5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
NEUSSNER-Risk maps for the support of reconstruction after Typhoon Haiyan-ID1...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Towards the Validation of National Risk Assessments against Historical Observ...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
The document discusses challenges facing agriculture in Central Asia due to climate change and water reservoirs. It notes that the region is experiencing rapid population growth, limited arable land, and impacts from water reservoirs. Adaptation approaches need to focus on increasing agricultural land and water productivity through new technologies, irrigation improvements, and drought/stress-resistant crop varieties. The effects of glacial melt and reservoirs on local climate and agriculture are also examined.
Critical Infrastructure and Disaster Risk Reduction Planning under Socioecono...Global Risk Forum GRFDavos
This document discusses approaches for designing critical infrastructure systems under uncertainty from socioeconomic and climate change. It suggests applying safety factors or designing flexible systems to deal with an uncertain future. Quantitative decision models were used to determine the optimal safety factor and measure the value of flexibility. The models showed the safety factor should be higher for inflexible systems and lower for flexible ones. Flexibility is more valuable when there is potential for significant learning and changes over the system's lifetime. The regulatory framework, such as requiring a risk-based versus rule-based approach, also influences design choices. The document concludes with design recommendations based on optimizing safety factors and valuing flexibility under different types and degrees of uncertainty.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
NEUSSNER-Risk maps for the support of reconstruction after Typhoon Haiyan-ID1...Global Risk Forum GRFDavos
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Towards the Validation of National Risk Assessments against Historical Observ...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
The document discusses challenges facing agriculture in Central Asia due to climate change and water reservoirs. It notes that the region is experiencing rapid population growth, limited arable land, and impacts from water reservoirs. Adaptation approaches need to focus on increasing agricultural land and water productivity through new technologies, irrigation improvements, and drought/stress-resistant crop varieties. The effects of glacial melt and reservoirs on local climate and agriculture are also examined.
Critical Infrastructure and Disaster Risk Reduction Planning under Socioecono...Global Risk Forum GRFDavos
This document discusses approaches for designing critical infrastructure systems under uncertainty from socioeconomic and climate change. It suggests applying safety factors or designing flexible systems to deal with an uncertain future. Quantitative decision models were used to determine the optimal safety factor and measure the value of flexibility. The models showed the safety factor should be higher for inflexible systems and lower for flexible ones. Flexibility is more valuable when there is potential for significant learning and changes over the system's lifetime. The regulatory framework, such as requiring a risk-based versus rule-based approach, also influences design choices. The document concludes with design recommendations based on optimizing safety factors and valuing flexibility under different types and degrees of uncertainty.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Extreme environmental events such as droughts, floods and heatwaves take place in space and time, and it is necessary to take this into account when evaluating their risks and estimating their probabilities. During this lecture, I will review recent work on this topic, focusing on max-stable
processes, which are the natural extension of univariate extreme-value models for more complex spatial phenomena. The most widely-used max-stable models, the Brown–Resnick and extremal-t processes will be described, followed by a brief overview of other types of models and of approaches to inference based on high threshold exceedances, with an emphasis on likelihood-based met
hods. The ideas will be illustrated by applications to heavy rainfall close to Jeddah and to high temperatures in the region of Madrid.
Application of GIS and Remote Sensing in Flood Risk ManagementAmitSaha123
Introduction to catastrophic disaster flood. Its impact on environment and human lives. GIS and Remote Sensing based solutions that can provide key approaches to mitigate flood related hazard as well as vulnerablities.
Justin Donaghy presented on using spatial data mining techniques to analyze and predict natural disasters. Spatial data mining aims to find patterns in geographical data. Donaghy discussed how John Snow first used spatial analysis to discover the source of a cholera outbreak in London. Challenges include inefficient algorithms when dealing with large datasets and lack of standardization. Data mining techniques like statistics, clustering, and classification could help predict events like heat waves and heavy precipitation. Improving distributed mining and developing spatial query languages may help make disaster prediction more accurate.
