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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 31366

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Special Issue Editors

Prof. Dr. Jian Chen

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Guest Editor

Department of Geological Engineering, China University of Geosciences (Beijing), Beijing 100083, China
Interests: geological hazards; landslides; engineering geology; risk assessment

Prof. Dr. Chong Xu

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Guest Editor

Geological Hazards Research Center, National Institute of Natural Hazards, Ministry of Emergency Management, Beijing, China
Interests: earthquake-triggered landslides; rainfall-triggered landslides; active faults; hazard and risk mapping; landslide inventory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geological hazards worldwide are known to be exacerbated due to climate change and anthropogenic activities, with more frequent ice avalanches, glacial activities, glacial lake bursts and alpine debris flows in high mountain regions, increasing the exposure and vulnerability of mountain settlements. Furthermore, catastrophic geological hazards sometimes produce a chain effect, that is, one hazard triggers another hazard in succession, leading to the amplification of the damage to the environment and human society. Although researchers have developed and used different approaches and strategies in the processes of geohazard field investigation, risk assessment, early warning, long-term monitoring and mitigation, advanced methods and cases on sustainable risk management still call for ongoing attention.

Risk management of geological hazards involves the application of some concepts or models to seek reasonable and effective recommendations for risk prevention and mitigation. By coordinating the relationship between human activities and geohazards, geohazard risk management has become an integral component of sustainable social development, as well as an important guarantee for reducing loss of life or injury, social economy and environmental losses caused by geological disasters and their secondary disasters.

The objective of the proposed Special Issue is to assemble original papers related to recent developments in theoretical frameworks, methodologies and applications for geohazard risk management from different worldwide regions. Case studies and review articles on assessment, early warning, long-term monitoring and mitigation are also welcome. It is expected that the Special Issue will provide the latest developments for institutions and stakeholders related to geohazard risk management on a global or regional scale.

We look forward to receiving your contributions.

Prof. Dr. Jian Chen
Prof. Dr. Chong Xu
Guest Editors

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Keywords

geological hazards
hazard susceptibility
risk analysis
risk assessment
risk management
disaster chain
machine learning
geoinformatics

Published Papers (14 papers)

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Editorial

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5 pages, 143 KiB

Open AccessEditorial

Geological Hazards and Risk Management

by Jian Chen and Chong Xu

Sustainability 2024, 16(8), 3286; https://doi.org/10.3390/su16083286 - 15 Apr 2024

Viewed by 514

Abstract

The occurrence of geological hazards is widespread, particularly in mountainous regions [...] Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

Research

Jump to: Editorial

18 pages, 8746 KiB

Open AccessArticle

An Infinite Slope Model Considering Unloading Joints for Spatial Evaluation of Coseismic Landslide Hazards Triggered by a Reverse Seismogenic Fault: A Case Study of the 2013 Lushan Earthquake

by Gao Li, Mingdong Zang, Shengwen Qi, Jingshan Bo, Guoxiang Yang and Tianhao Liu

Sustainability 2024, 16(1), 138; https://doi.org/10.3390/su16010138 - 22 Dec 2023

Viewed by 635

Abstract

Coseismic landslides pose a significant threat to the sustainability of both the natural environment and the socioeconomic fabric of society. This escalation in earthquake frequency has driven a growing interest in regional-scale assessment techniques for these landslides. The widely adopted infinite slope model, introduced by Newmark, is commonly utilized to assess coseismic landslide hazards. However, this conventional model falls short of capturing the influence of rock mass structure on slope stability. A novel methodology was previously introduced, considering the roughness of potential slide surfaces on the inner slope, offering a fresh perspective on coseismic landslide hazard mapping. In this paper, the proposed method is recalibrated using new datasets from the 2013 Lushan earthquake. The datasets encompass geological units, peak ground acceleration (PGA), and a high-resolution digital elevation model (DEM), rasterized at a grid spacing of 30 m. They are integrated within an infinite slope model, employing Newmark’s permanent deformation analysis. This integration enables the estimation of coseismic displacement in each grid area resulting from the 2013 Lushan earthquake. To validate the model, the simulated displacements are compared with the inventory of landslides triggered by the Lushan earthquake, allowing the derivation of a confidence level function that correlates predicted displacement with the spatial variation of coseismic landslides. Ultimately, a hazard map of coseismic landslides is generated based on the values of the certainty factor. The analysis of the area under the curve is utilized to illustrate the improved effectiveness of the proposed method. Comparative studies with the 2014 Ludian earthquake reveal that the coseismic landslides triggered by the 2013 Lushan earthquake predominantly manifest as shallow rock falls and slides. Brittle coseismic fractures are often associated with reverse seismogenic faults, while complaint coseismic fractures are more prevalent in strike–slip seismogenic faults. The mapping procedure stands as a valuable tool for predicting seismic hazard zones, providing essential insights for decision-making in infrastructure development and post-earthquake construction endeavors. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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26 pages, 19985 KiB

