Earthquake-triggered Landslide Hazard Research Articles

Earthquake-Triggered Landslide Hazard Modelling Based on Spatially Heterogeneous Non-Landslide Samples

Earthquake-Triggered Landslide Hazard Modelling Based on Spatially Heterogeneous Non-Landslide Samples

The probability of coseismic landslides in different peak ground accelerations: a case of 1927 Gulang M8.0 event

A catastrophic Ms 8.0 earthquake struck Gulang County, Gansu Province on May 23, 1927, and triggered numerous coseismic landslides. Based on a high-resolution remote sensing image from Google Earth Platform, we delineated 936 coseismic landslides with an area of 58.6 km2. Further, ten factors were selected as the impact factors for earthquake-triggered landslide hazard mapping of the earthquake. We propose a sampling method that selects the sliding and nonsliding samples established on the ratio of the study area to the landslide area based on the Bayesian theory, and a total of 247080 samples are selected. We establish a multi-factor impact model for landslide probabilities using the logistic regression (LR) model, calculate the regression coefficients based on LR models, and obtain the occurrence probability of coseismic landslides. The model is then applied to calculate the probability of earthquake landslides under different PGAs. The study areas are divided into extremely high-risk, high-risk, medium-risk, low-risk, and extremely low-risk areas. The results of this study provide scientific references for mitigating earthquake-related landslides in earthquake-prone areas.

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

Coseismic landslides are a major source of transportation disruption in mountainous areas, but few approaches exist for rapidly estimating impacts to road networks. We develop a model that links the U.S. Geological Survey (USGS) near-real-time earthquake-triggered landslide hazard model with Open Street Map (OSM) road network data to rapidly estimate segment-level obstruction risk following major earthquake activity worldwide. To train and validate the model, we process OSM data for 15 historical earthquakes and calculate the average segment-level landslide hazard from the USGS model for each event. We then fit a multivariate adaptive regression spline model for the probability of road obstruction as a function of road segment length and landslide hazard, using a training and validation dataset derived from the intersections of road networks with earthquake-triggered landslide inventories. The resulting probabilistic model is well calibrated across a range of earthquake events, with estimated obstruction probabilities matching the relative frequency of potential road obstructions. The model runs quickly and is capable of producing road segment-level obstruction estimates within minutes to hours of a major earthquake. However, in near-real-time application, the accuracy of the obstruction estimates will be dependent on the quality of the ShakeMap shaking estimates, which often improves with time as more information becomes available after the earthquake. By providing a rapid first-order translation of landslide hazard into potential infrastructure impacts, this model helps provide emergency responders with tangible information on initial areas of concern.

The Caracas, Venezuela, Seismic Microzoning Project: Methodology, results, and implementation for seismic risk reduction

The city of Caracas has been struck by earthquakes several times in its history, and the most recent one, the M6.6 1967 event, evidenced strong site effects within the sedimentary valley. Therefore, Caracas has been the object of research related to earthquake hazard and damage since then, and a seismic microzoning project has been formally developed in the years 2005 to 2009. The principal results constitute response spectra at different subsoil conditions within the sedimentary valley and estimation of landslide hazard for hillside areas. The methodology used for the development of the soil response comprises probabilistic assessment of seismic hazard at rock sites; identification of soil and basin site effects; definition of microzones of similar seismic response. The seismic hazard in the area of Caracas was detailed for PGA and A1 (1-sec. period response), at four macrozones. We developed generic profiles for dynamic response using 1D equivalent linear analysis, considering variations in sediment thickness and VS,30. The analytical results were calibrated and approximate 2D-3D basin effects included. The distribution of microzones in the valley is based on geomorphologic, geological and geophysical modeling, with soil profiles from deep boreholes, and predominant periods from H/V. The earthquake triggered landslide hazard is evaluated using information regarding geology, geomorphology, geotechnical information, slope, weathering, and anthropic alterations, employing a modified Newmark method with Arias intensities. Thus, priority areas for intervention may be identified. Part of the study includes the evaluation of buildings regarding their typified structural reliability, calibrated with the 1967 Caracas earthquake damages. The derived priorities for retrofitting of existing buildings regarding their location within the different microzones are one of the key issues in the county ordinances that have been developed for the 5 counties in the Metropolitan Region. So far, one of them has been signed by the respective mayor, and the remaining 4 are in progress. Once all are signed, we expect seismic disaster risk plans to be developed to guarantee the use of the technical information for earthquake risk mitigation.