A Quantitative Framework to Assess Communities Resilience at the State Level,...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Flooding is one of the most devastating natural
disasters in Nigeria. The impact of flooding on human activities
cannot be overemphasized. It can threaten human lives, their
property, environment and the economy. Different techniques
exist to manage and analyze the impact of flooding. Some of these
techniques have not been effective in management of flood
disaster. Remote sensing technique presents itself as an effective
and efficient means of managing flood disaster. In this study,
SPOT-10 image was used to perform land cover/ land use
classification of the study area. Advanced Space borne Thermal
Emission and Reflection Radiometer (ASTER) image of 2010 was
used to generate the Digital Elevation Model (DEM). The image
focal statistics were generated using the Spatial Analyst/
Neighborhood/Focal Statistics Tool in ArcMap. The contour map
was produced using the Spatial Analyst/ Surface/ Contour Tools.
The DEM generated from the focal statistics was reclassified into
different risk levels based on variation of elevation values. The
depression in the DEM was filled and used to create the flow
direction map. The flow accumulation map was produced using
the flow direction data as input image. The stream network and
watershed were equally generated and the stream vectorized. The
reclassified DEM, stream network and vectorized land cover
classes were integrated and used to analyze the impact of flood on
the classes. The result shows that 27.86% of the area studied will
be affected at very high risk flood level, 35.63% at high risk,
17.90% at moderate risk, 10.72% at low risk, and 7.89% at no
risk flood level. Built up area class will be mostly affected at very
high risk flood level while farmland will be affected at high risk
flood level. Oshoro, Imhekpeme, and Weppa communities will be
affected at very high risk flood inundation while Ivighe, Uneme,
Igoide and Iviari communities will be at risk at high risk flood
inundation level. It is recommended among others that buildings
that fall within the “Very High Risk” area should be identified
and occupants possibly relocated to other areas such as the “No
Risk” area.
Population Vulnerability Assessment Around Alpg Storage And Distribution Faci...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Modelling the Monthly Vulnerability of Land Degradation by Using the Method o...IJAEMSJORNAL
Land degradation being an aspect of desertification is one of the challenging environmental problems which depends on the process of a mathematical modelling. To tackle this formidable environmental science problem, we have developed a sound database system that is driven by a computationally efficient numerical scheme to clearly show that the loss of land’s biological and economic productivityand complexity as defined by UNCCD [1] is more vulnerable to depletion ranging from the average value vulnerability of depletion of 7.95 approximately to 0.6 approximately. As a response to decreasing the natural growth rate of land use from0.6 to 0.006 provided the initial consumption units of land use ranges from its value of 100 to 1500. On the basis of this quantification, when the notion of the human population modelling is considered, the results of this present analysis clearly show that the smaller the initial consumption of land use, the more vulnerable land degradation can occur whereas the bigger the initial consumption of land use is associated with a weak vulnerability to degradation which is clearly smaller than the average vulnerability to depletion. These detailed results that we have obtained showed clear sustainable development implication which has not been seen elsewhere; these are carefully presented and discussed quantitatively
TYUBEE-Assessment of vulnerability of rural households to climate hazards-ID1...Global Risk Forum GRFDavos
This study assessed the vulnerability of rural households to climate hazards in mountainous areas of Kwande Local Government Area, Benue State, Nigeria. The objectives were to investigate major climate hazards, analyze variation in household vulnerability levels, and assess adaptation strategies. Regarding climate hazards, erosion and flooding were most frequent while landslides caused the most damage. A vulnerability assessment of 50 households found that adaptive capacity factors like healthcare and roads were most vulnerable. Household vulnerability scores averaged 5.3 out of 7, indicating significant vulnerability. Common adaptation strategies included changing agriculture, relocating, and changing livelihoods.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Extreme environmental events such as droughts, floods and heatwaves take place in space and time, and it is necessary to take this into account when evaluating their risks and estimating their probabilities. During this lecture, I will review recent work on this topic, focusing on max-stable
processes, which are the natural extension of univariate extreme-value models for more complex spatial phenomena. The most widely-used max-stable models, the Brown–Resnick and extremal-t processes will be described, followed by a brief overview of other types of models and of approaches to inference based on high threshold exceedances, with an emphasis on likelihood-based met
hods. The ideas will be illustrated by applications to heavy rainfall close to Jeddah and to high temperatures in the region of Madrid.
Application of GIS and Remote Sensing in Flood Risk ManagementAmitSaha123
Introduction to catastrophic disaster flood. Its impact on environment and human lives. GIS and Remote Sensing based solutions that can provide key approaches to mitigate flood related hazard as well as vulnerablities.