Open AccessArticle

Landslide Susceptibility Prediction Using Machine Learning Methods: A Case Study of Landslides in the Yinghu Lake Basin in Shaanxi

by Sheng Ma, Jian Chen, Saier Wu and Yurou Li

Sustainability 2023, 15(22), 15836; https://doi.org/10.3390/su152215836 - 10 Nov 2023

Cited by 1 | Viewed by 1244

Abstract

Landslide susceptibility prediction (LSP) is the basis for risk management and plays an important role in social sustainability. However, the modeling process of LSP is constrained by various factors. This paper approaches the effect of landslide data integrity, machine-learning (ML) models, and non-landslide sample-selection methods on the accuracy of LSP, taking the Yinghu Lake Basin in Ankang City, Shaanxi Province, as an example. First, previous landslide inventory (totaling 46) and updated landslide inventory (totaling 46 + 176) were established through data collection, remote-sensing interpretation, and field investigation. With the slope unit as the mapping unit, twelve conditioning factors, including elevation, slope, aspect, topographic relief, elevation variation coefficient, slope structure, lithology, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), distance to road, distance to river, and rainfall were selected. Next, the initial landslide susceptibility mapping (LSM) was obtained using the K-means algorithm, and non-landslide samples were determined using two methods: random selection and semi-supervised machine learning (SSML). Finally, the random forest (RF) and artificial neural network (ANN) machine-learning methods were used for modeling. The research results showed the following: (1) The performance of supervised machine learning (SML) (RF, ANN) is generally superior to unsupervised machine learning (USML) (K-means). Specifically, RF in the SML model has the best prediction performance, followed by ANN. (2) The selection method of non-landslide samples has a significant impact on LSP, and the accuracy of the SSML-based non-landslide selection method is controlled by the ratio of the number of landslide samples to the number of mapping units. (3) The quantity of landslides has an impact on how reliably the results of LSM are obtained because fewer landslides result in a smaller sample size for LSM, which deviates from reality. Although the results in this dataset are satisfactory, the zoning results cannot reliably anticipate the recently added landslide data discovered by the interpretation of remote-sensing data and field research. We propose that the landslide inventory can be increased by remote sensing in order to achieve accurate and impartial LSM since the LSM of adequate landslide samples is more reasonable. The research results of this paper will provide a reference basis for uncertain analysis of LSP and regional landslide risk management. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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19 pages, 2462 KiB

Open AccessArticle

Probabilistic Approach to Transient Unsaturated Slope Stability Associated with Precipitation Event

by Katherin Rocio Cano Bezerra da Costa, Ana Paola do Nascimento Dantas, André Luís Brasil Cavalcante and André Pacheco de Assis

Sustainability 2023, 15(21), 15260; https://doi.org/10.3390/su152115260 - 25 Oct 2023

Cited by 2 | Viewed by 788

Abstract

The massif rupture is not always reached under saturated conditions; therefore, the analysis of the unsaturated phenomenon is necessary in some cases. This study performed a probabilistic approach for unsaturated and transient conditions to understand the contribution of physical and hydraulic parameters involved in slope stability. The proposed slope stability model was based on the infinite slope method and a new unsaturated constitutive shear strength model proposed in 2021 by Cavalcante and Mascarenhas. The first-order second-moment method, which incorporated multiple stochastic variables, was used in the probabilistic analysis, allowing the incorporation of seven independent variables for the probability of failure analysis as well as for quantifying the contribution of the variables to the total variance of a factor of safety at any state of moisture. This implementation allows a more realistic estimative for the probability of failure, showing in a practical way the decrease and increase of the probability of failure during a rain event. The model provided promising results highlighting the need to migrate from deterministic analyses to more robust probabilistic analyses, considering the most significant number of stochastic variables. The proposed model helps to understand the influence of moisture content on slope stability, being a possible tool in natural disaster risk management. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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17 pages, 14839 KiB

