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1.
The Wenchuan Ms 8.0 earthquake on May 12, 2008 induced a huge number of landslides. The distribution and volume of the landslides are very important for assessing risks and understanding the landslide - debris flow - barrier lake - bursts flood disaster chain. The number and the area of landslides in a wide region can be easily obtained by remote sensing technique, while the volume is relatively difficult to obtain because it requires some detailed geometric information of slope failure surface and sub-surface. Different empirical models for estimating landslide volume were discussed based on the data of 107 landslides in the earthquake-stricken area. The volume data of these landslides were collected by field survey. Their areas were obtained by interpreting remote sensing images while their apparent friction coefficients and height were extracted from the images unifying DEM (digital elevation model). By analyzing the relationships between the volume and the area, apparent friction coefficients, and the height, two models were established, one for the adaptation of a magnitude scale landslide events in a wide range of region, another for the adaptation in a small scope. The correlation coefficients (R2) are 0.7977 and 0.8913, respectively. The results estimated by the two models agree well with the measurement data.  相似文献   

2.
Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorologicalgeotechnical early warning system GRAPES-LFM(GRAPES: Global and Regional Assimilation and Pr Ediction System; LFM: Landslide Forecast Model),basing on the GRAPES model and the landslide predicting model TRIGRS(Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides.This integrated system is evaluated in Dehua County,Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP(National Centers for Environmental Prediction) FNL(Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety(FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides.  相似文献   

3.
Wudu County in northwestern China frequently experiences large-scale landslide events.High-magnitude earthquakes and heavy rainfall events are the major triggering factors in the region.The aim of this research is to compare and combine landslide susceptibility assessments of rainfalltriggered and earthquake-triggered landslide events in the study area using Geographical Information System(GIS) and a logistic regression model.Two separate susceptibility maps were produced using inventories reflecting single landslide-triggering events,i.e.,earthquakes and heavy rain storms.Two groups of landslides were utilized: one group containing all landslides triggered by extreme rainfall events between 1995 and 2003 and the other group containing slope failures caused by the 2008 Wenchuan earthquake.Subsequently,the individual maps were combined to illustrate the locations of maximum landslide probability.The use of the resulting three landslide susceptibility maps for landslide forecasting,spatial planning and for developing emergency response actions are discussed.The combined susceptibility map illustrates the total landslide susceptibility in the study area.  相似文献   

4.
GIS based spatial data analysis for landslide susceptibility mapping   总被引：5，自引：4，他引：1  
Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.  相似文献   

5.
Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of shallow landslides triggered by rainfall.As a result,these landslides influence the evolution of local surface topography.In this research,an area of 2.6 km 2 loess catchment in the Huachi County was selected as the study area locating in the Chinese Loess Plateau.The landslides inventory and landslide types were mapped using global position system(GPS) and field mapping.The landslide inventory shows that these shallow landslides involve different movement types including slide,creep and fall.Meanwhile,main topographic attributes were generated based on a high resolution digital terrain model(5 m × 5 m),including aspect,slope shape,elevation,slope angle and contributing area.These maps were overlaid with the spatial distributions of total landslides and each type of landslides in a geographic information system(GIS),respectively,to assess their spatial frequency distributions and relative failure potentials related to these selected topographic attributes.The spatial analysis results revealed that there is a close relation between the topographic attributes of the postlandsliding local surface and the types of landslide movement.Meanwhile,the types of landslide movement have some obvious differences in local topographic attributes,which can influence the relative failure potential of different types of landslides.These results have practical significance to mitigate natural hazard and understandgeomorphologic process in thick loess area.  相似文献   

6.
Landslides are common hazards in orogenic belt areas. However, it is difficult to quantitatively express the driving effects of tectonic uplift and stream erosion on the occurrence of landslides on large spatial scales by conducting field investigations. In this study, we analyzed a relatively large region that extends over the Yangbi River basin on the upper Lancang-Mekong in China. A series of quantitative indices, including kernel density of the landslide(KDL), hypsometric integral(HI), steepness index(ksn), stream power(?), and stream power gradient(ω) were used to explore the promoting effects of tectonic uplift and stream action intensity on landslides by mapping geomorphic dynamic parameters combined with actual landslide data. The analysis showed that the HI value in the highest landslide risk area was approximately 0.47, and that the KDL in the region can be expressed as a function of steepness or stream power gradient of the channel network, namely, KDL = 0.0127 Ln ksn-0.0167(R~2 = 0.72, P 0.001) and KDL = 0.0219 Ln ω-0.0558(R~2 = 0.21, P 0.02). Therefore, the lower reach of the Yangbi River basin, with higher steepness and stream power gradient, usually has a high uplifting rate and stream incision that drives landslides and causes the entire river network system to be in a stage of longterm active erosion. Furthermore, the results suggest that sediments were being rapidly discharged from the steep tributary channels to the mainstream. This practical situation highlights that the downstream area of the river basin is a high-risk area for landslide hazards, especially in association with heavy rainfall and earthquakes.  相似文献   

