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The landslide story
Abstract
The catastrophic Wenchuan earthquake induced an unprecedented number of
geohazards. The risk of heightened landslide frequency after a quake,
with potential secondary effects such as river damming and subsequent
floods, needs more focused attention.
The areas around the Ching-Shuei River saw numerous landslides (2004–2017) after the Jiji earthquake, profoundly harming the watershed’s geological environment. The 33 catchment areas in the Ching-Shuei River watershed and five typhoon and rainstorm events, with a total of 165 occurrences and non-occurrences, were analyzed, and the training and validation were categorized into 70% training and 30% validation. A landslide disaster is deemed, for the purposes of this research, to have taken place if SPOT satellite images taken before and after an incident show a Normalized Difference Vegetation Index difference larger than 0.25, a slope of less than 30 degrees, and a number of connected grids greater than 10. The analysis was carried out using the instability index method analysis with Rogers regression analysis and artificial neural network. The accuracy rates of neural network, logit regression, and instability index analyses were, respectively, 93.3%, 80.6%, and 70.9%. The neural network’s area under the curve was 0.933, indicating excellent discrimination ability; that of the logit regression analysis was 0.794, which is considered good; and that of the instability index analysis was 0.635, or fair. This suggests that any of the three models are suitable for the danger assessment of large post-earthquake debris flows. The results of this study also provide a reference and evidence for specific sites’ potential susceptibility to debris flows.
Landslide is a natural disaster in Indonesia, especially in the Aceh province, with its geological complex, high rainfall, and topography. The high-intensity landslides have occurred in Jantho and Lamno, located in the Northern part of Aceh, with high development costs of road infrastructure. Therefore, it is necessary to map the potential of landslides along the Jantho – Lamno road as disaster mitigation in the future. The research uses a digital elevation model (DEM) that applies slope, aspect, hill shade, curvature, elevation and geological observation to study the landslide probability. The DEM analysis shows the distribution of terrain with varying elevations of 300 – 1,200 m.a.s.l and slope characteristics with 10 – 50 degrees variations. Apart from that, curvature and aspect analysis describe the direction of slope reduction, which is more dominant towards the side of public infrastructure. Analysis of the four data distributions shows that the south side area has a large landslide potential. On the other hand, slope data slices at four locations could interpret landslide potential well. Based on data processing, we conclude that comparing DEM and geological observations is considered effective as a fast and economical method of mapping landslide probability, especially in tropical areas and high topography that is difficult to access.
Plain Language Summary
The Wenchuan earthquake triggered tens of thousands of landslides and caused severe surface damages, leading to adverse impacts on the local environment in the following period. Therefore, we implemented an approach that combines change detection techniques with long‐term remote sensing images to track the landslide activities from 2000 to 2021. Consequently, continuous landslide maps have been produced, and the post‐earthquake landslide activities were analyzed under different conditions considering various factors. We also explored the restorations for the undisturbed landslides after the earthquake using important ecological indicators. The results suggest that the recovery of landslide activity and surface evapotranspiration was rapid. However, the regrowth and succession of damaged plants required a longer time. Moreover, it would take decades to fully restore the vegetation ecological function, which shatters our original impression on the persistence of post‐earthquake landslide impacts.
Over the past decade, Unmanned Aerial Vehicles (UAVs) have emerged as essential tools for landslide studies, particularly in on-site investigations. This paper reviews UAV applications in landslide studies, with a focus on static geological characteristics, monitoring temporal and spatial dynamics, and responses post-events. We discuss the functions and limitations of various types of UAVs and sensors (RGB cameras, multi-spectral cameras, thermal IR cameras, SAR, LiDAR), outlining their roles and data processing methods in landslide applications. This review focuses on the UAVs’ roles in landslide geology surveys, emphasizing landslide mapping, modeling and characterization. For change monitoring, it provides an overview of the temporal and spatial evolution through UAV-based monitoring, shedding light on dynamic landslide processes. Moreover, this paper underscores UAVs’ crucial role in emergent response scenarios, detailing strategies and automated detection using machine learning algorithms. The discussion on challenges and opportunities highlights the need for ongoing UAV technology advancements, addressing regulatory hurdles, hover time limitations, 3D reconstruction accuracy and potential integration with technologies like UAV swarms.
Microfracture density in fault damage zones can reflect spatial variability that decays in intensity as a function of distance from the fault, which is crucial in understanding the mechanical, seismological, and fluid-flow properties of the fault system. However, few studies explored the characteristics of fracture density between the two sides of active dip-slip faults due to rare field observations. Here, we measured and modeled microfractures across an active thrust fault associated with the 2008 Mw 7.9 Wenchuan earthquake in the Longmen Shan, eastern Tibetan Plateau. The results showed that the microfracture density at the Qingping site developed more intensely in the hanging wall than in the footwall for an exposed thrust fault, indicating an asymmetrical pattern. The hidden thrust fault at the Jushui site showed that microfractures developed more intensely in vertical planes in the hanging wall than in the footwall, whereas microfractures developed similarly in horizontal planes within the two sides, indicating a quasiasymmetrical pattern. Comparing the data at the two sites with computational modeling, we suggest that fault geometry might exert a first-order control of the asymmetrical microfracture density pattern, which is helpful for revealing different deformational behaviors of rock masses in the fault damage zones and better understanding the hanging-wall effect for evaluating seismic hazards on active thrust faults.
An unstable wedge block with a volume of approximately 1,200,000 m3, intersected by an anti-dipped large fault and two outward-dipped faults, has been identified on the high-steep slope at the entrance of the tunnel spillway of the Shuangjiangkou hydropower station in China, a region characterized by high tectonic stresses. In this study, kinematic analysis was first conducted to preliminarily assess the possibility of block sliding, and then a three-dimensional discrete element code (3DEC) was utilized to analyze the mechanism of block instability during sequential excavation and reinforcement. The results showed that block sliding is caused by continuous excavation and deterioration of the mechanical properties of the bottom sliding surface. The failure behavior of the slope is primarily governed by the wedge block, which slides along the intersection line of two outward dipped faults. After the excavation of Layers 1–4, the shear displacements of the faults exhibited accelerated and abrupt characteristics. Finally, the pretension cable proved effective in restraining block sliding, increasing the factor of safety for the slope from 1.16 to 1.28 after complete excavation and reinforcement. This study offers significant insights into the analysis of failure mechanisms in similar engineering challenges.
Erosion and deposition induced by overtopping flow strongly impacts the breaching evolution of landslide dams. However, these two processes are not yet sufficiently captured in current dam breaching models. In this paper, we simulate the Erosion and Deposition process during overtopping dam breaching using a novel Smooth Particle Hydrodynamics (ED-SPH) method. A new multi-function boundary is proposed to prevent the penetration of water and soil particles and ensure steady inflows. Dam break and movable erosion scenarios are simulated as a means to validate the model. Dam breach simulations using the ED-SPH method reveal that the proposed model can capture the complex dam soil erosion, entrainment, and depositions behaviors. The soil deposition hinders the eroded particle movement and reduces the water velocity at the water-soil interface. If soil deposition is not considered, as in many existing models, the breaching time decreases and the outburst flood discharge is magnified. We further investigate the re-erosion of deposited soils by varying the re-erosion coefficient. With decreasing the re-erosion coefficient, the peak discharge increases whereas the residual dam height decreases due to the blockage by the deposited soils.