Open AccessArticle

Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018

by Chenchen Xie, Yuandong Huang, Lei Li, Tao Li and Chong Xu

Sustainability 2023, 15(18), 13930; https://doi.org/10.3390/su151813930 - 19 Sep 2023

Cited by 1 | Viewed by 1358

Abstract

In recent years, with the intensification of climate change, the occurrence of heavy rain events has become more frequent. Landslides triggered by heavy rainfall have become one of the common geological disasters around the world. This study selects an extreme rainfall event in August 2018 in Jiexi County, Guangdong province, as the research object. Based on high-resolution remote sensing images before and after the event, visual interpretation is conducted to obtain a detailed distribution map of rainfall-induced landslides. The results show that a total of 1844 rainfall-induced landslides were triggered within Jiexi County during this rainfall event. In terms of triggered scale, the total area of the landslides is 3.3884 million m², with the largest individual landslide covering an area of 22,300 m² and the smallest one covering an area of 417.78 m². The landslides are concentrated in the northeastern, central, and southwestern parts of the study area, consistent with the distribution trend of rainfall intensity. To investigate further the influence of the regional environment on landslide distribution, this study selects eight influencing factors, including elevation, slope aspect, slope angle, topographic wetness index (TWI), topographic relief, lithology, distance to river, and accumulated rainfall. The landslide number density (LND) and landslide area percentage (LAP) are used as evaluation indicators. Based on statistical analysis using a data analysis platform, the relationship between landslide distribution and influencing factors triggered by this event is revealed. The results of this study will contribute to understanding the development law of regional rainfall-induced landslides and provide assistance for disaster prevention and mitigation in the area. The research results show that the elevation range of 100–150 m is the high-risk zone for landslides. In addition, this study has verified previous findings that slopes in the southeast direction are more prone to landslides. The steeper the slope, the more significant its influence on landslide development. When the topographic wetness index (TWI) is less than 4, landslides tend to have a high-density distribution. Greater variation in terrain relief is more likely to trigger landslides. The instability of lithology in Mesozoic strata is the main cause of landslides. The farther away from the water system, the fewer landslides occur. An increase in cumulative rainfall leads to an increase in both the number and area of landslides. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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16 pages, 21191 KiB

Open AccessArticle

Influence of Soluble Salt NaCl on Cracking Characteristics and Mechanism of Loess

by Xin Wei, Li Dong, Xuanyi Chen and Yunru Zhou

Sustainability 2023, 15(6), 5268; https://doi.org/10.3390/su15065268 - 16 Mar 2023

Cited by 3 | Viewed by 1187

Abstract

Under the conditions of drought, cracks are likely to appear in loess due to shrinkage, which leads to salt precipitation and accumulation on the surface of loess. Therefore, salinized lands are created in loess areas. Deep study into the influence of soluble salt content on the cracking characteristics and mechanism of loess is of great significance to engineering constructions, geological problems, and disaster prevention for salinized lands in loess regions. In this paper, free desiccation experiments were carried out on the loess samples with different NaCl concentrations (a soluble salt). A high-resolution digital camera was used to obtain the sequence images of loess during the drying process. With the advantage of digital image correlation (DIC) technology and the non-contact full-field strain measurement method, the local displacement and strain on the surface of loess samples were calculated. The microstructure and main elements distribution of loess samples were obtained by scanning electron microscopy (SEM) and energy-dispersive spectrum (EDS) methods. Finally, the influence of NaCl concentrations on cracking characteristics and mechanism of loess was analyzed. The results show that, with the increase in NaCl concentration, the evaporation rate of loess samples decreased and the residual water content increased. The NaCl content can prevent the development of desiccation cracks in loess. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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22 pages, 6296 KiB

Open AccessArticle

Spatial and Temporal Analysis of Global Landslide Reporting Using a Decade of the Global Landslide Catalog

by Chelsea Dandridge, Thomas A. Stanley, Dalia B. Kirschbaum and Venkataraman Lakshmi

