Strength softening models of soil and its application in rainfall-induced landslide simulation

In this study, strength softening models are developed for exploring rainfall-induced landslide mechanism based on Mohr Coulomb strength theory with both saturation degree and temporal evolution into consideration. According to the ratio of two time scales available, the model can be classified into three categories, i.e., instant softening model, delay softening model, and coupling softening model. Corresponding evolution functions are specified to represent these kinds of softening processes and then applied to simulate landslide of homogeneous slopes triggered by rainfall, therefrom, useful conclusions can be drawn in the end.

Examination of Rainfall-Induced Landslide Failure Mechanisms via a Centrifuge Physical Simulation Test

Rainfall is one of the most important factors contributing to landslides, and gentle bedding incline, high-rainfall induced landslides are common throughout the world. Field observations and theoretical analyses have been used to assess slope instability caused by permeability variation. In this study, the influence of rainfall infiltration on gentle bedding incline slope behaviour was investigated using a centrifuge physical simulation test. The magnitude, pattern and development of pore water and earth pressure at the interface;the shear failure surface features;and the corresponding deformation and failure processes were considered. A model with interbedded sand and mud was created, and a centrifuge was used to simulate both natural and rainfall conditions. The weak intercalation was composed of single-material silty clay, and the landslide mass was composed of red-bed sandstone. A combination of photography, pore water pressure measurements and earth pressure measurements were used to examine the relationship between the pore water pressure, earth pressure and failure modes. When the slope experiences overall instability, the curves of the earth pressure and pore water pressure dramatically decrease. The results reveal that the failure shear surface largely depends on the differential creep caused by the properties of the rock mass and the rainfall infiltration.

Failure analysis on a heavy rainfall-induced landslide in Huay Khab Mountain in Northern Thailand

On 28 th July 2018,a massive landslide occurred in a mountainous area in Northern Thailand.The landslide after ten days of heavy rainfall generated the movement of uphill mountain soil into the populated village.This study presents a comprehensive failure analysis of local rainfallinduced landslides based on topographical and geological information.Rainfall measurement data were gathered from two rainfall stations close to the study area.The rainfall records show that the total monthly rainfalls in 2018 were significantly higher than the average monthly rainfalls over the past decade.Site investigation started with an unmanned aerial photogrammetric survey to generate a digital elevation model.Then,dynamic probing test,microtremor survey,and electrical resistivity survey were carried out along undisturbed soils beside the failed slope to evaluate the thickness of the soft soil cover on top of the rock basement.During the site survey,residual soil samples were collected to determine engineering properties in the laboratory.Finally,a slope stability analysis was performed to assess the landslide hazard based on the results of aerial photogrammetric survey,field exploration,and laboratory tests.The slope stability analysis and rainfall records revealed that the Huay Khab landslide was mainly caused by an increase in the water content of residual soils due to the prolonged rainfall which led to a sharp decrease in the shear strength.This leads to the conclusion that the proposed landslide investigation program could be used to assess the potential of landslide failure due to prolonged rainfall on a local scale.

Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview

In recent years,RS and GIS technologies have played an increasingly important role in various aspects of rainfall induced landslide research.In order to systematically understand their application situation,this paper extensively used various visualization analysis technologies for in-depth analysis of 1,161 documents collected by the WOS data platform in the past 27 years by combining quantitative and qualitative methods.Then,this article focuses on sub domain analysis from four aspects:landslide detection and monitoring,prediction models,sensitivity mapping,and risk assessment.The study found that the number of literature in thisfield has steadily increased and is expected to continue to rise.This literature review has attracted widespread attention from the academic community,but it challenging to meet research needs.Frequent and effective cooperationis between countries,institutions,and authors is very beneficial for promoting progress in thisfield.The future development direction is a new intelligent hybrid model that integrates multiple research methods.This study can provide researchers in thisfield with the core research force,hot topic evolution,and future development trends of future rainfall-induced landslides and contribute to landslide prevention and control decision-making and achieving the United Nations’sustainable development goals.

