Landslide Cases Research Articles

Event-based rainfall warning regression model for landslide and debris flow issuing

Debris flow and landslide warnings are currently based on real-time monitoring of rainfall according to predefined warning lines. Conventionally, the rainfall variables combinations cumulative rainfall–duration (Re–D) and mean rainfall intensity–cumulative rainfall (Im–Re) for setting rainfall thresholds are used separately for landslide warning. The variables used in the regression analysis are correlated and a physical relationship Im = Re/D is available. Two-dimensional warning lines lack spatial feature and may not sufficiently reflect the rainfall characteristics required to initiate debris flows. A technical procedure using 3D regression analysis of the rainfall parameters interaction analysis was proposed. The rainfall warning regression surface is set on the basis of rainfall variables such as average rainfall intensity, effective cumulative rainfall, and duration. Here, a three-parameter, paraboloid rainfall warning regression surface generated using the variables of Im, D, and Re to determine the rainfall characteristics necessary to initiate debris flows and landslides is proposed. The proposed rainfall warning regression model reflects the rainfall characterization using a 3D diagram than the conventional threshold line. The regression results are converted in a multiple Im–D rainfall warning regression diagram containing various Re quantities for issuing landslide and debris flow warnings. Results show that the types of rainfall required to initiate debris flows and landslides include high rainfall intensity within a short duration and high cumulative rainfall over a long duration; moreover, debris flows could be affected by postseismic effects. The regression surfaces vary for rainfall events associated with different typhoons, which suggest that the initiation of landslides and debris flows is affected by the event that causes rainfall. An inclined plane surface is commonly used for describing a rainfall-induced landslide and debris flow regression surface for issuing warnings. The regression surface has parabolic geometry in postseismic landslide areas. The interactions of rainfall parameters using a three-dimensional regression analysis were studied and it was applied to the case of a catastrophic landslide and debris flow at Xiaolin Village in Taiwan.

Effect of Landslide on Energy Efficiency Chain Based Routing Protocol for Wireless Sensor Network

Wireless sensor network has been used as a landslide monitoring tool for more than one decade. The robustness of the network is important as the systems need to survive in harsh conditions. In this paper, we consider the living time of the sensor network under the influences of the small-scale landslide. We investigate the performance of famous energy-efficient routing protocol PEGASIS in both landslide case and non-landslide case. Genetic Algorithm is also applied to enhance the effectiveness of PEGASIS. The simulation results in this paper showed that the Genetic Algorithm helps to delay the first node death if it is used at the beginning of data transmission while being used every round helps to prolong last node death slightly. The impact of the Genetic Algorithm on energy usage and route length is also examined. Under the effect of landslide, with only 70% of energy are spent, the simulated protocols reduced around 30% equivalent route length while managed to keep the living time up the network up to 90.76%, comparing to cases with no landslide.

Case Study of College Veng Road Section Landslide, Aizawl, Mizoram, India

Landslide is a very common feature along highways, roads and inhabited areas, in and around Mizoram. It is one of the most problematic hazards in the region. The present case of landslide, is in the ‘College Veng’ road section. It lies in the south eastern parts of the Aizawl town. This section is situated along the Sikulpuikawn-Bethlehem Veng road. The Coordinates of the “College Veng” slide are between 23°43՛28.56՛՛/92°43՛28.28՛՛ to 23°43՛28.56՛՛/92°43՛28.34՛՛. The slide took place on 17th September, 2017, at mid night. The section had a relatively high amount of dip (48°-50°), and has a lithology comprising of Shale and Sandstone intercalation. The total length of the slide section along the road was 75 feet, with a height of 25 feet. After the critical observation of the incidence, the major aggravating factors were found to be that the heavy rainfall induced the top most shale bed to move down the dip slope. Improper sewage and subsequent mud erosion at the bottom of the shale layer, further accelerated the down slope movement of the slided block.