Sustainability 2023, 15(4), 3323; https://doi.org/10.3390/su15043323 - 11 Feb 2023

Cited by 1 | Viewed by 2914

Abstract

Rainfall-triggered landslides can result in devastating loss of life and property damage and are a growing concern from a local to global scale. NASA’s global landslide catalog (GLC) compiles a record of rainfall-triggered landslide events from media reports, academic articles, and existing databases at global scale. The database consists of all types of mass movement events that are triggered by rainfall and represents a minimum number of events occurring between 2007 and 2018. The GLC collection is no longer being compiled, and the dataset will not be updated past 2018. The research presented here evaluates global patterns in landslide reporting from events in the GLC. The evaluation includes an analysis of the spatial and temporal distribution of global landslide events and associated casualties and comparisons with other landslide inventories. This database has been used to estimate landslide hotspots, evaluate geographic patterns in landslides, and train and validate landslide models from local to global scales. The most notable landslide hotspots are in the Pacific Northwest of North America, High Mountain Asia, and the Philippines. Additionally, the relationship between country GDP and income status with landslide occurrence was determined to have a positive correlation between economic status and landslide reporting. The GLC also indicates a reporting bias towards English-speaking countries. The general goal of this research is to assess the decade of global landslide reports from the GLC and show how this database can be used for rainfall-triggered landslide research. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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21 pages, 6868 KiB

Open AccessArticle

Integrated Approach for Landslide Risk Assessment Using Geoinformation Tools and Field Data in Hindukush Mountain Ranges, Northern Pakistan

by Nisar Ali Shah, Muhammad Shafique, Muhammad Ishfaq, Kamil Faisal and Mark Van der Meijde

Sustainability 2023, 15(4), 3102; https://doi.org/10.3390/su15043102 - 8 Feb 2023

Cited by 6 | Viewed by 2590

Abstract

Landslides are one of the most recurring and damaging natural hazards worldwide, with rising impacts on communities, infrastructure, and the environment. Landslide hazard, vulnerability, and risk assessments are critical for landslide mitigation, land use and developmental planning. They are, however, often lacking in complex and data-poor regions. This study proposes an integrated approach to evaluate landslide hazard, vulnerability, and risk using a range of freely available geospatial data and semi-quantitative techniques for one of the most landslide-prone areas in the Hindukush mountain ranges of northern Pakistan. Very high-resolution satellite images and their spectral characteristics are utilized to develop a comprehensive landslide inventory and predisposing factors using bi-variate models to develop a landslide susceptibility map. This is subsequently integrated with landslide-triggering factors to derive a Landslide Hazard Index map. A geospatial database of the element-at-risk data is developed from the acquired remote sensing data and extensive field surveys. It contains the building’s footprints, accompanied by typological data, road network, population, and land cover. Subsequently, it is analyzed using a spatial multi-criteria evaluation technique for vulnerability assessment and further applied in a semi-quantitative technique for risk assessment in relative risk classes. The landslide risk assessment map is classified into five classes, i.e., very low (18%), low (39.4%), moderate (26.3%), high (13.3%), and very high (3%). The developed landslide risk index map shall assist in highlighting the landslide risk hotspots and their subsequent mitigation and risk reduction. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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22 pages, 7384 KiB

Open AccessArticle

A New Approach to Spatial Landslide Susceptibility Prediction in Karst Mining Areas Based on Explainable Artificial Intelligence

by Haoran Fang, Yun Shao, Chou Xie, Bangsen Tian, Chaoyong Shen, Yu Zhu, Yihong Guo, Ying Yang, Guanwen Chen and Ming Zhang

Sustainability 2023, 15(4), 3094; https://doi.org/10.3390/su15043094 - 8 Feb 2023

