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Keywords = groundwater table and peak ground acceleration

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24 pages, 35052 KB  
Article
Using Keyhole Images to Map Soil Liquefaction Induced by the 1966 Xingtai Ms 6.8 and 7.2 Earthquakes, North China
by Yali Guo, Yueren Xu, Haofeng Li, Lingyu Lu, Wentao Xu and Peng Liang
Remote Sens. 2023, 15(24), 5777; https://doi.org/10.3390/rs15245777 - 18 Dec 2023
Cited by 2 | Viewed by 2217
Abstract
In March 1966, Ms 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldwork records, we interpreted and identified 66,442 [...] Read more.
In March 1966, Ms 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldwork records, we interpreted and identified 66,442 liquefaction points and analyzed the coseismic liquefaction distribution characteristics and possible factors that influenced the Xingtai earthquakes. The interpreted coseismic liquefaction was mainly concentrated above the IX-degree zone, accounting for 80% of all liquefaction points. High-density liquefaction zones (point density > 75 pieces/km2) accounted for 22% of the total liquefaction points. Most of the interpreted liquefaction points were located at the region with a peak ground acceleration (PGA) of >0.46 g. The liquefaction area on 22 March was significantly larger than that on 8 March. The region of liquefaction was mainly limited by sandy soil conditions, water system conditions, and seismic geological conditions and distributed in areas with loose fine sand and silt deposits, a high water table (groundwater level increases before both mainshocks corresponding to the liquefaction intensive regions), rivers, and ancient river channels. Liquefaction exhibited a repeating characteristic in the same region. Further understanding of the liquefaction characteristics of Xingtai can provide a reference for the prevention of liquefaction in northern China. Full article
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22 pages, 12112 KB  
Article
Estimating Liquefaction Susceptibility Using Machine Learning Algorithms with a Case of Metro Manila, Philippines
by Joenel Galupino and Jonathan Dungca
Appl. Sci. 2023, 13(11), 6549; https://doi.org/10.3390/app13116549 - 27 May 2023
Cited by 11 | Viewed by 9476
Abstract
Soil liquefaction is a phenomenon that can occur when soil loses strength and behaves like a liquid during an earthquake. A site investigation is essential for determining a site’s susceptibility to liquefaction, and these investigations frequently generate project-specific geotechnical reports. However, many of [...] Read more.
Soil liquefaction is a phenomenon that can occur when soil loses strength and behaves like a liquid during an earthquake. A site investigation is essential for determining a site’s susceptibility to liquefaction, and these investigations frequently generate project-specific geotechnical reports. However, many of these reports are frequently stored unused after construction projects are completed. This study suggests that when these unused reports are consolidated and integrated, they can provide valuable information for identifying potential challenges, such as liquefaction. The study evaluates the susceptibility of liquefaction by considering several geotechnical factors modeled by machine learning algorithms. The study estimated site-specific characteristics, such as ground elevation, groundwater table elevation, SPT N-value, soil type, and fines content. Using a calibrated model represented by an equation, the investigation determined several soil properties, including the unit weight and peak ground acceleration (PGA). The study estimated PGA using a linear model, which revealed a significant positive correlation (R2 = 0.89) between PGA, earthquake magnitude, and distance from the seismic source. On the Marikina West Valley Fault, the study also assessed the liquefaction hazard for an anticipated 7.5 M and delineated a map that was validated by prior studies. Full article
(This article belongs to the Special Issue Big Data in Seismology: Methods and Applications)
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16 pages, 3452 KB  
Article
Assessment of Soil Liquefaction Potential in Kamra, Pakistan
by Mahmood Ahmad, Xiao-Wei Tang, Feezan Ahmad and Arshad Jamal
Sustainability 2018, 10(11), 4223; https://doi.org/10.3390/su10114223 - 15 Nov 2018
Cited by 14 | Viewed by 6666
Abstract
In seismically active regions, soil liquefaction is a serious geotechnical engineering problem that mainly occurs in saturated granular soils with a shallow groundwater table. Significant seismic hazards are present in Kamra, Pakistan. With the rapid increase in construction in recent years, the evaluation [...] Read more.
In seismically active regions, soil liquefaction is a serious geotechnical engineering problem that mainly occurs in saturated granular soils with a shallow groundwater table. Significant seismic hazards are present in Kamra, Pakistan. With the rapid increase in construction in recent years, the evaluation of liquefaction is now considered to be more important for land use planning and development. The intent of this study is to highlight soil liquefaction susceptibility that will eventually support the national authorities in developing guidelines for sustainable development and the mitigation of liquefaction. The typical subsoil profile of Kamra consists of silty gravel (GM) overlain by silty sand (SM), poorly graded sand (SP), and fill layers. Kamra is close to the active Ranja–Khairabad fault with a peak ground acceleration of 0.24g. The river Sehat and the Ghazi Brotha canal pass through the study area. In this study, the soil liquefaction potential in Kamra was assessed at 10 different sites (50 boreholes) by using a stress-based procedure for calculating the factor of safety against soil liquefaction. The results revealed that the middle layers, i.e., poorly graded sand and silty sand in the subsoil profile, are extremely susceptible to liquefaction during earthquakes with magnitudes between 7.5 and 8.0 in Kamra. The correlation between the factor of safety and the equivalent clean-sand-corrected standard penetration test (SPT) blow counts according to the earthquake magnitudes was developed and can also be utilized for areas adjoining Kamra that have the same subsoil profile. Full article
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