Assessment of depth-averaged method in analysing runout of submarine landslide

Depth-averaged method (DAM) is one of the widely used numerical methods to back analyse the post-failure deposits of submarine landslides due to its high efficiency. However, its simplifications of the velocities along the thickness of the slide cannot capture complex behaviours such as shear band propagation. A novel non-averaged method, material point method (MPM), is used to validate the DAM analysis. The runout distances and morphologies of viscous debris flows predicted by the DAM and MPM are compared with those predicted by experiments and computational fluid dynamics analyses. The ranges of the shear strength, viscosity and sensitivity parameters are investigated to determine the feasibility of the DAM. The conventional DAM algorithm specialised for no-slip bases is enhanced to reproduce the phenomenon of block sliding of slides on frictional bases by considering the stability of the front and rear faces. Then, a spreading of horsts and grabens due to shear band propagation is presented with the MPM analysis. Two real cases of submarine landslides, Southern Mediterranean slide and Finneidfjord slide, were back-analysed with the DAM and MPM.

Slip surface identification based on engineering properties analysis of weathering breccia at landslide occured in mount pawinihan, central java, indonesia

Landslide mitigation may be performed in various methods, such as by identifying the weathering degree in order to determine the position of slip surface. Slip surface is imaginary plane beneath surface dividing the moving part of slope mass with the rest, In short, it may also be defined as the weakest zone where the landslide may occur. Therefore, slip surface is the main object of this research which result may be used as a reference for further mitigation step. This research is conducted in the landslide case of Mount Pawinihan, Banjarnegara. The research is conducted by identifying the weathering degree of heterogenic material based on the British Standard EN ISO 14689-1. Engineering properties sampling was conducted after identification of weathering zone and use systematic sampling base on zone of weathering. The research result shows that the landslide soil mass under study may be divided into four weathering zones exposing on surface, while the position of slip surface may be identified in the weathering zone 3 (moderately weathered). This zone is a boundary of rock and soil condition.

Effects of river flow velocity on the formation of landslide dams

Natural dams are formed when landslides are triggered by heavy rainfall during extreme weather events in the mountainous areas of Taiwan. During landslide debris movement, two processes occur simultaneously: the movement of landslide debris from a slope onto the riverbed and the erosion of the debris under the action of high-velocity river flow. When the rate of landslide deposition in a river channel is higher than the rate of landslide debris erosion by the river flow, the landslide forms a natural dam by blocking the river channel. In this study, the effects of the rates of river flow erosion and landslide deposition (termed the erosive capacity and depositional capacity, respectively) on the formation of natural dams are quantified using a physics-based approach and are tested using a scaled physical model. We define a dimensionless velocity index vde as the ratio between the depositional capacity of landslide debris (vd) and the erosive capacity of water flow (ve). The experimental test results show that a landslide dam forms when landslide debris moves at high velocity into a river channel where the river-flow velocity is low, that is, the dimensionless velocity index vde > 54. Landslide debris will not have sufficient depositional capacity to block stream flow when the dimensionless velocity index vde < 47. The depositional capacity of a landslide can be determined from the slope angle and the friction of the sliding surface, while the erosive capacity of a dam can be determined using river flow velocity and rainfall conditions. The methodology described in this paper was applied to seven landslide dams that formed in Taiwan on 8 August 2009 during Typhoon Morakot, the Tangjiashan landslide dam case, and the Yingxiu-Wolong highway K24 landslide case. The dimensionless velocity index presented in this paper can be used before a rainstorm event occurs to determine if the formation of a landslide dam is possible.

A comprehensive framework of TDR landslide monitoring and early warning substantiated by field examples

Due to the climate change and hazardous geological environment in Taiwan, real-time landslide monitoring for safety of adjacent tribes or infrastructures is much conspicuous. Time domain reflectometry (TDR) is considered as valuable technology for continuously capturing dynamics and locations of shear deformations with high temporal and spatial coverages. In this study, a comprehensive framework was proposed by integrating up-to-date procedure of installation guide, data acquisition, sliding deformation identification, and early warning processing. The advantages of the proposed framework were then examined and substantiated via field cases. The first case is at a large colluvium slope in Lushan, central Taiwan. The colluvium is still active after heavy rainfall events, but limited evidence of sliding characteristic was collected previously by manual inclinometer logging. Therefore, the TDR framework was deployed and multiple landslide surfaces at great depths were timely observed. Movement of colluvium mass was thereby interpreted as a buckling fold. Additionally, creep occurred among the colluvium layer during the monsoon season because of strength weakening influenced by pore pressure fluctuations. Monitoring results of the second landslide case in Jufan, northern Taiwan, reported the dynamics of a thin sliding plane captured with TDR high temporal resolution. This unique behavior was further applied for devising of a novel early-warning strategy in terms of time-variation of TDR response, validating that the comprehensive framework of TDR landslide can effectively contribute to early warning.

