vertical variability of both the apparent soil cohesion provided by roots and the root water uptake. A one-dimensional model of vertical soil water dynamics is employed for simulating soil suction regime, assumed representative of well-drained soils on steep forested plane slopes. The geo-mechanical and the soil-hydrological effects on slope stability are examined with an infinite slope stability model, generalized for unsaturated conditions. We show that in the case of a loamy-sand soil under a Mediterranean climatic regime, the geo-mechanical effect tends to be more relevant than the soil-hydrological effect during the rainy season, within depths up to twice the average root depth.

Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

Abstract. Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope. Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a) development of a perched water table above an impeding layer, and (b) hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

비 집수면적 산정기법에 따른 사면 안정성 비교·분석

최근 기후변화에 따른 집중호우의 증가 및 무분별한 유역개발에 의한 산사태 발생빈도 및 재해복구비용이 증가하고 있는 추세이다. 본 연구에서는 2011년 7월에 발생한 서울시 우면산 지역을 대상으로 뿌리 점착력을 고려한 GIS기반의 무한사면안정모형을 이용하여 사면안정해석을 수행하였다. 무한사면안정모형의 중요 매개변수인 습윤지수의 공간분포화를 위해 비 집수면적 개념을 도입하였으며, 세가지 기법(일방향 흐름기법, 다방향 흐름기법, 무한방향 흐름기법)를 이용하여 비 집수면적을 산정하고, 각 기법에 따른 대상유역내의 격자별 사면안전율의 변화양상을 분석하였다. 또한, 기존의 무한사면안정모형을 이용한 사면안정 해석에 일반적으로 적용되고 있는 공간집중형 습윤지수 결과와의 비교를 통하여 우면산 지역의 사면안정 해석의 차이점을 비교 분석하였다. 무한사면안정모형을 이용하여 산정된 사면안전율 분석결과, 거주지 주변의 절개지 부근과 산지정상부근의 급경사지에서 불안정 지역이 집중적으로 분포하고 있음을 확인하였으며, IFD와 집중형 습윤지수에 의한 불안정지역은 유사하게 나타난 반면, SFD와 MFD에 의한 불안정지역은 앞선 두 가지기법에 비해 작게 산정되었다. There has been an increase for the landslide areas and restoration expenses due, in large part, to the increased locally heavy rains caused by recent climate change as well as the reckless development. This study carried out a slope stability analysis by the application of distributed wetness index, using the GIS-based infinite slope stability model, which took the root cohesion effect into consideration, for part of Mt. Umyeon in Seoul, where landslide occurred in July 2011, in order to compensate the defects of existing analysis method, and subsequently compared its result with the case on the exploitation of lumped wetness index. In addition, this study estimated the distributed wetness index by methodology, applying three methods of specific catchment area calculation: single flow direction (SFD), multiple flow direction (MFD), and infinity flow direction (IFD), for catchment area, one of the variables of distributed wetness indices, and finally implemented a series of comparative analysis for slope stability by methodology. The simulation results showed that most unstable areas within the study site were dominantly located in cutting-area surroundings along with the residential area and the mountaintop and unstable areas of IFD and lumped wetness index method were similar while SFD and MFD provided smaller unstable areas than the two former methods.