Landslide-dammed lakes and their breaches can reactivate/accelerate landslides, causing potential damages. However, in the absence of displacement observations, the spatial-temporal deformation patterns of the landslide-dammed lakes and associated floods reactivated/accelerated landslides remain underexplored. In this study, we use the 2018 Baige landslide-dammed lake and associated floods reactivated/accelerated landslides to investigate the behaviors of such landslides. We first use an improved interferograms Stacking method to detect landslides, then utilize the multi-temporal interferometric synthetic aperture radar (MT-InSAR) to derive their deformation history. Through retrospective analysis of the deformation history and optical images, we find that the water level fluctuations and floods caused by the Baige landslide-dammed lake and its breaches reactivated/accelerated 6 landslides upstream and 5 landslides downstream. The area of the largest reactivated/accelerated landslide is about 5 km
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. The maximum velocity change of these reactivated/accelerated landslides is about 20 cm/year. Landslide reactivation/acceleration occurs progressively from the toe to head, resulting in varying reactivation/acceleration times for different parts. The velocity change and acceleration area have a linear relationship, with larger landslides showing larger velocity changes and prolonged activity than smaller ones. Among these 11 reactivated/accelerated landslides, 4 are located in the river narrow sections and their volumes are all larger than that of the Baige landslide. Thus, their failure may cause larger damages than that caused by the Baige landslide. Our findings contribute to a better understanding of landslide-induced geological hazard chains and landslide behaviors.
The purpose of this work is to carry out seismically induced landslide probabilistic hazard mapping for future seismic scenarios of Aba Prefecture and Chengdu Plain region, Sichuan Province, China. Nine earthquake events that occurred in the regions and neighboring areas are selected, which include a total of 251,260 landslide records. This work used 12 influencing factors including elevation, slope, aspect, relief, topographic wetness index (TWI), topographic position index (TPI), peak ground motion, distance to active faults, vegetation coverage, distance to roads, lithology, and annual rainfall to establish the LR model. Based on the probabilistic seismic hazard analysis (PSHA) method, the distribution of predicted seismic motion under four earthquake scenarios is calculated including frequent, occasional, rare, and very rare earthquake occurrence. Using the PGA distribution of the four scenarios as input peak ground motion parameters, we calculated the occurrence probability of coseismic landslides in the entire Aba Prefecture and Chengdu Plain region under the action of different ground motions. The result shows that the high-hazard areas are mainly concentrated in the Longmenshan fault zone, and the southern area of Kangding is also a potential high-hazard area for landsliding. Meanwhile, as the probability of exceedance decreases, the probability of corresponding earthquake-induced landslides hazard probability and the area of high-hazard regions also significantly increase. Especially, the Pengguan complex rock mass in the southwest of the Longmenshan fault zone is the potential high-hazard area for coseismic landslides.
Landslides caused by mega earthquakes and other extreme climate change pose a major threat to lives and infrastructure. However, the lack of a detailed and timely landslide inventory and relevant risk assessment attributable to ongoing conflicts limits the effective prevention measures in Afghanistan. This study presents the first landslide inventory covering the whole nation of Afghanistan from 2015 to the present utilizing Google Earth Pro imagery and manual interpretation. Based on this inventory of 3,260 mapped landslides, we analyzed the distributional characteristics of landslides in Afghanistan and conducted a risk assessment that included landslide susceptibility and hazard, and vulnerability of the bearing areas. The existing regional studies attest to the accuracy and reliability of the inventory, and the results of the risk assessment using the optimized neural network method in this study are well validated. This study can provide a good database for the Afghan government to carry out relevant pre-disaster warnings and post-disaster reconstruction, which can help to delineate hotspots where landslides may occur, and reduce potential economic losses and human casualties from future landslides.
The Beidou surface deformation measuring radar can realize the three-dimensional deformation measurement of the whole scene by using a single receiver. Since the system uses an in-orbit satellite as a transmitter, its long-term measurement costs are much lower than GBSAR and space-borne InSAR systems. However, due to the small power of navigation star to earth, the signal to noise ratio of scene echo is low. Based on the comparison between the high precision GBSAR one-dimensional deformation measurement data and the deformation measurement results of the Beidou surface deformation measurement radar repeater, this paper initially verifies the deformation measurement capability of the Beidou surface deformation measurement radar. This paper first introduces the Beidou surface deformation measuring radar, and then lists the PS processing flow of the Beidou surface deformation measuring radar according to the characteristics of the system. Finally, a multi-system joint verification experiment is carried out in Zhujiawan area of Chongqing, and a cross-system measurement accuracy verification method is proposed. Based on the three days’ measurement results, it is proved that GBSAR and Beidou surface deformation measurement radar have the same measurement results, and the three-dimensional deformation measurement results of the strong scattering point are consistent with the actual situation. The experiment proves that the Beidou surface deformation measuring radar has the ability to measure the three-dimensional deformation of the whole scene and can be widely used in disaster prediction.
Seismic waves induced by incident acoustic waves from air disturbances can be used to image near-surface structures. In this article, we analyze seismic waveforms recorded by a dense array on the Xishancun landside in Li County, Sichuan Province, southwest China during the Lunar New Year’s Eve (27 January 2017). A total of eight event clusters have been identified as a result of firework explosions. For each cluster, which comprises dozens of individual events with high similarity, we manually pick arrival times of the first event recorded by the array and locate it with a grid-search method. We then rotate three-component waveforms of all events from the east, north, and vertical coordinate system to the local LQT coordinates (L, positive direction perpendicular to the landslide surface and pointing downwards; Q, positive direction is from the launch location of firework to the station along the landslide surface; T, perpendicular to the plane formed by the L and Q directions, and the selected positive direction of the T axis makes LQT form the left-hand coordinate system), and stack the LQT components for those events with cross-correlation values CC ≥ 0.8 with respect to the first event. Characteristics of the stacked LQT components are also examined. The particle motions at each station are retrograde ellipse in the frequency range of ∼5–50 Hz, suggesting air-coupled Rayleigh waves generated by the firework explosions. Spectrograms of the Rayleigh waves also show clear dispersions, which might be used to image near-surface velocity structures. Although we cannot directly extract the phase velocities due to the limitation of the seismic array, our study shows that the fireworks might provide a low-cost and easy-to-use seismic source for imaging near-surface structures.
Since the 2008 Wenchuan (Ms. 8.0) Earthquake, the foreland rivers of the Longmen Mountains have suffered from significant bed degradation, among which the Shi‐ting River has experienced the largest local degradation of more than 20 m in 7 years. Potential reasons of the dramatic degradation include: (1) sediment disconnectivity due to in‐channel weirs; (2) the mobilization effect on gravel of an increased sand supply as a result of earthquake‐induced landslides; and (3) sediment extraction due to intensive mining. In this paper, we study the complex interaction among the above‐mentioned factors in the Shi‐ting River, using a one‐dimensional river morphodynamic model. Simulation results show that in‐channel weirs can reduce bedload transport and lead to bed degradation that is proportional to weir height. When coupled with additional sand supply, the weirs preferentially trap gravel and deliver sand, augmenting the downstream mobility of gravel and thus the degradation. For the Shi‐ting River, the simulated bed degradation agrees well with the observation when an annual sediment mining of 16 million tons is implemented in the simulation, along with the effects of in‐channel weirs and sand supply. The contribution of sediment mining is one order of magnitude larger than the coupling effect of weirs and sand supply. Both the simulation and observation show that the largest bed degradation occurs downstream of the Renmin Weir, due to the large spatial interval between the Renmin Weir and the next grade control structure.