Extension and application of Discontinuous Deformation Analysis with a damped contact spring model

Discontinuous Deformation Analysis (DDA) is widely used in geological and geotechnical engineering. To provide an alternative approach to considering damping effect in dynamic analysis, a damped contact spring model is implemented. The model assumes that the damping component – linear dashpot - takes place in joints of DDA models. The normal and shear damping forces are determined according to the relative velocities of the two contacted points. A semi-analytical solution is also proposed to calculate damping coefficient from a given damping ratio. The viscous damping effect produced by the damped contact spring model is independent to step size. The proposed model is incorporated into DDA program, and then several classic damping dynamic examples are constructed to validate the contact model, showing good agreement with analytical solutions. After that, a seismic spectrum of a recorded ground motion is analyzed to show the contact model is suitable for response spectrum generation. Finally, the Donghekou landslide case is studied under different parameters, suggesting that the proper consideration of damping is essential to natural hazard analysis.

Landslide prediction based on a combination intelligent method using the GM and ENN: two cases of landslides in the Three Gorges Reservoir, China

Through the mathematical description of landslide evolution, landslide behavior can be simply studied by the corresponding displacement time sequence. Thus, to predict landslides, a new intelligent prediction method that combines the gray system method (GM) and an evolutionary neural network (ENN) is proposed. In this method, the original displacement is divided into two components: the displacement trend and deviation sequences, which are predicted by the GM and a new ENN combined by immunized continuous ant colony optimization and modified back propagation algorithm. This new method is applied to two typical landslides in the Three Gorges Reservoir of China to show that the forecasting precision of the new method is highly accurate in these cases. For comparison with other methods (GM and ENN), the forecasting performance of the new method is analyzed in depth. The results show that the generalization prediction precision of the new method is much higher than those of the GM and ENN. Finally, the influences of the extrapolation prediction time and the prediction step for the new method are comprehensively analyzed. The results show that the lower the extrapolation prediction time and the prediction step are, the higher the extrapolation prediction precision.

Characteristics and mechanism of loess landslide induced by drill vibration

In order to reveal the disaster mechanism of loess landslide induced by rig vibration, based on the analysis of typical cases of loess landslide, the disaster process of loess landslide triggered by rig vibration was analyzed through field investigation, physical model test and stress path test. The results showed that the instability mechanism of vibration-type loess landslide was a dynamic process under the action of vibration load. This process can be summarized as follows: stable loess slope – vibration load of drilling rig – adjustment of slope stress – shear failure occurs under continuous load – slope body begins to slide after sliding surface gradually forms – landslide forms

Effects of vegetation on hydrological response of silty volcanic covers

This work examines the hydrological behaviour of a silty volcanic layer exposed to the atmosphere for 3 years under vegetated conditions. The layer was extensively monitored to measure energy fluxes, water fluxes, and internal variables (suction, water content, water storage, and temperature). Measurements were used to build representations of the layer’s behaviour patterns depending on its surface covering, comparing the behaviour in vegetated conditions with behaviour observed under bare conditions over the previous 4 years. Results show that during cold–dry periods, differences in terms of fluxes and hydrological variables between the bare and vegetated conditions reduce to negligible levels, but increase significantly during hot–dry and transition periods. As the soil forming the layer was selected to have the same intrinsic and state properties as the layer in a specific rainfall-induced landslide case history that occurred in Nocera Inferiore (South Italy) in 2005, the experimental results are used to re-interpret such a landslide, considering the effects of vegetation and referring to a coupled thermohydraulic model. The experimental results are used to calibrate the model, and this is then used to interpret around 10 years of meteorological variables recorded at the landslide site, including the landslide time. Comparison with interpretations made previously as a bare soil hypothesis shows how neglecting the effects of vegetation might imply a loss in prediction accuracy of soil state variables (suction and water storage) related to the slope stability.

