Journal articles on the topic 'Earthquake-Induced landslides'
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1
Arifianti, Yukni, Pamela Pamela, Prahara Iqbal, Sumaryono Sumaryono, Amalfi Omang, and Hilda Lestiana. "SUSCEPTIBILITY ASSESSMENT OF EARTHQUAKE-INDUCED LANDSLIDES: THE 2018 PALU, SULAWESI MW 7.5 EARTHQUAKE, INDONESIA." Rudarsko-geološko-naftni zbornik 38, no. 3 (2023): 43–54. http://dx.doi.org/10.17794/rgn.2023.3.4.
Abstract:
A catastrophic Palu earthquake on September 28th, 2018 with Mw 7.5 triggered countless slope failures, generating numerous landslides. This paper presents a practical method for susceptibility assessment of earthquake-induced landslides in the Palu region and the surrounding area. The statistical weight of evidence (WoE) model was used to assess the relationship between landslides induced by seismic motion and its causative factors to determine the susceptibility level and derive an earthquake-induced landslide susceptibility map of this study area. The 1273 landslides were classified into two data series, training data for modelling (70%) and test data for validation (30%). The six selected thematic maps as landslide causative factors are lithology, land use, peak ground acceleration (PGA), and slope (gradient, aspect, elevation). The selection of causative factors considerably influences the frequency of landslides in the area. The result is satisfactory because the AUC value of the chosen model excelled the minimum limit, which is 0.6 (60%). The estimated success rate of the model is 85.7%, which shows that the relevancy of the model is good with the occurrence of landslides. The prediction rate of 84.6% indicates that the applied model is very good at predicting new landslides.
2
Litoseliti, Aspasia, Ioannis K. Koukouvelas, Konstantinos G. Nikolakopoulos, and Vasiliki Zygouri. "An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece." ISPRS International Journal of Geo-Information 9, no. 7 (July 20, 2020): 457. http://dx.doi.org/10.3390/ijgi9070457.
Abstract:
Assessment of landslide hazard across mountains is imperative for public safety. Pre- and post-earthquake landslide mapping envisage that landslides show significant size changes during earthquake activity. One of the purposes of earthquake-induced landslide investigation is to determine the landslide state and geometry and draw conclusions on their mobility. This study was based on remote sensing data that covered 72 years, and focused on the west slopes of the Skolis Mountains, in the northwest Peloponnese. On 8 June 2008, during the strong Movri Mountain earthquake (Mw = 6.4), we mapped the extremely abundant landslide occurrence. Historical seismicity and remote sensing data indicate that the Skolis Mountain west slope is repeatedly affected by landslides. The impact of the earthquakes was based on the estimation of Arias intensity in the study area. We recognized that 89 landslides developed over the last 72 years. These landslides increased their width (W), called herein as inflation or their length (L), termed as enlargement. Length and width changes were used to describe their aspect ratio (L/W). Based on the aspect ratio, the 89 landslides were classified into three types: I, J, and Δ. Taluses, developed at the base of the slope and belonging to the J- and Δ-landslide types, are supplied by narrow or irregular channels. During the earthquakes, the landslide channels migrated upward and downward, outlining the mobility of the earthquake-induced landslides. Landslide mobility was defined by the reach angle. The reach angle is the arctangent of the landslide’s height to length ratio. Furthermore, we analyzed the present slope stability across the Skolis Mountain by using the landslide density (LD), landslide area percentage (LAP), and landslide frequency (LF). All these parameters were used to evaluate the spatial and temporal landslide distribution and evolution with the earthquake activity. These results can be considered as a powerful tool for earthquake-induced landslide disaster mitigation
3
Chang, Chaoyu, Jingshan Bo, Wenhao Qi, Feng Qiao, and Da Peng. "Distribution of large- and medium-scale loess landslides induced by the Haiyuan Earthquake in 1920 based on field investigation and interpretation of satellite images." Open Geosciences 14, no. 1 (January 1, 2022): 995–1019. http://dx.doi.org/10.1515/geo-2022-0403.
Abstract:
Abstract Studying the distribution law and influencing factors of coseismic landslides has important scientific significance and engineering value for understanding the mechanism of seismic landslides and predicting the occurrence of seismic landslides. After a hundred years, these large- and medium-scale landslides induced by the 1920 Haiyuan earthquake are still well-preserved and have extremely high academic research value. About 620 loess seismic landslides induced by the Haiyuan earthquake in 1920 were investigated on site. On this basis, the shape differences between seismic landslides and gravity landslides were summarized; 605 landslides were identified by satellite images, and the Haiyuan earthquake-induced loess landslide database containing seismic information and landslide information was established. The distribution law and morphological characteristics of large- and medium-sized landslides induced by the Haiyuan earthquake were systematically counted according to the conditions of the landslide-intensive area, intensity, and fault upper and lower plates. The influencing factors of loess earthquake landslides were summarized, and the following conclusions were obtained: (1) 1,225 large- and medium-sized landslides were induced by the Haiyuan earthquake in 1920. These landslides have the characteristics of long sliding distance, large single scale, and strong disaster-causing. They are mainly distributed in three concentrated areas of Xiji, Haiyuan, and Pengyang. The landslide morphological characteristics of the three landslide-intensive areas are different because the landslide sliding mechanism caused by topography and lithology is different. (2) The landslide distribution has obvious clustering, zonation, and directivity, and has an obvious river distance effect and fault hanging wall effect. (3) The internal influencing factors such as stratum lithology, topography, fault location, and direction, and the role of water control the occurrence location and scale of landslide. The external factor of an earthquake is an important incentive and control factor for landslide occurrence.
4
Nonomura, Atsuko, Shuichi Hasegawa, Tatsuya Abe, Sakae Mukoyama, and Yoshiyuki Kaneda. "Validation of an Index for Susceptibility to Earthquake-Induced Landslides Derived from Helicopter-Borne Electromagnetic Resistivity and Digital Elevation Data." Geosciences 11, no. 2 (February 19, 2021): 95. http://dx.doi.org/10.3390/geosciences11020095.
Abstract:
Catastrophic earthquake-induced landslides can occur on slopes composed of loosened and fractured rock masses. Although it is impossible to prevent such landslides, estimation of the susceptibility of slopes to earthquake-induced landslides is useful for risk management. An index of susceptibility to earthquake-induced landslides (ISEL) was developed by using helicopter-borne electromagnetic resistivity data. However, the ISEL has not yet been validated through the analysis of pre-earthquake data. In this study, ISEL values were estimated from resistivity and digital elevation data obtained in 2013 around Mt. Aso, Kyushu, before the 2016 Kumamoto earthquake. Although most of the landslides around Mt. Aso during the 2016 Kumamoto earthquake were mass movements of volcanic tephra layers, some of them occurred on loosened rock masses. Landslide susceptible areas at loosened rock masses are the target for ISEL value estimation. Our results validated the effectiveness of the ISEL as a predictor of earthquake-induced rock mass landslides.
5
Chen, X. L., H. L. Ran, and W. T. Yang. "Evaluation of factors controlling large earthquake-induced landslides by the Wenchuan earthquake." Natural Hazards and Earth System Sciences 12, no. 12 (December 12, 2012): 3645–57. http://dx.doi.org/10.5194/nhess-12-3645-2012.
Abstract:
Abstract. During the 12 May 2008, Wenchuan earthquake in China, more than 15 000 landslides were triggered by the earthquake. Among these landslides, there were 112 large landslides generated with a plane area greater than 50 000 m2. These large landslides were markedly distributed closely along the surface rupture zone in a narrow belt and were mainly located on the hanging wall side. More than 85% of the large landslides are presented within the range of 10 km from the rupture. Statistical analysis shows that more than 50% of large landslides occurred in the hard rock and second-hard rock, like migmatized metamorphic rock and carbonate rock, which crop out in the south part of the damaged area with higher elevation and steeper landform in comparison with the northeast part of the damaged area. All large landslides occurred in the region with seismic intensity ≥ X except a few of landslides in the Qingchuan region with seismic intensity IX. Spatially, the large landslides can be centred into four segments, namely the Yingxiu, the Gaochuan, the Beichuan and the Qingchuan segments, from southwest to northeast along the surface rupture. This is in good accordance with coseismic displacements. With the change of fault type from reverse-dominated slip to dextral slip from southwest to northeast, the largest distance between the triggered large landslides and the rupture decreases from 15 km to 5 km. The critical acceleration ac for four typical large landslides in these four different segments were estimated by the Newmark model in this paper. Our results demonstrate that, given the same strength values and slope angles, the characteristics of slope mass are important for slope stability and deeper landslides are less stable than shallower landslides. Comprehensive analysis reveals that the large catastrophic landslides could be specifically tied to a particular geological setting where fault type and geometry change abruptly. This feature may dominate the occurrence of large landslides. The results will be useful for improving reliable assessments of earthquake-induced landslide susceptibility, especially for large landslides which may result in serious damages.
6
Shahi, Tapendra Kumar. "Earthquake-Induced Shallow Landslide Susceptibility Assessment of Gorkha District." Journal of Advanced College of Engineering and Management 5 (December 18, 2019): 181–93. http://dx.doi.org/10.3126/jacem.v5i0.26766.
Abstract:
Nepal is very seriously affected by landslides every year causing loss of life and property. Large scale earthquakes that occurred in different time periods such as on 15th January, 1934 or that on 25th April 2015 have proved Nepal as seismically vulnerable -place. Nepal has witnessed several landslides during and after the earthquake events making some areas of land quite vulnerable for settlement and other usages. Therefore in order to minimize the impacts of landslides caused due to earthquakes, highly susceptible locations should be identified and spatial planning is made accordingly. Considering topographic effects in amplification of earthquake ground motion, Uchida et al. (2004) have developed a topographical parameter based empirical description of landslide susceptibility during an earthquake. In this research, the method proposed by Uchida et al. (2004) is utilized in raster GIS and landslide susceptibility analysis is performed in the study area of SulikotGaupalika of Gorkha district, Nepal which was severely hit by several landslides due to “Gorkha Earthquake 2015". The landslide inventory map of SulikotGaupalika due to “Gorkha Earthquake 2015" is obtained and is correlated with landslide susceptibility values as obtained by using Uchida et al. (2004). The analysis shows that the method proposed by Uchida et al. (2004) is more than 68.9% accurate in delineating the probable locations of earthquake induced landslides. By calibrating landslide data and landslide susceptibility values in a small site (i.e. SulikotGaupalika) within the study area, a final landslide susceptibility map is prepared for the whole study area of Gorkha district. The resultant susceptibility map is very useful for planning settlements, development activities and reconstruction planning.
