scholarly journals Integrated Seismic Risk Assessment in Nepal

2022 ◽  
Author(s):  
Sanish Bhochhibhoya ◽  
Roisha Maharjan
Keyword(s):  
Risk Assessment ◽  
Social Vulnerability ◽  
Seismic Risk ◽  
Exposure Model ◽  
Earthquake Risk ◽  
Seismic Risk Assessment ◽  
True Nature ◽  
Average Annual Loss ◽  
Physical Risk ◽  
Vulnerability Score

Abstract. As Nepal is at high risk of earthquakes, the district-wide (VDC/Municipality level) study has been performed for vulnerability assessment of seismic-hazard, and the hazard-risk study is incorporated with social conditions as it has become a crucial issue in recent years. There is an interrelationship between hazards, physical risk, and the social characteristics of populations which are significant for policy-makers and individuals. Mapping the spatial variability of average annual loss (seismic risk) and social vulnerability discretely does not reflect the true nature of parameters contributing to the earthquake risk, so when the integrated risk is mapped, such combined spatial distribution becomes more evident. The purpose of this paper is to compute the risk analysis from the exposure model of the country using OpenQuake and then integrate the results with socio-economic parameters. The methodology of seismic-risk assessment and the way of combining the results of the physical risk and socio-economic data to develop an integrated vulnerability score of the regions has been described. This study considers all 75 districts and corresponding VDC/Municipalities using the available census. The combined vulnerability score has been developed and presented by integrating earthquake risk and social vulnerability aspects of the country and represented in form of the map produced using ArcGIS 10. The knowledge and information of the relationship between earthquake hazards and the demographic characteristics of the population in the vulnerable area are imperative to mitigate the local impact of earthquakes. Therefore, we utilize social vulnerability study as part of a comprehensive risk management framework to recuperate and recover from natural disasters.

scholarly journals Comprehensive seismic risk assessment map of South Korea developed using seismic, geotechnical, and social vulnerability indicators

2021 ◽  
Author(s):  
Seonyoung Lee ◽  
Seokhoon Oh
Keyword(s):  
Risk Assessment ◽  
South Korea ◽  
Social Vulnerability ◽  
Seismic Risk ◽  
Seismic Risk Assessment ◽  
Spatial Continuity ◽  
The Social ◽  
Vulnerability Indicators ◽  
Bedrock Depth ◽  
Vulnerability Indicator

Abstract At present, because it is not possible to predict earthquakes, disaster preparedness is vital for the reduction of damages. The awareness about earthquakes has substantially increased after the occurrence of two >M L 5 events in 2016 and 2017 in South Korea. This study presents the seismic risk assessment conducted for the entire country of South Korea. This assessment was performed using seismic, geotechnical, and social vulnerability indicators. The seismic vulnerability indicator was estimated using a probabilistic seismic hazard and fault-line density map that are directly related to the occurrence of earthquakes. The geotechnical vulnerability indicator was derived using bedrock depth data and extrapolation of digital elevation model data through geostatistical techniques. The seismic and geotechnical indicators were integrated based on the bedrock depth distribution. The social vulnerability indicator considered the distribution of relevant parameters such as vulnerable people, old houses, and road information. These statistical data without spatial continuity were incorporated into a map using principal component analysis. A five-grade classification of risks presented by the seismic and geotechnical vulnerability map and the social vulnerability index map was developed to facilitate simultaneous assessment. A risk matrix was applied to the two maps to produce a comprehensive seismic risk assessment map of South Korea, in which the southeastern and northwestern regions of South Korea present a high seismic risk. The results of this study will serve toward seismic risk management and minimize seismic disaster damages in South Korea.

scholarly journals Development of an Exposure Vulnerability Index Map Using GIS Modeling for Preliminary Seismic Risk Assessment in Sabah, Malaysia