A method for quick assessment of earthquake-triggered landslide hazards: a case study of the Mw6.1 2014 Ludian, China earthquake

Rapid assessment of the distribution of earthquake-triggered landslides is an important component of effective disaster mitigation. The effort should be based on both seismic landslide susceptibility and the ground shaking intensity, which is usually measured by peak ground acceleration (PGA). In this paper, we address this issue by analyzing data from the Mw6.1 2014 Ludian, China earthquake. The Newmark method of rigid-block modeling was applied to calculate the critical acceleration of slopes in the study area, which serve as measurement of slope stability under seismic load. The assessment of earthquake-triggered landslide hazard was conducted by comparing these critical accelerations with the distribution of known PGA values. The study area was classified into zones of five levels of landslide hazard: high, moderate high, moderate, light, and very light. Comparison shows that the resulting landslide hazard zones agree with the actual distribution of earthquake-triggered landslides. Nearly 70% of landslides are located in areas of high and moderately high hazard, which occupy only 17% of the study region. This paper demonstrates that using PGA, combined with the analysis of seismic landslide susceptibility, allows a reliable assessment of earthquake-triggered landslides hazards. This easy-operation mapping method is expected to be helpful in emergency preparedness planning, as well as in seismic landslide hazard zoning.

A subaqueous hazard map for earthquake-triggered landslides in Lake Zurich, Switzerland

The awareness of geohazards in the subaqueous environment has steadily increased in the past years and there is an increased need to assess these hazards in a quantitative sense. Prime examples are subaqueous landslides, which can be triggered by a number of processes including earthquakes or human activities, and which may impact offshore and onshore infrastructure and communities. In the literature, a plenitude of subaqueous landslide events are related to historical earthquakes, including cases from lakes in Switzerland. Here, we present an approach for a basin-wide earthquake-triggered subaquatic landslide hazard assessment for Lake Zurich, which is surrounded by a densely populated shoreline. Our analysis is based on high-resolution sediment-mechanical and geophysical input data. Slope stabilities are calculated with a grid-based limit equilibrium model on an infinite slope, which uses Monte Carlo sampled input data from a sediment-mechanical stratigraphy of the lateral slopes. Combined with probabilistic ground-shaking forecasts from a recent national seismic hazard analysis, subaquatic earthquake-triggered landslide hazard maps are constructed for different mean return periods, ranging from 475 to 9975 years. Our results provide a first quantitative landslide hazard estimation for the lateral slopes in Lake Zurich. Furthermore, a back-analysis of a case-study site indicates that pseudostatic accelerations in the range between 0.04 and 0.08 g were needed to trigger a well-investigated subaqueous landslide, dated to ~2210 cal. years B.P.

Slope instabilities triggered by the 11th May 2011 Lorca earthquake (Murcia, Spain): comparison to previous hazard assessments and proposition of a new hazard map and probability of failure equation

The Lorca Basin has been the object of recent research aimed at studying the phenomena of earthquake-induced landslides and its assessment in the frame of different seismic scenarios. However, it has not been until the 11th May 2011 Lorca earthquakes when it has been possible to conduct a systematic approach to the problem. In this paper we present an inventory of slope instabilities triggered by the Lorca earthquakes which comprises more than 100 cases, mainly rock and soil falls of small size (1–100 $$\hbox {m}^{3}$$ ). The distribution of these instabilities is here compared to two different earthquake-triggered landslide hazard maps: one considering the occurrence of the most probable earthquake for a 475-years return period in the Lorca Basin $$(\hbox {M}_{\mathrm{w}}=5.0)$$ based on both low- and high-resolution digital elevation model (DEM); and a second one matching the occurrence of the $$\hbox {M}_{\mathrm{w}}=5.2$$ 2011 Lorca earthquake, which was performed using the higher resolution DEM. The most frequent Newmark displacements related to the slope failures triggered by the 2011 Lorca earthquakes are lower than 2 cm in both the hazard scenarios considered. Additionally, the predicted Newmark displacements were correlated to the inventory of slope instabilities to develop a probability of failure equation. The fit seems to be very good since most of the mapped slope failures are located on the higher probability areas. The probability of slope failure in the Lorca Basin for a seismic event similar to the $$\hbox {M}_{\mathrm{w}}$$ 5.2 2011 Lorca earthquake can be considered as very low (0–4 %).