7
Lai, Chun Jing, Yan Peng Zhu, Chun Qing Wang, and Tian Zhong Ma. "Theory Study on Similitude Design of Shaking Table Tests of Earthquake-Induced Landslide." Applied Mechanics and Materials 353-356 (August 2013): 2294–300. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.2294.
Abstract:
Based on analysis of characteristics of earthquake-induced landslides and summary of main factors of controlling earthquake-induced landslides, three main factors which are seismic parameters, topography and landforms features and engineering properties of soil are considered the main factor affecting on earthquake-induced landslides. These factors should be focused on to meet the similitude ratio design of the dynamics of landslide in Shaking table test design. Based on study of dynamic similitude law of landslide, the method of changing model soil specifications is used to prepare the model soil which is in accordance with the maximum shear modulus of prototype soil. Also, the engineering properties similitude of model soil is checked by the method of shear wave velocity similitude. By taking the theory of vibration behavior theory of similarity and dynamic failure similar, the formula of dynamic parameters similitude ratio was got. This formula provides calculating methods using shaking table test to simulate earthquake induced landslide.
8
Yang, Zongji, Bo Pang, Wufan Dong, and Dehua Li. "Spatial Pattern and Intensity Mapping of Coseismic Landslides Triggered by the 2022 Luding Earthquake in China." Remote Sensing 15, no. 5 (February 27, 2023): 1323. http://dx.doi.org/10.3390/rs15051323.
Abstract:
On 5 September 2022, an Mw 6.6 earthquake occurred in Luding County in China, resulting in extensive surface rupture and casualties. Sufficient study on distribution characteristics and susceptibility regionalization of the earthquake-induced disasters (especially coseismic landslides) in the region has great significance to mitigation of seismic hazards. In this study, a complete coseismic landslide inventory, including 6233 landslides with 32.4 km2 in area, was present through multi-temporal satellite images. We explored the distribution and controlling conditions of coseismic landslides induced by the 2022 Luding event from the perspective of epicentral distance. According to the maximum value of landslide area density, the geographical location with the strongest coseismic landslide activity intensity under the influence of seismic energy, the macro-epicenter, was determined, and we found a remarkable relationship with the landslide distribution and macro-epicentral distance, that is, both the landslide area and number density associatively decreased with the increase in macro-epicentral distance. Then, a fast and effective method for coseismic landslide intensity zoning based on the obvious attenuation relationship was proposed, which could provide theoretical reference for susceptibility mapping of coseismic landslides induced by earthquakes in mountainous areas. Additionally, to quantitatively assess the impact of topographic, seismogenic and lithological factors on the spatial pattern of coseismic landslides, the relationships between the occurrences of coseismic landslides and influencing factors, i.e., elevation, slope angle, local relief, aspect, distance to fault and lithology, were examined. This study provides a fresh perspective on intensity zoning of coseismic landslides and has important guiding significance for post-earthquake reconstruction and land use in the disaster area.
9
Aimaiti, Yusupujiang, Wen Liu, Fumio Yamazaki, and Yoshihisa Maruyama. "Earthquake-Induced Landslide Mapping for the 2018 Hokkaido Eastern Iburi Earthquake Using PALSAR-2 Data." Remote Sensing 11, no. 20 (October 10, 2019): 2351. http://dx.doi.org/10.3390/rs11202351.
Abstract:
Timely information about landslides during or immediately after an event is an invaluable source for emergency response and management. Using an active sensor, synthetic aperture radar (SAR) can capture images of the earth’s surface regardless of weather conditions and may provide a solution to the problem of mapping landslides when clouds obstruct optical imaging. The 2018 Hokkaido Eastern Iburi earthquake (Mw 6.6) and its aftershocks not only caused major damage with severe loss of life and property but also induced many landslides across the area. To gain a better understanding of the landslides induced by this earthquake, we proposed a method of landslide mapping using pre- and post-event Advanced Land Observation Satellite 2 Phased Array L-band Synthetic Aperture Radar 2 (ALOS-2 PALSAR-2) images acquired from both descending and ascending orbits. Moreover, the accuracy of the classification results was verified by comparisons with high-resolution optical images, and ground truth data (provided by GSI, Japan). The detected landslides show a good match with the reference optical images by visual comparison. The quantitative comparison results showed that a combination of the descending and ascending intensity-based landslide classification had the best accuracy with an overall accuracy and kappa coefficient of 80.1% and 0.45, respectively.
10
Sørensen, Mathilde B., Torbjørn Haga, and Atle Nesje. "Earthquake-induced landslides in Norway." Natural Hazards and Earth System Sciences 23, no. 4 (April 27, 2023): 1577–92. http://dx.doi.org/10.5194/nhess-23-1577-2023.
Abstract:
Abstract. Norway is located in an intraplate setting with low-to-moderate seismicity. The mountainous landscape leads to a high level of landside activity throughout the country. Earthquake-induced landslides (EQILs) are common in seismically active areas, but there are only a few studies of EQILs in intraplate regions. We systematically analyse all earthquakes in Norway with magnitudes ≥ 4.5 in the time period 1800–2021 CE. For each event we search for reports of EQILs in the available macroseismic data and in the Norwegian landslide database. We furthermore consider precipitation data from the Norwegian Centre for Climate Services to evaluate the role of precipitation in the triggering of the identified potential EQILs. Through this approach, we identify 22 EQILs that have been triggered by eight earthquakes in the magnitude range 4.5–5.9. The events are widely distributed in northern and southern Norway. The maximum landslide distance limits and landslide-affected areas are much larger than those found in empirical studies of global datasets and are in agreement with data from other intraplate regions. For four of the earthquakes, it seems that landslide triggering was due to a combined effect of precipitation and earthquake ground shaking. Our observations confirm that intraplate earthquakes have the potential to trigger EQILs over large distances, most likely due to the low ground motion attenuation in such regions. Slope susceptibility seems to be another important factor in the triggering. Our conclusions demonstrate the importance of considering EQIL potential in earthquake risk management in intraplate regions.
11
Tsou, Ching-Ying, Daisuke Higaki, Masahiro Chigira, Hiroshi Yagi, Vishu Dangol, Shanmukhesh Amatya, Kazunori Hayashi, and Hiroki Kato. "Topographic characteristics of landslides induced by the 2015 Gorkha earthquake, Nepal." Journal of Nepal Geological Society 55, no. 1 (June 4, 2018): 69–75. http://dx.doi.org/10.3126/jngs.v55i1.22792.
Abstract:
The 2015 Gorkha earthquake and its aftershocks induced landslides in central Nepal. In this study, field surveys were conducted, and Google Earth satellite images were analysed for pre- and post-mainshock and aftershock scenarios to clarify the distribution of landslides. A total of 13,097 new landslides and 750 enlarged landslides were identified and mapped as polygon-based data over an area of 7.8 × 103 km2 between the epicenters of the main shock and the largest aftershock at the mountainous southern margin of the High Himalayas. Shallow-disrupted landslides were the most common type of mass movement. The areas of individual landslides ranged from 10 to 3.2× 105 m2, covering a cumulative area of 5.4 × 107 m2 or 0.7% of the study area. The landslide density was high in the Gorkha, Rasuwa, and Sindhupalchok districts, indicating that these areas suffered greater damage. Landslides occurred mainly on steep slopes (>35°) in V-shaped inner gorges, on geologically controlled steep slopes such as the scarp slopes (infacing slopes) of mountain ridges, and on terrace scarps. The results suggest that earthquake-induced landslides occur on slopes preconditioned by topographic and litho-structural factors. Based on our observations, recommendations for the mitigation of future landslide disasters are provided.
12
Li, Yange, Jianling Huang, Hao Pu, Zheng Han, Wei Li, and Bin Yan. "Semiautomatic Landslide Detection Using Remote Sensing and Slope Units." Transportation Research Record: Journal of the Transportation Research Board 2604, no. 1 (January 2017): 104–10. http://dx.doi.org/10.3141/2604-13.
Abstract:
Landslides induced by earthquakes and rainfall pose severe threats to the infrastructure of highways and high-speed railways. To plan an immediate emergency response, the location and scale of these landslides should be known beforehand. Traditionally, to detect multitemporal landslides induced by earthquakes and the long-term effects, along with other factors such as subsequent rainfall, one had to carry out image classification multiple times to calculate the variance information. The accuracy of that method is affected by accumulated errors from multi-classification, and the process is very time-consuming. In this paper, a semiautomatic approach is proposed for rapid mapping of multi-temporal landslides. The approach can obtain the variance information of each landslide event in one detection process. In addition, slope units are introduced to separate the extracted conjoined landslides. The area of Chenjiaba, China, which is located in the highest seismic intensity zone of the Wenchuan earthquake in Beichuan and had strong rainfall 4 months after the earthquake, was selected as a case study to demonstrate the validity of this methodology. Accuracy assessment was carried out by comparing extracted landslides with a manually prepared landslide inventory map. Correctly detected were 90.1% and 94.2% of earthquake- and rainfall-induced landslides, respectively. Results show that this approach is capable of mapping temporal landslides efficiently and quickly.
13
Bloom, Colin K., Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason. "Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand." Natural Hazards and Earth System Sciences 23, no. 9 (September 7, 2023): 2987–3013. http://dx.doi.org/10.5194/nhess-23-2987-2023.
