2021
DOI: 10.3390/geosciences11040154
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Site Amplification Analysis of Dushanbe City Area, Tajikistan to Support Seismic Microzonation

Abstract: Being a country exposed to strong seismicity, the estimation of seismic hazard in Tajikistan is essential for urbanized areas, such as the rapidly growing capital city Dushanbe. To ensure people’s safety and adequate construction work, a detailed seismic microzonation is the key to proper hazard planning. Existing estimations of seismic hazard date back to 1978; they are based on engineering geological investigations and observed macroseismic data. Thereupon relies the Tajik Building Code, which considers seis… Show more

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Cited by 6 publications
(25 citation statements)
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“…This allowed for a more accurate assessment of the site effects and determination of the PGA in the study area, contributing to more substantiated seismic microzonation and seismic hazard assessment. The results also confirmed the impact of strong seismic amplification due to local topographical and ground characteristics, in line with the conclusions of previous studies [11,34].…”
Section: Introductionsupporting
confidence: 91%
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“…This allowed for a more accurate assessment of the site effects and determination of the PGA in the study area, contributing to more substantiated seismic microzonation and seismic hazard assessment. The results also confirmed the impact of strong seismic amplification due to local topographical and ground characteristics, in line with the conclusions of previous studies [11,34].…”
Section: Introductionsupporting
confidence: 91%
“…The second terrace is elevated by a 1-3 m step above the Varzob River floodplain and is overlaid by a loess cover ranging from 5 to 10 m in thickness. The third terrace, which gently slopes southwestward, is predominantly composed of loess strata 20-40 m thick and features a pronounced escarpment of 12-18 m leading down to the second terrace, as detailed in the study by Hakimov et al [34].…”
Section: Study Areamentioning
confidence: 82%
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“…It provides a critical review of almost all relevant existing statistical methods. Generally, landslide studies are performed according to several hazard assessment models: expert or heuristic models, statistical models [22], statistical and geotechnical models [23,24], spatial multi-criteria evaluation (SMCE) [16], spatially explicit deep learning neural network models [25], machine learning models [26] and some of them also consider seismic microzonation models [27]. Regarding the landslide data input, it has been shown that the performance of a susceptibility model varies slightly after progressive updating and addition of landslide data over time [28].…”
Section: Introductionmentioning
confidence: 99%