Landslide Behavior Research Articles

Correction to: Evolution of hydro‑mechanical behaviours and its influence on slope stability for a post‑earthquake landslide: implications for prolonged landslide activity

There has been considerable research on the prolonged effects and evolution of post-earthquake landslides, as they are of significance for disaster relief and rebuilding plans in earthquake-impacted regions. There is a need to better quantify these prolonged effects and evolution based on the hydro-mechanical mechanisms of post-earthquake landslides. This study investigated the evolution of the hydro-mechanical behaviour and parameters of a single landslide by integrating experimental and theoretical analyses. Analyses were undertaken using a time series of in situ monitoring data over five hydrological years on a single landslide site in the Baisha River basin of Dujiangyan, in the Wenchuan earthquake region, China. Results indicated a linear increase in the angle of internal friction under prolonged effects, while soil cohesion decreased non-linearly, gradually approaching a lower limit. The saturated hydraulic conductivity ( $${K}_{s}$$ ) increased, and the soil residual water content ( $${\theta }_{r}$$ ) evolution curve conformed to the Boltzmann function distribution model. The soil–water characteristic curve parameters gradually increased. Based on the hydro-mechanical parameter evolution, the spatiotemporal decay of the landslide over the next decade under extreme rainfall conditions was predicted using the rainfall slope stability models and TRIGRS. This paper proposed a mechanistic explanation for the prolonged effects of a post-earthquake landslide in response to rainfall. Furthermore, it provided a reliable theoretical basis for the early warning and prevention of such landslides.

Landslide tsunamis: Comparison between depth-averaged and Navier–Stokes models

Two approaches are proposed to simulate tsunamis generated by granular landslides: a depth-averaged model, AVALANCHE, and laminar Navier–Stokes simulations using the OpenFOAM model. Both models are validated against two 2D benchmarks, a subaerial and a submerged one involving a triangle initial slide shape. In both models, the landslide is defined as a viscous fluid flowing downslope. Except in the first instants, both models can reproduce either the landslide behavior or the generated first water waves but cannot reproduce simultaneously both the landslide and the water surface. There is an overlap in the optimal viscosity range between both models. Sensitivity studies are carried out by varying the slope angle and the landslide submergence for the subaerial benchmark. The largest waves are obtained for initial landslide position close to the free surface. The height of the generated waves increases linearly with the slope angle and the landslide Reynolds number in the depth-averaged model. The relationships are more complex in the Navier–Stokes model. For low slide Reynolds numbers and with an initial slide close to the free surface, both models produce similar waves. Nine additional cases are performed with a k−ε turbulence closure model and varying the submergence and the slope angle.

The Role of Satellite InSAR for Landslide Forecasting: Limitations and Openings

The paper explores the potential of the satellite advanced differential synthetic aperture radar interferometry (A-DInSAR) technique for the identification of impending slope failure. The advantages and limitations of satellite InSAR in monitoring pre-failure landslide behaviour are addressed in five different case histories back-analysed using data acquired by different satellite missions: Montescaglioso landslide (2013, Italy), Scillato landslide (2015, Italy), Bingham Canyon Mine landslide (2013, UT, USA), Big Sur landslide (2017, CA, USA) and Xinmo landslide (2017, China). This paper aimed at providing a contribution to improve the knowledge within the subject area of landslide forecasting using monitoring data, in particular exploring the suitability of satellite InSAR for spatial and temporal prediction of large landslides. The study confirmed that satellite InSAR can be successful in the early detection of slopes prone to collapse; its limitations due to phase aliasing and low sampling frequency are also underlined. According to the results, we propose a novel landslide predictability classification discerning five different levels of predictability by satellite InSAR. Finally, the big step forward made for landslide forecasting applications since the beginning of the first SAR systems (ERS and Envisat) is shown, highlighting that future perspectives are encouraging thanks to the expected improvement of upcoming satellite missions that could highly increase the capability to monitor landslides’ pre-failure behaviour.