Rainfall early warning threshold and its spatial distribution of rainfall-induced landslides in China

In order to investigate the spatial distribution of early warning threshold for landslide induced by rainfall in China,the literatures about rainfall thresholds of landslides in China in recent 20 years are selected.Statistical analysis and visualization methods were employed to systematically analyze the research progress of rainfall early warning thresholds at various scales.Taking the typical rainfall intensity-duration(I-D)threshold model as the research object,combined with the geographical characteristics of China and the average annual rainfall of 20 years,the spatial distribution of early warning thresholds for rainfall-induced landslide in China is depicted.The results show that the inspired rain intensity coefficientαof the rainfall threshold(I-D curve)in China roughly increases gradually with the decrease of topography.Moreover,under consistent annual rainfall conditions,the scalar indexβexhibits regular changes corresponding to variations in terrain.Topography and rainfall are the two main factors strongly associated with the rainfall threshold.This research establishes a clear framework for studying the early warning thresholds for rainfall-induced landslides in China and holds significant scientific implications for developing more effective rainfall threshold models.

Rainfall-induced landslide stability analysis in response to transient pore pressure——A case study of natural terrain landslide in Hong Kong

Transient pore pressure in response to short intense rainfall process plays an important role in shallow landslide occurrence. Using GIS technology, we carry out the rainfall-induced landslide stability analysis in response to transient pore pressure by means of transient and unsaturated rainfall infiltration modeling. A case study is performed on the shallow landslide stability analysis in Hong Kong. Detailed analysis and discussion reached some useful conclusions on the tempo-spatial behavior and characteristics of slope stability response and pore pressure response to typical rainfall process. Comparison analysis is performed on some important issues including landslide stability response in different types of slopes with different hydraulic properties, antecedent rainfall and landslide stability, and the nature of pore pressure response time. These studies might give us an important insight into landslide tringgering mechanism and the hydrological process in response to rainfall, and provide systematic information and evidences for effective risk assessment and warning system establishment.

A new method for spatio-temporal prediction of rainfall-induced landslide

Geological condition and rainfall are two most principal conditions inducing landslides in the Chongqing region. By analyzing the forming conditions of rainfall-induced landslides, a new method for spatio-temporal prediction of rainfall-induced landslide is brought forward on the basis of grading and overlapping geological condition and rainfall factor in this paper. At first, semi-quantitative assessment and grading for the geological condition of a certain area or slope can be carried out with the multi-factor interactive matrix. Then the severity of rainfall in that area is grading according to the maximum daily rainfall and the total rainfall in a rainfall course. Finally, the “landslide probability judgement factor” can be worked out through grading and overlapping “geological condition influenc- ing factor” and “rainfall influencing factor”, by which the landslide can be graded into 4 grades, they are landslide extremely easily happening, landslide easily happening, landslide difficultly happening and landslide hardly ever happening respectively. More accurate spatio-temporal prediction of rain- fall-induced landslides can come true on the ground of detailed geological survey of some dangerous slopes in an area and more precise weather forecast. Finally, the reliability and feasibility of carrying out the spatio-temporal prediction of rainfall-induced landslides with the method of “two factors” grading and overlapping are validated by the example of Jipazi landslide.

A static and dynamic factorscoupled forecasting model of regional rainfall-induced landslides:A case study of Shenzhen

Most rainfall-induced landslide forecasting models focus on the relation between landslides and rainfall,which is one of the dynamic factors,and seldom consider the stacitc factors,such as geological and geograpical factors.Landslide susceptibility,however,is determinded by both static and dynamic factors.This article proposes a static and dynamic factors-coupled forecasting model(SDFCFM) of regional rainfall-induced landslides,which quantitatively considers both the static and dynamic factors that affect landslides.The generalized additive model(GAM) is applied to coupling both factors to get the landslide susceptibility.In the case study,SDFCFM is applied to forecast the landslide occurrences in Shenzhen during a rainfall process in 2008.Compared with the rainfall logistic regression model,the resulting landslide susceptibility map illustrates that SDFCFM can reduce the forecast redundancy and improve the hit ratio.It is both applicable and practical.The application of SDFCFM in landslide warning and prevention system will improve its efficiency and also cut down the cost of human and matreial resources.

