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Illustration of how sediment from earthquake‐triggered landslides that is delivered to the fluvial system can lead to river‐channel aggradation. This results in a decrease in accommodation space and thus increases the probability and severity of overbank flooding. The sequence of events described represents a cascade of sedimentary hazards that can hamper reconstruction following earthquakes. (a) River channels prior to delivery of sediment from landslides. (b) Aggraded channels that can no longer accommodate storm flow, leading to flooding (after Dingle et al., 2017). (c) Imagery and photographs of the coseismic Wenjia landslide and the Mianyuan River in Sichuan, China, immediately after and then years after the earthquake. The landslide deposits were remobilized and developed into a catastrophic debris flow during the 13 August 2010 rainstorm. The debris flow partially dammed the Mianyuan River, causing flooding of the newly reconstructed Qingping town. Red outlined buildings were partially buried by the post‐seismic debris flow.
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Large earthquakes initiate chains of surface processes that last much longer than the brief moments of strong shaking. Most moderate‐ and large‐magnitude earthquakes trigger landslides, ranging from small failures in the soil cover to massive, devastating rock avalanches. Some landslides dam rivers and impound lakes, which can collapse days to cent...
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As natural disasters are induced by geodynamic activities or abnormal changes in the environment, geological hazards tend to wreak havoc on the environment and human society. Recently, the dramatic increase in the volume of various types of Earth observation 'big data' from multiple sources, and the rapid development of deep learning as a state-of-...
Citations
... This weakening is caused by cracks, micro-cracks, and/or fissures that develop within brittle rock or cohesive soils due to permanent slope displacement during ground shaking (e.g., Arata et al., 2020;Gischig et al., 2016;Parker et al., 2015;Wolter et al., 2016). It alters post-seismic hillslope conditions, reduces rainfall thresholds, and makes hillslopes more susceptible than they were in pre-seismic conditions (e.g., Fan et al., 2019;Tanyaş et al., 2021). ...
Reduction in shear strength (RSS) of hillslope materials due to earthquakes have been rarely discussed numerically in regional scale analyses. Despite the limited literature, an empirical relationship between peak ground acceleration (PGA) and RSS was proposed based on Newmark's permanent-deformation analysis coupled with static limit equilibrium approach. However, the empirical relationship is solely based on co- and post-seismic landslide inventories associated with the 2008 Wenchuan earthquake and transferability of the approach is yet to be tested. To address this issue, we apply the same method to areas affected by the 2015 Gorkha and 2018 Palu earthquakes. Our results showed a good agreement in variation of the RSS with respect to PGA. This suggests that the approach is transferable for the estimation of co-seismic hillslope weakening in other geographies. We also analyzed the RSS in sedimentary, metamorphic and igneous rocks. Our results showed that igneous rocks feature the highest RSS in response to given ground shaking and it is followed by metamorphic and sedimentary rocks. Ultimately, we also discussed the RSS likely caused by precipitation events. Our findings imply that the RSS caused by 0.1 g of ground shaking may be 14 times larger than RSS due to precipitation. This argument needs further analyses but overall, our findings provide new insights into hillslope weakening in relation to both earthquake and precipitation.
... The seismic risk to such lowlands is broadly recognized [11][12][13][14][15][16] but remains poorly constrained with respect to response magnitude and cascading hazards 17 . In part, the large size of these basins means that they often extend >100 km from the nearest faults and may only be impacted by larger, less frequent events for which there are scant historical records. ...
Earthquakes present severe hazards for people and economies and can be primary drivers of landscape change yet their impact to river-channel networks remains poorly known. Here we show evidence for an abrupt earthquake-triggered avulsion of the Ganges River at ~2.5 ka leading to relocation of the mainstem channel belt in the Bengal delta. This is recorded in freshly discovered sedimentary archives of an immense relict channel and a paleo-earthquake of sufficient magnitude to cause major liquefaction and generate large, decimeter-scale sand dikes >180 km from the nearest seismogenic source region. Precise luminescence ages of channel sand, channel fill, and breached and partially liquefied floodplain deposits support coeval timing of the avulsion and earthquake. Evidence for reorganization of the river-channel network in the world’s largest delta broadens the risk posed by seismic events in the region and their recognition as geomorphic agents in this and other tectonically active lowlands. The recurrence of comparable earthquake-triggered ground liquefaction and a channel avulsion would be catastrophic for any of the heavily populated, large river basins and deltas along the Himalayan arc (e.g., Indus, Ganges, Brahmaputra, Ayeyarwady). The compounding effects of climate change and human impacts heighten and extend the vulnerability of many lowlands worldwide to such cascading hazards.