2021 ◽  
Vol 16 (1) ◽  
pp. 111-119
Author(s):  
Noor Suhaiza Sauti ◽  
Mohd Effendi Daud ◽  
Masiri Kaamin ◽  
Suhaila Sahat
Keyword(s):  
Risk Assessment ◽  
Seismic Hazard ◽  
Seismic Risk ◽  
Geographical Location ◽  
Vulnerability Index ◽  
Geographical Information ◽  
Earthquake Risk ◽  
Seismic Risk Assessment ◽  
High Exposure ◽  
Gis Modeling

This research was conducted with a view to updating the management of earthquakes through an exposure vulnerability and potential seismic risk assessment, along with its application in Sabah (a state in East Malaysia). A set of indicators and methodologies has been proposed in this study with the goal of evaluating the level of exposure vulnerability and potential risk of certain locations to earthquake events at the local district scale. This study specifically involves the development of exposure vulnerability indicators; the statistical analysis method to standardize multivariate data together with a weight calculation of indicator variables; and a mathematical combination of different indicators for the development of the index map using the spatial analysis function of Geographical Information System (GIS) tools. Then, the derived exposure vulnerability index (EVI) map is overlaid with the seismic hazard in determining the geographical location of the most vulnerable areas and their exposure to seismic hazard events. As a result, and based on the available data, the exposure vulnerability index map shows that most districts in Sabah are at relatively low and moderate levels of risk except for a few districts, with several major cities in Sabah, such as Kota Kinabalu, Penampang, Sandakan and Tawau municipality, being situated at a high or very high exposure index. The combination of EVI maps and hazard maps indicate the dominance of the two factors influencing the potential level of earthquake risk. Studies reveal most of the southwest and central parts of the region are not at risk, as both exposure and hazard factors are at a low level. The proposed approach depicts an instrument for identifying cost-effective risk reduction initiatives by providing a scientific method for regional risk planning and management strategies. This research represents the first attempt to evaluate Sabah’s vulnerability to this type of natural disaster by understanding the spatial relationship between exposure vulnerability and earthquake hazard, which undoubtedly could be improved in several aspects.

Global Seismic Risk Assessment: the Wrong, the Right, and the Truth.

2021 ◽  
Author(s):  
Vitor Silva
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Current Practice ◽  
New Technologies ◽  
Risk Model ◽  
Economic Losses ◽  
Earthquake Risk ◽  
Loss Assessment ◽  
Risk Models ◽  
Seismic Risk Assessment

<p>The increase in the global population, climate change, growing urbanization and settlement in regions prone to natural hazards are some of the factors contributing to the increase in the economic and human losses due to disasters. Earthquakes represent on average approximately one-fifth of the annual losses, but in some years this proportion can be above 50% (e.g. 2010, 2011). This impact can affect the sustainable development of society, creation of jobs and availability of funds for poverty reduction. Furthermore, business disruption of large corporations can result in negative impacts at global scale. Earthquake risk information can be used to support decision-makers in the distribution of funds for effective risk mitigation. However, open and reliable probabilistic seismic risk models are only available for less than a dozen of countries, which dampers disaster risk management, in particular in the under-developed world. To mitigate this issue, the Global Earthquake Model Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate relevant earthquake risk metrics, which are now publicly available to the community.</p><p>The development of the global seismic risk model also allowed the identification of several issues that affect the reliability and accuracy of existing risk models. These include the use of outdated exposure information, insufficient consideration of all sources of epistemic and aleatory uncertainty, lack of results regarding indirect human and economic losses, and inability to forecast detailed earthquake risk to the upcoming decades. These challenges may render the results from existing earthquake loss models inadequate for decision-making. It is thus urgent to re-evaluate the current practice in earthquake risk loss assessment, and explore new technologies, knowledge and data that might mitigate some of these issues. A recent resource that can support the improvement of exposure datasets and the forecasting of exposure and risk into the next decades is the Global Human Settlement Layer, a collection of datasets regarding the built-environment between 1974 and 2010. The consideration of this type of information and incorporation of large sources of uncertainty can now be supported by artificial intelligence technology, and in particular open-source machine learning platforms. Such tools are currently being explored to predict earthquake aftershocks, to estimate damage shortly after the occurrence of destructive events, and to perform complex calculations with billions of simulations. These are examples of recent resources that must be exploited for the benefit of improving existing risk models, and consequently enhance the likelihood that risk reduction measures will be efficient.</p><p>This study presents the current practice in global seismic risk assessment with all of its limitations, it discusses the areas where improvements are necessary, and presents possible directions for risk assessment in the upcoming years.</p>