Abstract:
Abstract. Coastal hillslopes often host higher concentrations of earthquake-induced landslides than those further inland, but few studies have investigated the reasons for this occurrence. As a result, it is unclear if regional earthquake-induced landslide susceptibility models trained primarily on inland hillslopes are effective predictors of coastal susceptibility. The 2016 Mw 7.8 Kaikōura earthquake on the northeastern South Island of New Zealand resulted in ca. 1600 landslides > 50 m2 on slopes > 15∘ within 1 km of the coast, contributing to an order of magnitude greater landslide source area density than inland hillslopes within 1 to 3 km of the coast. In this study, logistic regression modelling is used to investigate how landslide susceptibility differs between coastal and inland hillslopes and to determine the factors that drive the distribution of coastal landslides initiated by the 2016 Kaikōura earthquake. Strong model performance (area under the receiver operator characteristic curve or AUC of ca. 0.80 to 0.92) was observed across eight models, which adopt four simplified geology types. The same landslide susceptibility factors, primarily geology, steep slopes, and ground motion, are strong model predictors for both inland and coastal landslide susceptibility in the Kaikōura region. In three geology types (which account for more than 90 % of landslide source areas), a 0.03 or less drop in model AUC is observed when predicting coastal landslides using inland-trained models. This suggests little difference between the features driving inland and coastal landslide susceptibility in the Kaikōura region. Geology is similarly distributed between inland and coastal hillslopes, and peak ground acceleration (PGA) is generally lower in coastal hillslopes. Slope angle, however, is significantly higher in coastal hillslopes and provides the best explanation for the high density of coastal landslides during the 2016 Kaikōura earthquake. Existing regional earthquake-induced landslide susceptibility models trained on inland hillslopes using common predictive features are likely to capture this signal without additional predictive variables. Interestingly, in the Kaikōura region, most coastal hillslopes are isolated from the ocean by uplifted shore platforms. Enhanced coastal landslide susceptibility from this event appears to be a legacy effect of past erosion from wave action, which preferentially steepened these coastal hillslopes.
14
Dangi, Harish, Tara Nidhi Bhattarai, and Prem Bahadur Thapa. "An approach of preparing earthquake induced landslide hazard map: a case study of Nuwakot District, central Nepal." Journal of Nepal Geological Society 58 (June 25, 2019): 153–62. http://dx.doi.org/10.3126/jngs.v58i0.24600.
Abstract:
The Gorkha Earthquake-2015 triggered landslides which are widespread in central Nepal. The landslides swept away physical infrastructures like roads, schools, public and residential buildings, and cultivated lands at several locations. This indicated that the decision makers were not aware of the fact that the locations for possible earthquake-induced landslides can be predicted, and physical infrastructure development can be planned accordingly. What is needed for the purpose is an earthquake-induced landslide hazard map which is a useful tool in decision making, particularly for finding safer geographical locations for residential and public building construction, and also for other physical infrastructure development. Immediately after the Gorkha Earthquake-2015, JICA prepared an earthquake-induced landslide hazard map of the Gorkha and the Sindhupalchowak Districts using a certain methodology. But there remains a research question regarding whether the same methodology can be applied in preparing earthquake-induced landslide hazard maps of other earthquake-affected districts located away from the epicenter area. The main purpose of this research was to apply the JICA methodology to prepare an earthquake-induced landslide hazard map of the Nuwakot District, central Nepal which is the one if the most affected district by Gorkha earthquake 2015. The second purpose was to examine whether the map captured the ground reality or not. While preparing the input data required, four major disaster factors were taken into consideration which includes, among others, slope inclination, slope direction, relationship with the major thrust and distance from the epicenter. These factors were classified and characterized according to their nature and condition. The result was then analyzed by using quantification theory. An earthquake-induced landslide hazard map was then prepared using QGIS as a major software tool. The map was also verified through ground-truthing visiting several locations of the study site. The proposed methodology can be used to prepare similar maps in other affected districts of Gorkha earthquake 2015, and suitable sites for constructing physical infrastructures like roads, residential and public buildings can also be identified using the maps.
15
Noviandi, Rozaqqa, Takashi Gomi, Hefryan S. Kharismalatri, Roy C. Sidle, Rasis P. Ritonga, and Katsushige Shiraki. "The Mobility of Landslides in Pumice: Insights from a Flume Experiment." Water 14, no. 19 (September 30, 2022): 3083. http://dx.doi.org/10.3390/w14193083.
Abstract:
Risk of landslide hazards strongly depends on how far landslide sediment travels, known as landslide mobility. Previous studies mentioned enhanced mobility of earthquake-induced landslides in volcanic deposits compared to those from other geologic/soil settings. A flume apparatus constructed at a 1:300 scale was used to examine the mobility of landslides with pumice. Four pumice samples were collected from landslides induced by the 2018 Eastern Iburi earthquake, Hokkaido, Japan. Laboratory tests confirmed the unique low specific gravity of the pumice (1.29–1.33), indicating numerous voids within pumice particles. These voids allowed pumice to absorb a substantial amount of water (95–143%), about 9–15 times higher than other coarse-grained soils. Our flume experiments using various saturation levels (0–1) confirmed the influence of this inner-particle water absorption on pumice mobility. Because a low value of specific gravity indicates a low strength of soil, grain crushing may occur on the pumice layer, causing water from the internal voids to discharge and fluidize the transported landslide mass. Our findings indicate that such earthquake-induced landslides can be as mobile as those induced by rainfall, depending on the initial water content of the pumice layers. These conditions might be associated with water accumulation from previous rainfall events and the water-holding capability on pumice layers.
16
Li, Xiu Zhen, Ji Ming Kong, and Sheng Wei Li. "Travel Distance Prediction of Landslides Triggered by the M8.0 Wenchuan Earthquake." Applied Mechanics and Materials 71-78 (July 2011): 1736–40. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.1736.
Abstract:
Volume and slope are two important factors affecting the runout distance of landslides. Field investigation on 46 landslides triggered by the Wenchuan earthquake show that there are positive linear correlations between the logarithmic values of landslide volume and travel distance. And there is also a positive linear relationship between the equivalent friction coefficient and tangent value of initial slope angle for the landslides. On the basis, we obtained an empirical-statistic equation between the horizontal and vertical travel distance, the volume and initial slope angle. This can provide a basis for prediction of earthquake-induced landslides.
17
Shao, Xu, Ma, and Zhou. "Effects of Seismogenic Faults on the Predictive Mapping of Probability to Earthquake-Triggered Landslides." ISPRS International Journal of Geo-Information 8, no. 8 (July 26, 2019): 328. http://dx.doi.org/10.3390/ijgi8080328.
Abstract:
The seismogenic fault is crucial for spatial prediction of co-seismic landslides, e.g., in logistic regression (LR) analysis considering influence factors. On one hand, earthquake-induced landslides are usually densely distributed along the seismogenic fault; on the other hand, different sections of the seismogenic fault may have distinct landslide-triggering capabilities due to their different mechanical properties. However how the feature of a fault influence mapping of landslide occurrence probability remains unclear. Relying on the landslide data of the 2013 Lushan, China Mw 6.6 earthquake, this study attempted to further address this issue. We quantified the seismogenic fault effects on landslides into three modes: the distance effect, the different part effects, and the combined effects of the two. Four possible cases were taken into consideration: zoning the study area vertical and parallel to the fault (case 1), zoning the study area only vertical to the fault (case 2), zoning the study area only parallel to the fault (case 3), and without such study-area zonations (case 4). Using the LR model, predictive landslide probability maps were prepared on these four cases. The model also fully considered other influencing factors of earthquake landslides, including elevation, slope, aspect, topographic wetness index (TWI), peak ground acceleration (PGA), lithology, rainfall, distance from the epicenter, distance from the road, and distance from the river. Then, cross-comparisons and validations were conducted on these maps. For training datasets, results show that the success rates of earthquake-triggered landslides for the former three scenarios were 85.1%, 84.2%, and 84.7%, respectively, while that of the model for case 4 was only 84%. For testing datasets, the prediction rates of the four LRs were 84.45%, 83.46%, 84.22%, and 83.61%, respectively, as indicated by comparing the test dataset and the landslide probability map. This means that the effects of the seismogenic fault, which are represented by study-area zonations vertical and parallel to the fault proper, are significant to the predictive mapping of earthquake-induced landslides.
18
Coviello, Velio, Lucia Capra, Gianluca Norini, Norma Dávila, Dolors Ferrés, Víctor Hugo Márquez-Ramírez, and Eduard Pico. "Earthquake-induced debris flows at Popocatépetl Volcano, Mexico." Earth Surface Dynamics 9, no. 3 (May 21, 2021): 393–412. http://dx.doi.org/10.5194/esurf-9-393-2021.
Abstract:
Abstract. The 2017 Mw 7.1 Puebla–Morelos intraslab earthquake (depth: 57 km) severely hit Popocatépetl Volcano, located ∼ 70 km north of the epicenter. The seismic shaking triggered shallow landslides on the volcanic edifice, mobilizing slope material saturated by the 3 d antecedent rainfall. We produced a landslide map based on a semi-automatic classification of a 50 cm resolution optical image acquired 2 months after the earthquake. We identified hundreds of soil slips and three large debris flows for a total affected area of 3.8 km2. Landslide distribution appears controlled by the joint effect of slope material properties and topographic amplification. In most cases, the sliding surfaces correspond with discontinuities between pumice-fall and massive ash-fall deposits from late Holocene eruptions. The largest landslides occurred on the slopes of aligned ENE–WSW-trending ravines, on opposite sides of the volcano, roughly parallel to the regional maximum horizontal stress and to volcano-tectonic structural features. This suggests transient reactivation of local faults and extensional fractures as one of the mechanisms that weakened the volcanic edifice and promoted the largest slope failures. The material involved in the larger landslides transformed into three large debris flows due to liquefaction. These debris flows mobilized a total volume of about 106 m3 of material also including large wood, were highly viscous, and propagated up to 7.7 km from the initiation areas. We reconstructed this mass wasting cascade by means of field evidence, samples from both landslide scarps and deposits, and analysis of remotely sensed and rainfall data. Although subduction-related earthquakes are known to produce a smaller number of landslides than shallow crustal earthquakes, the processes described here show how an unusual intraslab earthquake can produce an exceptional impact on an active volcano. This scenario, not related to the magmatic activity of the volcano, should be considered in multi-hazard risk assessment at Popocatépetl and other active volcanoes located along volcanic arcs.