Using Physical Model Experiments for Hazards Assessment of Rainfall-Induced Debris Landslides

Using physical simulation models, rainfall-induced landslides have been simulated under various rainfall intensities. During these simulations, we have monitored the physical and mechanical behaviors of the landslide over the slip surface at different heights of the model slopes, as well as taking the whole slope to identify its deformation and failure processes. The results show that the rainfall duration corresponding to the initiation of the debris landslide and is exponentially related to rainfall intensity. Corresponding to the three intervals of the rainfall intensity, there are three types of slope failure modes:(1) the small-slump failure at the leading edge of the slope;(2) the block-slump failure but sometimes there are large blocks sliding down;and(3) the bulk failure but sometimes there is the block-slump failure. Based on the total rainfall-lasting time and the associated proportion of failed mass volume, the early warning of debris landslide can be classified into five grades, i.e., red, orange to red, orange, yellow to orange and yellow, which correspond to the five slope failure modes, respectively.

Quantitative Risk Analysis of a Rainfall-Induced Complex Landslide in Wanzhou County,Three Gorges Reservoir,China

On 4 April 2013,a 1.5 million cubic meter landslide occurred in Sunjia Town,Wanzhou County,Three Gorges Reservoir,China.After initiation,the Sunjia landslide traveled about 30 m toward the northeast and destroyed most of the infrastructure in its path.The landslide was triggered by heavy rainfall and previous slope excavations,but this slope also displayed a complicated failure process:the overlying earth slope first deformed and then induced sliding along underlying rock surfaces.Surface displacements that resulted from continuous creeping of the post-event slope were observed by an emergency monitoring system that revealed the disequilibrium state of the slope.To discuss the stability and future movements of the remaining unstable debris deposits,we developed a geotechnical model of the post-slide slope,calculated how it can slide again in an extreme rainfall scenario,and estimated the potential runout distance using the Tsunami Squares method.We then estimated the number of people and the value of the infrastructure threatened by this potential landslide.Lastly,we analyzed the vulnerability of elements at risk and quantitatively evaluated the hazard risk associated with the most dangerous scenario.This quantitative risk analysis provides a better understanding of,and technical routes for,hazard mitigation of rainfallinduced complex landslides.

Influence of anthropogenic activities on landslide susceptibility:A case study in Solan district,Himachal Pradesh,India

Landslides in the Himalayan region are primarily controlled by natural parameters,including rainfall,seismic activity,and anthropogenic parameters,such as the construction of large-scale projects like road development,tunneling and hydroelectric power projects and climate change.The parameters which are more crucial among these are a matter of scientific study and analysis.This research,taking Solan district,Himachal Pradesh,India,as the study area,aims to assess the impact of anthropogenic activities on landslide susceptibility at a regional scale.Landslide distribution was characterized into two groups,namely Rainfall-Induced Landslide(RIL)and Human-Induced Landslide(HIL)based on triggering factors.Multiple data such as slope angle,aspect,profile curvature,distance to drainage,distance to lineament,lithology,distance to road,normalized difference vegetation index(NDVI)and land use land cover(LULC)have been considered for delineating the landslide susceptibility zonation(LSZ)map.The effect of anthropogenic activities on landslide occurrences has been examined through the distribution of landslides along national highways and land use land cover changes(LULCC).Two sets of LSZ maps with a LULC of time interval covering five years(2017&2021)were prepared to compare the temporal progression of LULC and landslide susceptibility during the five years.The results indicated the significant impact of anthropogenic activities on the landslide susceptibility.LSZ map of the year 2021 shows that 23%area falls into high and very high susceptible classes and 48%area falls into very low and low susceptibility classes.Compared to LSZ map of 2017,high and very high susceptible classes have been increased by 15%,whereas very low and low susceptible classes have been reduced by 7%.The present case study will help to understand the potential driving parameters responsible for HIL and also suggest the inclusion of LULC in landslide susceptibility analysis.The study will demonstrate new opportunities for research that could help decision-makers prepare for future disasters,both in the Indian Himalayan region and other areas.