Justin Donaghy presented on using spatial data mining techniques to analyze and predict natural disasters. Spatial data mining aims to find patterns in geographical data. Donaghy discussed how John Snow first used spatial analysis to discover the source of a cholera outbreak in London. Challenges include inefficient algorithms when dealing with large datasets and lack of standardization. Data mining techniques like statistics, clustering, and classification could help predict events like heat waves and heavy precipitation. Improving distributed mining and developing spatial query languages may help make disaster prediction more accurate.
A Quantitative Framework to Assess Communities Resilience at the State Level,...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Flooding is one of the most devastating natural
disasters in Nigeria. The impact of flooding on human activities
cannot be overemphasized. It can threaten human lives, their
property, environment and the economy. Different techniques
exist to manage and analyze the impact of flooding. Some of these
techniques have not been effective in management of flood
disaster. Remote sensing technique presents itself as an effective
and efficient means of managing flood disaster. In this study,
SPOT-10 image was used to perform land cover/ land use
classification of the study area. Advanced Space borne Thermal
Emission and Reflection Radiometer (ASTER) image of 2010 was
used to generate the Digital Elevation Model (DEM). The image
focal statistics were generated using the Spatial Analyst/
Neighborhood/Focal Statistics Tool in ArcMap. The contour map
was produced using the Spatial Analyst/ Surface/ Contour Tools.
The DEM generated from the focal statistics was reclassified into
different risk levels based on variation of elevation values. The
depression in the DEM was filled and used to create the flow
direction map. The flow accumulation map was produced using
the flow direction data as input image. The stream network and
watershed were equally generated and the stream vectorized. The
reclassified DEM, stream network and vectorized land cover
classes were integrated and used to analyze the impact of flood on
the classes. The result shows that 27.86% of the area studied will
be affected at very high risk flood level, 35.63% at high risk,
17.90% at moderate risk, 10.72% at low risk, and 7.89% at no
risk flood level. Built up area class will be mostly affected at very
high risk flood level while farmland will be affected at high risk
flood level. Oshoro, Imhekpeme, and Weppa communities will be
affected at very high risk flood inundation while Ivighe, Uneme,
Igoide and Iviari communities will be at risk at high risk flood
inundation level. It is recommended among others that buildings
that fall within the “Very High Risk” area should be identified
and occupants possibly relocated to other areas such as the “No
Risk” area.
Population Vulnerability Assessment Around Alpg Storage And Distribution Faci...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Modelling the Monthly Vulnerability of Land Degradation by Using the Method o...IJAEMSJORNAL
Land degradation being an aspect of desertification is one of the challenging environmental problems which depends on the process of a mathematical modelling. To tackle this formidable environmental science problem, we have developed a sound database system that is driven by a computationally efficient numerical scheme to clearly show that the loss of land’s biological and economic productivityand complexity as defined by UNCCD [1] is more vulnerable to depletion ranging from the average value vulnerability of depletion of 7.95 approximately to 0.6 approximately. As a response to decreasing the natural growth rate of land use from0.6 to 0.006 provided the initial consumption units of land use ranges from its value of 100 to 1500. On the basis of this quantification, when the notion of the human population modelling is considered, the results of this present analysis clearly show that the smaller the initial consumption of land use, the more vulnerable land degradation can occur whereas the bigger the initial consumption of land use is associated with a weak vulnerability to degradation which is clearly smaller than the average vulnerability to depletion. These detailed results that we have obtained showed clear sustainable development implication which has not been seen elsewhere; these are carefully presented and discussed quantitatively
TYUBEE-Assessment of vulnerability of rural households to climate hazards-ID1...Global Risk Forum GRFDavos
This study assessed the vulnerability of rural households to climate hazards in mountainous areas of Kwande Local Government Area, Benue State, Nigeria. The objectives were to investigate major climate hazards, analyze variation in household vulnerability levels, and assess adaptation strategies. Regarding climate hazards, erosion and flooding were most frequent while landslides caused the most damage. A vulnerability assessment of 50 households found that adaptive capacity factors like healthcare and roads were most vulnerable. Household vulnerability scores averaged 5.3 out of 7, indicating significant vulnerability. Common adaptation strategies included changing agriculture, relocating, and changing livelihoods.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Vietnam has approved 815 hydropower projects with a total installed capacity of 24,324.3MW. While hydropower dams can help with flood mitigation, many in Vietnam are poorly managed and negatively impact the environment and local communities. The document calls for improving forest management, expanding rainfall monitoring networks, installing monitoring equipment at reservoirs, and establishing dam safety committees to better leverage hydropower for flood control while reducing negative impacts.