Cited by 9 | Viewed by 1900

Abstract

Landslides are a common and costly geological hazard, with regular occurrences leading to significant damage and losses. To effectively manage land use and reduce the risk of landslides, it is crucial to conduct susceptibility assessments. To date, many machine-learning methods have been applied to the landslide susceptibility map (LSM). However, as a risk prediction, landslide susceptibility without good interpretability would be a risky approach to apply these methods to real life. This study aimed to assess the LSM in the region of Nayong in Guizhou, China, and conduct a comprehensive assessment and evaluation of landslide susceptibility maps utilizing an explainable artificial intelligence. This study incorporates remote sensing data, field surveys, geographic information system techniques, and interpretable machine-learning techniques to analyze the sensitivity to landslides and to contrast it with other conventional models. As an interpretable machine-learning method, generalized additive models with structured interactions (GAMI-net) could be used to understand how LSM models make decisions. The results showed that the GAMI-net model was valid and had an area under curve (AUC) value of 0.91 on the receiver operating characteristic (ROC) curve, which is better than the values of 0.85 and 0.81 for the random forest and SVM models, respectively. The coal mining, rock desertification, and rainfall greater than 1300 mm were more susceptible to landslides in the study area. Additionally, the pairwise interaction factors, such as rainfall and mining, lithology and rainfall, and rainfall and elevation, also increased the landslide susceptibility. The results showed that interpretable models could accurately predict landslide susceptibility and reveal the causes of landslide occurrence. The GAMI-net-based model exhibited good predictive capability and significantly increased model interpretability to inform landslide management and decision making, which suggests its great potential for application in LSM. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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23 pages, 15315 KiB

Open AccessArticle

Study on Disaster Mechanism of Oil and Gas Pipeline Oblique Crossing Landslide

by Fa-You A, Teng-Hui Chen, Cheng Yang, Yu-Feng Wu and Shi-Qun Yan

Sustainability 2023, 15(4), 3012; https://doi.org/10.3390/su15043012 - 7 Feb 2023

Cited by 3 | Viewed by 1151

Abstract

Landslides are one of the most serious geological disasters in oil and gas pipelines. According to investigations, the cross-cutting relationship between landslides and pipelines can be divided into three types: pipeline longitudinal crossing landslide, pipeline transversely crossing landslide, and pipeline oblique crossing landslide. This different cross-cutting relationship is one of the important factors affecting pipeline landslide disasters. As a result, it is necessary to study the stress and deformation characteristics of oil and gas pipelines under different cross-cutting relationships, which is of great significance for the prevention and control of oil and gas pipeline landslides. In this paper, an ideal pipe-soil coupling interaction model of oil and gas pipeline oblique crossing landslide was established using FLAC3D. The influence of the buried depth of the pipeline, the displacement of the sliding body, and the different intersection angles of landslide and pipeline on the deformation and stress of the pipeline under the action of a landslide is analyzed, and a typical case of pipeline oblique crossing landslide is used for analysis. The results demonstrated that the stress of pipeline oblique crossing landslide is complex, and the stress concentration is obvious at the shear outlet and the trailing edge of the landslide. The stress at the shear outlet is the largest, which should be regarded as the key location. The displacement and stress of pipeline oblique crossing landslide are obviously affected by the displacement of the sliding body and the buried depth of the pipeline. The displacement and stress of the pipeline increase significantly with the increase of the displacement of the sliding body. With the increase of pipeline buried depth, the displacement of the pipeline shows an overall decrease, and when the buried depth of the pipeline is 3–3.5 m, the displacement and stress are close to the peak, indicating that the buried depth is of great risk. The intersection angle between the pipeline and landslide has a significant effect on the stress of the pipeline. The smaller the intersection angle, the safer the pipeline is. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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21 pages, 27713 KiB

Open AccessArticle

Seismotectonics of Shallow-Focus Earthquakes in Venezuela with Links to Gravity Anomalies and Geologic Heterogeneity Mapped by a GMT Scripting Language

by Polina Lemenkova and Olivier Debeir

Sustainability 2022, 14(23), 15966; https://doi.org/10.3390/su142315966 - 30 Nov 2022