Combining hazard, social vulnerability and resilience to provide a proposal for seismic risk assessment

2019 ◽  
Vol 23 (9) ◽  
pp. 1225-1241
Author(s):  
Oscar Luigi Azzimonti ◽  
Matteo Colleoni ◽  
Mattia De Amicis ◽  
Ivan Frigerio
Keyword(s):  
Risk Assessment ◽  
Social Vulnerability ◽  
Seismic Risk ◽  
Seismic Risk Assessment

scholarly journals Residential building stock modelling for mainland China targeted for seismic risk assessment

2021 ◽  
Vol 21 (10) ◽  
pp. 3031-3056
Author(s):  
Danhua Xin ◽  
James Edward Daniell ◽  
Hing-Ho Tsang ◽  
Friedemann Wenzel
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Seismic Risk ◽  
Residential Buildings ◽  
Mainland China ◽  
Residential Building ◽  
Exposure Model ◽  
Building Stock ◽  
Seismic Risk Assessment ◽  
Residential Building Stock

Abstract. To enhance the estimation accuracy of economic loss and casualty in seismic risk assessment, a high-resolution building exposure model is necessary. Previous studies in developing global and regional building exposure models usually use coarse administrative-level (e.g. country or sub-country level) census data as model inputs, which cannot fully reflect the spatial heterogeneity of buildings in large countries like China. To develop a high-resolution residential building stock model for mainland China, this paper uses finer urbanity-level population and building-related statistics extracted from the records in the tabulation of the 2010 population census of the People's Republic of China (hereafter abbreviated as the “2010 census”). In the 2010 census records, for each province, the building-related statistics are categorized into three urbanity levels (urban, township, and rural). To disaggregate these statistics into high-resolution grid level, we need to determine the urbanity attributes of grids within each province. For this purpose, the geo-coded population density profile (with 1 km × 1 km resolution) developed in the 2015 Global Human Settlement Layer (GSHL) project is selected. Then for each province, the grids are assigned with urban, township, or rural attributes according to the population density in the 2015 GHSL profile. Next, the urbanity-level building-related statistics can be disaggregated into grids, and the 2015 GHSL population in each grid is used as the disaggregation weight. Based on the four structure types (steel and reinforced concrete, mixed, brick and wood, other) and five storey classes (1, 2–3, 4–6, 7–9, ≥10) of residential buildings classified in the 2010 census records, we reclassify the residential buildings into 17 building subtypes attached with both structure type and storey class and estimate their unit construction prices. Finally, we develop a geo-coded 1 km × 1 km resolution residential building exposure model for 31 provinces of mainland China. In each 1 km × 1 km grid, the floor areas of the 17 residential building subtypes and their replacement values are estimated. The model performance is evaluated to be satisfactory, and its practicability in seismic risk assessment is also confirmed. Limitations of the proposed model and directions for future improvement are discussed. The whole modelling process presented in this paper is fully reproducible, and all the modelled results are publicly accessible.