Landslide hazard mapping using GIS and weight of evidence model in Qingshui River watershed of 2008 Wenchuan earthquake struck region

Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using weight of evidence modeling in Qingshui (清水) River watershed, Deyang (德阳) City, Sichuan (四川) Province, China. Two thousand three hundred and twenty-one landslides were interpreted in the study area from aerial photographs and multi-source remote sensing imageries post-earthquake, verified by field surveys. The landslide inventory in the study area was established. A spatial database, including landslides and associated controlling parameters that may have influence on the occurrence of landslides, was constructed from topographic maps, geological maps, and enhanced thematic mapper (ETM+) remote sensing imageries. The factors that influence landslide occurrence, such as slope angle, aspect, curvature, elevation, flow accumulation, distance from drainages, and distance from roads were calculated from the topographic maps. Lithology, distance from seismogenic fault, distance from all faults, and distance from stratigraphic boundaries were derived from the geological maps. Normalized difference vegetation index (NDVI) was extracted from ETM+ images. Seismic intensity zoning was collected from Wenchuan (汶川) Ms8.0 Earthquake Intensity Distribution Map published by the China Earthquake Administration. Landslide hazard indices were calculated using the weight of evidence model, and landslide hazard maps were calculated from using different controlling parameters cases. The hazard map was compared with known landslide locations and verified. The success accuracy percentage of using all 13 controlling parameters was 71.82%. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low, and very low. The validation results showed satisfactory agreement between the hazard map and the existing landslides distribution data. The landslide hazard map can be used to identify and delineate unstable hazard-prone areas. It can also help planners to choose favorable locations for development schemes, such as infrastructural, buildings, road constructions, and environmental protection.

Landslide hazard assessment of the 2008 Wenchuan earthquake: a case study in Beichuan area

The Wenchuan earthquake (magnitude Ms = 8.0) of 12 May 2008 triggered widespread and large-scale landslides over an area of about 50 000 km2. A study was undertaken to determine the primary factors associated with seismic landslide occurrence. An index-based approach used to assess earthquake-triggered landslide hazard in the central part of the Wenchuan earthquake area affected is described. Slope gradient, relief amplitude, lithology, bedding–slope relations, fault proximity, stream proximity, and antecedent rainfall are recognized as factors that may have had an important influence on landslide occurrence. The assessment of the influence of each of these factors is presented through use of a series of maps showing areas of low, moderate, high, and very high landslide hazard. Areas identified as having “very high and high landslide hazard” were located along the earthquake-source fault and along both banks of the Jian River. The role of rainfall is very significant for future landslide occurrence in the earthquake area. The results of this study will assist decision makers in the selection of safe sites during the reconstruction process. The maps can also be used for landslide risk management in the study area.

GIS-based earthquake-triggered landslide hazard zoning using contributing weight model

Earthquake-triggered landslides have aroused widespread attention because of their tremendous ability to harm people’s lives and properties. The best way to avoid and mitigate their damage is to develop landslide hazard maps and make them available to the public in advance of an earthquake. Future construction can then be built according to the level of hazard and existing structures can be retrofit as necessary. During recent years various approaches have been made to develop landslide hazard maps using statistical analysis or physical models. However, these methods have limitations. This study introduces a new GIS-based approach, using the contributing weight model, to evaluate the hazard of seismically-induced landslides. In this study, the city and surrounding area of Dujiangyan was selected as the research area because of its moderate-high seismic activity. The parameters incorporated into the model that related to the probability of landslide occurrence were: slope gradient, slope aspect, geomorphology, lithology, base level, surface roughness, earthquake intensity, fault proximity, drainage proximity, and road proximity. The parameters were converted into raster data format with a resolution of 25×25m2 pixels. Analysis of the GIS correlations shows that the highest earthquake-induced landslide hazard areas are mainly in the hills and in some of the moderately steep mountainous areas of central Dujiangyan. The highest hazard zone covers an area of 11.1% of the study area, and the density distribution of seismically-induced landslides was 3.025/km2 from the 2008 Wenchuan earthquake. The moderately hazardous areas are mainly distributed within the moderately steep mountainous regions of the northern and southeastern parts of the study area and the hills of the northeastern part; covering 32.0% of the study area and with a density distribution of 2.123/km2 resulting from the Wenchuan earthquake. The lowest hazard areas are mainly distributed in the topographically flat plain in the northeastern part and some of the relatively gently slopes in the moderately steep mountainous areas of the northern part of Dujiangyan and the surrounding area. The lowest hazard areas cover 56.9% of the study area and exhibited landslide densities of 0.941/km2 and less from the Wenchuan earthquake. The quality of the hazard map was validated using a comparison with the distribution of landslides that were cataloged as occurring from the Wenchuan earthquake. 43.1% of the study area consists of high and moderate hazardous zones, and these regions include 83.5% of landslides caused by the Wenchuan earthquake. The successful analysis shows that the contributing weight model can be effective for earthquake-triggered landslide hazard appraisal. The model’s results can provide the basis for risk management and regional planning is.