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Song, Chang-Ho, Ji-Sung Lee, Yong-Soo Ha, and Yun-Tae Kim. "Rainfall and Earthquake-induced Landslide Susceptibility Assessment." Journal of the Korean Society of Hazard Mitigation 23, no. 1 (February 28, 2023): 165–77. http://dx.doi.org/10.9798/kosham.2023.23.1.165.
Abstract:
When rainfall and earthquake occur simultaneously, large-scale landslides can cause direct damage to lives and structures. To reduce such large-scale landslide damage, rainfall and earthquake-induced landslide susceptibility has to be evaluated. Therefore, in this study, landslide susceptibility was evaluated by considering only rainfall, only earthquake, and both rainfall and earthquake in the Atsuma region of Japan, where a large-scale landslide was triggered by a combination of rainfall and earthquake. Through quantitative index analysis, the accuracy of the landslide susceptibility map was improved when both rainfall and earthquake were considered. The proposed method was also applied to the Naari basin in Yangnam-myeon, Gyeongju as a pilot district. We found that the landslide-susceptible area increased when rainfall and earthquake were considered simultaneously than when rainfall and earthquake were considered separately. Through such research, can be used as basic data for complex disaster vulnerability assessment.
20
Filion, Louise, François Quinty, and Christian Bégin. "A chronology of landslide activity in the valley of Rivière du Gouffre, Charlevoix, Quebec." Canadian Journal of Earth Sciences 28, no. 2 (February 1, 1991): 250–56. http://dx.doi.org/10.1139/e91-024.
Abstract:
Data on earthquake-induced landslides in the valley of Rivière du Gouffre in the Charlevoix region of Quebec are presented. A set of 37 radiocarbon dates obtained from tree trunks buried in flow material and found at the bottom of a small lake was used to reconstruct landslide activity. In addition, large subfossil tree trunks were sampled for tree-ring analysis. The radiocarbon dates indicate that most landslide activity in the area is recent (<600 BP). Two tree-ring-dated landslides were triggered by a large earthquake in AD 1663.
21
Lee, Shing Tsz, Teng To Yu, and Wen Fei Peng. "Effect of Earthquake on Subsequent Typhoon-Induced Landslides Using Remote Sensing Imagery in the 99 Peaks Region, Central Taiwan." Key Engineering Materials 500 (January 2012): 773–79. http://dx.doi.org/10.4028/www.scientific.net/kem.500.773.
Abstract:
The effect of Chi-Chi earthquake on typhoon-triggered landslides was estimated using accuracy curves method in seismic landslide hazard model. The logistic regression model and geographic information system (GIS) are chosen to perform the seismic landslide hazard analysis. An inventory map of the landslides from SPOT images taken before and after the events was used to produce a dependent variable, which takes a value of 0 and 1 for the absence and presence of landslides. A set of independent parameters include lithology, elevation, slope gradient, slope aspect, terrain roughness, land use and Arias intensity (Ia) with topographic effect. Subsequently, the logistic regression is used to find the best fitting function to describe the relationship between occurrence or non-occurrence of landslides within an individual grid cell. The decreased effect of the earthquake was measured using accuracy curves method. It found that the effect of earthquake decreases with time. The landslide events of 2004 had little correlation with the Chi-Chi earthquake. Nevertheless, after period of 5 years, the seismic intensity from the Chi-Chi earthquake might still have affected conditions of landslides in the study area.
22
Yagi, Hiroshi, Kazunari Hayashi, Daisuke Higaki, Ching-Ying Tsou, and Go Sato. "Dormant landslides distributed in upper course of Sun Kosi Watershed and landslides induced by Nepal Gorkha Earthquake 2015." Journal of Nepal Geological Society 55, no. 1 (June 4, 2018): 61–67. http://dx.doi.org/10.3126/jngs.v55i1.22790.
Abstract:
This study detected 897 dormant landslides of deep-seated type in the upper course of the Sun Kosi Watershed. It also shows geology and slope gradient that are prone to cause deep-seated landslides in the Great Himalaya and Midland zones. The dormant landslides are predominantly distributed in geological areas of the Augen Gneiss, Benighat Slate, Robang Phyllite and the Kuncha Phyllite, considering both landslide area ratio and site number. Landslides of deep-seated type are also found prone to develop on dip-slope. Occurrence of landslides usually increases over 20 degrees of slope angle for each geological type, though the number of landslides in the phyllite area increases below 20 degrees. It is very clear that landslides in phyllite area are prone to occur from relatively lower slope angles compared to those occurring in quartzite, gneiss and the Sermathang Formation. Nepal Gorkha Earthquake 2015 caused 1804 landslides in this study area. Most of the earthquake-induced landslides are of shallow types that occurred just below break of slope, showing a shoulder shaped profile along the deep gorge. They are predominantly distributed on steep slopes in the geological areas of slate, gneiss and dolomite. None of the dormant landslides of large scale was activated by the earthquake.
23
Li, Y., G. Chen, C. Tang, G. Zhou, and L. Zheng. "Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network." Natural Hazards and Earth System Sciences 12, no. 8 (August 31, 2012): 2719–29. http://dx.doi.org/10.5194/nhess-12-2719-2012.
Abstract:
Abstract. A GIS-based method for the assessment of landslide susceptibility in a selected area of Qingchuan County in China is proposed by using the back-propagation Artificial Neural Network model (ANN). Landslide inventory was derived from field investigation and aerial photo interpretation. 473 landslides occurred before the Wenchuan earthquake (which were thought as rainfall-induced landslides (RIL) in this study), and 885 earthquake-induced landslides (EIL) were recorded into the landslide inventory map. To understand the different impacts of rainfall and earthquake on landslide occurrence, we first compared the variations between landslide spatial distribution and conditioning factors. Then, we compared the weight variation of each conditioning factor derived by adjusting ANN structure and factors combination respectively. Last, the weight of each factor derived from the best prediction model was applied to the entire study area to produce landslide susceptibility maps. Results show that slope gradient has the highest weight for landslide susceptibility mapping for both RIL and EIL. The RIL model built with four different factors (slope gradient, elevation, slope height and distance to the stream) shows the best success rate of 93%; the EIL model built with five different factors (slope gradient, elevation, slope height, distance to the stream and distance to the fault) has the best success rate of 98%. Furthermore, the EIL data was used to verify the RIL model and the success rate is 92%; the RIL data was used to verify the EIL model and the success rate is 53%.
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Meena and Tavakkoli Piralilou. "Comparison of Earthquake-Triggered Landslide Inventories: A Case Study of the 2015 Gorkha Earthquake, Nepal." Geosciences 9, no. 10 (October 10, 2019): 437. http://dx.doi.org/10.3390/geosciences9100437.
Abstract:
Despite landslide inventories being compiled throughout the world every year at different scales, limited efforts have been made to critically compare them using various techniques or by different investigators. Event-based landslide inventories indicate the location, distribution, and detected boundaries of landslides caused by a single event, such as an earthquake or a rainstorm. Event-based landslide inventories are essential for landslide susceptibility mapping, hazard modeling, and further management of risk mitigation. In Nepal, there were several attempts to map landslides in detail after the Gorkha earthquake. Particularly after the main event on 25 April 2015, researchers around the world mapped the landslides induced by this earthquake. In this research, we compared four of these published inventories qualitatively and quantitatively using different techniques. Two principal methodologies, namely the cartographical degree of matching and frequency area distribution (FAD), were optimized and applied to evaluate inventory maps. We also showed the impact of using satellite imagery with different spatial resolutions on the landslide inventory generation by analyzing matches and mismatches between the inventories. The results of our work give an overview of the impact of methodology selection and outline the limitations and advantages of different remote sensing and mapping techniques for landslide inventorying.
25
Wu, Chunhung. "Using the Spatiotemporal Hot Spot Analysis and Multi-Annual Landslide Inventories to Analyze the Evolution and Characteristic of Rainfall-Induced Landslide at the Subwatershed Scale in Taiwan." Water 15, no. 7 (April 1, 2023): 1355. http://dx.doi.org/10.3390/w15071355.
Abstract:
This study used rainfall and annual landslide data for the 2003–2017 period in Taiwan to determine the long-term evolution of landslides and conducted a spatiotemporal analysis of landslides at the subwatershed scale. The historically severe landslide induced by Typhoon Morakot in 2009 was mainly distributed in the central mountainous region and southern Taiwan. The Mann–Kendall trend test revealed that in 2003–2017, 13.2% of subwatersheds in Taiwan exhibited an upward trend of landslide evolution. Local outlier analysis results revealed that the landslide high–high cluster was concentrated in the central mountainous region and southern Taiwan. Moreover, the spatiotemporal analysis indicated 24.2% of subwatersheds in Taiwan in 2003–2017 as spatiotemporal landslide hot spots. The main patterns of spatiotemporal landslide hot spots in 2003–2017 were consecutive, intensifying, persistent, oscillating, and sporadic hot spots. The recovery rate in the first two years after the extreme rainfall-induced landslide event in Taiwan was 22.2%, and that in the third to eighth years was 31.6%. The recovery rate after extreme rainfall-induced landslides in Taiwan was higher than that after major earthquake-induced landslides in the world, and the new landslides were easily induced in the area of rivers and large landslide cases after Typhoon Morakot in 2009.
26
Parker, R. N., G. T. Hancox, D. N. Petley, C. I. Massey, A. L. Densmore, and N. J. Rosser. "Spatial distributions of earthquake-induced landslides and hillslope preconditioning in northwest South Island, New Zealand." Earth Surface Dynamics Discussions 3, no. 1 (January 6, 2015): 1–52. http://dx.doi.org/10.5194/esurfd-3-1-2015.