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To enhance the timeliness and accuracy of spatial prediction of coseismic landslides, we propose an improved three-stage spatial prediction strategy and develop corresponding hazard assessment software named Mat.LShazard V1.0. Based on this software, we evaluate the applicability of this improved spatial prediction strategy in six earthquake events that have occurred near the Sichuan–Yunnan region, including the Wenchuan, Ludian, Lushan, Jiuzhaigou, Minxian, and Yushu earthquakes. The results indicate that in the first stage (immediately after the quake event), except for the 2013 Minxian earthquake, the area under the curve (AUC) values of the modeling performance are above 0.8. Among them, the AUC value of the Wenchuan earthquake is the highest, reaching 0.947. The prediction results in the first stage can meet the requirements of emergency rescue by immediately obtaining the overall predicted information of the possible coseismic landslide locations in the quake-affected area. In the second and third stages, with the improvement of landslide data quality, the prediction ability of the model based on the entire landslide database is gradually improved. Based on the entire landslide database, the AUC value of the six events exceeds 0.9, indicating a very high prediction accuracy. For the second and third stages, the predicted landslide area (Ap) is relatively consistent with the observed landslide area (Ao). However, based on the incomplete landslide data in the meizoseismal area, Ap is much smaller than Ao. When the prediction model based on complete landslide data is built, Ap is nearly identical to Ao. This study provides a new application tool for coseismic landslide disaster prevention and mitigation in different stages of emergency rescue, temporary resettlement, and late reconstruction after a major earthquake.
Unlike strong earthquake-triggered or heavy rainfall-triggered landslides, silent large-scale landslides (SLL) occur without significant triggering factors and cause unexpected significant disaster risks and mass casualties. Understanding the initiation mechanism of SLLs is crucial for risk reduction. In this study, the mechanism of the Zhaobishan SLL was investigated, and the SLL was jointly controlled by weak-soil (fractured rock mass) and strong-water (abundant water replenishment) conditions under the impact of active tectonism and complex hydraulic properties. Strong tectonic uplift, high fault density, and historical earthquakes led to weak-soil conditions conducive to the Zhaobishan SLL. The combined effect of unique lithology, antiform, and cultivated land contributed to the water replenishment characteristics of extensive runoff confluence (3.16 times that of the landslide body) and supported long-distance groundwater replenishment, thereby forming strong-water conditions for the landslide. The amplified seepage amount caused the strength of the soil mass on the sliding surface to decrease to 0.4 times its initial strength, eventually triggering the Zhaobishan SLL, which occurred 4.6 days after the peak rainfall. Moreover, the landslide deposits have accumulated on the semi-diagenetic clay rock, thereby controlling the subsequent recurring debris flows in the Lengzi Gully. To reduce disaster risk of SLL in vulnerable mountainous regions, the water confluence area behind the main scarp of the landslides and the hysteresis characteristics between landslides and peak rainfall should be further considered, and recurring debris flows following massive landslides also should be focused.
The current research aims to examine the long-term evolution of the western cliffs of Lefkada Island following the occurrence of the last two strong earthquakes, on 14 August 2003 and 17 November 2015, respectively. Medium resolution satellite data (Landsat) and very high-resolution data (Ikonos, Pleiades, and airphotos) were processed in Google Earth Engine and Erdas imagine software, respectively. The study area covers a 20 km-long region of the western cliffs of Lefkada Island, extending from Egremni beach to the South to Komilio beach to the North. Relief, vegetation, and inclination changes were detected in the ArcGis environment. The results were associated with in situ data provided through the installation of a sediment trap. The analysis of the results proved that seismicity is the main factor that formed the western coastline of Lefkada Island, affecting the integrity of the cliffs. Specifically, large earthquakes cause immediate vegetation and topographic (inclination changes, mass movements) modifications in the western cliffs of the island. Meanwhile, small earthquakes (magnitudes < 4.1) contribute to the cliff’s evolution during the inter-seismic era. The intensity of these aforementioned changes was closely related to the seismic activity that occurred in the vicinity of the study area. In addition, it was found that precipitation and wind do not exert a similar influence on the cliff’s evolution.
Landslide movements and soil loss due to erosion have increased dramatically, causing numerous human and economic losses. Therefore, it is necessary to delimit these risks in order to prevent and mitigate the effects in natural parks of great value, as is the case of the Arribes del Duero Natural Park. As for landslide movements, they are evaluated by estimating the susceptibility to their occurrence, taking into account the different thematic layers: lithology, geomorphology (slopes, curvature, orientations), hydrogeology and vegetation, weighting each of them using the analytical hierarchy method. Then, by means of map algebra, the cartography of susceptibility to landslides is obtained. On the other hand, the RUSLE equation was used to calculate erosive losses. The results of the gravitational susceptibility are grouped into five classes: very high, high, medium, low and very low, so that the first corresponds to areas of high slope, without vegetation, south facing, with a lithology of quartzites, metapelites and gneisses (canyons, sloping valleys) and, on the contrary, the sectors of lower susceptibility coincide with flat areas, more density of vegetation, north facing, with conglomerates, cobbles, sands and clays, corresponding to erosion surfaces or valley bottoms. In terms of erosion results, the greatest losses are found in areas of steep slopes, with little or no vegetation and with poorly developed soils. Finally, taking into account the cartography of landslide risk, the cartography of potential water erosion and land use, it is possible to determine which conservation practices should be carried out, as well as the land uses that are less susceptible to these movements, highlighting in our study the importance of vineyards in their control.
In recent decades, natural disasters have increased drastically, with slope movements being the most damaging geological hazard, causing thousands of deaths and considerable economic losses. To reduce these losses, it is necessary to carry out cartographies that spatially delimit these risks, preventing and mitigating the effects through the analysis of susceptibility in areas of great environmental value, as is the case of the Arribes del Duero Natural Park. For this purpose, different statistical methods combined with Geographic Information Systems have been developed. The susceptibility assessment methodology is carried out by integrating different thematic layers: lithology, geomorphology (slopes, curvature, aspect), hydrogeology and vegetation, performing map algebra and taking into consideration their weighting using deterministic methods (analytical hierarchy method). The susceptibility results are grouped into Very High, High, Medium, Low and Very Low so that the areas of Very High susceptibility correspond to areas of the high slope, without vegetation, south facing, with a lithology of quartzites, metapelites, and gneisses (canyons, steep valleys) and, in the case of very low susceptibility, with a lithology of quartzites, metapelites, and gneisses, On the contrary, the sectors of lower susceptibility coincide with flat areas, denser vegetation, north facing, with a lithology of conglomerates, pebbles, sands and clays, such as erosion surfaces or valley bottoms. The analysis carried out in this current investigation will allow the territorial delimitation of problem areas and the establishment of risk mitigation and management measures.
In mountainous areas, landslides induced by destructive earthquakes are one of the main causes of human casualties, which is an important link in the chain of earthquake hazards. Earthquake-triggered landslides are mainly controlled by three factors, namely seismic property, topography, and geology. Many studies have been conducted on these controlling factors of earthquake-triggered landslides. However, little is known about the effect of coseismic displacement on the distribution of landslides under different slope aspects and slope angles, hindering our understanding of the mechanism of inducing landslides by the combination of surface displacement and slope geometry at the local scale and leading to controversial opinions about the abnormal number of earthquake-triggered landslides in several cases. Here, we took the 2008 Wenchuan Mw7.9 earthquake in China, the 2015 Gorkha Mw7.8 earthquake in Nepal, and the 2016 Kaikōura Mw7.8 earthquake in New Zealand as examples to investigate the relationship between the distribution of large earthquake-triggered landslides and the three-dimensional (3D) coseismic displacement field. We divided the landslide-prone area around the epicenter into regular grids and calculated the 3D coseismic displacement in each grid according to the radar satellite images and slip distribution model. Then, the 3D coseismic displacement was projected to two coordinate systems related to the slope where the landslides were located for statistical analysis. We determined that the surface uplift perpendicular to the slope is more likely to induce landslides, particularly when combined with large slope angles. Meanwhile, the number of landslides will be significantly reduced where the subsidence occurs. Regardless of uplift or subsidence, landslides are more likely to occur when the direction of coseismic horizontal displacement is far from the slope. The larger the slope angles are, the greater the effects of horizontal displacement and slope aspect. A dominant slope aspect also exists for earthquake-triggered landslides, which is different from the mean slope aspect calculated from the background topography. This dominant aspect angle is related to the focal mechanism and striking angle of surface rupture. These results indicate that we can simulate the 3D coseismic displacement field from known fault location and earthquake mechanism and combine the topographic data for landslide risk assessment in earthquake-prone mountainous areas to minimize the damage caused by possible earthquake-triggered landslides.