... Simultaneously, with the gradual coarsening of channel material, the rainfall threshold for debris flow occurrence gradually increased over time (Fan et al. 2019). Therefore, the activity of debris flow has the spatiotemporal evolution characteristics after the Wenchuan earthquake. ...
... Additionally, numerous previous studies indicated that the rainfall threshold for debris flows initiation gradually increased after the Wenchuan earthquake Fan et al. 2019). However, our analysis shows that the hourly rainfall intensity and cumulative rainfall that triggered debris flow in the Banzi gully on June 26, 2023, were lower than that recorded in previous studies, e.g., the hourly rainfall intensity and cumulative rainfall of debris flow on August 20, 2019, in the Wenchuan County were 13.70 mm/h and 47.10 mm, respectively (Xiong et al. 2021b). ...
Catastrophic debris flow triggered by a June 26, 2023 rainstorm suggests the debris flow is still active 15 years after the Wenchuan seismic Abstract The Wenchuan earthquake strongly disturbed the earth surface and induced sufficient loose debris in the mountain basin, which supplies sufficient solid materials for debris flow initiation. Recently, a catastrophic debris flow was induced by strong rainfall on June 26, 2023 in the Banzi basin. Inconsistent with the first few years of the Wenchuan earthquake, the hillslope landslide sediment supply for debris flow occurrence is limited after 15 years of the Wenchuan earthquake, and the materials supplied for debris flow in the later period are mainly obtained from alluvium deposited along the channel. Simultaneously, this debris flow was triggered by flash flood through strongly erosion channel materials. However, although 15 years have passed since the Wenchuan earthquake, the triggering rainfall conditions have still not returned to pre-earthquake level. This debris flow first initiated in the upper branches of the basin and then gradually transported downstream at an average discharge of 806.99 m 3 /s, and approximately 82.80 × 10 4 m 3 solid materials were transported out the Banzi basin to form a debris flow fan with length of 120 m and width of 260 m in the Minjiang River, which poses a serious threat to the resettled population and destroy the reconstruction infrastructures. Importantly, there are still sufficient solid materials deposited in the basin, this could result in debris flow activity continuing for an unpredictable time. Therefore, implementation early warning, prevention, and mitigation measures in this basin are still important for debris flow disaster management in the later period of Wenchuan earthquake.
... The seismogenic fault has a significant impact on landslide occurrence, with the distribution of coseismic landslide density closely related to fault slip distribution. Proximity to the seismogenic fault is a key factor in the occurrence of earthquake-induced landslide events (Fan et al., 2019;Zhao, 2021). The high-risk areas identified in the mapping results are primarily due to long-term riverbank erosion and the ongoing promotion of development zones and tourist attractions, which encourage regular human engineering activities that promote landslide development (Cao et al., 2019;Liang et al., 2024). ...
Earthquake-induced landslides cause extensive harm, necessitating accurate predictions for effective risk management. To tackle the dual challenges posed by inadequate model accuracy and the absence of frequency-derived landslide intensity as critical information, this paper presents a robust modelling method that generates high-resolution landslide hazard map for risk assessment. Firstly, the Frequency Ratio (FR) model is employed to quantitatively explore the correlation between geo-environmental factors and landslide occurrences, enabling the exclusion of less significant factors. Subsequently, these FR values are integrated into the Light Gradient Boosting Machine (LightGBM) model, resulting in the composite model, FR-LightGBM. To test the proposed model, data from the areas affected by the Luding earthquake based on the seismic landslide intensity model following the 2022 Ms 6.8 earthquake in Sichuan, China, is examined. Model validation, using the area under the curve (AUC) of the receiver operating characteristic curve, highlighted the superior predictive accuracy of the FR-LightGBM model, marking a 3.5 % improvement in AUC value compared to both the Convolutional Neural Network (CNN) and Logistic Regression (LR) models. The results have identified high-risk areas along the Dadu riverside and the Xianshuihe fault zone correspond well with the actual landslide distribution. Overall, the practical applicability of the FR-LightGBM model is significantly enhanced by its capacity to prioritize lithology, faults, and aspect as crucial factors. Additionally, based on an extended landslide inventory established using high spatial resolution (2 m) satellite imagery from the Chinese Gaofen satellite series, the proposed approach delivered a high-resolution (12.5 m) hazard map across the Luding earthquake area, contributing to relevant studies and risk management.
... Landslides, as geological disasters with cascade effects, pose significant threats to human life, property, and environmental sustainability, thereby severely impeding sustainable development [1]. Due to complex geological conditions, intense tectonic activity, and extensive engineering construction, landslides are widespread in China, causing substantial losses through the frequent occurrence of landslide disasters. ...