Evaluating volume of coseismic landslide clusters by flow direction-based partitioning

A strong earthquake can trigger thousands of co-seismic landslides. The evaluation of the volume of such co-seismic landslides is essential for landslide risk assessment and long-term post-earthquake hazard evaluation. Empirical volume-area power laws are often applied to estimate the landslide volume. When several small landslide deposits form a large cluster on the hillslope, blurry boundaries of the clustered co-seismic landslides may lead to seemingly one large landslide and grossly overestimated landslide volume. In this paper, we propose a flow direction-based method to identify the boundaries of a cluster of landslides and to partition co-seismic landslides. Three watersheds that were severely impacted by co-seismic landslides in the Wenchuan earthquake region are chosen for case studies. Each co-seismic landslide cluster in these watersheds was interpreted from images taken shortly after the earthquake, and partitioned into individual landslides in accordance with a flow direction map that is processed based on a local digital terrain model. Finally, the volume of each individual landslide is calculated using an empirical volume-area power law. The adopted power law scaling relationship is selected from six widely used empirical relations and verified by 11 local landslide cases. The proposed flow-direction based partitioning method is further verified by clear boundaries of landslides that were exposed after storms, as well as supplementary field survey results. The proposed method results in similar landslide boundaries and volumes as the field survey results. The uncertainty of this approach is below 19%. If no partitioning is conducted, the total volume of the landslide cluster can approach twice that from the field investigations.

Effect of Rainfall Pattern on Landslide Occurrence: Focusing on Wonju-si and Chuncheon-si Area

산사태는 국토 황폐화의 원인인 동시에 국민의 재산과 생명을 위협하는 자연재해이다. 우리나라는 국토의 70% 이상이 산지지형이며 산지에 근접한 주거형태로 인해 산사태의 위험성이 높다. 원주시와 춘천시는, 강원도 지역의 도심지임에도 불구하고, 군사지역을 제외하면 산사태 위험지역에 속한다. 2011년의 경우, 원주시가 여름철 총강우량과 집중호우의 발생횟수가 춘천시보다 많았음에도 불구하고 춘천시에 더 많은 산사태 피해가 발생했다. 이 연구에서는 2010년, 2011년, 2013년 원주시와 춘천시의 산사태 사례를 대상으로 강우패턴과 산사태 발생과의 연관성을 로지스틱 회귀분석을 이용해 분석했다. 그 결과, 두 지역 모두 집중호우가 2시간 연속적으로 관측되었을 때 대부분 산사태가 발생했다. 또한 24시간 누적강우량에 비해 집중호우의 발생이 산사태에 더 민감하게 나타났다. 통계적으로 산사태의 발생 가능성은 집중호우가 연속될 경우에 약 4.64배, 24시간 누적강우량이 증가할수록 약 1.04배로 각각 증가하는 것으로 조사되었다. 이에 따라 두 지역의 집중호우의 연속 관측시간과 24시간 누적강우량이 산사태 발생에 미치는 핵심요인임을 알 수 있었다.Landslide is one of natural disasters that cause land degradation and threaten people s lives and property. In Korea, more than 70% of the land is mountainous, and there is a high risk of landslides due to the residential form close to mountainous areas. Although Wonju-si and Chuncheon-si are urban areas in Gangwon province, except for military areas, they belong to landslide hazard area. In 2011, despite the fact that the total number of severe rain storm and heavy rainfall during summer in Wonju-si was higher than that in Chuncheon-si, more landslide damage occurred in Chuncheon-si. In this study, the correlation between rainfall pattern and landslide occurrence was analyzed using logistic regression analysis for landslide cases of Wonju-si and Chuncheon-si in 2010, 2011 and 2013. As a result, landslides occurred when the severe rain storm was observed continuously for more than 2 hours in both areas. Also, severe rain storm was more sensitive to landslide than 24 hour cumulative rainfall. The possibility of landslide was statistically analyzed to be about 4.64 times when the severe rain storm were continuous and about 1.04 times when the accumulated rainfall of 24 hour increased. Accordingly, it was found that the effects of continuous observation time of severe rain storm and accumulated rainfall of 24 hours on landslide occurrence were important in both areas.