The document discusses how the Internet of Things (IoT) could help with disaster and risk management. It describes the IoT as physical objects connected to the internet that can be remotely monitored and controlled. Examples are given of projects using IoT technologies like sensors and earth observation data to help with early warning systems, monitoring health risks, and supporting critical decision making. The conclusion argues that the IoT should be further developed and integrated into frameworks like the post-2015 DRR accord, with an emphasis on open standards, secure and scalable infrastructure, and partnerships between technical and disaster management experts.
Similar to IDRC global risk of population by SDS-Yang Hui-Min_template2 (20)
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Disaster risk reduction and nursing - human science research the view of surv...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Global alliance of disaster research institutes (GADRI) discussion session, A...Global Risk Forum GRFDavos
Global Alliance of Disaster Research Institutes (GADRI) aims to reduce disaster risk and increase resilience through interdisciplinary research. GADRI brings together institutions to support research efforts through cooperation instead of competition. It also guides new researchers and maintains institutional memory to build upon past work. Some challenges GADRI may face include coordinating a global alliance. Solutions include facilitating cooperative work between members and guiding the expanding field of disaster reduction research.
Towards a safe, secure and sustainable energy supply the role of resilience i...Global Risk Forum GRFDavos
The document discusses concepts related to ensuring a safe, secure, and sustainable energy supply. It introduces the concepts of risk assessment, resilience management, security of supply, sustainability, and multi-criteria decision analysis. It then presents a case study from the EU SECURE project that used these concepts to evaluate policy scenarios according to various environmental, economic, social, and security indicators. The study found that global climate policy scenarios generally performed best, though they were vulnerable to certain shocks like nuclear accidents or carbon capture failures. Overall policies that reduced fossil fuel use and led to greater diversification of energy sources and imports improved sustainability and security.
Making Hard Choices An Analysis of Settlement Choices and Willingness to Retu...Global Risk Forum GRFDavos
1) The document analyzes data from surveys of Syrian refugees in Turkey to understand their choices regarding returning to Syria, staying in Turkey, or migrating elsewhere.
2) It finds that as the duration of living as a refugee increases, the probability of returning to Syria decreases significantly, while the likelihood of migrating to another country increases.
3) Refugees who experienced greater damage, losses, or deaths due to the war in Syria are less likely to return and more likely to migrate internationally in search of asylum.
The Relocation Challenges in Coastal Urban Centers Options and Limitations, A...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Involving the Mining Sector in Achieving Land Degradation Neutrality, Simone ...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Disaster Risk Reduction and Nursing - Human Science research the view of surv...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Training and awareness raising in Critical Infrastructure Protection & Resili...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
IDRC Davos 2016 - Workshop Awareness Raising, Education and Training - Capaci...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
The document summarizes the Global Alliance of Disaster Research Institutes (GADRI). GADRI is a global network of over 100 disaster research institutes that aims to enhance disaster risk reduction through knowledge sharing. It holds symposia, workshops, and other events on topics like flash floods, earthquakes, and geohazards. Notable upcoming events include the Third Global Summit of Research Institutes for Disaster Risk Reduction in 2017. GADRI's goals are to establish collaborative research initiatives, form international working groups, and disseminate findings to influence disaster policy.
The document discusses capacity development for disaster risk reduction at the national and local levels. It explores strengths and weaknesses of current DRR capacity development efforts, and presents UNITAR's contribution through a new K4Resilience hub initiative. The initiative aims to strengthen DRR capacity development at national and sub-national levels by transferring knowledge and technology, advocating for positive change, achieving economies of scale in training, and facilitating peer-to-peer learning and mainstreaming of knowledge through strategies at the national and sub-national levels.