Landslide susceptibility mapping (LSM) constitutes a valuable analytical instrument for estimating the likelihood of landslide occurrence, thereby furnishing a scientific foundation for the prevention of natural hazards, land-use planning, and economic development in landslide-prone areas. Existing LSM methods are predominantly data-driven, allowing for significantly enhanced monitoring accuracy. However, these methods often overlook the consideration of landslide mechanisms and uncertainties associated with non-landslide samples, resulting in lower model reliability. To effectively address this issue, a knowledge-guided landslide susceptibility assessment framework is proposed in this study to enhance the interpretability and monitoring accuracy of LSM. First, a landslide knowledge graph is constructed to model the relationships between landslide entities and summarize landslide susceptibility rules. Next, combining the obtained landslide rules with geographic similarity principles, high-confidence non-landslide samples are selected to optimize the quality of the samples. Subsequently, a Landslide Knowledge Fusion Cell (LKF-Cell) is utilized to couple landslide data with landslide knowledge, resulting in the acquisition of informative and semantically rich landslide event features. Finally, a precise and credible landslide susceptibility assessment model is built based on a convolutional neural network (CNN), and landslide susceptibility spatial distribution levels are mapped. The research findings indicate that the CNN-based model outperforms traditional machine learning algorithms in predicting landslide probability; in particular, the Area Under the Curve (AUC) of the model was improved by 3–6% after sample optimization, and the AUC value of the LKF-Cell method was 6–11% higher than the baseline method.
... The evolution of streambeds in areas that receive debris flows receives much attention (Fan et al., 2018;Fan et al., 2019;Ming et al., 2016;Prancevic et al., 2014). Previous research focused on the aggradation of riverbeds caused by high-intensity sediment transport with debris flow, and flooding in the floodplain (Hürlimann et al., 2019;James, 1991;Sutherland et al., 2002). ...
The evolution of riverbeds is greatly impacted by changes in the water-sediment relationship resulting from the movement of debris flows. However, little is known about the influence of management in chronic sediment source areas on the evolution of main-stem riverbed morphology. In this study, we used multi-source remote sensing images covering the past 50 years along with water-sediment and topo-graphic data from a river basin, and sediment transport data from debris flows, to analyze the evolutionary processes of the middle and lower reaches of the Daying River (DYR) at the China-Myanmar border. Our results showed that (1) management of the sediment source area shifted the riverbed morphology from aggradation to erosion, transforming the river surface from wide and shallow to narrow and deep, and the channel from multi-threaded to single-threaded; (2) the active alluvial area, marginal bar area, and average river width exhibited an inverted V-shaped trend, increasing by at least 23% and then decreasing by more than 59%; and (3) the evolution of riverbed morphology contributed to the stability of downstream riverbeds, improved flood control, and enhanced utilization of the floodplains. K E Y W O R D S Daying River, debris control, gully sediment yield, river aggradation, riverbed evolution, water-sediment relationship
... Co-seismic landslides are devastating geohazards that can claim thousands of lives, damage infrastructure, and impede rescue operations via disrupting transportation and communication facilities (Guzzetti, 2000;Jibson et al., 2000;Zhang et al., 2014;Kargel et al., 2016;Robinson et al., 2018;Fan et al., 2019;Chen et al., 2023a). Global empirical models have been developed to provide near-real-time assessments of co-seismic landslide distribution and hazard hotspots (Kritikos et al., 2015;Nowicki Jessee et al., 2018;Tanyas et al., 2019;Lombardo et al., 2021). ...
... In northern Algeria, almost every year (generally in winter), landslides lead to damage to constructions, roads, settlements, and agricultural fields. In this part of the country, landslides are the result of interactions between hydrometeorological, geomorphological, geological, and seismic factors (Fan et al. 2019). Previous studies have suggested a direct relationship between landslide intensity and earthquake magnitude and PGA variations (Keefer. ...