Settlements and slides: a large landslide case study from the Central Cordillera of the Philippines

The Central Cordillera of Luzon in the Philippines is home to some of the most complex geology, active plate margin tectonism, heaviest rainfall and steepest terrain in the world. It also hosts a thriving agricultural community that has developed its agrarian, municipal and transport infrastructure in a landscape of marginal stability and extreme geomorphological sensitivity. The village of Pilando occupies a saddle on a prominent ridge where it is crossed by the Halsema Highway. As a result of landslide displacements, both the highway and the village have been subsiding for several decades and many dwellings have had to be abandoned. From topographical survey and visual observation, average rates of settlement vary between c. 0.1 and 0.4 m a −1 . The apparent depth and areal extent of ground movement are such that attempts to stabilize the area would be both impracticable and uneconomic. Realignment and relocation are options that might be considered but many adjacent slopes are unstable or have failed in the past and those that have not are highly sensitive to earthworks and drainage disturbance. Unfortunately, there are many areas of the Central Cordillera that are affected by similar slope instability problems. The interpretation of satellite imagery available on Google Earth, supported by geomorphological field observation, can assist in the delineation and assessment of these notably unstable areas for land use planning and slope management purposes.

Regional Rainfall Warning System for Landslides with Creep Deformation in Three Gorges using a Statistical Black Box Model

Establishing an efficient regional landslide rainfall warning system plays an important role in landslide prevention. To forecast the performance of landslides with creep deformation at a regional scale, a black box model based on statistical analysis was proposed and was applied to Yunyang County in the Three Gorges Reservoir area (TGRA), China. The data samples were selected according to the characteristics of the landslide displacement monitoring data. Then, the rainfall criteria applied to different time periods were determined by correlation analysis between rainfall events and landslides and by numerical simulation on landslide movement under certain rainfall conditions. The cumulative rainfall thresholds that were determined relied on the displacement ratio model, which considered landslide scale characteristics and the statistical relationship between daily rainfall data and monthly displacement data. These thresholds were then applied to a warning system to determine a five-level warning partition of landslides with creep deformation in Yunyang County. Finally, landslide cases and displacement monitoring data were used to validate the accuracy of the model. The validation procedure showed that the warning results of the model fit well with actual conditions and that this model could provide the basis for early warning of landslides with creep deformation.

Determination of the Probabilities of Landslide Events—A Case Study of Bhutan

Landslides have been and are prominent and devastating natural disasters in Bhutan due to its orography and intense monsoonal rainfall. The damage caused by landslides is huge, causing significant loss of lives, damage to infrastructure and loss of agricultural land. Several methods have been developed to understand the relationship between rainfall and landslide incidences. The most common method to understand the relationship is by defining thresholds using empirical methods which are expressed in either intensity-duration or event rainfall-duration terms. However, such thresholds determine the results in a binary form which may not be useful for landslide cases. Apart from defining thresholds, it is significant to validate the results. The article attempts to address both these issues by adopting a probabilistic approach and validating the results. The region of interest is the Chukha region located along the Phuentsholing-Thimphu Highway, which is a significant trade route between neighbouring countries and the national capital Thimphu. In the present study, probabilities are determined by Bayes’ theorem considering rainfall and landslide data from 2004 to 2014. Singular (rainfall intensity, rainfall duration and event rainfall) along with a combination (rainfall intensity and rainfall duration) of precipitation parameters were considered to determine the probabilities for landslide events. A sensitivity analysis was performed to verify the determined probabilities. The results depict that a combination of rainfall parameters is a better indicator to forecast landslides as compared to single rainfall parameter. Finally, the probabilities are validated using landslide records for 2015 using a threat score. The validation signifies that the probabilities can be used as the first line of action for an operational landslide warning system.