Abstract:
Abstract. Current models to explain regional-scale landslide events are not able to account for the possible effects of the legacy of previous earthquakes, which have triggered landslides in the past and are known to drive damage accumulation in brittle hillslope materials. This paper tests the hypothesis that spatial distributions of earthquake-induced landslides are determined by both the conditions at the time of the triggering earthquake (time-independent factors), and also the legacy of past events (time-dependent factors). To explore this, we undertake an analysis of failures triggered by the 1929 Buller and 1968 Inangahua earthquakes, in the northwest South Island of New Zealand. The spatial extent of landslides triggered by these events was in part coincident (overlapping). Spatial distributions of earthquake-triggered landslides are determined by a combination of earthquake and local characteristics, which influence the dynamic response of hillslopes. To identify the influence of a legacy from past events, we use logistic regression to control for the effects of time-independent variables (seismic ground motion, hillslope gradient, lithology, and the effects of topographic amplification caused by ridge- and slope-scale topography), in an attempt to reveal unexplained variability in the landslide distribution. We then assess whether this variability can be attributed to the legacy of past events. Our results suggest that the 1929 Buller earthquake influenced the distribution of landslides triggered by the 1968 Inangahua earthquake. Hillslopes in regions that experienced strong ground motions in 1929 were more likely to fail in 1968 than would be expected on the basis of time-independent factors alone. This effect is consistent with our hypothesis that unfailed hillslopes in the 1929 earthquake were weakened by damage accumulated during this earthquake and its associated aftershock sequence, and this weakening then influenced the performance of the landscape in the 1968 earthquake. While our results are tentative, the findings emphasize that a lack of knowledge of the damage state of hillslopes in a landscape potentially represents an important source of uncertainty when assessing landslide susceptibility. Constraining the damage history of hillslope materials, through analysis of historical events, therefore provides a potential means of reducing this uncertainty.
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Marc, Odin, Robert Behling, Christoff Andermann, Jens M. Turowski, Luc Illien, Sigrid Roessner, and Niels Hovius. "Long-term erosion of the Nepal Himalayas by bedrock landsliding: the role of monsoons, earthquakes and giant landslides." Earth Surface Dynamics 7, no. 1 (January 25, 2019): 107–28. http://dx.doi.org/10.5194/esurf-7-107-2019.
Abstract:
Abstract. In active mountain belts with steep terrain, bedrock landsliding is a major erosional agent. In the Himalayas, landsliding is driven by annual hydro-meteorological forcing due to the summer monsoon and by rarer, exceptional events, such as earthquakes. Independent methods yield erosion rate estimates that appear to increase with sampling time, suggesting that rare, high-magnitude erosion events dominate the erosional budget. Nevertheless, until now, neither the contribution of monsoon and earthquakes to landslide erosion nor the proportion of erosion due to rare, giant landslides have been quantified in the Himalayas. We address these challenges by combining and analysing earthquake- and monsoon-induced landslide inventories across different timescales. With time series of 5 m satellite images over four main valleys in central Nepal, we comprehensively mapped landslides caused by the monsoon from 2010 to 2018. We found no clear correlation between monsoon properties and landsliding and a similar mean landsliding rate for all valleys, except in 2015, where the valleys affected by the earthquake featured ∼5–8 times more landsliding than the pre-earthquake mean rate. The long-term size–frequency distribution of monsoon-induced landsliding (MIL) was derived from these inventories and from an inventory of landslides larger than ∼0.1 km2 that occurred between 1972 and 2014. Using a published landslide inventory for the Gorkha 2015 earthquake, we derive the size–frequency distribution for earthquake-induced landsliding (EQIL). These two distributions are dominated by infrequent, large and giant landslides but under-predict an estimated Holocene frequency of giant landslides (> 1 km3) which we derived from a literature compilation. This discrepancy can be resolved when modelling the effect of a full distribution of earthquakes of variable magnitude and when considering that a shallower earthquake may cause larger landslides. In this case, EQIL and MIL contribute about equally to a total long-term erosion of ∼2±0.75 mm yr−1 in agreement with most thermo-chronological data. Independently of the specific total and relative erosion rates, the heavy-tailed size–frequency distribution from MIL and EQIL and the very large maximal landslide size in the Himalayas indicate that mean landslide erosion rates increase with sampling time, as has been observed for independent erosion estimates. Further, we find that the sampling timescale required to adequately capture the frequency of the largest landslides, which is necessary for deriving long-term mean erosion rates, is often much longer than the averaging time of cosmogenic 10Be methods. This observation presents a strong caveat when interpreting spatial or temporal variability in erosion rates from this method. Thus, in areas where a very large, rare landslide contributes heavily to long-term erosion (as the Himalayas), we recommend 10Be sample in catchments with source areas > 10 000 km2 to reduce the method mean bias to below ∼20 % of the long-term erosion.
28
Havenith, Hans-Balder, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, et al. "Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences." Natural Hazards and Earth System Sciences 22, no. 10 (October 18, 2022): 3361–84. http://dx.doi.org/10.5194/nhess-22-3361-2022.
Abstract:
Abstract. First analyses of landslide distribution and triggering factors are presented for the region affected by the 14 August 2021 earthquake (Mw=7.2) in the Nippes Department, Haiti. Landslide mapping was mainly carried out by comparing pre- and post-event remote imagery (∼0.5–1 m resolution) available on Google Earth Pro® and Sentinel-2 (10 m resolution) satellite images. The first covered about 50 % of the affected region (for post-event imagery and before completion of the map in January 2022), and the latter were selected to cover the entire potentially affected zone. On the basis of the completed landslide inventory, comparisons are made with catalogs compiled by others both for the August 2021 and the January 2010 seismic events, including one open inventory (by the United States Geological Survey) that was also used for further statistical analyses. Additionally, we studied the pre-2021 earthquake slope stability conditions. These comparisons show that the total number of landslides mapped for the 2021 earthquake (7091) is larger than the one recently published by another research team for the same event but slightly smaller than the number of landslides mapped by a third research team. It is also clearly smaller than the one observed by two other research teams for the 2010 earthquake (e.g., 23 567, for the open inventory). However, these apparently fewer landslides triggered in 2021 cover much wider areas of slopes (>80 km2) than those induced by the 2010 event (∼25 km2 – considering the open inventory). A simple statistical analysis indicates that the lower number of 2021 landslides can be explained by the missing detection of the smallest landslides triggered in 2021, partly due to the lower-resolution imagery available for most of the areas affected by the recent earthquake; this is also confirmed by an inventory completeness analysis based on size–frequency statistics. The much larger total area of landslides triggered in 2021, compared to the 2010 earthquake, can be related to different physical reasons: (a) the larger earthquake magnitude in 2021, (b) the more central location of the fault segment that ruptured in 2021 with respect to coastal zones, (c) and possible climatic preconditioning of slope instability in the 2021 affected area. These observations are supported by (1) a new pre-2021 earthquake landslide map; (2) rainfall distribution maps presented for different periods (including October 2016 – when Hurricane Matthew had crossed the western part of Haiti), covering both the 2010 and 2021 affected zones; and (3) shaking intensity prediction maps.
29
Liu, Wen, Fumio Yamazaki, and Yoshihisa Maruyama. "Detection of Earthquake-Induced Landslides during the 2018 Kumamoto Earthquake Using Multitemporal Airborne Lidar Data." Remote Sensing 11, no. 19 (October 1, 2019): 2292. http://dx.doi.org/10.3390/rs11192292.
Abstract:
A series of earthquakes hit Kumamoto Prefecture, Japan, continuously over a period of two days in April 2016. The earthquakes caused many landslides and numerous surface ruptures. In this study, two sets of the pre- and post-event airborne Lidar data were applied to detect landslides along the Futagawa fault. First, the horizontal displacements caused by the crustal displacements were removed by a subpixel registration. Then, the vertical displacements were calculated by averaging the vertical differences in 100-m grids. The erosions and depositions in the corrected vertical differences were extracted using the thresholding method. Slope information was applied to remove the vertical differences caused by collapsed buildings. Then, the linked depositions were identified from the erosions according to the aspect information. Finally, the erosion and its linked deposition were identified as a landslide. The results were verified using truth data from field surveys and image interpretation. Both the pair of digital surface models acquired over a short period and the pair of digital terrain models acquired over a 10-year period showed good potential for detecting 70% of landslides.
30
Huang, Yidan, and Lingkan Yao. "Size distribution law of earthquake-triggered landslides in different seismic intensity zones." Nonlinear Processes in Geophysics 28, no. 2 (April 16, 2021): 167–79. http://dx.doi.org/10.5194/npg-28-167-2021.
Abstract:
Abstract. The Ms 8.0 Wenchuan earthquake in 2008 and Ms 7.0 Lushan earthquake in 2013 produced thousands of landslides in the southern region of the Longmen Mountains in China. We conducted field investigations and analyzed remote sensing data to determine the distribution law of earthquake-triggered landslides. The results show a strong negative power law relationship between the size and frequency of landslides in VII, VIII, and IX seismic intensity zones, a weak power law in the X seismic intensity zone, and a lognormal distribution in the XI seismic intensity zone. Landslide density increases with increasing seismic intensity. A sandpile cellular automata model was built under the conceptual framework of self-organized criticality theory to simulate earthquake-induced landslides. Data from the simulations demonstrate that, with increasing disturbance intensity, the dynamical mechanism of the sandpile model changes from a strong power law to a weak power law and then to a lognormal distribution. Results from shaking table experiments of a one-sided slope sandpile show that, for peak ground acceleration (PGA) in the range of 0.075–0.125 g, the relation between the amount and frequency of sand follows a negative power law. For PGA between 0.15 and 0.25 g, the relation obeys a lognormal distribution. This verifies that the abovementioned distribution of earthquake-induced landslides should be a universal law from a physical viewpoint and may apply to other areas. This new perspective may be used to guide the development of an inventory of earthquake-triggered landslides and provide a scientific basis for their prediction.
31
Tanyaş, Hakan, Dalia Kirschbaum, and Luigi Lombardo. "Capturing the footprints of ground motion in the spatial distribution of rainfall-induced landslides." Bulletin of Engineering Geology and the Environment 80, no. 6 (April 18, 2021): 4323–45. http://dx.doi.org/10.1007/s10064-021-02238-x.