Reduction of natural disaster in Bulgaria by adopting DInSAR as a landslide monitoring approach

1. Extended abstractMonitoring the actual behavior of landslides is essential for assessing and predicting the risk of disaster. However, since the target area is usually huge, monitoring has not often been conducted due to technical difficulties and cost problem.Synthetic Aperture Radar (SAR) is a high-resolution radar device that is mounted on an artificial satellite. It transmits pulse waves to the Earth’s surface and receives the reflections. Differential Interferometric SAR (DInSAR) is a technique for detecting the displacements of the Earth’s surface using SAR data and it has the potential to be an efficient, effective, and economical method for monitoring the landslide behavior in extensive areas. The great advantage of DInSAR is that it can monitor huge areas without the use of any sensors on the ground surface.The author is now conducting a project of application of DInSAR to monitor the landslide behavior in the northern Black Sea coast in Bulgaria as an international collaboration with Bulgaria, Japan, Indonesia and Croatia by members of ISRM.The distribution maps and the time-transition of the displacements in that area were obtained over a period of six years starting in 2014. DInSAR was able to detect the typical landslide behavior in northern Black Sea coast. The results agreed well with the actual behavior described in the Bulgarian official report of landslides. This study can suggest that DInSAR will be a useful tool for long-term continuous landslide monitoring in the northern Black Sea coast. The SAR application project will continue.

Application of SBAS-DInSAR to monitoring landslides along the northern Black Sea coast in Bulgaria

The Black Sea coast of Bulgaria is well known as an active landslide area across which various landslides extend. Monitoring the real behavior of landslides has not often been conducted due to technical difficulties and cost issues, although it is essential to reveal the mechanism of these landslides and to solve the problems they cause. In this paper, SBAS-DInSAR is applied to monitor the landslide displacements along the northern Black Sea coast. The results are compared with the field observation results described in the official annual reports of landslides issued in Bulgaria and other published papers. It is found that the SBAS-DInSAR results show a good agreement with the actual behavior and verify its applicability for monitoring landslides in extensive areas along the northern Black Sea coast.

Machine learning driven landslide susceptibility prediction for the Uttarkashi region of Uttarakhand in India

ABSTRACT A landslip is derived from nature and sometimes caused by human activities that endanger humanity and habitation. This work focuses on landslide behaviour for sustainable landslide mitigation and susceptibility analysis. The current research aims to evaluate three state-of-the-art machine learning techniques including, Random Forest (RF), Backpropagation Neural Network (BPNN), and Bayesian Network (BN), to predict the landslide susceptibility for the Uttarakashi district, Uttarakhand (India). For this purpose, a total of 554 landslide locations and eleven influencing factors were integrated to construct a landslide susceptibility map. The landslide inventory data were separated into training and testing sets. The receiver operating characteristic (ROC) with other statistical metrics, including sensitivity, specificity, precision, recall, and accuracy, was applied to compare the performance of machine learning techniques. The results indicated that the area under the curve (AUC) value for the RF model (AUC=0.89) is high. Furthermore, our findings showed that the RF model performs the best among all the other models with the highest training and testing accuracy, 96% and 86%, respectively. The final landslide susceptibility map is grouped into three classes, i.e. Low, Moderate, and High. The study outcome would provide support to disaster management officials in effective decision-making to prioritise necessary actions.

When hazard avoidance is not an option: lessons learned from monitoring the postdisaster Oso landslide, USA

On 22 March 2014, a massive, catastrophic landslide occurred near Oso, Washington, USA, sweeping more than 1 km across the adjacent valley flats and killing 43 people. For the following 5 weeks, hundreds of workers engaged in an exhaustive search, rescue, and recovery effort directly in the landslide runout path. These workers could not avoid the risks posed by additional large-scale slope collapses. In an effort to ensure worker safety, multiple agencies cooperated to swiftly deploy a monitoring and alerting system consisting of sensors, automated data processing and web-based display, along with defined communication protocols and clear calls to action for emergency management and search personnel. Guided by the principle that an accelerating landslide poses a greater threat than a steadily moving or stationary mass, the system was designed to detect ground motion and vibration using complementary monitoring techniques. Near real-time information was provided by continuous GPS, seismometers/geophones, and extensometers. This information was augmented by repeat-assessment techniques such as terrestrial and aerial laser scanning and time-lapse photography. Fortunately, no major additional landsliding occurred. However, we did detect small headscarp failures as well as slow movement of the remaining landslide mass with the monitoring system. This was an exceptional response situation and the lessons learned are applicable to other landslide disaster crises. They underscore the need for cogent landslide expertise and ready-to-deploy monitoring equipment, the value of using redundant monitoring techniques with distinct goals, the benefit of clearly defined communication protocols, and the importance of continued research into forecasting landslide behavior to allow timely warning.