Zastosowanie bezzałogowego statku latającego (UAV) w monitoringu powierzchniowym ruchów masowych na przykładzie osuwiska w Kasince Małej (Beskid Wyspowy, Zewnętrzne Karpaty Zachodnie)

The application an unnamed aerial vehicle (UAV) in landslides surface monitoring – case study of the Kasinka Mala landslide (Beskid Wyspowy Mts., Outer Carpathians Mts.). A b s t r a c t. Landslide monitoring is applied in case of a hazard for existing infrastructure located on hazardous landslide. It is the exact case of the Kasinka Ma³a landslide in the Outher Carpathians which causes a danger for the surrounding infrastructure. In order to measure the terrain deformations caused by landslide movements, the unnamed aerial vehicle equipped with a non-metric camera has been used. As a result of processing of aerial photos, orthophotomaps as well as digital elevation models have been produced. It enabled providing information about vertical and horizontal displacements caused by the landslide. The results of analysis shows that the mass movements occur at a different pace, but also that there are stable areas in the landslide. The application of UAV photogrammetry for landslide monitoring allows getting the information about the displacements in the unvegetated areas.

Sentinel-1 SAR Amplitude Imagery for Rapid Landslide Detection

Despite landslides impact the society worldwide every day, landslide information is inhomogeneous and lacking. When landslides occur in remote areas or where the availability of optical images is rare due to cloud persistence, they might remain unknown, or unnoticed for long time, preventing studies and hampering civil protection operations. The unprecedented availability of SAR C-band images provided by the Sentinel-1 constellation offers the opportunity to propose new solutions to detect landslides events. In this work, we perform a systematic assessment of Sentinel-1 SAR C-band images acquired before and after known events. We present the results of a pilot study on 32 worldwide cases of rapid landslides entailing different types, sizes, slope expositions, as well as pre-existing land cover, triggering factors and climatic regimes. Results show that in about eighty-four percent of the cases, changes caused by landslides on SAR amplitudes are unambiguous, whereas only in about thirteen percent of the cases there is no evidence. On the other hand, the signal does not allow for a systematic use to produce inventories because only in 8 cases, a delineation of the landslide borders (i.e., mapping) can be manually attempted. In a few cases, cascade multi-hazard (e.g., floods caused by landslides) and evidences of extreme triggering factors (e.g., strong earthquakes or very rapid snow melting) were detected. The method promises to increase the availability of information on landslides at different spatial and temporal scales with benefits for event magnitude assessment during weather-related emergencies, model tuning, and landslide forecast model validation, in particular when accurate mapping is not required.

Two methodologies to calibrate landslide runout models

Extremely rapid, flow-like landslides pose a significant hazard worldwide; however, the analysis of the impact area and velocity of these flows is not routine. Semi-empirical numerical models are one tool that is available for performing this sort of analysis. These models are physically based; however, certain input parameters are determined through model calibration, using back-analysis of real landslide cases. Objective, repeatable calibration methods are needed for this approach to be useful for landslide runout prediction. The present analysis describes the application of optimization theory and Bayesian statistics to calibrate these types of models. Two complementary methods are presented. The first uses the Gauss-Marquardt-Levenberg optimization algorithm to efficiently determine a set of best-fit calibrated model parameters. The second uses a posterior analysis to quantify errors associated with parameter calibration, which can then be used for probabilistic forward analysis. Three case histories are presented to demonstrate how the new methods are able to rapidly calibrate a runout model, reduce subjectivity inherent in the calibration process, and provide information on parameter uncertainty.

복합재해 영향을 고려한 산불 후 산사태 잠재적 피해 위험도 분석

Compound disaster is the type that increases the impact affected by two or more hazard events, and attention to compound disaster and multi-hazards risk is growing due to potential damages which are difficult to predict. The objective of this study is to analyze the possible impacts of post-fire landslide scenario quantitatively by using TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis), a physics-based landslide model. In the case of wildfire, soil organic material and density are altered, and saturated hydraulic conductivity decrease because of soil exposed to high temperature. We have included the change of soil saturated hydraulic conductivity into the TRIGRS model through literature review. For a case study, we selected the area of 8km2 in Pyeongchang County. The landslide modeling process was calibrated before simulate the post-wildfire impact based on landslide inventory data to reduce uncertainty. As a result, the mean of the total factor of safety values in the case of landslide was 2.641 when rainfall duration is 1 hour with rainfall intensity of 100mm per day, while the mean value for the case of post-wildfire landslide was lower to 2.579, showing potential landslide occurrence areas appear more quickly in the compound disaster scenario. This study can be used to prevent potential losses caused by the compound disaster such as post-wildfire debris flow or landslides.