In recent decades, there have been several extreme earthquakes around the world, with the 2008 Wenchuan earthquake resulting in the highest number of landslides and substantial deposition of loose material on steep terrain and deep gullies, thereby promoting post-earthquake debris flows. Our monitoring indicates that debris flows have become long-term threats for over a decade after the earthquake, and it is crucial to determine the long-term spatial and temporal changes of debris flows and the evolving influence of condition factors in the earthquake-affected area. Thus, we established a database of 1628 debris flow events occurring between 2000 and 2020 within the 31,627 km2 area affected by the Wenchuan earthquake. The database included information on the date of occurrence, GNSS (Global Navigation Satellite System) coordinate at the gully outlet, event washout volume, and scale level obtained from various sources. Post-seismic debris flow activity witnessed a significant increase, followed by oscillation with rainfall and gradual weakening. Using the average washout volume for each scale in different periods, we applied a grid calculation method to characterize the debris flow intensity (DFI) using the total debris flow volume of cells in different epochs to study the spatial and temporal evolution of debris flow activity. Thus, based on the DFI calculation, we introduced the certainty factor and Geodetector to determine the dynamic evolution of condition factors. Our results indicate that lithology, rainfall, and slope degree primarily controlled debris flows before the earthquake. However, coseismic landslides became the main promoting factor after the earthquake. As loose materials were consumed, hydrodynamic and topographic factors began to play a more significant role in controlling debris flows. During this process, the requirements for rainfall, slope degree, and terrain relief amplitude increased over time. Based on the annual volume of debris flows from 2000 to 2020, we developed a preliminary conceptual model, which indicated that post-earthquake debris flow activity can be categorized into three phases: active (2008–2013), unstable (2014–2033), and recession (2034–2045), with the debris flow activity anticipated to return to pre-earthquake levels by 2045.
Regional modeling of landslide hazards is an essential tool for the assessment and management of risk in mountain environments. Previous studies that have focused on modeling earthquake-triggered landslides report high prediction accuracies. However, it is common to use a validation strategy with an equal number of landslide and non-landslide samples, scattered homogeneously across the study area. Consequently, there are overestimations in the epicenter area, and the spatial pattern of modeled locations does not agree well with real events. In order to improve landslide hazard mapping, we proposed a spatially heterogeneous non-landslide sampling strategy by considering local ratios of landslide to non-landslide area. Coseismic landslides triggered by the 2008 Wenchuan Earthquake on the eastern Tibetan Plateau were used as an example. To assess the performance of the new strategy, we trained two random forest models that shared the same hyperparameters. The first was trained using samples from the new heterogeneous strategy, and the second used the traditional approach. In each case the spatial match between modeled and measured (interpreted) landslides was examined by scatterplot, with a 2 km-by-2 km fishnet. Although the traditional approach achieved higher AUC ROC (0.95) accuracy than the proposed one (0.85), the coefficient of determination (R ² ) for the new strategy (0.88) was much higher than for the traditional strategy (0.55). Our results indicate that the proposed strategy outperforms the traditional one when comparing against landslide inventory data. Our work demonstrates that higher prediction accuracies in landslide hazard modeling may be deceptive, and validation of the modeled spatial pattern should be prioritized. The proposed method may also be used to improve the mapping of precipitation-induced landslides. Application of the proposed strategy could benefit precise assessment of landslide risks in mountain environments.
Landslides are notoriously difficult to predict because numerous spatially and temporally varying factors contribute to slope stability. Artificial neural networks (ANN) have been shown to improve prediction accuracy but are largely uninterpretable. Here we introduce an additive ANN optimization framework to assess landslide susceptibility, as well as dataset division and outcome interpretation techniques. We refer to our approach, which features full interpretability, high accuracy, high generalizability and low model complexity, as superposable neural network (SNN) optimization. We validate our approach by training models on landslide inventories from three different easternmost Himalaya regions. Our SNN outperformed physically-based and statistical models and achieved similar performance to state-of-the-art deep neural networks. The SNN models found the product of slope and precipitation and hillslope aspect to be important primary contributors to high landslide susceptibility, which highlights the importance of strong slope-climate couplings, along with microclimates, on landslide occurrences.
China has a significant portion of land in landslide-prone areas, and remote sensing technologies are becoming a tool of choice to investigate and monitor landslides. Although much progress has been made with remote sensing technologies and their applications in China, there is no systematical summary report. Thus, we summarize Synthetic Aperture Radar (SAR), optical remote sensing, and laser technologies currently being used in China, and their associated platforms (space-borne, air-borne, and ground-based). Multi-temporal optical images and time series SAR are often used to detect active landslides at time scales of years and months. The latest optical images and SAR intensity images are usual adopted to map fresh landslides, especial for coseismic landslides. LiDAR technology has been widely applied to identify ancient landslides. Combining advantages and limitations of every technology, an integrated space-air-ground collaborative investigation strategy has been proposed for early identification and early warning of landslides. Additionally, a comprehensive landslide investigation integrating multidisciplinary approaches, including remote sensing, geology, and geophysical exploration, could be a further developing trend, because remote sensing technologies just provide surface information, while a complete understanding of landslides requires more than surface information – knowledge of geotechnical parameters, geological features, and field conditions is also needed.
The 2008 Wenchuan earthquake triggered rapid local geomorphic changes, shifting abundant material through exogenic processes and generating vast amounts of loose material. The substantial material movement increased the geohazard (flash floods, landslides and debris flows) risks induced by extreme precipitation in the area. Intervention measures such as check dams, levees and vegetated slopes have been constructed in specific locations to reduce sediment transport and thereby mitigate the impact of ensuing geohazards. This study assessed the short–medium-term effects of interventions, including multiple control measures, in a post-earthquake mountainous region. Taking the Xingping valley as an example, we used CAESAR-Lisflood, a two-dimensional landscape evolution model, to simulate three scenarios, unprotected landscape, present protected landscape and enhanced protected landscape, between 2011 and 2013. We defined two indices to assess the intervention effects of the three scenarios by comparing the geomorphic changes and sediment yields. The results show that the mitigation measures are effective, especially the geotechnical engineering efforts in combination with ecological engineering in the upstream area. The spatial patterns of erosion and deposition change considerably due to the intervention measures. Additionally, the effectiveness of each intervention scenario shows a gradual decline over time, mainly due to the reduction in the reservoir storage capacity. The enhanced scenario performs better than the present one, with a more gradual downward trend of effectiveness. The simulation results evaluated the ability and effectiveness of comprehensive control measures and will support optimal mitigation strategies.
On September 5, 2022, an Ms6.8 earthquake struck Luding County, Sichuan Province, China. Through creating a coseismic landslide prediction model, we obtained the spatial distribution of the triggered geological hazards immediately after the earthquake. Through collecting all available multi-source optical remote sensing images of the earthquake-affected area via UAV and satellite platforms, the exact information of coseismic landslide was achieved by pattern recognition and visual inspection. According to the current results, the Luding earthquake triggered 5336 landslides with a total area of 28.53km2. The spatial distribution of the coseismic landslides is correlated statistically to various seismic, terrain, and geological factors, to evaluate their susceptibility at regional scale and to identify the most typical characteristics of these failures. The results reveal that the coseismic landslides mainly occurred on the sides of the Xianshuihe fault (within 1.2 km) and Dadu River (within 0.5 km) in striped patterns. They are concentrated in the regions with an elevation range of 1000–1800 m, a slope range of 25–55°, and lithologies of acid plutonic rocks, mixed sedimentary rocks, and siliciclastic sedimentary rocks. Besides, the coseismic landslides of the Luding earthquake are smaller in size and shallower than those triggered by the 2008 Wenchuan earthquake and the 2017 Jiuzhaigou earthquake. Rapidly achieving the spatial locations and distribution patterns of the coseismic landslides enables to provide effective support and guidance to emergency rescue, risk mitigation, and reconstruction planning.