Abstract:
AbstractThe coupled effect of earthquakes and rainfall is rarely investigated in landslide susceptibility assessments although it could be crucial to predict landslide occurrences. This is even more critical in the context of early warning systems and especially in cases of extreme precipitation regimes in post-seismic conditions, where the rock masses are already damaged due to the ground shaking. Here, we investigate this concept by accounting for the legacy of seismic ground shaking in rainfall-induced landslide (RFIL) scenarios. We do this to identify whether ground shaking plays a role in the susceptibility to post-seismic rainfall-induced landslides and to identify whether this legacy effect persists through time. With this motivation, we use binary logistic regression and examine time series of landslides associated with four earthquakes occurred in Indonesia: 2012 Sulawesi (Mw = 6.3), 2016 Reuleut (Mw = 6.5), 2017 Kasiguncu (Mw = 6.6) and 2018 Palu (Mw = 7.5) earthquakes. The dataset includes one co-seismic and three post-seismic landslide inventories for each earthquake. We use the peak ground acceleration map of the last strongest earthquake in each case as a predisposing factor of landslides representing the effect of ground shaking. We observe that, at least for the study areas under consideration and in a probabilistic context, the earthquake legacy contributes to increase the post-seismic RFIL susceptibility. This positive contribution decays through time. Specifically, we observe that ground motion is a significant predisposing factor controlling the spatial distribution of RFIL in the post-seismic period 110 days after an earthquake. We also show that this effect dissipates within 3 years at most.
32
Gunawan Tejakusuma, Iwan, Firman Prawiradisastra, Khori Sugianti, Adrin Tohari, Zufialdi Zakaria, Syakira Trisnafiah, Riski Fitriani, Dimas Biwas Putra, Antonina Pri Martireni, and Bayu Budiman. "Characteristics of landslides induced by an earthquake from a hidden strike-slip active fault in the Cianjur Area of West Java." E3S Web of Conferences 447 (2023): 01009. http://dx.doi.org/10.1051/e3sconf/202344701009.
Abstract:
On November 21, 2022, the Cianjur area in West Java, Indonesia, experienced devastating landslides caused by a magnitude 5.6 earthquake, with the epicenter traced to a hidden active fault approximately 11 kilometers beneath the surface, known as the Cugenang Fault. This study investigates the post-disaster landslides and aims to discover the characteristics of the landslides triggered by this earthquake. The methodology involves literature review, lithology descriptions, landslide slip surface analysis, soil analysis, slope assessment, land cover and land use change examination, landslide orientation evaluation, and distance measurements to the earthquake's epicenter and the Cugenang fault. Drones aided spatial landslide analysis. The study highlights the strong link between intense shaking along the active fault and landslide occurrences. Due to lithological bedding control, these landslides all head southwest and are located 0.35 to 0.67 kilometres from the fault. The residual soil, highly weathered breccia, and possible tuff volcanic deposits, which act as a sliding plane, lie in a similar direction to the slope, creating a vulnerable setting for landslides. The morphology and exposures of the Sarampad and Rawacina landslides showed similar phenomena to liquefaction. Land use changes, including slope cutting without proper stabilization measures, contribute to landslides to a certain degree.
33
Guo, Bin, Xiangjun Pei, Min Xu, and Tiantao Li. "Analyzing Rainfall Threshold for Shallow Landslides Using Physically Based Modeling in Rasuwa District, Nepal." Water 14, no. 24 (December 13, 2022): 4074. http://dx.doi.org/10.3390/w14244074.
Abstract:
On 25 April 2015, an M7.8 large earthquake happened in Nepal, and 4312 landslides were triggered during or after the earthquake. The 2015 earthquake happened years ago, but the risk of rainfall-induced landslides is still high. Rainfall-induced shallow landslides threaten both human lives and economy development, especially in the Rasuwa area. Due to financial conditions and data availability, a regional-scale rainfall threshold can be an effective method to reduce the risk of shallow landslides. A physically based model was used with limited data. The dynamic hydrological model provides the soil moisture and groundwater change, and the infinite slope stability model produces the factor of safety. Remote sensing data, field investigation, soil sample tests, and literature review were used in the model parameterization. The landslide stability condition of 2016 was simulated. In addition, intensity-antecedent rainfall thresholds were defined based on the physically based modelling output. Sixty groups of data were used for validation, and the 15-day intensity-antecedent rainfall threshold has the best performance with an accuracy of 88.33%.
34
Marc, O., and N. Hovius. "Amalgamation in landslide maps: effects and automatic detection." Natural Hazards and Earth System Sciences 15, no. 4 (April 2, 2015): 723–33. http://dx.doi.org/10.5194/nhess-15-723-2015.
Abstract:
Abstract. Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% incorrectly amalgamated landslides missed and 3.9–4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
35
Marc, O., and N. Hovius. "Amalgamation in landslide maps: effects and automatic detection." Natural Hazards and Earth System Sciences Discussions 2, no. 12 (December 16, 2014): 7651–78. http://dx.doi.org/10.5194/nhessd-2-7651-2014.
Abstract:
Abstract. Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area-frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in datasets produced by automated mapping. We present 5 inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area-frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and DEM analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% wrongly amalgamated landslides missed and 3.9–4.8% correct polygons wrongly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
36
Rodrı́guez, C. E., J. J. Bommer, and R. J. Chandler. "Earthquake-induced landslides: 1980–1997." Soil Dynamics and Earthquake Engineering 18, no. 5 (July 1999): 325–46. http://dx.doi.org/10.1016/s0267-7261(99)00012-3.
37
Kunwar, Saket. "SEGMENTATION AND CLASSIFICATION OF NEPAL EARTHQUAKE INDUCED LANDSLIDES USING SENTINEL-1 PRODUCT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 769–74. http://dx.doi.org/10.5194/isprs-archives-xli-b7-769-2016.
Abstract:
On April 26, 2015, an earthquake of magnitude 7.8 on the Richter scale occurred, with epicentre at Barpak (28°12'20''N,84°44'19''E), Nepal. Landslides induced due to the earthquake and its aftershock added to the natural disaster claiming more than 9000 lives. Landslides represented as lines that extend from the head scarp to the toe of the deposit were mapped by the staff of the British Geological Survey and is available freely under Open Data Commons Open Database License(ODC-ODbL) license at the Humanitarian Data Exchange Program. This collection of 5578 landslides is used as preliminary ground truth in this study with the aim of producing polygonal delineation of the landslides from the polylines via object oriented segmentation. Texture measures from Sentinel-1a Ground Range Detected (GRD) Amplitude data and eigenvalue-decomposed Single Look Complex (SLC) polarimetry product are stacked for this purpose. This has also enabled the investigation of landslide properties in the H-Alpha plane, while developing a classification mechanism for identifying the occurrence of landslides.
38
Kunwar, Saket. "SEGMENTATION AND CLASSIFICATION OF NEPAL EARTHQUAKE INDUCED LANDSLIDES USING SENTINEL-1 PRODUCT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 769–74. http://dx.doi.org/10.5194/isprsarchives-xli-b7-769-2016.
Abstract:
On April 26, 2015, an earthquake of magnitude 7.8 on the Richter scale occurred, with epicentre at Barpak (28°12'20''N,84°44'19''E), Nepal. Landslides induced due to the earthquake and its aftershock added to the natural disaster claiming more than 9000 lives. Landslides represented as lines that extend from the head scarp to the toe of the deposit were mapped by the staff of the British Geological Survey and is available freely under Open Data Commons Open Database License(ODC-ODbL) license at the Humanitarian Data Exchange Program. This collection of 5578 landslides is used as preliminary ground truth in this study with the aim of producing polygonal delineation of the landslides from the polylines via object oriented segmentation. Texture measures from Sentinel-1a Ground Range Detected (GRD) Amplitude data and eigenvalue-decomposed Single Look Complex (SLC) polarimetry product are stacked for this purpose. This has also enabled the investigation of landslide properties in the H-Alpha plane, while developing a classification mechanism for identifying the occurrence of landslides.
39
Lee, S. T., T. T. Yu, W. F. Peng, and C. L. Wang. "Incorporating the effects of topographic amplification in the analysis of earthquake-induced landslide hazards using logistic regression." Natural Hazards and Earth System Sciences 10, no. 12 (December 3, 2010): 2475–88. http://dx.doi.org/10.5194/nhess-10-2475-2010.
Abstract:
Abstract. Seismic-induced landslide hazards are studied using seismic shaking intensity based on the topographic amplification effect. The estimation of the topographic effect includes the theoretical topographic amplification factors and the corresponding amplified ground motion. Digital elevation models (DEM) with a 5-m grid space are used. The logistic regression model and the geographic information system (GIS) are used to perform the seismic landslide hazard analysis. The 99 Peaks area, located 3 km away from the ruptured fault of the Chi-Chi earthquake, is used to test the proposed hypothesis. An inventory map of earthquake-triggered landslides is used to produce a dependent variable that takes a value of 0 (no landslides) or 1 (landslides). A set of independent parameters, including lithology, elevation, slope gradient, slope aspect, terrain roughness, land use, and Arias intensity (Ia) with the topographic effect. Subsequently, logistic regression is used to find the best fitting function to describe the relationship between the occurrence and absence of landslides within an individual grid cell. The results of seismic landslide hazard analysis that includes the topographic effect (AUROC = 0.890) are better than those of the analysis without it (AUROC = 0.874).
40
Parker, R. N., G. T. Hancox, D. N. Petley, C. I. Massey, A. L. Densmore, and N. J. Rosser. "Spatial distributions of earthquake-induced landslides and hillslope preconditioning in the northwest South Island, New Zealand." Earth Surface Dynamics 3, no. 4 (October 20, 2015): 501–25. http://dx.doi.org/10.5194/esurf-3-501-2015.