Cited by 9 | Viewed by 1771

Abstract

This paper presents a cartographic framework based on algorithms of GMT codes for mapping seismically active areas in Venezuela. The data included raster grids from GEBCO, EGM-2008, and vector geological layers from the USGS. The data were iteratively processed in the console of GMT, converted by GDAL, formatted, and mapped for geophysical data visualisation; the QGIS was applied for geological mapping. We analyzed 2000 samples of the earthquake events obtained from the IRIS seismic database with a 25-year time span (1997–2021) in order to map the seismicity. The approach to linking geological, topographic, and geophysical data using GMT scripts aimed to map correlations among the geophysical phenomena, tectonic processes, geological setting, seismicity, and earthquakes. The practical application of the GMT scripts consists in automated mapping for the visualization of geological risks and hazards in the mountainous region of the Venezuelan Andes. The proposed method integrates the approach of GMT scripts with state-of-the-art GIS techniques, which demonstrated its effectiveness as a tool for mapping spatial datasets and rapid data processing in an iterative regime. In this context, using GMT and GIS to find similarities between the regional earthquake distribution and the geological and topographic setting is essential for hazard risk assessment. This study can serve as a basis for predictive seismic analysis in geologically vulnerable regions of Venezuela. In addition to a technical demonstration of GMT algorithms, this study also contributes to geological and geophysical mapping and seismic hazard assessments in South America. We present the full scripts used for mapping in a GitHub repository. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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18 pages, 5648 KiB

Open AccessArticle

Effect of Land Use and Drainage System Changes on Urban Flood Spatial Distribution in Handan City: A Case Study

by Beibei Liu, Chaowei Xu, Jiashuai Yang, Sen Lin and Xi Wang

Sustainability 2022, 14(21), 14610; https://doi.org/10.3390/su142114610 - 7 Nov 2022

Cited by 4 | Viewed by 2273

Abstract

This study simulated urban flooding under various land use and drainage system conditions and described the process of historical ground–underground construction and its influence on spatial variations in waterlogging, taking Handan City as an example. The obtained results can provide support for urban water security and sustainable urban water resource management. The land use change, represented by the expansion of sealed surfaces, has a positive impact on the distribution and the volume of flood in Handan City, while the drainage system has the opposite effect. The flooding distribution changes over decades reveal that flooding risk is reduced in most areas by improved drainage conditions but exacerbated in impervious areas and riversides due to increasing impermeable areas, the rapid draining of pipes, and poor outlet conditions. This study demonstrates how the dual changes in land use and drainage pipeline networks affect urban flooding distribution; we suggest considering land use and the extension of drainage pipelines in future construction. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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24 pages, 5541 KiB

Open AccessArticle

Predicting Factors Affecting Preparedness of Volcanic Eruption for a Sustainable Community: A Case Study in the Philippines

by Josephine D. German, Anak Agung Ngurah Perwira Redi, Ardvin Kester S. Ong, Yogi Tri Prasetyo and Vince Louis M. Sumera

Sustainability 2022, 14(18), 11329; https://doi.org/10.3390/su141811329 - 9 Sep 2022

Cited by 19 | Viewed by 8365

Abstract

Volcanic eruption activity across the world has been increasing. The recent eruption of Taal volcano and Mt. Bulusan in the Philippines affected several people due to the lack of resources, awareness, and preparedness activities. Volcanic eruption disrupts the sustainability of a community. This study assessed people’s preparedness for volcanic eruption using a machine learning ensemble. With the high accuracy of prediction from the ensemble of random forest classifier (93%) and ANN (98.86%), it was deduced that media, as a latent variable, presented as the most significant factor affecting preparedness for volcanic eruption. This was evident as the community was urged to find related information about volcanic eruption warnings from media sources. Perceived severity and vulnerability led to very high preparedness, followed by the intention to evacuate. In addition, proximity, subjective norm, and hazard knowledge for volcanic eruption significantly affected people’s preparedness. Control over individual behavior and positive attitude led to a significant effect on preparedness. It could be posited that the government’s effective mitigation and action plan would be adhered to by the people when disasters, such as volcanic eruptions, persist. With the threat of climate change, there is a need to reevaluate behavior and mitigation plans. The findings provide evidence of the community’s resilience and adoption of mitigation and preparedness for a sustainable community. The methodology provided evidence for application in assessing human behavior and prediction of factors affecting preparedness for natural disasters. Finally, the results and findings of this study could be applied and extended to other related natural disasters worldwide. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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18 pages, 4100 KiB

Open AccessArticle

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

by Muhammad Waseem, Zia Ur Rehman, Fabio Sabetta, Irshad Ahmad, Mahmood Ahmad and Mohanad Muayad Sabri Sabri

Sustainability 2022, 14(13), 8152; https://doi.org/10.3390/su14138152 - 4 Jul 2022

Cited by 4 | Viewed by 1528

Abstract

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. Full article

(This article belongs to the Special Issue Geological Hazards and Risk Management)

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