7.
Guizhou Karst Plateau is located at the center of the karst region in Asia, where landslides are a typical disaster. Affected by the local karst environment, the landslides in this region have their own characteristics. In this study, 3975 landslide records from inventories of the Guizhou karst plateau are studied. The geographical detector method is used to detect the dominant casual factor and predominant multi-factor combinations for the local landslides. The results show that landslides are prone to areas on slopes between 10° and 35°, of clay rock, in close proximity to gullies, and especially in areas of moderate vegetation, dryland, and mild rocky desertification. Continuous precipitation over 10 days has a great effect on landslide occurrence. Compared with the individual factors, the impact of two-factor interaction has greater explanatory power for landslide volume. The volume of earthquake-induced landslides is predominantly controlled by the interactions of faults and slopes, while that of humaninduced landslides is affected by the interactions of land cover and hydrological conditions. For rainfallinduced landslides, the dominant interactions vary in different regions. In the central karst basin, the interactions between faults and precipitation can explain over 90% of the variations in landslide volumes. In the southern hilly karst region, the interactions between lithology and slope can explain over 71% of the variations in landslide volume and those between fault and land-use can explain 50% of the variations of the landslide volumes in the northeastern mountainous karst region.  相似文献   

8.
Tropical cyclone(TC) Cempaka which occurred on 27–29 November 2017 has caused floods, landslides, and strong winds in certain areas of Java Island. Pacitan Regency was the most severely affected by TC Cempaka. The landslide frequency–area distribution curve of event inventory i.e. TC Cempaka can help to understand landslide susceptibility, hazard, vulnerability, and risk. Landslides were identified by using a local government database and by comparing pre-and post-event high-resolution satellite imageries. Field investigation was carried out in March 2018 to November 2018 to verify the landslide location and update the information. Power law, inverse gamma, and double Pareto model were employed to describe the frequency–magnitude of landslide(mLS) triggered by TC Cempaka. The exponent β values of power law, inverse gamma, and double Pareto were 2.6±0.28(fitted for 8.5% of dataset), 2.2±0.08(fitted for 83% of dataset), and 2.3±0.09(best fitted for dataset), respectively. The P-values were 0.51, 0.67, and 0.91 for power law, inverse gamma, and double Pareto, respectively. This study revealed that rollover occurred at 200 and 300 m2 for double Pareto and inverse gamma, respectively. The cutoff points totaled 1096.49 ± 236.44 and 7235.4 ± 1896.7 m2 for double Pareto and power law, respectively. Rollover phenomenon was real and existed in the dataset because it was far from the minimum resolvable size of the landslide that the authors can delineate from the satellite images. mLS for Pacitan was distributed at around 2 to 4. The magnitude of large landslides was 3.2, that of medium landslides was less than 3, and that of small landslides was almost 4. Numerical estimation calculated a fixed mLS=3.01. Comparison analysis of β values obtained from several landslide inventories triggered by heavy rainfall suggests that the variability of β is related to the intensity and duration of rainfall. Triggering events, such as intensity and duration of rainfall, affect the proportion of large landslides that occur in an area. More complete landslide inventories and rainfall data or other landslide triggering factors from other areas are required for further relationship analysis between the β value and landslide triggering factors.  相似文献   

9.
On August 10, 2019, due to the effect of a rainstorm caused by Super Typhoon Lekima, a landslide occurred in Shanzao Village, China. It blocked the Shanzao stream, forming a barrier lake, and then the barrier lake burst. This is a rare natural disaster chain of typhoon–rainstorm–landslide–barrier lake–flooding. This study was built on field surveys, satellite image interpretation, the digital elevation model(DEM), engineering geological analysis and empirical regression. The purpose was to reveal the characteristics and causes of the landslide, the features and formation process of the barrier lake and the dam break flooding discharge. The results show that the volume of the landslide deposit is approximately 2.4 × 105 m3. The burst mode of the landslide dam is overtopping, which took only 22 minutes from the formation of the landslide dam to its overtopping. The dam-break peak flow was 1353 m3/s, and the average velocity was 2.8-3.0 m/s. This study shows that the strongly weathered rock and soil slope has low strength and high permeability under the condition of heavy rainfall, which reminds us the high risk of landslides and the importance of accurate early warning of landslides under heavy rainfalls in densely populated areas of Southeast China, as well as the severity of the disaster chain of typhoon–rainstorm–landslide–barrier lake–flooding.  相似文献   