Dynamic factors influencing the post-disaster resettlement success Lessons fr...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Consequences of the Armed Conflict as a Stressor of Climate Change in Colombi...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Disaster Risk Perception in Cameroon and its Implications for the Rehabilitat...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Systematic Knowledge Sharing of Natural Hazard Damages in Public-private Part...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Exploring the Effectiveness of Humanitarian NGO-Private Sector Collaborations...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Can UK Water Service Providers Manage Risk and Resilience as Part of a Multi-...Global Risk Forum GRFDavos
The document discusses a study examining how well UK water service providers incorporate risk management and resilience as part of a multi-agency approach. The researchers analyzed 38 Community Risk Registers and found inconsistencies in style, structure, and level of detail when assessing risks like water infrastructure failures or drought. They conclude that improved consistency is needed in how water providers engage in and contribute their risk assessments to the community planning process.
A Holistic Approach Towards International Disaster Resilient Architecture by ...Global Risk Forum GRFDavos
6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
A Holistic Approach Towards International Disaster Resilient Architecture by ...
IDRC global risk of population by SDS-Yang Hui-Min_template2
1. Assessment of global affected demographic risk
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
by sand-dust storm and its spatial pattern
Huimin Yang, Lianyou Liu, Xingming Zhang,
Jing’aWang, Peijun Shi
State Key Laboratory of Earth Surface Processes
and Resource Ecology,
School of Geography,
Beijing Normal University,
China
2. 5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
Outline
1. Research Advance of SDS
2. Data and Methods
3. Results and Analysis
3. 5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
1. Research Advance Of SDS
4. Korla City
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
1. Research advance of SDS
• Sand and dust storm(SDS)is a type of disastrous weather which
occurs chiefly in arid and semi-arid desertified regions.
• SDS is a weather phenomenon of wind-borne sand and dust particles
blown by strong winds on the ground and makes air particularly
turbid, with horizontal visibility less than 1 km.
• Adverse effects:such as reducing land productivity, affecting
transport facilities and power lines, polluting the air, threating human
health, affecting global climate, etc.
5. 5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
Engelstaedter, et al.,2003
www.grforum.org
1. Research advance of SDS
• Global SDS-prone areas are located in North Africa, Middle East,
central Asia, north America, south America, Australia and other places.
• A lot of studies have been conducted on the temporal and spatial
pattern of SDS from regional perspective: such as the spatial-temporal
distribution of SDS in central Asia, Turkmenistan, China, etc .
6. 1. Research advance of SDS
• At present, a lot of studies have been conducted on the spatial-temporal
distribution, causes, source regions, and disaster theories
of SDS with fruitful results. SDS disaster risk assessment is
important for SDS disaster reduction, especially from regional
perspective to a global scale.
• In this study, the global affected demographic risk by SDS(RPOP-SDS
) was evaluated and its spatial pattern was analysed in the
aspects of hazard, hazard-formative environment and hazard-affected
body (exposure) , With SDS kinetic energy as the key
indicator of hazard, this study is intended to provide a new
solution to assessing SDS risk.
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
7. 5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
2. Data and Methods
8. 5th International Disaster and Risk Conference IDRC 2014
2. Data and Methods
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
Previous H
Flow chart
9. 5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
www.grforum.org
2. Data and Methods
Data Source Remarks
Global surface
China Meterological Administration
synoptic timing data
(CMA),http://cdc.cma. gov.cn/home.do
set
January 1, 1982--2011,
65 indices, 9728stations。
Population Oak Ridge National Laboratory
(ORNL) ,http://www.ornl.gov/gist
2010,resolution of
1km*1km,raster
Global Aridity Index
Climate Database
Consultative Group for International
Agriculture Research(CGIAR),
http://www.csi.cgiar.org
resolution of 30 arc-second,
raster
Circum-Arctic Map
of Permafrost
National Snow and Ice Data Center,
ftp://sidads.colorado.edu
/pub/DATASETS/fgdc/ggd318_map_cir
cumarctic/
vector data(*.shp)
2.1 Data sources
10. R EHV
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2.2. Methods
(1) Three-dimensional evaluating model of risk
Disaster is the comprehensive product of hazard-formative environment
(E), hazards (H) and hazard-affected body (exposure). disaster risk(R) is the
potential loss induced by natural hazards. hazard-formative environment
could reduce or magnify the effect of hazards on exposures.