Identification, Monitoring, and Assessment of an Active Landslide in Tavan-Hauthao, Sapa, Laocai, Vietnam – A Multidisciplinary Approach

The active landslide located in the Tavan-Hauthao, Sapa district, Laocai province, Vietnam was investigated using geophysical methods (2D Electrical Resistivity and Tomography), geotechnical investigations, and a ground survey to assess the geologic condition of the sliding block and surrounding ground. Landslide displacement was measured using 15 surface monitoring points. Numerical modeling was done to assess the behavior of an active landslide. This multi-disciplinary approach helped in interpreting landslide stratigraphy, geotechnical characteristics of the sliding groundmass, depth, and nature of the sliding plane. The surface area of the slide is approximately 1200 m2. Studying this active landslide is important as it affects the road No. 152, which is an important road connecting the Sapa Ancient Rock Field. This study involved surface topographical survey, surface and sub-surface geological, and geotechnical investigations including Standard Penetration Test and Electrical Resistivity Tomography. Geologic and geotechnical data were used to characterize an active landslide block, which is composed of different soil layers underlaid by granitic rock. The surface electrical-resistivity measurements across the Sapa landslide resulted in inverted-resistivity sections with distinct resistivity contrasts that correlated well with the geology and geo-hydrology observed in boreholes.

Rigorous Analysis of Stress-Dependent Landslide Movements with Groundwater Fluctuations Applicable to Disaster Prevention in Monsoon Asia

In this study, novel finite element approaches are proposed for numerical analysis of stress-dependent landslide movement with groundwater fluctuation by rainfall. Two new constitutive parameters that are capable of directly controlling the relationship between the apparent factor of safety and sliding velocity are incorporated into a specific material formulation used in finite element analysis for the first time. For the numerical simulation of the measured time history of the sliding displacement caused by the groundwater fluctuations, such required analytical parameters can also approximately be determined by back analysis. The proposed models are applied to a landslide field experiment on a natural slope caused by rainfall in real time in Futtsu City, Chiba Prefecture of Japan to check its applicability. The predicted and measured time histories along the horizontal direction on the upper, middle, and lower slope are compared. In addition, the deformation pattern, shear strain pattern, and possible failure mechanisms of the natural slope of such a field experiment landslide are discussed in detail based on the analysis results of the finite element method (FEM)-based numerical simulation. Moreover, the creeping landslides and possible landslide sites for further application of the proposed models are briefly discussed in the cases of Nepal and Japan as examples in Asia. It is believed that the proposed newly developed numerical models will help in understanding the secondary creep behavior of landslides triggered by extreme rainfall, and at the same time, long-term management of such landslides will be much easier in monsoon Asia. Finally, it is expected that this study will be extended for simulation of the tertiary creep behavior of landslides induced by rainfall in the near future.

Monitoring and Data Analysis in Small-Scale Landslide Physical Model

Physical modeling of landslides using scaled landslide models began in the 1970s in Japan at scaled natural slope physical models. Laboratory experiments of landslide behavior in scaled physical models (also known as flume or flume test) started in the 1980s and 1990s in Canada, Japan, and Australia under 1 g conditions. The main purpose of the landslide physical modeling in the last 25 years was research of initiation, motion, and accumulation of fast flow-like landslides caused by infiltration of water in a slope. In October 2018, at the Faculty of Civil Engineering University of Rijeka, started a four-year research project “Physical modeling of landslide remediation constructions’ behavior under static and seismic actions” funded by the Croatian Science Foundation. This paper presents an overview of the methods and monitoring equipment used in the physical models of a sandy slope exposed to artificial rainfall. Landslide development was monitored by observation of volumetric water content and acceleration as well as by observations of surface displacement by means of high-speed stereo cameras, terrestrial laser scanning, and structure-from-motion photogrammetry. Some of the preliminary results of the initial series of experiments are presented, and advantages and disadvantages of the used equipment are discussed.

UAV photogrammetry-based remote sensing and preliminary assessment of the behavior of a landslide in Guizhou, China