10.
Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.  相似文献   

11.
Debris flows in Jiangjia Ravine in Yunnan province,China are not only triggered by intense storms but also by short-duration and low-intensity rainfalls.This reflects the significance of antecedent rainfall.This paper tries to find the debris flowtriggering threshold by considering antecedent rainfall through a case study in Jiangjia Ravine.From 23 debris flow events,the I-D(Intensity-Duration) threshold was found,which is very close to the line of 95th percentile regression line of rainfall events,representing that 95% of rainfalls can potentially induce debris flows and reflects the limitation of I-D threshold application in this area.Taking into account the effect of antecedent rainfall,the debris flowtriggering threshold for rainfall quantity and intensity is statistically and empirically derived.The relationships can be used in debris flow warning system as key thresholds.Coupling with the rainfall characteristics in this area,new thresholds are proposed as triggering and warning thresholds.  相似文献   

12.
Earthquake-induced potential landslides are commonly estimated using landslide susceptibility maps. Nevertheless, the fault location is not identified and the ground motion caused by it is unavailable in the map. Thus, potential coseismic landslides for a specific fault motion-induced earthquake could not be predicted using the map. It is meaningful to incorporate the fault location and ground motion characteristics into the landslide predication model. A new method for a specific fault motion-induced coseismic landslide prediction model using GIS (Geographic Information System) is proposed herein. Location of mountain ridges, slope gradients over 45 o , PVGA (Peak Vertical Ground Accelerations) exceeded 0.15 g, and PHGA (Peak Horizontal Ground Accelerations) exceeded 0.25 g of slope units were representing locations that initiated landslides during the 1999 Chi-Chi earthquake in Taiwan. These coseismic landslide characteristics were used to identify areas where landslides occurred during Meishan fault motion-induced strong ground motions in Chiayi County in Taiwan. The strong ground motion (over 8 Gal in the database, 1 Gal = 0.01 m/s 2 , and 1 g = 981 Gal) characteristics were evaluated by the fault length, site distance to the fault, and topography, and their attenuation relations are presented in GIS. The results of the analysis show that coseismic landslide areas could be identified promptly using GIS. The earthquake intensity and focus depth have visible effects on ground motion. The shallower the focus depth, the larger the magnitude increase of the landslides. The GIS-based landslide predication method is valuable combining the geomorphic characteristics and ground motion attenuation relationships for a potential region landslide hazard assessment and in disaster mitigation planning.  相似文献   

13.
《山地科学学报》2020,17(2):340-357
Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.  相似文献   

14.
Panzhihua city(26°05’-27°21’N,101°08’102°15’E),located in a mountainous area,is one of the large cities in Sichuan province,China.A landslide occurred in the filling body of the eastern part of the Panzhihua airport on October 3,2009(hereafter called the 10.3 landslide).We conducted field survey on the landslide and adopted emergency monitoring and warning models based on the Internet of Things(IoT) to estimate the losses from the disaster and to prevent a secondary disaster from occurring.The results showed that four major features of the airport site had contributed to the landslide,i.e,high altitude,huge amount of filling rocks,deep backfilling and great difficulty of backfilling.The deformation process of the landslide had six stages and the unstable geological structure of high fillings and an earthquake were the main causes of the landslide.We adopted relative displacement sensing technology and Global System for Mobile Communications(GSM) technology to achieve remote,real-time and unattended monitoring of ground cracks in the landslide.The monitoring system,including five extensometers with measuring ranges of 200,450 and 700 mm,was continuously working for 17 months and released 7 warning signals with an average warning time of about 26 hours.At 10 am on 6 December 2009,the system issued a warning and on-site workers were evacuated and equipment protected immediately.At 2:20 pm on 7 December,a medium-scale collapse occurred at the No.5 monitoring site,which justified the alarm and proved the reliability and efficiency of the monitoring system.  相似文献   