Earthquake Risk Assessment

2017 ◽  
Author(s):  
Max Wyss
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Population Data ◽  
Earthquake Hazard ◽  
Return Time ◽  
Earthquake Risk ◽  
Seismic Gap ◽  
World Population ◽  
Seismic Risk Assessment ◽  
Rupture Length

This article discusses the importance of assessing and estimating the risk of earthquakes. It begins with an overview of earthquake prediction and relevant terms, namely: earthquake hazard, maximum credible earthquake magnitude, exposure time, earthquake risk, and return time. It then considers data sources for estimating seismic hazard, including catalogs of historic earthquakes, measurements of crustal deformation, and world population data. It also examines ways of estimating seismic risk, such as the use of probabilistic estimates, deterministic estimates, and the concepts of characteristic earthquake, seismic gap, and maximum rupture length. A loss scenario for a possible future earthquake is presented, and the notion of imminent seismic risk is explained. Finally, the chapter addresses errors in seismic risk estimates and how to reduce seismic risk, ethical and moral aspects of seismic risk assessment, and the outlook concerning seismic risk assessment.

scholarly journals Techniques and parameters for earthquake risk assessment

1989 ◽  
Vol 22 (4) ◽  
pp. 202-218 ◽  
Author(s):  
S. T. Algermissen
Keyword(s):  
Risk Assessment ◽  
Data Base ◽  
Seismic Risk ◽  
Risk Assessments ◽  
Earthquake Risk ◽  
Seismic Risk Assessment ◽  
Single Structure ◽  
Earthquake Risk Assessment ◽  
Principal Elements

The principal elements of seismic risk assessment are outlined. An approach to seismic risk assessment is developed that provides quite satisfactory risk assessments on a scale of a single structure to regional assessments of risk. An example of a contemporary risk assessment is discussed and the development of a data base for routine risk assessments is advocated.

Global Seismic Risk Assessment: the Wrong, the Right, and the Truth

2020 ◽  
Author(s):  
Vitor Silva
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Current Practice ◽  
New Technologies ◽  
Risk Model ◽  
Economic Losses ◽  
Earthquake Risk ◽  
Loss Assessment ◽  
Risk Models ◽  
Seismic Risk Assessment

<p>The increase in the global population, climate change, growing urbanization and settlement in regions prone to natural hazards are some of the factors contributing to the increase in the economic and human losses due to disasters. Earthquakes represent on average approximately one-fifth of the annual losses, but in some years this proportion can be above 50% (e.g. 2010, 2011). This impact can affect the sustainable development of society, creation of jobs and availability of funds for poverty reduction. Furthermore, business disruption of large corporations can result in negative impacts at global scale. Earthquake risk information can be used to support decision-makers in the distribution of funds for effective risk mitigation. However, open and reliable probabilistic seismic risk models are only available for less than a dozen of countries, which dampers disaster risk management, in particular in the under-developed world. To mitigate this issue, the Global Earthquake Model Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate relevant earthquake risk metrics, which are now publicly available to the community.</p><p>The development of the global seismic risk model also allowed the identification of several issues that affect the reliability and accuracy of existing risk models. These include the use of outdated exposure information, insufficient consideration of all sources of epistemic and aleatory uncertainty, lack of results regarding indirect human and economic losses, and inability to forecast detailed earthquake risk to the upcoming decades. These challenges may render the results from existing earthquake loss models inadequate for decision-making. It is thus urgent to re-evaluate the current practice in earthquake risk loss assessment, and explore new technologies, knowledge and data that might mitigate some of these issues. A recent resource that can support the improvement of exposure datasets and the forecasting of exposure and risk into the next decades is the Global Human Settlement Layer, a collection of datasets regarding the built-environment between 1974 and 2010. The consideration of this type of information and incorporation of large sources of uncertainty can now be supported by artificial intelligence technology, and in particular open-source machine learning platforms. Such tools are currently being explored to predict earthquake aftershocks, to estimate damage shortly after the occurrence of destructive events, and to perform complex calculations with billions of simulations. These are examples of recent resources that must be exploited for the benefit of improving existing risk models, and consequently enhance the likelihood that risk reduction measures will be efficient.</p><p>This study presents the current practice in global seismic risk assessment with all of its limitations, it discusses the areas where improvements are necessary, and presents possible directions for risk assessment in the upcoming years.</p>

Sign in / Sign up

Export Citation Format

Share Document