Unmanned Aerial Vehicle (UAV) technique has been widely utilized in geohazards assessment. In this work, the effectiveness of the UAV photogrammetry in the remote sensing and assessment of the landslide behavior is demonstrated through a case study of a landslide that occurred in Guizhou, China on 10 June 2018. The post-landslide assessments were conducted through a field investigation by a team of experts; and, two UAV photogrammetry-based surveys were carried out. On the basis of a detailed inspection of the high-resolution aerial photographs collected from the UAV photogrammetry and historical satellite imagery, subsurface stratigraphic configuration revealed from borehole explorations and the local rainfall data collected, the failure mechanism of this landslide is investigated. The occurrence of this landslide is probably attributed to the combined influence of the long-term rainfall and the engineering activities at this site. An automatic landslide cracks recognition model, which is based on the deep learning-based image recognition technique of RetinaNet, is further developed to map the cracks at the landslide site. The effectiveness of this automatic crack recognition model is validated through quantitative comparisons between the landslide cracks recognized and the field survey results. Based upon the landslide cracks identified on two different dates after this landslide event (by the field survey and automatic crack recognition model) and the subsurface displacement revealed from a drilled hole, the evolution behavior of this landslide is analyzed. The results show that the stability of this landslide was not achieved during the first slide in June 2018 and the limit of the landslide was increased much from June to November 2018. In such a situation, the elements at risk in the zones that are potentially impacted by this landslide are identified (with the aid of the UAV images collected), and a preliminary consequence assessment is conducted.

On the rainfall induced deep-seated and shallow landslide hazard in Taiwan

Abstract Due to vibrant tectonic activity in the Taiwan area, the rock formations are highly fractured. The weathered formations or colluviums are susceptible to landslides due to the dynamic change in river morphology. The impact of climate change makes the landslide hazard more significant over the past decade. Focusing on the slate formation region in the upstreams of the Tachia River, Wu River, and Chuoshui River in Taiwan, this study explored the behavior of deep-seated and shallow landslides. In order to more accurately distinguish the deep-seated and shallow landslides, this study adopts the SHALSTAB model with the consideration of slope angle. And then, based on the classified deep-seated and shallow landslide inventories, the landslide susceptibility models, i.e., Logistic Regression and Support Vector Machine models, were created. These susceptibility models were developed for different watershed and in different scales; their performances were evaluated and compared, including the AUC values and the control factor weightings. A random sampling logic was proposed to increase the analysis efficiency, and results show a promising performance. The developed models in this study can more properly and efficiently generate susceptibility maps for landslide hazard assessment and mitigation.

The dendrogeomorphic spatio-temporal reconstruction of flow-like landslides activity in one of the most susceptible region of Central Europe (the Vsetínské vrchy Mts.)

Flow-like landslides are a dangerous landslide type. They often express gradual movement or seeming dormancy, but occasional reactivation can, in extreme cases, result in catastrophic events. To predict their future behaviour, knowledge of past spatio-temporal development and relationships with hydrometeorological triggers is crucial. Moreover, regional data are more robust than case studies. Dendrogeomorphic (tree-ring-based) methods are a very precise approach for reconstructing past landslide behaviour. Nevertheless, regional reconstructions are very rare, which is probably due to their time-consuming procedures. This paper presents the results of a regional tree-ring-based reconstruction of the spatio-temporal development of flow-like landslides in a selected region in the Outer Western Carpathians. Six selected landslides were studied via analysis of 614 increment cores that came from 307 disturbed trees. The reconstruction provided data for approximately 70 individual landslide reactivation phases that were distributed in 44 event years. Events with regional extension (at least half of the studied landslides were active) were detected in six years (1940, 1941, 1953, 1961, 1985, and 1997). Periods of increased (1950s, 1990s) as well as decreased (1940s, 1970s, 2010s) landslide activity were reconstructed. The use of tree-ring data enabled the construction of landslide probability maps. Based on this analysis, all studied landslides exhibit extremely high probabilities of reactivation during a temporal horizon of 100 years, but even over shorter periods (5 and 20 years), their probability of reactivation is very high. Finally, analysis of meteorological triggers suggests the positive effect of precipitation in May (and possibly in September) to activate landslides with regional extent. Extreme short-duration (1-day) precipitation events probably do not play a role in landslide triggering. Moreover, gradual increases in precipitation totals during periods of at least one-half year preceding the event years were detected.

When image correlation is needed: Unravelling the complex dynamics of a slow-moving landslide in the tropics with dense radar and optical time series