15.
China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.  相似文献   

16.
In the purple hilly region, erosions and landslides are all serious, and it is of great scientific value and practical significance to study their formation mechanism and distribution features there.In this paper, soil micromorphological methods and techniques were used to study the erosion zonal distribution in the region. The results indicated: (1)According to erosion process, the spacial distribution zones of the erosions and landslides in the purple hilly region with different solums were divided into scouring erosion zone, transport-diffusion zone, rocks and soil turbulence zone and sediment-bury zone; (2) The soil micromorphologic taxonomic feature identifying different erosion-landslide zone were found by studying the soil micromorphology of erosive zone in purple hilly region; (3) As for the erosion-landslide formation in the region, besides the external factors, the internal factors were found more important and favorable for landslide formation through the studies on the micormorphologieal features of slide soil.  相似文献   

17.
Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.  相似文献   

18.
Among the triggering factors of post-earthquake bedrock landslides,rainfall plays an important role.However,with slope variation,the mechanism of its effects on the failure of rock landslides is not clear.Here,from the viewpoint of fracture mechanics,and based on post-earthquake conditions,the mechanisms of crack propagation,water infiltration and development of the sliding surface were investigated.Then,according to the upper boundary theorem,the effects of water infiltrated into fractures on the stability of rock slopes were analyzed quantitatively.Finally,an example is presented to verify the theory.The results show that the propagation and coalescence of cracks and the lubrication of incipient sliding surfaces are the main causes of the failure of post-earthquake rock landslides in response to rainfall.  相似文献   

19.
The Lamuajue landslide is located in Lamuajue village on the right bank of the Meigu River,Sichuan Province, China. This landslide is an ancient landslide with an extremely wide distribution area,covering an area of 19 km~2 with a maximum width of5.5 km and an estimated residual volume of 3×10~8 m~3.The objectives of this study were to identify the characteristics and failure mechanism of this landslide. In this study,based on field investigations,aerial photography, and profile surveys, the boundary,lithology, structure of the strata, and characteristics of the landslide deposits were determined. A gently angled weak interlayer consisting of shale was the main factor contributing to the occurrence of the Lamuajue landslide. The deposition area can be divided into three zones: zone A is an avalanche deposition area mainly composed of blocks,fragments, and debris with diameters ranging from0.1 m to 3 m; zone B is a residual integrated rock mass deposition area with large blocks,boulders and "fake bedrock"; and zone C is a deposition zone of limestone blocks and fragments. Three types of failure mechanism were analyzed and combined to explain the Lamuajue landslide based on the features of the accumulation area. First, a shattering-sliding mechanism caused by earthquakes in zone A. Second,a sliding mechanism along the weak intercalation caused by gravity and water in zone B. Third,a shattering-ejection mechanism generated by earthquakes in zone C. The results provide a distinctive case for the study of gigantic landslides induced by earthquakes, which is very important for understanding and assessing ancient earthquakeinduced landslides.  相似文献   

20.
《山地科学学报》2020,17(3):686-708
Landslides in Tianshui Basin, Gansu Province, Northwest China, severely affect the local population and the economy;therefore,understanding their evolution and kinematics is of great interest for landslide risk assessment and prevention. However, there is no unified classification standard for the types of loess landslides in Tianshui.In this study, we explored the landslide distribution and failure characteristics by means of field investigation,remotesensinginterpretation,geological mapping, drilling exploration and shearwave velocity tests, and established a database of Tianshui landslides. Our analysis shows that shear zones in mudstone usually develop in weak intercalated layers. Landslides occur mainly along the West Qinling faults on slopes with gradients of 10° to 25° and on southeast-and southwest-facing slopes.These landslides were classified into five types: loess landslides, loess–mudstone interface landslides, loess flow-slides, loess–mudstone plane landslides and loess–mudstone cutting landslides. We discussed the evolution and failure process of each landslide type and analyzed the formation mechanism and motion characteristics of large-scale landslides. The analysis results show that the landslides in the study area are characterized by a gentle slope, long runout and high risk. The relationship between the runout L and the vertical drop H of the large-scale landslides in the study area is L 4 H. There are good correlations between the equivalent friction coefficient of largescale landslides and their maximum height, runout,area and volume. The sliding zone of large-scale landslides often develops in the bedrock contact zone or in a weak interlayer within mudstone. From microstructure analysis, undisturbed mudstone consists mainly of small aggregates with dispersed inter-aggregate pores, whereas sheared clay has a more homogeneous structure. Linear striations are well developed on shear surfaces, and the clay pores in those surfaces have a more uniform distribution than those in undisturbed clay.  相似文献   

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