Landslides pose a significant risk to human life. The Twisting Theory (TWT) and Crown Clustering Algorithm (CCA) are innovative adaptive algorithms that can determine the shape of a landslide and predict its future evolution based on the movement of position sensors located in the affected area. In the first part of this study, the TWT and CCA will be thoroughly explained from a mathematical and theoretical perspective. In the second part, these algorithms will be applied to real-life cases, the Assisi landslide (1995–2008) and the Corvara landslide (2000–2008). A correlation of 0.9997 was attained between the model estimates and the expert’s posterior measurements at both examined sites. The results of these applications reveal that the TWT can accurately identify the overall shape of the landslides and predict their progression, while the CCA identifies complex cause-and-effect relationships among the sensors and represents them in a clear, weighted graph. To apply this model to a wider area and secure regions at risk of landslides, it is important to emphasize its operational feasibility as it only requires the installation of GNSS sensors in a predetermined grid in the target area.
A cataclastic rock mass is a poor type of engineering geological rock mass. The determination of the shear failure characteristics and shear strengths of cataclastic rock masses can provide key basis for the design and construction of infrastructure. Physical model samples of a sandstone cataclastic rock mass were first produced by a combination of three-dimensional (3D) printing technology and manual pouring. Shear tests were conducted with respect to the shear stresses parallel to the trace line plane and perpendicular to the trace line plane of the cataclastic rock mass model. Based on an extensive analysis of the shear failure characteristic, shear stress evolution characteristic curve and shear strength. When the shear stress was parallel to the trace line plane, and when the rock block that was cut and confined by the trace line exhibited a significant tip, the end stress concentration effect of the cataclastic rock mass was more significant during the shear process with the anisotropy of the rock block increased. In addition, the shapes of the rock blocks that were confined and cut by the joints were the main influencing factors of the strength of the cataclastic rock mass. When the shear stress was perpendicular to the trace line plane, the structure of the rock wall was the main influencing factor of the deformation and failure process of the shear failure plane and the shear strength. The physical and mechanical properties of the shear failure plane of the cataclastic rock mass were found to be closely related to the joint–rock wall system characteristics of the cataclastic rock mass. Therefore, when determining the shear strength of cataclastic rock mass, the shape and combination form of the rock block, shear direction, and structural failure characteristics of the rock wall should be comprehensively considered during the shear process.
Landslides are destructive to property, infrastructure and people in potential landslide zones. Identifying potential landslides is an important step in landslide preparedness and will help develop sustainable landslide risk management. Interferometric synthetic aperture radar (InSAR) and landslide susceptibility assessment (LSA) have poor reliability in individually identifying potential landslide zones. This study proposes a threshold model for identifying potential landslide zones that fuses the InSAR two-dimensional (vertical direction and east-west direction) deformation rates and LSA results. The deformation rate threshold for this threshold model is |DU| or |DE|>10 mm/year (DU and DE are the vertical and the east-west deformation rates, respectively), with threshold levels of LSA set to high and very high susceptibility. The criterion of potential landslide zones is ((|DU| or |DE|>10 mm/year) ∩ (high or very high susceptibility of LSA)), and points with similar deformation and susceptibility are clustered by the K-means algorithm, and the potential landslide zones are obtained by elimination, smooth and speckle removal operations. The results showed that the InSAR two-dimensional deformation rates DU and DE were −32.71 − 12.72 mm/year and −14.88 − 24.81 mm/year, respectively, during 2015–2020 in Lanzhou city. The LSA showed that very low, low, medium, high, and very high susceptibility accounted for 55.36%, 10.54%, 21.37%, 9.63%, 3.1% of the total area, respectively. Using the proposed threshold model, 117 potential landslide zones were identified in Lanzhou. The overlap rate between potential landslide zones and the landslide inventory was 40.17%, indicating that about 40% of the potential landslide zones overlapped with the landslide inventory and that about 60% were new potential landslide zones in Lanzhou. The feasibility of the threshold model in identifying potential landslides was confirmed by field research and time-series InSAR analysis on typical areas (L1, L2, L3, and L4), which had large deformation variables and landslide features. The proposed method can quickly determine the spatial location of potential landslides, providing targeting data for landslide field investigations, technical support for rapid early landslide identification, and data support for landslide management and prevention in Lanzhou.
Landslide databases are a potential tool for the analysis of landslide susceptibility, hazard,
and risk. Additionally, the spatio-temporal distribution of landslides and their correlation
with their triggering factors are inputs that facilitate the evaluation of landslide prediction
models and the determination of thresholds necessary for early warning systems (EWS).
This study presents an analysis of four widely known global databases—the International
Disaster database (EM-DAT), the Disaster Inventory System (DesInventar), the Global
Landslide Catalog (GLC), and the Global Fatal Landslide database (GFLD)—which con-
tain relevant landslide information for different regions of the world. These databases were
analysed and compared by means of the spatio-temporal distributions of their records.
Subsequently, these databases were merged and depurated to obtain a more robust data-
base, namely the Unified Global Landslide Database (UGLD), with 161 countries, 37,946
landslides, and 185,753 fatalities registered between 1903 and 2020. The merging process
among the databases resulted in a small number of repeated landslides, indicating that the
databases collect very different landslide information and complement each other. Finally,
an update of the spatial and temporal analysis of landslides in the world was performed
with the new database, in which patterns, trends, and the main triggers were presented and
analysed. The results obtained from the analysis of the UGLD database show the American
and Asian continents as the continents with the highest number of landslides and asso-
ciated fatalities, showing a bimodal and unimodal annual temporal pattern, respectively.
Regarding the most frequent triggers of landslides, rainfall, anthropogenic intervention,
and earthquakes stand out
Of the catastrophic earthquakes over the past few decades, the 2008 Wenchuan earthquake triggered the greatest number of landslides and deposited a large amount of loose material on steep terrains and deep gullies, which was highly conducive to the occurrence of post-earthquake debris flows. It is of great importance to clarify the evolution of debris flow activity for hazard evaluation, prediction, and prevention after a strong earthquake, especially in the face of large debris flow hazards. We established a long-time span database consisting of 1668 debris flow events before and after the earthquake, with information including the occurrence time, location, and scale (small, medium, and large). In order to analyze how the environmental background before and after the earthquake controlled the debris flow activity, we examined various controlling factors, including the material source, topography (relative relief and slope degree), rainfall, normalized vegetation index, and lithology. After completing the analysis of the spatial and temporal evolution of the debris flow events in the database, a 10 × 10 km grid was introduced to grade the controlling factors in ArcGIS. Based on the same grid, the density of debris flow events for each scale in different time periods was calculated and graded. We introduced the certainty factor to figure out the spatial–temporal relationships between debris flow activities at each scale and the controlling factors. The results can provide guidance on how to dynamically adjust our strategies for debris flow prevention after a strong earthquake. Lastly, Spearman rank correlation analysis was performed to clarify the variation in the magnitude of the influence of controlling factors on the debris flow activities of different scales with time. This can provide a reference for the dynamic evaluation of debris flow hazards in the Wenchuan earthquake-affected area.