Slow-moving landslides exhibit persistent but non-uniform motion at low rates which makes them exceptional natural laboratories to study the mechanisms that control the dynamics of unstable hillslopes. Here we leverage 4.5+ years of satellite-based radar and optical remote sensing data to quantify the kinematics of a slow-moving landslide in the tropical rural environment of the Kivu Rift, with unprecedented high spatial and temporal resolution. We measure landslide motion using sub-pixel image correlation methods and invert these data into dense time series that capture weekly to multi-year changes in landslide kinematics. We cross-validate and compare our satellite-based results with very-high-resolution Unoccupied Aircraft System topographic datasets, and explore how rainfall, simulated pore-water pressure, and nearby earthquakes control the overall landslide behaviour. The landslide exhibited seasonal and multi-year velocity variations that varied across the landslide kinematic units. While rainfall-induced changes in pore-water pressure exerts a primary control on the landslide motion, these alone cannot explain the observed variability in landslide behaviour. We suggest instead that the observed landslide kinematics result from internal landslide dynamics, such as extension, compression, material redistribution, and interactions within and between kinematic units. Our study provides, a rare, detailed overview of the deformation pattern of a landslide located in a tropical environment. In addition, our work highlights the viability of sub-pixel image correlation with long time series of radar-amplitude data to quantify surface deformation in tropical environments where optical data is limited by persistent cloud cover and emphasize the importance of exploiting synergies between multiple types of data to capture the complex kinematic pattern of landslides.

A multidisciplinary investigation of deep-seated landslide reactivation triggered by an extreme rainfall event: a case study of the Monesi di Mendatica landslide, Ligurian Alps

In November 2016, an extreme rainfall event affected the Ligurian Alps (NW Italy). Consequently, several landslides and debris flows occurred in the upper Tanarello stream basin. In particular, the village of Monesi di Mendatica was severely damaged by two landslide phenomena: the activation of a rotational landslide, which caused the total collapse of two buildings and part of the main road, and the reactivation of a deep-seated planar massive and a complex landslide, which widely fractured most of the buildings in the village. The latter phenomenon was mostly unknown and had never been monitored prior to the 2016 event. Due to the extensive damage, the village of Monesi was completely evacuated, and the road connecting a ski resort area in the upper part of the valley was closed. Furthermore, a potentially dangerous situation related to the eventual progressive evolution of this landslide that could cause a temporary occlusion of the Tanarello stream still remains. For this reason, we defined the landslide behaviour, triggering conditions and chronological evolution leading to the 2016 event using a multidisciplinary approach. This approach consisted of field surveys, satellite DInSAR time series analyses, digital image correlation techniques, rainfall records analyses, postevent monitoring campaigns and subsurface investigation data analyses, and numerical modelling. This multidisciplinary approach enhanced our understanding of this landslide, which is fundamental to better comprehend its behaviour and possible evolution.

Recharge response and kinematics of an unusual earthflow in Liechtenstein

Understanding landslide behavior over medium and long timescales is crucial for predicting landslide hazard and constructing accurate landscape evolution models. The behavior of landslides in soil that undergo periodic displacements, termed earthflows or compound soil slides, is especially difficult to forecast at these timescales. This is because velocities can increase by orders of magnitude over annual to decadal timescales, due to processes such as changing recharge conditions, erosion of the landslide toe, and retrogression of the landslide head. In this paper, we provide a detailed analysis of the Schlucher landslide, an unusual earthflow that is perched above the village of Malbun, Liechtenstein. This landslide had been displacing by 10 to 20 cm/year until 2015, when displacements on the order of 2 m/year occurred from 2016 to 2018. These large displacements damaged landslide mitigation measures, caused numerous surface deformation features, and threatened the local population downstream of the earthflow. This landslide has an unusually long monitoring record, with accurate displacement and climatic data available since 1983. We analyze this nearly 40-year monitoring time series to estimate recharge from snowmelt and rainfall, and its correlation with displacement. We also analyze recently collected, high-resolution surface and subsurface data in order to understand landslide response to recharge, landslide kinematics through time, and catastrophic failure potential. We find that interannual displacements can be explained with variations in recharge; however, periodic surges with recurrence times of tens of years must be explained by other mechanisms. In particular, recharge into the landslide during the recent acceleration (2016 to 2018) was not anomalously high. Instead, we argue that loss of internal strength is responsible for this recent acceleration period, and that this mechanism should be considered when forecasting the surge potential for certain earthflows and soil slides.

