Macrozonation of seismic transient and permanent ground deformation of Iran

Farahani, Saeideh; Behnam, Behrouz; Tahershamsi, Ahmad

doi:10.5194/nhess-20-2889-2020

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…Second, ground motion prediction has been a significant technique for seismic hazard and risk assessment and provides a crucial clue on earthquake risk mitigation [ 91 ]. In a region with intensive crustal movement, a landslide susceptibility map can be employed to predict the permanent ground displacement (PGD) triggered by an earthquake [ 2 ]. The PGD, combined with the transient ground displacement, is a vital basis for earthquake risk evaluation and control [ 2 , 91 ].…”

Section: Discussionmentioning

confidence: 99%

“…In a region with intensive crustal movement, a landslide susceptibility map can be employed to predict the permanent ground displacement (PGD) triggered by an earthquake [ 2 ]. The PGD, combined with the transient ground displacement, is a vital basis for earthquake risk evaluation and control [ 2 , 91 ].…”

Section: Discussionmentioning

confidence: 99%

“…Thus, an imperious demand is suggested for the valid prevention and control of landslides to effectively mitigate the massive damage to people and engineering infrastructures. Landslide susceptibility evaluation (LSE) can predict the dangerous region where landslides may occur [ 1 ]; thus, it has become a crucial technique for disaster prevention and attracted great attention from the worldwide scientists [ 2 , 3 , 4 , 5 , 6 , 7 ]. Moreover, about 80% of these disastrous landslides have not been discovered in advance [ 8 ], called as potential or hidden landslides, which causes disaster control measures to miss the best time.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning

Wang

Zhang

Jia

et al. 2022

IJERPH

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Catastrophic landslides have much more frequently occurred worldwide due to increasing extreme rainfall events and intensified human engineering activity. Landslide susceptibility evaluation (LSE) is a vital and effective technique for the prevention and control of disastrous landslides. Moreover, about 80% of disastrous landslides had not been discovered ahead and significantly impeded social and economic sustainability development. However, the present studies on LSE mainly focus on the known landslides, neglect the great threat posed by the potential landslides, and thus to some degree constrain the precision and rationality of LSE maps. Moreover, at present, potential landslides are generally identified by the characteristics of surface deformation, terrain, and/or geomorphology. The essential disaster-inducing mechanism is neglected, which has caused relatively low accuracies and relatively high false alarms. Therefore, this work suggests new synthetic criteria of potential landslide identification. The criteria involve surface deformation, disaster-controlling features, and disaster-triggering characteristics and improve the recognition accuracy and lower the false alarm. Furthermore, this work combines the known landslides and discovered potential landslides to improve the precision and rationality of LSE. This work selects Chaya County, a representative region significantly threatened by landslides, as the study area and employs multisource data (geological, topographical, geographical, hydrological, meteorological, seismic, and remote sensing data) to identify potential landslides and realize LSE based on the time-series InSAR technique and XGBoost algorithm. The LSE precision indices of AUC, Accuracy, TPR, F1-score, and Kappa coefficient reach 0.996, 97.98%, 98.77%, 0.98, and 0.96, respectively, and 16 potential landslides are newly discovered. Moreover, the development characteristics of potential landslides and the cause of high landslide susceptibility are illuminated. The proposed synthetic criteria of potential landslide identification and the LSE idea of combining known and potential landslides can be utilized to other disaster-serious regions in the world.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning

Wang

Zhang

Jia

et al. 2022

IJERPH

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“…Numerous studies have focused on linkages between social and ecological components as well as the capacity of coastal systems to resist disruptions and recover from them. For instance, studies have looked at the adaptability of coastal communities to sea level rises and storm events [22,23], the resilience of coral reefs to climate change and ocean acidification, the function of ecosystem services in promoting coastal resilience [24], the dynamic behavior of infrastructure in coastal areas [25,26], and macro-zonation [27,28].…”

Section: Resilience In Coastal Sessmentioning

confidence: 99%

Enhancing Resilience in Coastal Regions from a Socio-Ecological Perspective: A Case Study of Andhra Pradesh, India

et al. 2023

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Addressing the second priority of the Sendai Framework on Disaster Risk Reduction (SFDRR) for strengthening disaster risk governance, this paper considers coastal regions from a Socio-Ecological System (SES) perspective. It identifies the drivers of risk and critical linkages between various key components of coastal SESs that can potentially influence the resilience of coastal regions. The study considers that, in a coastal area, where the system is complex with numerous stakeholders, any decision taken in the form of developmental policy or as an adaptive practice is critical for system changes, thereby making risk anticipation and its management difficult. To further conduct a detailed investigation of this subject, seven settlements along the coastal Andhra Pradesh (India) region were methodically selected. Herein, focus group discussions were conducted to prepare fuzzy cognitive maps (FCM), which were further analyzed through the mental modeler online platform. By analyzing the structural metrics of the FCM, saltwater intrusion was identified as a significant system component. Furthermore, the study also analyzed the effects of change on the characteristics of selected SES components regarding the effectiveness of existing governance strategies and, conversely, the impact of implementing governance strategies on the identified critical components of SES. By critically examining the various scenarios thus generated, the research identifies various components, generating vulnerabilities in human systems. The derived results were cross-validated through community consultation, and the temporal variations in the state of system components were mapped. The study is expected to provide considerable input to policymakers for enhancing decision-making in coastal regions from an SES perspective.

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“…Global ground motion prediction equation evaluations for usage in seismic hazard analyses has also been a subject of interest in the neighboring countries of Pakistan using similar methods (e.g., Zafrani and Farhadi [9] in Iran and P. Anbazhagan et al [10] in India). Seismotectonic and seismic hazard studies for this region are active, and some examples of such studies are (1) a seismic hazard map for the Middle East region, including Pakistan, by Girdani et al [11], (2) macrozonation of the ground displacements in Iran by Farhani et al [12], and (3) a study on plate deformations of the Eurasian and Arabian plates by Allen et al [13].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Predictive Performance of Regional and Global Ground Motion Predictive Equations for Shallow Active Regions in Pakistan

et al. 2022

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Ground motion prediction equations are a key element of seismic hazard assessments. Pakistan lacks a robust ground motion prediction equation specifically developed using a Pakistan seismic ground motion databank. In this study, performance assessment of the ground motion prediction equations for usage in seismic hazard and risk studies in Pakistan, a seismically highly active region, is performed. In this study, an evaluation of the global ground motion prediction equations developed for the shallow active regions is carried out based on a databank of strong ground motion that was compiled in this study. Thirteen ground motion prediction equations were considered applicable, and their goodness of fit was evaluated using the databank of 147 peak ground acceleration of 27 shallow earthquakes in Pakistan. Residual analysis and three goodness of fit procedures were implemented in the evaluation of the equations. The results of this study suggest that global ground motion prediction equations can be applicable in the shallow active regions of Pakistan. These equations were developed based on data from Europe and the Middle East. Next Generation Attenuation West-2 equations were also applicable, but they did not perform as well as the European and Middle Eastern databank-derived equations. A total of four global equations were applicable in Pakistan. The best performing equation in this study should be applied with the highest weight, and the others should be applied with small weights on the logic tree to perform better. These equations can be employed in seismic hazard and risk assessment studies for disaster risk mitigation measures.

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Macrozonation of seismic transient and permanent ground deformation of Iran

Cited by 12 publications

References 28 publications

Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning

Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning

Enhancing Resilience in Coastal Regions from a Socio-Ecological Perspective: A Case Study of Andhra Pradesh, India

Evaluation of the Predictive Performance of Regional and Global Ground Motion Predictive Equations for Shallow Active Regions in Pakistan

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