(1)
Where R is risk, E is stability of hazard-formative environment, H is danger
of hazards; V is vulnerability of exposure. This three- dimensional model is a
modification of previous two- dimensional models。
The RPOP-SDS was determined by product of normalized kinetic energy,
population density and aridity index by grid, country unit and
comparable area unit, respectively (Fig. 4, Fig. 5 and Fig. 6).
11. max
x
max -min
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2.2. Methods
(2) Data Processing
Hazard-formative environment
In this study, areas prone to desertification were taken as the main
research areas. Aridity is considered as a key factor of the SDS
hazard-formative environment because of its prominent influence
on vegetation, soil property, the ultimate intensity and frequency of
SDS.
The aridity index data were normalized by formula (2):
(2)
The normalized aridity map of global areas prone to SDS is shown as Fig. 1.
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2.2. Methods
(2) Data Processing
Hazard-formative environment
Fig. 1 Normalized aridity map of global areas prone to sand and dust storms
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2.2. Methods
(2) Data Processing
SDS hazard
The SDS hazard is determined both by its magnitude and frequency.
During an SDS event, SDS energy plays a decisive role in soil wind
erosion, sand entrainment and dust emission, blown sand and dust
transport, so it might be a more appropriate parameter for
quantifying SDS.
During typical SDS events, PM10 accounts for the majority of the
particulate matter in atmosphere(Zhuang et al., 2001; Jayaratne et
al., 2011).
14. 10 5 10 vis PM V
8 1.5977
1.5977 2 1
4 p vis E V v
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2.2. Methods
(2) Data Processing
SDS hazard
In the centre of a sand desert, PM10 has negative power functions with
visibility (Yang et al., 2006; Wang et al., 2008).
(3)
where Vvis is visibility, and PM10 is in μg·m-3.
We combined formula (3) with the classical kinetic energy formula ,the
kinetic energy per cubic meter of SDS (Ep) can be expressed by formula (4).
(4)
where v is the maximum wind velocity (m/s) at 10 m high.
15. x -min
max -min
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2.2. Methods
(2) Data Processing
SDS hazard——SDS kinetic energy of 100-year return period
Information diffusion method was used in calculating SDS kinetic
energy of different return periods, SDS kinetic energy of different
return periods corresponded with a exceedance probability Pi,
therefore making the exceedance probability Pi = 0.01 over 100-
year return period. Then, SDS kinetic energy under this scenario
was calculated. Finally kinetic energy was normalized with formula
(5). (5)
Through the inverse distance weighted method, the normalized map
of global SDS kinetic energy based on100-year return period is
shown as Fig. 2.
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2.2. Methods
(2) Data Processing
SDS hazard
Fig. 2 normalized map of global sand and dust storm kinetic energy based on 100-year
return period
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2.2. Methods
(2) Data Processing
Exposure
The global population distribution data is originally from the
global population database(2010 ), with a resolution of 1 km ×
1 km.
For comparability, population density was normalized with
formula (5), and the normalized map of global population
distribution in 2010 is shown as Fig. 3.
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2.2. Methods
(2) Data Processing
Exposure
Fig. 3 Normalized map of global population distribution in 2010
19. 3. Results and Analysis
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——Risk R EHV
——global RPOP-SDS was divided into five grades, namely, extremely high,
high, moderate, low, and extremely low.
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3. Results and analysis
• 3.1. Spatial pattern of RPOP-SDS by grid
Fig. 4 Grade map of affected population risk by sand and dust storms (by grid)
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3. Results and analysis
• 3.2. Spatial Pattern of RPOP-SDS by Country Unit
Fig. 5 Grade map of affected population risk by sand and dust storms in different countries
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3. Results and analysis
• 3.3. Spatial pattern of RPOP-SDS by comparable area unit
Fig. 6 Grade map of affected population risk by sand and dust storms in different regions
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To the end!
Thank you for your attention!
Editor's Notes
方法与模型 method and model H for short (缩写为H) definition Because of difference in unit of these three parts.so normaliztion is needed.
技术路线图 technology roadmap global aridity index(AI)
Years encounter 年遇型 No vulnerability curve→relative risk level
Where Ix is dimensionless normalized data normalized by original data, x is original data, min is minimum of original data, and max is maximum of original data.