The age-dependent sensitivity of Picea abies (L.) H. Karst. to landslide movements

Dendrogeomorphic dating of past landslide events is a valuable tool for the assessment of landslide activity, providing unique data for the analysis of triggers or the modelling of landslide behaviour in the future. Unfortunately, tree-ring-based methods as well as dating approaches suffer from some limitations. One of the less frequently addressed limits of dendrogeomorphic analysis concerns the changing capacity of trees to record landslide events in their tree-ring series with increasing age. This study uses, to date, the most extensive database of tree-ring series (1736) of 868 disturbed individuals of Picea abies (L.) H. Karst. subjected to 20 landslides in the Outer Wester Carpathians for the assessment of their age-dependent sensitivity. The distribution of the total number of 1485 growth disturbances (reaction wood - RW and abrupt growth suppression - GS) throughout all decades of tree life shows evidence of distinct changes in the capacity for trees to record landslide signals with increasing age. The occurrence of RW dominated in the juvenile decades of tree life and then increased again in the 9th decade. The frequency of GS gradually increased and culminated during the 7th and 8th decades. The two intensities of growth disturbance (strong and moderate) expressed temporally balanced ratios, suggesting an effect of disturbance intensity rather than changing tree age. The important factors controlling age-dependent tree sensitivity to landslide movements based on the results seem to be changing stem elasticity, decreasing annual increment rates, root system development and increasing tree body weight. Moreover, this study demonstrates that landslide type (e.g., rigid block vs. plastic flow-like landslides) and bedrock geology distinctly modify age-dependent sensitivity that should be taken into account during the sampling of trees for landslide dating.

BFTS - Engineering geologists' field station to study reservoir landslides

Abstract Accurate characterization and assessment of complex landslide behaviors represent a major challenge. The engineering geologist usually relies on analytical solutions, numerical simulation, and model testing for such evaluations. In recent years, in-situ experimental and monitoring platforms have become increasingly popular for studying landslide behaviors; they provide more reliable data and complement traditional evaluation methods. The impoundment of the 660 km long reservoir behind the Three Gorges Dam has initiated or reactivated thousands of landslides in the greater reservoir region. To study the long-term landslide behaviors during the Three Gorges Reservoir (TGR) operation, a field test station, known as the Badong Field Test Site (BFTS), was constructed at the site of the Huangtupo landslide that reactivated in the TGR Area (TGRA). BFTS is an engineering geologist's field station to study landslides, especially those in the TGRA. This article introduces BFTS from multiple perspectives, including its primary purposes, the facilities and research activities at BFTS, the role of BFTS in the prevention and mitigation of landslides in the TGRA, and the educational functions of BFTS.

Postfailure Characterization of Shallow Landslides Using the Material Point Method

Although the mechanisms of slope failure caused by rising groundwater have been widely investigated, the kinematic behavior of landslides in the postfailure stage, which contains essential information for hazard mitigation and risk assessment, has not yet been fully studied. Thus, in this study, a series of numerical simulations using the material point method (MPM) were conducted to analyze the kinematic behavior and soil movement of shallow landslides (infinite slope problems). First, the proposed MPM formulation was validated in a full-scale landslide flume test. The simulated results of final slope profile, runout distance, deposit height, shear band development, slope displacement, and velocity accorded with the experimental results, suggesting that the MPM can quantitatively simulate large deformations. A parametric study of shallow slopes with various hydrological conditions and soil hydraulic and soil mechanical parameters was then performed to assess the influence of the aforementioned factors on landslide kinematics. The simulation results indicated that mechanical behavior at the slope toe is complex; the multiple plastic shear bands generated at the slope toe were due to a combination of shearing and compression. The deposition profile of the slopes was significantly influenced by all input parameters. Among the aforementioned parameters, soil cohesion, location of the groundwater table, and saturated soil permeability most greatly affected runout distance in the sensitivity assessment. Soil friction angle had a minor influence on the kinematic behavior of the slope.

Identification of Construction Failures Due to Landslide Using Resistivity Methods on Kayulangi - Tarengge Km 531 + 600 Road

Landslides are one of the natural indication of equilibrium their morphological forms, mass transfer in landslide countermeasures. Various research methods can be carried out both in general and detail. causes of landslides. The purpose of conducting the research is to identify the behavior of landslides in terms of soil / rock layers and groundwater availability with the aim of identifying potential indication of construction failure. Based on the results of the research, the landslide on the north side of KM 531 + 600 based on the results of the field identification shows that the landslide material is in the form of sandy clay with the type of landslide is creeping with a maximum landslide depth of 3m and a slope length of 30m. Recommended treatment is the construction of a retaining wall with a distance of at least 3m from the shoulder of the road combined with the arrangement of surface water flow drainage on slopes. The retaining wall is equipped with a pipe to drain groundwater with a pipe diameter of at least 2 inches and a maximum space between the pipes of 1m, and on the KM 531 + 600 drainage channel it is necessary to carry out construction rehabilitation and equipped with a sediment pond and channel construction designed to reduce flow speed Surface water.