Garhwal Himalaya is the worst affected landslide prone region in Indian subcontinent mainly due to its complex geological settings and active tectonic activities. The data showed that every year, around 400 fatalities occur in Himalayan terrain due to landslide. In the current study, we have mapped the landslide susceptibility zones in the segment of Garhwal Himalaya using robust machine and deep learning algorithms. Individual machine and deep learning models have its own limitations like low generation capacity with nonlinear functions to describe the intricate relationship among predictors. In this study total five models i.e., SVM (Support Vector Machine), RF (Random Forest), bagging, ANN (Artificial Neural Network), DLNN (Deep Learning Neural Network) have been used along with twenty landslide controlling factors. Here, the principal objective of the study is to precisely delineate landslide susceptibility zones of the Garhwal Himalaya. The selecting factors have been considered through multi-collinearity test and information gain ratio statistics and the previous landslide points have been taken as training (70%) and testing (30%) dataset. According to area under curve value (AUC), the DLNN technique has high capability (AUC = 0.925) and accuracy for landslide area demarcation. The approach of integrated physical and social factors creates more precise prediction aptitude that can support large scale landslide management. These high precision models identified most of the parts of Rudraprayag and Tehri Garhwal as a very high landslide susceptibility zone. The generated maps can assist to policy makers for micro scale landslide management and sustainable land use planning particularly in Himalayan terrain.
Driven by earthquakes and intense rainfall, steep tectonically active mountains are hotspots of terrestrial organic carbon mobilization from soils, rocks, and vegetation by landslides into rivers. Subsequent delivery and fluvial mobilization of organic carbon from different sources can impact atmospheric CO2 concentrations across a range of timescales. Extreme landslide triggering events can provide insight on processes and rates of carbon export. Here we used suspended sediment collected from 2005 to 2012 at the upper Min Jiang, a main tributary of the Yangtze River on the eastern margin of the Tibetan Plateau, to compare the erosion of terrestrial organic carbon before and after the 2008 Wenchuan earthquake and a storm-derived debris flow event in 2005. To constrain the source of riverine particulate organic carbon (POC), we quantified lignin phenols and n-alkanoic acids in the suspended sediments, catchment soils and landslide deposits. We found that riverine POC had higher inputs of less-degraded, discrete organic matter at high suspended sediment loads, while the source of POC seemed stochastic at low suspended sediment concentrations. The debris flow in 2005 mobilized a large amount of POC, resulting in an export of lignin within a single day equivalent to a normal year. In comparison, the 2008 Wenchuan earthquake increased the flux of POC and particulate lignin, albeit with limited impact on POC sources in comparison to seasonal variations. Our results highlight the important role of episodic events in the fluvial export of terrestrial carbon.
Cycles of stress build-up and release are inherent to tectonically active planets. Such stress oscillations impart strain and damage, prompting mechanically loaded rocks and materials to fail. Here, we investigate, under uniaxial conditions, damage accumulation and weakening caused by time-dependent creep (at 60, 65, and 70% of the rocks’ expected failure stress) and repeating stress oscillations (of ± 2.5, 5.0 or 7.5% of the creep load), simulating earthquakes at a shaking frequency of ~ 1.3 Hz in volcanic rocks. The results show that stress oscillations impart more damage than constant loads, occasionally prompting sample failure. The magnitudes of the creep stresses and stress oscillations correlate with the mechanical responses of our porphyritic andesites, implicating progressive microcracking as the cause of permanent inelastic strain. Microstructural investigation reveals longer fractures and higher fracture density in the post-experimental rock. We deconvolve the inelastic strain signal caused by creep deformation to quantify the amount of damage imparted by each individual oscillation event, showing that the magnitude of strain is generally largest with the first few oscillations; in instances where pre-existing damage and/or the oscillations’ amplitude favour the coalescence of micro-cracks towards system scale failure, the strain signal recorded shows a sharp increase as the number of oscillations increases, regardless of the creep condition. We conclude that repetitive stress oscillations during earthquakes can amplify the amount of damage in otherwise mechanically loaded materials, thus accentuating their weakening, a process that may affect natural or engineered structures. We specifically discuss volcanic scenarios without wholesale failure, where stress oscillations may generate damage, which could, for example, alter pore fluid pathways, modify stress distribution and affect future vulnerability to rupture and associated hazards.
Ground shaking on steep slopes often triggers numerous landslides, which dramatically modify the landscape and have long-term effects on vegetation dynamics. However, we still have a limited understanding of the quantitative topographic evolution and the duration of post-seismic impacts on the landscapes due to the lack of long-term consistent observation, especially in low-elevation mountain regions. To address this issue, we used high-resolution pre-and post-earthquake DEMs to investigate topographic changes, as well as multi-period and multi-scale remote sensing images to analyze the post-seismic landslides and vegetation recovery in the sites affected by the Mw 6.6 2004 Chuetsu earthquake, Japan. Using a vegetation recovery rate (VRR) time series from 2004 to 2021, we examined the decaying tendency of post-seismic landslide activities and predicted the vegetation recovery rate. Our findings indicate that the Chuetsu earthquake mostly steepens and roughens the terrain in low-elevation areas. The changes to slope aspects are associated with coseismic lateral displacement. The vegetation damage area accounted for 87.98 % of the entire area after the earthquake, and the VRR reaches 85.55 % by June 2021. The number of active landslides decreased to 14.45 % after 15 years. Meanwhile, we predict that vegetation recovery areas will be restored to pre-earthquake levels in 2024, and the landslide activity rate will decrease by less than 1 % in 2026, indicating a stable hillslope devoid of debris flows in the future.
From 12 to 14 August 2010, heavy rainstorms occurred in the Sichuan
province in SW China in areas which were affected by the 2008 Wenchuan
Earthquake, inducing catastrophic debris flows. This disaster is named
as "the 8.13 debris flows". The results of the research presented in
this paper show that the 8.13 debris flows are characterized by a
simultaneous occurrence, rapid-onsets, destructive impacts, and disaster
chain effects. They are located along the seismic fault, because the
source materials mainly originate from loose deposits of landslides
which were triggered by the Wenchuan Earthquake. The presence of large
amounts of these loose materials on the slopes and the development of
high intensity rainfall events are the main causes for the formation of
these debris flows. The study of the 8.13 debris flows can provide a
benchmark for the analysis of the long-term evolution of these debris
flows in order to make proper engineering decisions. A flexible drainage
system is proposed in this paper as a preventive measure to mitigate the
increasing activity of these debris flows in the earthquake-affected
area.
The Mw 7.9 Wenchuan, China, earthquake ruptured two large thrust faults along the Longmenshan thrust belt at the eastern margin of the Tibetan Plateau. This earthquake generated a 240-km-long surface rupture zone along the Beichuan fault and an additional 72-km-long surface rupture zone along the Pengguan fault. Maximum vertical and horizontal offsets of 6.5 m and 4.9 m, respectively, were measured along the Beichuan fault. A maximum vertical offset of 3.5 m was measured along the Pengguan fault. Coseismic surface ruptures, integrated with aftershocks and industry seismic profiles, show that two imbricate structures have ruptured simultaneously, resulting in the largest continental thrust event ever documented. Large oblique thrusting observed during this earthquake indicates that crustal shortening is an important process responsible for the high topography in the region, as everywhere along the edge of Tibetan Plateau.