About 270 landslides have been triggered in the Mila region (northeast Algeria) linked to the 7 August 2020 Mw 5 earthquake,
but they have not been analyzed and mapped throughout the region. As a consequence, the potential link between the
earthquake, faults, and the set of large landslides registered subsequently in the same region has not yet been studied,
understood, and mapped. However, the geology and morphology of large and deep landslides lying dormant in the region,
which could be reactivated in case of seismic activity, are located close to faults and present the same morphological
characteristics as landslides triggered by the main shock. The aim of this paper is to present the relationship between
the seismotectonic and large landslide distribution and to compare landslide susceptibility maps by the application of
geographical information system (GIS)-based frequency ratio (FR) and weighting of evidence (Wi) statistical methods. A
landslide inventory map was developed using interferometric synthetic aperture radar (InSAR) post-seismic deformation
maps, aerial photographs, and field survey investigations. The analysis of the spatial distribution of large landslides, together
with information on aftershocks and electrical resistivity tomography (ERT) sections, shows that the spatial distribution
of large landslides is consistent with epicenter locations along a NW–SE axis and two NE–SW axes. Evidence of NE–SW
faults related to a N120E striking dextral strike–slip fault is also discussed. Various factors are shown to be associated with
landslide occurrence, such as lithology, distance to fault, slope degree, slope aspect, distance to rivers, drainage density,
elevation, rainfall, peak ground acceleration (PGA) in soil and rock estimated according to the Mila earthquake (Mw = 5),
and epicentral distance. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve approach
was used to confirm and validate the accuracy of the two models. The obtained AUC values were 89.05% and 87.57% for
the FR and Wi models, respectively, indicating high levels of prediction accuracy. The large landslides triggered in the Mila
region are found to be directly related to the seismotectonic structure, and a seismic sequence interspersed with moderate
earthquakes over a short period. The results are presented as a landslide susceptibility map showing areas highly vulnerable to
landslides and those with moderate and low vulnerability. It is expected that this will be very helpful for landslide prevention
and infrastructure planning in Mila City.
... Landslide disasters are common geological disasters, occurring widely in strong earthquake areas, reservoir areas and mountainous areas [1][2][3][4]. Due to the suddenness, concealment and frequency characteristics, the infrastructure and live of the residents are seriously threatened by landslides. Therefore, landslide hazard evaluation plays an important role in land use planning, engineering site selection, and landslide risk mitigation [5,6]. ...
The landslide hazard assessment plays a crucial role in landslide risk mitigation and land use planning. The result of landslide hazard assessment corrected by surface deformation, obtained through time-series InSAR, has usually proven to have good application capabilities. However, the issue lies in the uncertainty of InSAR results, where some deformations cannot be calculated, and some are not true deformations. This uncertainty of InSAR results will lead to errors in landslide hazard assessment. Here, we attempt to evaluate landslide hazards by considering combined rainfall and surface deformation. The main objective of this research was to mitigate the impact of bias and explore the accurate landslide hazard assessment method. A total of 201 landslides and 11 geo-environment factors were utilized for landslide susceptibility assessment by support vector machine (SVM) model in Wanzhou District, Three Gorges Reservoir Area (TGRA). The preliminary hazard is obtained by analyzing the statistical data of landslides and rainfall. Based on the SAR image data of Sentinel-1A satellites from September 2019 to October 2021, the SBAS-InSAR method was used to analyze surface deformation. The correlation between surface deformation and rainfall was analyzed, and the deformation factor variables were applied to landslide hazard assessment. The research results demonstrate that the error caused by the uncertainty of InSAR results can be effectively avoided by analyzing the relationship between rainfall and surface deformation. Our results can effectively adjust and correct the hazard results and eliminate the errors in the general hazard assessment. Our proposed method can be used to assess the landslide hazard in more detail and provide a reference for fine risk management and control.
... Consequently, GMMs may not capture significant features of earthquake waveforms, such as topographic amplification, shaking duration, and rupture directivity. These characteristics are crucial in understanding phenomena like landslide occurrence (Fan et al., 2019;Dahal et al., 2023). A better way for accurately estimating ground shaking intensity parameters involves the computation of broadband synthetic seismograms. ...
After an earthquake event, major ground effects include landslides. In Italy, the most common type of earthquake-induced landslides are rockfalls. The assessment of the extent and magnitude of an earthquake-induced landslide event may be of importance for both preparedness and response operations. An earlier work devised a modeling chain including an empirical ground shaking scenario and a three-dimensional model for rockfalls, which can be calibrated and possibly applied in real time after an earthquake event. In this study, we explore the combined use of two physics-based methods for both earthquake and rockfall modeling and their possible contribution towards a better understanding of the triggering mechanisms and characterization of seismically induced rockfalls. Specifically, by modeling a set of ground shaking scenarios, which account for increasingly complex details (including multiple seismic events, as well as point and extended sources) and the related rockfall scenarios, we aim to capture the main spatial patterns of observed rockfalls. Application of the proposed modeling chain suggests an advantage of using multiple sources over a single source, and point sources with respect to approximate extended representations when constrained by limited available data. This follows from the comparison of rockfall trajectory simulations for the Friuli 1976 event in Northern Italy with observed rockfalls induced by the seismic sequence. The obtained results evidence the opportunity of including topographic effects in the ground shaking simulations and highlights the possibility of further investigating the cumulative effect of complex seismic sequences and their influence on modulating landslide susceptibility.