Abstract:
Abstract. Current models to explain regional-scale landslide events are not able to account for the possible effects of the legacy of previous earthquakes, which have triggered landslides in the past and are known to drive damage accumulation in brittle hillslope materials. This paper tests the hypothesis that spatial distributions of earthquake-induced landslides are determined by both the conditions at the time of the triggering earthquake (time-independent factors) and the legacy of past events (time-dependent factors). To explore this, we under\\-take an analysis of failures triggered by the 1929 Buller and 1968 Inangahua earthquakes, in the northwest South Island of New Zealand. The spatial extents of landslides triggered by these events were in part coincident. Spatial distributions of earthquake-triggered landslides are determined by a combination of earthquake and local characteristics, which influence the dynamic response of hillslopes. To identify the influence of a legacy from past events, we first use logistic regression to control for the effects of time-independent variables. Through this analysis we find that seismic ground motion, hillslope gradient, lithology, and the effects of topographic amplification caused by ridge- and slope-scale topography exhibit a consistent influence on the spatial distribution of landslides in both earthquakes. We then assess whether variability unexplained by these variables may be attributed to the legacy of past events. Our results suggest that hillslopes in regions that experienced strong ground motions in 1929 were more likely to fail in 1968 than would be expected on the basis of time-independent factors alone. This effect is consistent with our hypothesis that unfailed hillslopes in the 1929 earthquake were weakened by damage accumulated during this earthquake and its associated aftershock sequence, which influenced the behaviour of the landscape in the 1968 earthquake. While our results are tentative, they suggest that the damage legacy of large earthquakes may persist in parts of the landscape for much longer than observed sub-decadal periods of post-seismic landslide activity and sediment evacuation. Consequently, a lack of knowledge of the damage state of hillslopes in a landscape potentially represents an important source of uncertainty when assessing landslide susceptibility. Constraining the damage history of hillslopes, through analysis of historical events, therefore provides a potential means of reducing this uncertainty.
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Xu, C. "LANDSLIDES TRIGGERED BY THE 2015 GORKHA, NEPAL EARTHQUAKE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1989–93. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1989-2018.
Abstract:
The 25 April 2015 Gorkha Mw 7.8 earthquake in central Nepal caused a large number of casualties and serious property losses, and also induced numerous landslides. Based on visual interpretation of high-resolution optical satellite images pre- and post-earthquake and field reconnaissance, we delineated 47,200 coseismic landslides with a total distribution extent more than 35,000&thinsp;km<sup>2</sup>, which occupy a total area about 110&thinsp;km<sup>2</sup>. On the basis of a scale relationship between landslide area (A) and volume (V), V = 1.3147&thinsp;&times;&thinsp;A<sup>1.2085</sup>, the total volume of the coseismic landslides is estimated to be about 9.64&thinsp;&times;&thinsp;10<sup>8</sup>&thinsp;m<sup>3</sup>. Calculation yields that the landslide number density, area density, and volume density are 1.32&thinsp;km<sup>&minus;2</sup>, 0.31&thinsp;%, and 0.027&thinsp;m, respectively. The spatial distribution of these landslides is consistent with that of the mainshock and aftershocks and the inferred causative fault, indicating the effect of the earthquake energy release on the pattern on coseismic landslides. This study provides a new, more detailed and objective inventory of the landslides triggered by the Gorkha earthquake, which would be significant for further study of genesis of coseismic landslides, hazard assessment and the long-term impact of the slope failure on the geological environment in the earthquake-scarred region.
42
Tian, Shu Jun, and Ji Ming Kong. "Statistical Analysis the Distribution of Landslide Triggered by m 8.0 Wenchuan, China Earthquake of May 12, 2008." Applied Mechanics and Materials 353-356 (August 2013): 1236–39. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.1236.
Abstract:
Abundant landslides were triggered by Wenchuan earthquake. The paper mapped 4722 earthquake-induced landslides and used Geographic Information System to finish the statistical data about the occurrence of landslides correlating with environmental factors including distance from middle faults, lithology, altitude, river, and slope steepness. Because the seismic energy released along the middle faults and the attenuation of energy was obvious in minor axis, the zonal distribution of landslides was consistent with strike of middle faults and about 64.42% of landslides occurred within 20 km from middle faults of Longmenshan. As the middle faults and front faults both belonged to thrust faults, the impact of earthquake in hanging wall was higher than that in footwall. Therefore, the density of landslide in hanging wall of middle faults was obviously higher than that in footwall. As the release of seismic energy was restricted by landform and river, landslides were concentrative and consistent with the spatial distribution of rivers in the mountainous terrain. The scale effect of seismic acceleration was so intense in top of mountain with high difference in elevation along river that the origin of most landslides were in upside of slope. About 99.43% of landslides distributed in area where the seismic intensity was more than VII.
43
Shao, Xiaoyi, Chong Xu, and Siyuan Ma. "Preliminary Analysis of Coseismic Landslides Induced by the 1 June 2022 Ms 6.1 Lushan Earthquake, China." Sustainability 14, no. 24 (December 9, 2022): 16554. http://dx.doi.org/10.3390/su142416554.
Abstract:
At 17:00 (UTC+8) on 1 June 2022, an Ms 6.1 reverse earthquake struck Lushan County, Ya’an City, Sichuan Province. This earthquake event had a focal depth of 10 km and the epicenter was located at 30.37° N and 102.94° E. The purpose of this study is to document a comprehensive coseismic landslide inventory for this event and analyze the distribution pattern and factors controlling the landslides. After careful visual interpretations, this quake event was determined to have in total triggered about 2352 landslides in an area of 3900 km2, including both shallow disrupted landslides and collapses, for which the spatial distribution was statistically related to regional topography, geology, and seismicity. Notably, a vast majority of the landslides were located on the NW plate of the seismogenic fault, and were distributed in the area with a seismic intensity of VII. In addition, coseismic landslides were more likely to appear in areas with high altitude, relief, and large slope. The landslide area density (LAD) increased with an increase in the above factors and is explained by an exponential relationship, indicating that the occurrence of coseismic landslides in this area was more easily affected by topographic factors than seismic factors. Most small-scale landslides were clustered in the ridge area, which shows the seismic amplification effects of mountain slopes. Due to the impact of seismic wave propagation direction, hillslopes facing northeast-east (NE-E) were more prone to collapse than southwest-facing ones. Based on the distribution pattern of the landslides, we suggest that the seismogenic fault of this event was NW dipping. These findings indicate that it is effective to identify the dipping of seismogenic faults using the spatial distribution pattern of coseismic landslides.
44
Gadtaula, Arishma, and Subodh Dhakal. "Landslide susceptibility mapping using Weight of Evidence Method in Haku, Rasuwa District, Nepal." Journal of Nepal Geological Society 58 (June 25, 2019): 163–71. http://dx.doi.org/10.3126/jngs.v58i0.24601.
Abstract:
The 2015 Gorkha Earthquake resulted in many other secondary hazards affecting the livelihoods of local people residing in mountainous area. Plenty of earthquake induced landslides and mass movement activities were observed after earthquake. Haku region of Rasuwa was also one of the severely affected areas by co-seismic landslides triggered by the disastrous earthquake. Statistics shows that around 400 families were relocated from Haku Post-earthquake (MoFA, 2015). A total of 101 co-seismic landslides were focused during the study and were verified during the fieldwork in Haku village. The conditioning factors used in this study were slope, aspect, elevation, curvature (plan and profile), landuse, geology and PGA. The conditioning factor maps were prepared in GIS working environment and further analysis was conducted with the assistance of Google earth. This study used Weight of Evidence (WoE), a bivariate statistical model and its performance was assessed. The susceptibility map was further characterized into five different classes namely very low, low, high, medium and very high susceptibility zones. The statistical analysis obtained from the results of the susceptibility map prepared by using WoE model gave the results that maximum area percentage of landslide distribution was observed in medium and high susceptibility classes i.e. 38% and 33% followed by very high (13%), low (10%) and very low classes (5.8%) About 25% of the total landslides are separated to validate the prepared model used in the landslide susceptibility zonation. The overlay method predicts the reliability of the model.
45
Chunga, Kervin, Franz A. Livio, Carlos Martillo, Hernán Lara-Saavedra, Maria Francesca Ferrario, Ivan Zevallos, and Alessandro Maria Michetti. "Landslides Triggered by the 2016 Mw 7.8 Pedernales, Ecuador Earthquake: Correlations with ESI-07 Intensity, Lithology, Slope and PGA-h." Geosciences 9, no. 9 (August 26, 2019): 371. http://dx.doi.org/10.3390/geosciences9090371.
Abstract:
We provide a dataset of the landslides induced by the 2016 Pedernales megathrust earthquake, Ecuador (Mw 7.8, focal depth of 20 km) and compare their spatial distribution with mapped bedrock lithology, horizontal peak ground acceleration (PGA-h) and the macroseismic intensity based on earthquake-induced environmental effects (ESI-07). We studied 192 coseismic landslides (classified as coherent, disrupted and lateral spreads) located in the epicentral area, defined by the VII to IXESI-07 isoseismals. Based on our findings, lahar deposits, tuffs and volcanoclastic units are the most susceptible to landslides occurrence. Alluvial plains with fluvial loose fine sand are the most susceptible setting for lateral spreading, with a maximum intensity of IXESI-07. The coherent landslides are frequently found in altered shale and siltstone geological units with moderate slopes (8°–16°), with typical intensity ranging between VII and VIIIESI-07. Our analysis draws a typical framework for slope movements triggered by subduction earthquakes in Ecuador. The most dangerous setting is the coastal region, a relatively highly urbanized area located near the epicenter and where liquefaction can trigger massive lateral spreading events. Coherent and disrupted landslides, dominating the more internal hilly region, can be triggered also in moderate slope settings (i.e., less than 10°). Indeed, the regression analysis between seismic intensity, PGA-h and landslide occurrence shows that most of the events occurred at PGA-h values between 0.4 g and 1.2 g, at a distance of 30 to 50 km from the rupture plane. Our database suggests that lithology and hillslope geometry are the main geological/geomorphological factors controlling coseismic landslides occurrence; while the distance from the rupture plane plays a significant role on determining the landslide size. Finally, we underline that coseismically-triggered landslides are among the most common environmental effects occurring during large subduction events that can be effectively used to properly evaluate the earthquake macroseismic field. The landslide inventory we compiled is suitable for assessing the vulnerability of physical environment from subduction earthquakes in Ecuador, and offers a primary data source for future worldwide analysis.
46
Román-Herrera, José Carlos, Martín Jesús Rodríguez-Peces, and Julio Garzón-Roca. "Comparison between Machine Learning and Physical Models Applied to the Evaluation of Co-Seismic Landslide Hazard." Applied Sciences 13, no. 14 (July 18, 2023): 8285. http://dx.doi.org/10.3390/app13148285.