Earthquake-triggered landslide dams are potentially dangerous disrupters of water and sediment flux in mountain rivers, and capable of releasing catastrophic outburst flows to downstream areas. We analyze an inventory of 828 landslide dams in the Longmen Shan mountains, China, triggered by the Mw 7.9 2008 Wenchuan earthquake. This database is unique in that it is the largest of its kind attributable to a single regional-scale triggering event: 501 of the spatially clustered landslides fully blocked rivers, while the remainder only partially obstructed or diverted channels in steep watersheds of the hanging wall of the Yingxiu-Beichuan Fault Zone. The size distributions of the earthquake-triggered landslides, landslide dams, and associated lakes (a) can be modeled by an inverse gamma distribution; (b) show that moderate-size slope failures caused the majority of blockages; and (c) allow a detailed assessment of seismically induced river-blockage effects on regional water and sediment storage. Monte Carlo simulations based on volumetric scaling relationships for soil and bedrock failures respectively indicate that 14% (18%) of the estimated total coseismic landslide volume of 6.4 (14.6) × 109 m3 was contained in landslide dams, representing only 1.4% of the > 60,000 slope failures attributed to the earthquake. These dams have created storage capacity of ~ 0.6 × 109 m3 for incoming water and sediment. About 25% of the dams containing 2% of the total river-blocking debris volume failed one week after the earthquake; these figures had risen to 60% (~ 20%), and > 90% (> 90%) within one month, and one year, respectively, thus also emptying ~ 92% of the total potential water and sediment storage behind these dams within one year following the earthquake. Currently only ~ 0.08 × 109 m3 remain available as natural reservoirs for storing water and sediment, while ~ 0.19 × 109 m3, i.e. about a third of the total river-blocking debris volume, has been eroded by rivers. Dam volume and upstream catchment area control to first order the longevity of the barriers, and bivariate domain plots are consistent with the observation that most earthquake-triggered landslide dams were ephemeral. We conclude that the river-blocking portion of coseismic slope failures disproportionately modulates the post-seismic sediment flux in the Longmen Shan on annual to decadal timescales.
Floods from failures of landslide dams can pose a hazard to people and
property downstream, which have to be rapidly assessed and mitigated in
order to reduce the potential risk. The Tangjiashan landslide dam
induced by the Mw = 7.9 2008 Wenchuan earthquake had
impounded the largest lake in the earthquake affected area with an
estimated volume of 3 × 108 m3, and the
potential catastrophic dam breach posed a serious threat to more than
2.5 million people in downstream towns and Mianyang city, located 85 km
downstream. Chinese authorities had to evacuate parts of the city until
the Tangjiashan landslide dam was artificially breached by a spillway,
and the lake was drained. We propose an integrated approach to simulate
the dam-breach floods for a number of possible scenarios, to evaluate
the severity of the threat to Mianyang city. Firstly, the
physically-based BREACH model was applied to predict the flood
hydrographs at the dam location, which were calibrated with
observational data of the flood resulting from the artificial breaching.
The output hydrographs from this model were inputted into the 1-D-2-D
SOBEK hydrodynamic model to simulate the spatial variations in flood
parameters. The simulated flood hydrograph, peak discharge and peak
arrival time at the downstream towns fit the observations. Thus this
approach is capable of providing reliable predictions for the decision
makers to determine the mitigation plans. The sensitivity analysis of
the BREACH model input parameters reveals that the average grain size,
the unit weight and porosity of the dam materials are the most sensitive
parameters. The variability of the dam material properties causes a
large uncertainty in the estimation of the peak flood discharge and peak
arrival time, but has little influence on the flood inundation area and
flood depth downstream. The effect of cascading breaches of smaller dams
downstream of the Tangjiashan dam was insignificant, due to their rather
small volumes, which were only 2% of the volume of the Tangjiashan lake.
The construction of the spillway was proven to have played a crucial
role in reducing the dam-breach flood, because all the other natural
breach scenarios would have caused the flooding of the downstream towns
and parts of Mianyang city. However, in retrospect improvements on the
spillway design and the evacuation planning would have been possible.
The dam-break flood risk will be better controlled by reducing the
spillway channel gradient and the porosity of the coating of the channel
bottom. The experience and lessons we learned from the Tangjiashan case
will contribute to improving the hazard mitigation and risk management
planning of similar events in future.
Recent two-dimensional dynamic simulations of dip-slip faulting (Niel-sen, 1998; Oglesby et al., 1998, 2000; Shi et al., 1998) have shown that the asym-metric geometry of dip-slip faults that intersect the free surface can have large effects on the dynamics of earthquake rupture. The nonvertical dip angle of such faults leads to larger motion on the footwall than the hanging wall, as well as much larger motion from thrust/reverse faults than from normal faults with the same geometry and stress magnitudes. In the present work we perform full three-dimensional simulations of thrust/reverse, normal, and strike-slip faults, and show that the same effects exist in three dimensions. Strike-slip fault motion is either in between or lower than the motion of both dip-slip faults. Additional three-dimensional effects include strong rake rotation at the free surface. The results confirm the findings of the previous studies and further elucidate the dynamic effects of the free surface on fault rupture, slip, and ground motion. They are also borne out by early analyses of the 1999 Chi-Chi (Taiwan) thrust earthquake, which displayed higher motion on the hanging wall than on the footwall, and a strong oblique component of motion at the surface.
The disastrous 12 May 2008 Wenchuan earthquake in China took the local population as well as scientists by surprise. Although the Longmen Shan fault zone?which includes the fault segments along which this earthquake nucleated?was well known, geologic and geodetic data indicate relatively low (<3 mm yr-1) deformation rates. Here we invert Global Positioning System and Interferometric Synthetic Aperture Radar data to infer fault geometry and slip distribution associated with the earthquake. Our analysis shows that the geometry of the fault changes along its length: in the southwest, the fault plane dips moderately to the northwest but becomes nearly vertical in the northeast. Associated with this is a change in the motion along the fault from predominantly thrusting to strike-slip. Peak slip along the fault occurs at the intersections of fault segments located near the towns of Yingxiu, Beichuan and Nanba, where fatalities and damage were concentrated. We suggest that these locations represent barriers that failed in a single event, enabling the rupture to cascade through several fault segments and cause a major moment magnitude (Mw) 7.9 earthquake. Using coseismic slip distribution and geodetic and geological slip rates, we estimate that the failure of barriers and rupture along multiple segments takes place approximately once in 4,000 years.
Recent two-dimensional dynamic simulations of dip-slip faulting (Nielsen, 1998; Oglesby et al., 1998, 2000; Shi et al., 1998) have shown that the asymmetric geometry of dip-slip faults that intersect the free surface can have large effects on the
dynamics of earthquake rupture. The nonvertical dip angle of such faults leads to larger motion on the footwall than the hanging
wall, as well as much larger motion from thrust/reverse faults than from normal faults with the same geometry and stress magnitudes.
In the present work we perform full three-dimensional simulations of thrust/reverse, normal, and strike-slip faults, and show
that the same effects exist in three dimensions. Strike-slip fault motion is either in between or lower than the motion of
both dip-slip faults. Additional three-dimensional effects include strong rake rotation at the free surface. The results confirm
the findings of the previous studies and further elucidate the dynamic effects of the free surface on fault rupture, slip,
and ground motion. They are also borne out by early analyses of the 1999 Chi-Chi (Taiwan) thrust earthquake, which displayed
higher motion on the hanging wall than on the footwall, and a strong oblique component of motion at the surface.
This paper presents the preliminary results of an extensive study of the mapping the distribution of landslides triggered by the Wenchuan earthquake in Sichuan Province, China, on 12 May 2008. An extensive landslide interpretation was carried out using a large set of optical high resolution satellite images (e.g. ASTER, ALOS, Cartosat-1, SPOT-5 and IKONOS) as well as air photos for both the pre- and post-earthquake situation. Landslide scarps were mapped as points using multi-temporal visual image interpretation taking into account shape, tone, texture, pattern, elevation and ridge and valley orientation. Nearly 60,000 individual landslide scarps were mapped. The landslide distribution map was compared with the inventory map that was prepared directly after the earthquake, which contains about 11,000 individual landslide points, through the calculation of normalized landslide isopleths maps. Remarkable differences were observed, as the earlier inventory mapping did not consider the pre-earthquake situation and did not consider all individual landslides.As part of the landslide inventory, landslides were identified that had blocked the drainage and had formed landslide dams. The landslide distribution was compared with a number of aspects, such as the seismic parameters (distance to epicenter, distance to fault rupture, co-seismic fault geometry and co-seismic slip distribution), and geology. The most remarkable correlation found was with the co-seismic slip distribution and the fault geometry. Landslide distribution in the section of the fault that had mainly a thrust component with low angle fault plane was found to be much higher than the sections that had steeper fault angles and a major strike slip component.