OBTAINING PROBABILISTIC ESTIMATES OF DISPLACEMENT ON A LANDSLIDE DURING FUTURE EARTHQUAKES

The assessment of earthquake triggered landslide hazard may be undertaken using both deterministic and probabilistic techniques. Probabilistic methods have been developed because much of the data can be considered as random variables where parameters such as the angle of internal friction and moisture content do not have a single fixed value but may assume any number of values across a range. This random variability can be modelled by a probability density function (PDF) which describes the relative likeli-hood that a random variable will assume a particular value. Instead of using just the average or expected value of an input parameter, the complete range of possible values can be used to estimate a range of possible outcomes. Thus the probability of a slope being unstable can be obtained rather than a single indicator of stability. Such proba-bilistic analyses allow for the incorporation of the likely variability of each parameter and therefore allow a more intimate assessment of slope stability to be derived. Utilising empirical relationships for calculating earthquake ground motions and associated slope displacement, an investigation was undertaken to identify the contribution that modern simulation techniques could make to the assessment of earthquake-triggered landslides. To achieve this, geotechnical and earthquake data obtained from a deep-seated landslide triggered during the M w 7.0 Loma Prieta earthquake was used. By incorporating the variability of the geotechnical parameters and the uncertainty in earthquake location the model derived the probabilities associated with increasing amounts of slope displacement during future probable earthquakes. Analysis was undertaken for four of the principal fault segments in the San Francisco Bay area. These estimates were then combined with the occurrence probabilities of the earthquakes to provide temporal estimates of dis-placement for a 30 year period. Results indicated that a M w 7.0 earthquake located on the Peninsula Segment of the San Andreas fault was most hazardous with a 11% chance of minor slope displacement (≥0.10 m) and a 6% chance of moderate slope displacement (≥0.30 m) within the next 30 years.

Evaluating earthquake-triggered landslide hazard at the basin scale through gis in the Upper Sele river Valley

To evaluate techniques for assessing earthquake-triggeredlandslide hazard in the Southern Apennines (Italy), a GIS-based analysis was used to modelseismically induced slope deformations. Geological, geotechnical, geomorphological and seismologicaldata were integrated into a standard earthquake slope stability model. The model assessed thelandslide potential that existed during the 1980 Irpinian earthquake in the Upper Sele river Valley.The standard Newmark displacement analysis, widely used for predicting the location of shallowunstable slopes, does not take into account errors and/or uncertainties in the input parameters.Therefore, a probabilistic Newmark displacement analysis technique has been used. Probabilistictechniques allow, e.g., an estimation of the probability that a slope will exceed a certain criticalvalue of Newmark displacement. In our probabilistic method, a Monte-Carlo based simulation modelis used in conjunction with a GIS. The random variability of geotechnical data is modelled by probabilitydensity functions (pdfs), while for the seismic input three different regression laws wereconsidered. Input probability distributions are sampled and the resulting values input into empiricalrelations for estimating Newmark displacement. The outcome is a map in which to each siteis related a spatial probability distribution for the expected displacement in response to seismic loading.Results of the experiments show a high grade of uncertainty in the application of the Newmarkanalysis both for the deterministic and probabilistic approach in a complex geological setting suchas the high Sele valley, quite common in the Southern Apennines. They show a strong dependence onthe reliability of the spatial data used in input, so that, when the model is used at basin scale,results are strongly influenced by local environmental condition (e.g., topography, lithology, groundwatercondition) and decrease the model performance.