Abstract:
A comparative methodology between advanced statistical tools and physical-based methods is carried out to ensure their reliability and objectivity for the evaluation of co-seismic landslide hazard maps. To do this, an inventory of landslides induced by the 2011 Lorca earthquake is used to highlight the usefulness of these methods to improve earthquake-induced landslide hazard analyses. Various statistical models, such as logistic regression, random forest, artificial neural network, and support vector machine, have been employed for co-seismic landslide susceptibility mapping. The results demonstrate that machine learning techniques using principal components (especially, artificial neural network and support vector machine) yield better results compared to other models. In particular, random forest shows poor results. Artificial neural network and support vector machine approaches are compared to the results of physical-based methods in the same area, suggesting that machine learning methods can provide better results for developing co-seismic landslide susceptibility maps. The application of different advanced statistical models shows the need for validation with an actual inventory of co-seismic landslides to ensure reliability and objectivity. In addition, statistical methods require a great amount of data. The results establish effective land planning and hazard management strategies in seismic areas to minimize the damage of future co-seismic landslides.
47
Dellow, G., M. Yetton, C. Massey, G. Archibald, D. J. A. Barrell, D. Bell, Z. Bruce, et al. "Landslides caused by the 22 February 2011 Christchurch earthquake and management of landslide risk in the immediate aftermath." Bulletin of the New Zealand Society for Earthquake Engineering 44, no. 4 (December 31, 2011): 227–38. http://dx.doi.org/10.5459/bnzsee.44.4.227-238.
Abstract:
At 12.51 pm (NZST) on 22 February 2011 a shallow, magnitude MW 6.2 earthquake with an epicentre located just south of Christchurch, New Zealand, caused widespread devastation including building collapse, liquefaction and landslides. Throughout the Port Hills of Banks Peninsula on the southern fringes of Christchurch landslide and ground damage caused by the earthquake included rock-fall (both cliff collapse and boulder roll), incipient loess landslides, and retaining wall and fill failures. Four deaths from rock-fall occurred during the mainshock and one during an aftershock later in the afternoon of the 22nd. Hundreds of houses were damaged by rock-falls and landslide-induced ground cracking.
Four distinct landslide or ground failure types have been recognised. Firstly, rocks fell from lava outcrops on the Port Hills and rolled and bounced over hundreds of metres damaging houses located on lower slopes and on valley floors. Secondly, over-steepened present-day and former sea-cliffs collapsed catastrophically. Houses were damaged by tension cracks on the slopes above the cliff faces and by debris inundation at the toe of the slopes. Thirdly, incipient movement of landslides in loess, ranging from a few millimetres up to 0.35 metres, occurred at several locations. Again houses were damaged by extension fissuring at the head of these features and compressional movement at the toe. The fourth mode of failure observed was retaining wall and fill failures, including shaking-induced settlement and fill displacement. These failures commonly affected both houses and roads.
In the days and weeks immediately following the earthquake a major concern was how to manage the risks from another large aftershock or a long return period rainstorm, in the areas worst affected by landslides, should one occur. Each of the four identified landslide types required a different risk management strategy. The rock-fall and boulder roll hazard was managed by identifying buildings at risk and enforcing mandatory evacuation. In the days immediately following the earthquake this process was based on expert opinion. In the weeks after the earthquake this process was rapidly enhanced with empirical data to confirm the risk. The rock-falls associated with cliff collapse were managed by evacuating properties damaged by extensional ground cracking at the top of the cliffs, adjacent properties, and properties damaged by debris inundation at the toe of the cliffs. The incipient landslide hazard was managed by rapidly deploying movement monitoring technologies to determine if these features were still moving and to monitor their response to on-going aftershock activity. The fill and retaining wall failures were managed by encouraging public reporting of areas of concern for rapid assessment by a geotechnical professional.
The success of the landslide risk management strategy was demonstrated by the magnitude MW 6.0 earthquake of 13 June when rock-falls and boulder roll damaged evacuated buildings and ground cracking and debris inundation further damaged evacuated areas. Some incipient landslides reactivated, producing similar movement patterns to the 22 February 2011 earthquake. Several retaining walls identified as dangerous and cordoned off also collapsed. No lives were lost and no serious injuries were reported from landslides in the 13 June 2011 earthquake.
48
Dou, Jie, Ali P. Yunus, Dieu Tien Bui, Mehebub Sahana, Chi-Wen Chen, Zhongfan Zhu, Weidong Wang, and Binh Thai Pham. "Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM." Remote Sensing 11, no. 6 (March 15, 2019): 638. http://dx.doi.org/10.3390/rs11060638.
Abstract:
Landslides are typically triggered by earthquakes or rainfall occasionally a rainfall event followed by an earthquake or vice versa. Yet, most of the works presented in the past decade have been largely focused at the single event-susceptibility model. Such type of modeling is found insufficient in places where the triggering mechanism involves both factors such as one found in the Chuetsu region, Japan. Generally, a single event model provides only limited enlightenment of landslide spatial distribution and thus understate the potential combination-effect interrelation of earthquakes- and rainfall-triggered landslides. This study explores the both-effect of landslides triggered by Chuetsu-Niigata earthquake followed by a heavy rainfall event through examining multiple traditional statistical models and data mining for understanding the coupling effects. This paper aims to compare the abilities of the statistical probabilistic likelihood-frequency ratio (PLFR) model, information value (InV) method, certainty factors (CF), artificial neural network (ANN) and ensemble support vector machine (SVM) for the landslide susceptibility mapping (LSM) using high-resolution-light detection and ranging digital elevation model (LiDAR DEM). Firstly, the landslide inventory map including 8459 landslide polygons was compiled from multiple aerial photographs and satellite imageries. These datasets were then randomly split into two parts: 70% landslide polygons (5921) for training model and the remaining polygons for validation (2538). Next, seven causative factors were classified into three categories namely topographic factors, hydrological factors and geological factors. We then identified the associations between landslide occurrence and causative factors to produce LSM. Finally, the accuracies of five models were validated by the area under curves (AUC) method. The AUC values of five models vary from 0.77 to 0.87. Regarding the capability of performance, the proposed SVM is promising for constructing the regional landslide-prone potential areas using both types of landslides. Additionally, the result of our LSM can be applied for similar areas which have been experiencing both rainfall-earthquake landslides.
49
Zhang, Pengfei, Hengzhi Qiu, Chong Xu, Xiaoli Chen, and Qing Zhou. "Analysis of the Controlling Effect of Excess Topography on the Distribution of Coseismic Landslides during the Iburi Earthquake, Japan, on 6 September 2018." Remote Sensing 15, no. 20 (October 20, 2023): 5035. http://dx.doi.org/10.3390/rs15205035.
Abstract:
Coseismic landslides cause changes in the hillside material, and this erosion process plays an important role in the evolution of the topography. Previous studies seldom involved research on the influence of excess topography on the occurrences of coseismic landslides. The Iburi earthquake, which occurred in Japan on 6 September 2018 and triggered a large number of landslides, provided a research example to explore the relationship between coseismic landslides and excess topography. We used the average slope of the lithology as the threshold slope of the corresponding stratum to calculate the excess topography of the different lithological units. Based on the advanced spaceborne thermal emission and reflection radiometer (ASTER) digital elevation model (DEM) with a resolution of 30 m, a quantitative analysis was conducted on the excess topography in the study area. The results indicate that the excess topography in the study area was mainly distributed in the valleys on both sides of the river, and the thickness of the excess topography on the high and steep ridges was generally greater than that at the foot of the slope, which has a relatively flat topography or a low elevation. In the area affected by the earthquake, approximately 94.66% of the coseismic landslides (with an area of approximately 28.23 m2) developed in the excess topography area, indicating that the distribution of the excess topography had a strong controlling influence on the spatial distribution of the coseismic landslides. The Iburi earthquake mainly induced shallow landslides, but the thickness of the landslide body was much smaller than the excess topography height in the landslides-affected area. This may imply that the excess topography was not completely removed by the coseismic landslides, and the areas where the earthquake landslides occurred still have the possibility of producing landslides in the future.
50
Rosly, Mohammad Haziq, Habib Musa Mohamad, Nurmin Bolong, and Noor Sheena Herayani Harith. "An Overview: Relationship of Geological Condition and Rainfall with Landslide Events at East Malaysia." Trends in Sciences 19, no. 8 (March 29, 2022): 3464. http://dx.doi.org/10.48048/tis.2022.3464.
Abstract:
Tropical country like Malaysia is rich with residual soil and nurtured with high rainfall amount on average 2,550 mm per year. From 2009 until 2018, there are many landslide events reported in the news at Ranau, Sabah and Canada Hill Miri, Sarawak that occurred during rainy season and the landslide recurs within same location over the years. The objective of this study is to determine the relationship of landslide events with geological condition and rainfall at Ranau, Sabah and Canada Hill Miri, Sarawak. Historical landslide data were obtained from local news, previous researchers, and local authorities. Integrated review was conducted to meet the objective. In summary, both areas are prone to landslide due to the high average amount rainfall recorded and the geological properties that are susceptible to landslide occurrence namely shale interbedded with sandstone. Sandstone and shale contact are easily accessible by water weaken the contact surface lead to landslides incidents. Besides, Shale classified as highly plastic soil due to high amount of clay. Clay soil depends on its matric suction to sustain its strength towards sliding. Thus, increasing of pore pressure from rain infiltration reduce the matric suction and eventually reduce the shear strength. Ranau is located at seismically active area compare to Miri and other locations in Sabah crossing Lobou-Lobou fault, Mensaban fault and Mesilou fault. Theoretically, slope instability due to earthquake happened because the cementation of soil may be broken and lead to lesser roughness between soil surfaces resulting in reduction of internal friction angle and cohesion of soil.
HIGHLIGHTS
Rainfall-induced landslides are the common landslides phenomenon worldwide including East Malaysia.
However, due to the high number of seismic activity, Earthquake-induced landslides should not be neglected as one of slope failure phenomena in East Malaysia
Combinations of both Rainfall and Earthquake are required to be investigated due to the presence of both landslide triggering factors from historical data at East Malaysia
GRAPHICAL ABSTRACT