The Wenchuan earthquake on May 12, 2008 triggered massive landslides and a subsequent, strong rainfall prompted the development of new landslides as well as the reactivation of some pre-existing landslides. The highest seismic intensity zone of the Wenchuan earthquake in Beichuan, China was selected as a case study to analyze the influence of the earthquake and the subsequent, heavy rains on landslide evolution. We selected this study area (414 km 2) since it was close to the coseismic surface rupture and because it suffered strong ground motion. Based on the interpretation of high-resolution aerial photographs and remote sensing imagery combined with field investigation, 40 pre-earthquake landslides and 2221 coseismic landslides were identified with total landslide areas of 2.68 km 2 and 30.81 km 2 , respectively. There were 134 large (over 50,000 m 2), co-seismic landslides that covered a surface area of 15.54 km 2 and represented approximately 50.4% of the total area of the co-seismic landslides. The coseismic landslides were mainly located on the hanging wall of the causative fault and on the steep, valley sides of the Jian River and its tributaries. A strong rainfall event occurred four months after the Wenchuan earthquake and induced 969 new landslides (which covered a 6.90 km 2 area) and enlarged 169 existing landslides (2.48 km 2). The landslides were identified in SPOT5 images. Ultimately, we found that earthquake tremors and the subsequent rainstorm severely disturbed the surface strata, resulting in a large number of landslides.
The 2008 Wenchuan earthquake in Sichuan of China was the result of quake-triggering along an active several hundred-kilometer-long
fault. The subsequent landslides and debris flow geohazards are dominating factors in planning post-disaster recovery and
rebuilding. This paper presents recommendations for coping with large-scale geohazards and disasters. It is essential to establish
a national emergency management system for huge scale catastrophe and earthquake precursor identification. Town construction
must be kept away from active faults, especially to improve town safety in areas with high risk of seismic and geological
hazards, and it is important to improve geohazard investigation and remediation for mountain areas that have become loosened
by earthquake activity. Geological factors must be better understood to reduce direct and secondary risks and effects of earthquakes.
Site selections for public relocation require clear and informed analysis of geological and social risk reduction, so that
relocation, infrastructure reconstruction, and commemorative relic-sites can be protected.
KeywordsWenchuan Earthquake–Geohazard–Reconstruction
The 2008 Wenchuan earthquake (M
s = 8.0; epicenter located at 31.0° N, 103.4° E), with a focal depth of 19.0km was triggered by the reactivation of the Longmenshan
fault in Wenchuan County, Sichuan Province, China on 12 May 2008. This earthquake directly caused more than 15,000 geohazards
in the form of landslides, rockfalls, and debris flows which resulted in about 20,000 deaths. It also caused more than 10,000
potential geohazard sites, especially for rockfalls, reflecting the susceptibility of high and steep slopes in mountainous
areas affected by the earthquake. Landslide occurrence on mountain ridges and peaks indicated that seismic shaking was amplified
by mountainous topography. Thirty-three of the high-risk landslide lakes with landslide dam heights greater than 10m were
classified into four levels: extremely high risk, high risk, medium risk, and low risk. The levels were created by comprehensively
analyzing the capacity of landslide lakes, the height of landslide dams, and the composition and structure of materials that
blocked rivers. In the epicenter area which was 300km long and 10km wide along the main seismic fault, there were lots of
landslides triggered by the earthquake, and these landslides have a common characteristic of a discontinuous but flat sliding
surface. The failure surfaces can be classified into the following three types based on their overall shape: concave, convex,
and terraced. Field evidences illustrated that the vertical component of ground shaking had a significant effect on both building
collapse and landslide generation. The ground motion records show that the vertical acceleration is greater than the horizontal,
and the acceleration must be larger than 1.0g in some parts along the main seismic fault. Two landslides are discussed as
high speed and long runout cases. One is the Chengxi landslide in Beichuan County, and the other is the Donghekou landslide
in Qingchuan County. In each case, the runout process and its impact on people and property were analyzed. The Chengxi landslide
killed 1,600 people and destroyed numerous houses. The Donghekou landslide is a complex landslide–debris flow with a long
runout. The debris flow scoured the bank of the Qingjiang River for a length of 2,400m and subsequently formed a landslide
dam. This landslide buried seven villages and killed more than 400 people.
The Ms 8.0 Wenchuan earthquake of May 12, 2008 is one of the most disastrous earthquakes in China. The earthquake triggered tens of thousands of landslides over a broad area, including shallow, disrupted landslides, rock falls, deep-seated landslides, and rock avalanches, some of which buried large sections of some towns and dammed the rivers. The purpose of this study is to investigate correlations between the occurrence of landslides with geologic and geomorphologic conditions, and seismic parameters. Over 56,000 earthquake-triggered landslides, with a total area of 811 km2, are interpreted using aerial photographs and remote sensing images taken following the earthquake. The spatial distribution of these landslides is analyzed statistically using both landslide-point density (LPD), defined as the number of landslides per square kilometer, and landslide-area density (LAD), the percentage of the area affected by landslides, to determine how the occurrence of landslides correlates with distance from the epicenter, distance from the major surface rupture, seismic intensity and peak ground acceleration (PGA), slope angle, slope aspect, elevation, and lithology. It is found that both LAD and LPD have strong positive correlations with slope steepness, distance from the major surface rupture and seismic intensity, and that Pre-Sinian schist, and Cambrian sandstone and siltstone intercalated with slate have the most concentrated landslide activities, followed by the Permian limestone intercalated with shale, and Devonian limestone. Statistical analyses also indicate that the major surface rupture has influence on the spatial distribution of landslides, because LAD and LPD are relatively higher on the hanging wall than on the footwall. However, the correlation between the occurrence of landslides with distance from the epicenter of the earthquake is complicated, rather than a relatively simple negative correlation as found from other reported cases of earthquakes. This is possibly due to complicated rupture processes of the earthquake.
Satellite images and aerial-photography following the Wenchuan earthquake show that a broad area experienced severe landsliding in association with the main earthquake and aftershocks. A zone of high density landsliding (> 10% landslide surface area affected) stretches for ~ 240 km along the earthquake region, in proximity to the Yingxiu, Beichuan and Pennguan faults, which ruptured during the earthquake. The width of this severe landsliding zone varies along the strike, from ~ 25–30 km wide in the southwestern section of the earthquake region, to ~ 3–5 in the northeastern section. These variations coincide with differences in hillslope gradients, bedrock lithologies, co-seismic slip and ground shaking observed in these sections of the earthquake region. In general, there is good correlation between the magnitude and distribution of ground shaking experienced during the earthquake and mapped landslide density, though limited data and varying fault models prevent any in-depth comparison with high-resolution maps of ground shaking experienced. Landslides associated with Wenchuan earthquake highlight interesting aspects of erosion and tectonic evolution of the Longmen Shan. Short-term erosion rates in the Longmen Shan region measured from cosmogenic nuclides prior to the earthquake were ~ 0.2–0.3 mm/yr, reflecting the last 2000–3000 years — a time period shorter than the estimated recurrence interval of large earthquakes along the fault that ruptured, while long-term erosion rates measured by low-temperature thermochronology were higher, 0.5–0.7 mm/yr for the last 8–10 Ma. Integrating the total amount of erosion associated the earthquake into the short-term erosion rate estimates pushes the rate much higher. This suggests that the earthquake and associated landslide erosion was necessary for the landscape to ‘catch-up’ and balance the long-term tectonic growth of the Longmen Shan, particularly in the southwestern section of the earthquake region. Taken together, the earthquake and associated landslide erosion can be seen as the most recent expression of the rapid deformation/uplift and erosion that previous geomorphic evidence and geodynamic models had argued for along Longmen Shan front.
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