Geotechnical and GIS-based environmental factors and vulnerability studies of the Okemesi landslide,Nigeria

Landslide is a geological hazard typically associated with extreme events such as earthquakes,heavy rainfall,volcanic eruptions,changes in groundwater level,etc.This study was carried out in Okemesi-Ekiti(also known as Okemesi),Southwest Nigeria,with the purpose of using remote sensing and GIS technologies to analyze the environmental factors(grain size,direct shear strength resistance,rainfall data,wet density,surface,and slope)resulting in the occurrence of the Okemesi landslide.The study also aimed to conduct a vulnerability analysis in the study area to identify regions with a probability of landslide occurrence.The grain size analysis of the soil in the Okemesi landslide area showed that slope materials comprised 17.14%gravel,59.31%sand,and 19.48%fines,thus the soil type could be classified as poorly graded gravely sand with a high possibility of landslide occurrence.The geomorphic characteristics of the study area was characterized by slopes ranging from 0.00°to 49.00°,while most slopes in the area were less than 8.00°.The slope aspect direction was mainly in south(157.51°–202.50°),southwest(202.51°–247.50°),west(247.51°–292.50°),and north(0.00°–22.50°and 337.51°–360.00°).The highlands were primarily bounded by the slope directions of north(0.00°–22.50°and 337.51°–360.00°),northeast(22.51°–67.50°),east(67.51°–112.51°),and southeast(112.51°–157.50°),which indicated the potential direction of mass movement.The study area can be divided into three vulnerability zones:high,medium,and low,with the area percentages of 9.00%,61.80%,and 29.20%,respectively.The analysis suggested that the Okemesi landslide was likely triggered by rainfall,which might have weakened the physical structure of slope materials.Understanding the causes and impacts of landslides is crucial for policymakers to implement measures to mitigate landslide hazards,protect infrastructure,and prevent the loss of life in the landslide-prone regions.

Studies of Rainfall Induced Landslides Along NH-39 of Manipur,India

Landslide is one of the most frequently occurring natural hazards in Manipur which is a tectonically active area.Rainfall-induced landslides are studied along NH-39 to find out the impact of rainfall.Though rainfall-induced landslides are usually shallow slips in nature and the volume of slip mass is not very large, the damage caused to the properties and infrastructures can be quite serious due to their highly frequent occurrences.NH-39,which is one of the life lines of Manipur,is regularly affected by frequent landslides during rainy season and the frequency is increasing at present as compared to the recent past.Several lands-

Matrix Suction of Unsaturated Colluvium Slope Influenced by Rainfall and Plant Condition:A Case of Taiwan Huafan University

This study investigates the variation of matrix suction, water content and ground water level before and after the rainfall for the unsaturated colluvium slope in the campus of Fuafan University. The measuring devices including electrical matrix suction, water content and ground water level were set up in different surface of planting condition for each depth in real-time. It is observed that the matrix suction in the time from July to September is higher; however, when heavy rains caused by typhoon happened, matrix suction will drop rapidly. This variation is obvious in short grass zone and less clear in the broadleaftree zone. The maximum value in short grass zone, long grass zone and broadieaf tree zone at 2 m depth are 90.3, 68.2, 18.5 kPa, respectively. These results are expected to serve as a reference for the study of slope stability mechanisms.

GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas

Rainwater runoff that does not infiltrate the soil during heavy rainfall may increase slope instability. The effect of runoff is usually neglected in conventional rainfall-induced slope failure analysis to simplify the model. To analyze the effect of runoff on slope stability, this study simultaneously simulated the effects of surface runoff and rainfall infiltration on bank slopes in the Three Gorges Reservoir Area. A shallow slope failure method that can be used to analyze runoff was proposed based on the modified Green-Ampt model, the simplified Saint-Venant model, and the infinite slope model. In this model, the modified Green–Ampt model was used to estimate the rainfall infiltration capacity and the wetting front depth. The eight-flow(D8) method and the simplified Saint-Venant model were selected to estimate the distribution of runoff. By considering the wetting front depth as the slip surface depth, the factor of safety of the slope could be determined using the infinite slope stability model. A comparison of the different models reveals that runoff can escalate the instability of certain slopes, causing stable slopes to become unstable. Comparison of the unstable areas obtained from the simulation with the actual landslide sites shows that the model proposed in this study can successfully predict landslides at these sites. The slope instability assessment model proposed in this study offers an alternative approach for estimating high-risk areas in large mountainous regions.

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity,but it is still an open issue to assess and quantify their impacts.Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover(LULC)and climate.We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity.The future climate change factors were obtained from a 4-member multimodel ensemble that was derived from statistically downscaled regional climate simulations.The future LULC maps were simulated by the land change modeller(LCM)integrated into IDRISI Selva software.A total of six scenarios were defined by considering the rainfall(antecedent conditions and extreme events)and LULC changes towards two time periods(mid and late XXI century).A physically-based model was used to assess landslide susceptibility under these different scenarios.The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future.Under the scenario with a return period of 100 years,the antecedent rainfall in summer will increase by up to 63%whereas the event rainfall will increase by up to 54%for the late 21st century.The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land.The magnitude of this change can reach+22.1%(forest)and–9.2%(farmland)from 2010 until 2100,respectively.We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change,leading to an over decrease in stability over the study area.This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change.Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.

Precipitation data and their uncertainty as input for rainfallinduced shallow landslide models

Physical models used toforecast the temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws.Owing to the existing measuring technology and our knowledge of the physical laws controlling landslide initiation,model uncertainties are due to an inability to accurately quantify the model input parameters and rainfall forcing data.An uncertainty analysis of slope instability prediction provides a rationale for refining the geotechnical models.The Transient Rainfall Infiltration and Grid-based Regional Slope Stability-Probabilistic(TRIGRS-P)model adopts a probabilistic approach to compute the changes in the Factor of Safety(FS)due to rainfall infiltration.Slope Infiltration Distributed Equilibrium(SLIDE)is a simplified physical model for landslide prediction.The new code(SLIDE-P)is also modified by adopting the same probabilistic approach to allow values of the SLIDE model input parameters to be sampled randomly.This study examines the relative importance of rainfall variability and the uncertainty in the other variables that determine slope stability.The precipitation data from weather stations,China Meteorological Administration Land Assimilation System 2.0(CLDAS2.0),China Meteorological Forcing Data set precipitation(CMFD),and China geological hazard bulletin are used to drive TRIGRS,SLIDE,TRIGRS-P and SLIDE-P models.The TRIGRS-P and SLIDE-P models are used to generate the input samples and to calculate the values of FS.The outputs of several model runs with varied input parameters and rainfall forcings are analyzed statistically.A comparison suggests that there are significant differences in the simulations of the TRIGRS-P and SLIDE-P models.Although different precipitation data sets are used,the simulation results of TRIGRS-P are more concentrated.This study can inform the potential use of numerical models toforecast the spatial and temporal occurrence of regional rainfall-induced shallow landslides.

Slope failure simulations with MPM

The simulation of slope failures,including both failure initiation and development,has been modelled using the material point method（MPM）.Numerical case studies involving various slope angles,heterogeneity and rainfall infiltration are presented.It is demonstrated that,by utilising a constitutive model which encompasses,in a simplified manner,both pre-and post-failure behaviour,the material point method is able to simulate commonly observed failure modes.This is a step towards being able to better quantify slope failure consequence and risk.