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At the forefront of the Global Earthquake Model (GEM) is the development of uniform standards, datasets, and state-of-the-art modeling tools for the communication of earthquake risk. For a more holistic assessment of the scale and consequences of earthquake impacts, spatially enabled and open databases, methods, and Open Source software tools are b...
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... Each sub-component was then summed to derive a final composite score. Since there are five sub-components, the summed score of the composite index ranges between 0 and 5 (0 being the least socially vulnerable and 5 being the most). As a subsequent step, the composite social vulnerability scores were rescaled using Min-Max rescaling to produce a final composite score between zero and one (0 being the least socially vulnerable and 1 being the most vulnerable). An aggregation method using equal weights was applied due to the lack of theoretical justification for weighting one variable over another for use in this proof of concept. The evaluation of integrated risk (i.e. the combination of estimated losses with the social vulnerability index outlined above) required the modeling of expected economic losses for each county (or first order impacts) and the modeling of conditions within social systems that create the potential for harm and loss. The modeled losses in the form of estimates of average annual loss for each county were also rescaled using the Min-Max rescaling method to render them commensurate to the social vulnerability index. To derive an estimate of integrated risk, a total risk index was constructed via the convolution of the social vulnerability index with the estimates of physical earthquake risk. Carreño et al. (2007; 2012) provide the aggregation method that was adopted for this work due to its mathematical simplicity. In this method, the direct potential impact of an earthquake (in a general sense) is denoted as R T = R F ( 1 + F ) where R T is a total risk index, R F is a physical earthquake risk index which is an average annual loss estimate for Portugal derived utilizing the physical risk model outlined above, and F is the composite social vulnerability index which may be described as an aggrevating coefficient of the estimated loss. The probabilistic seismic hazard for mainland Portugal was calculated using the Classical PSHA- based hazard calculator (Pagani et al. 2014). A large number of seismic hazard curves were derived following a 0.01x0.01 decimal degrees spatial resolution considering a wide spectrum of epistemic uncertainties (e.g. various ground motion prediction models, seismic zonations, magnitude-frequency distributions), through the employment of a logic tree structure. Using the set of hazard curves at each location, a mean seismic hazard map for a probability of exceedance of 10% in 50 years was calculated, as depicted in Figure 2. The appraisal of the spatial distribution of hazard in Portugal indicates an expected higher peak ground acceleration on rock for the Lower Tagus Valley (region around Lisbon) and the south of Portugal, thus highlighting regions where a combination of seismically vulnerable structures and high population concentration could lead to significant earthquake losses. The hazard results were combined with the exposure and vulnerability models to derive loss exceedance curves for each county. These curves were converted into annual rate of exceedance, and numerically integrated in order to obtain the average annual economic loss, as illustrated in Figure 3. In addition to hazard and physical risk, understanding the distribution of the social vulnerability of populations is an integral part of disaster management, planning, and mitigation. Figure 4 depicts the spatial variation in social vulnerability for Portugal’s counties. The classification scheme was simplified (i.e. high, moderate, low) for presentation purposes. The counties delineated in the darker shades of red along the classification continuum exhibit higher levels of social vulnerability. While the spatial pattern is not uniform throughout, there are significant pockets of social vulnerability that could warrant management concern given the seismic threat. Of special interest is the clustering of moderate to high and high levels of social vulnerability in the southwestern portion of the country. Here, counties that host cities such as Santarem, Setubal, and Faro have populations with high levels of social vulnerability. These areas are also in zones of high seismicity (see Figure 2) and zones of high physical earthquake risk (see Figure 3). In addition to these clusters of counties with high social vulnerability and physical risk, there is another large section in Portugal’s northern portion with high levels of social vulnerability. These are in largely rural areas outside of the high-risk zones. However, exceptions in these areas exist where counties are exposed to considerable risk of loss and that also contain highly socially vulnerable populations. Populations within these counties may not only suffer greater impacts due to ground shaking and building damage, they may also lack the ability to adequately mitigate, prepare for, and recover from a damaging earthquake event. The spatial distribution of risk within these counties is compounded when viewed as an integrated risk map (Figure 5). The impacts from an earthquake will be expressed differentially across communities. To be effective, governments, disaster planners, and managers must not only understand the physical agents of earthquake risk, but also the social characteristics that give rise to vulnerabilities within the communities they protect. This paper presented a method, workflow, and analysis conducted within GEM’s OpenQuake that consists of a spatial delineation of physical earthquake risk combined with an index of social vulnerability. The overall approach leads to an encompassing perspective on risk assessment that considers loss and damage as part of a dynamic system, and our findings suggest that there are spatial differences in physical earthquake risk, social vulnerability, and integrated risk within Portugal. Disaster mitigation and planning under such circumstances may require special attention where different aspects of social vulnerability affect the way in which communities may prepare for and respond to the seismic threat. In sum, the approach mainstreams risk and social vulnerability into policy discussions on earthquake loss and damage reduction, makes it possible to use risk estimates in benchmarking exercises to monitor changes in loss potential over time, and recognizes that both the causes and solutions for earthquake loss are found in human, environmental, and built-environment relationships. Boruff BJ and Cutter SL (2007) “The Environmental Vulnerability of Caribbean Island Nations,” Geographical Review, 97(1): 932-942 Burton, CG and Cutter SL (2008) “Levee Failures and Social Vulnerability in the Sacramento-San Joaquin Delta Area, California, “ Natural Hazards Review” , 9(3): 136-149 Burton CG, Khazai B, Silva V, (in press) “Social Vulnerability and Integrated Risk Assessment within the Global Earthquake Model”, Proceedings of 10 th National Conference in Earthquake Engineering , Earthquake Engineering Research Institute, Anchorage, Alaska Cardona, OD (2005) Indicators of Disaster Risk and Risk Management, IADB-UNC/IDEA Program for Latin America and the Caribbean, Universidad Nacional de Colombia, Instituto de Estudios Ambientales (IDEA), Manizales Carreño M-L, Cardona OD, Barbat AH (2007) “Urban Seismic Risk Evaluation: A Holistic Approach,” Natural Hazards, 40: 137-172 Carreño M-L, Cardona OD, Barbat AH (2012) “New Methodology for Urban Seismic Risk Assessment from a Holistic Perspective,” Bulletin of Earthquake Engineering , 40: 137-172 Carvalho EC, Coelho E, Campos Costa A, Sousa ML, Candeias P (2002) “Vulnerability Evaluation of Residential Buildings in Portugal,” Proceedings of the 12th European Conference on Earthquake Engineering , London, United Kingdom Cutter, SL (1996) “Vulnerability to Environmental Hazards,” Progress in Human Geography , 20: 529-539 Cutter SL, Boruff BJ, Shirley WL (2003) “Social Vulnerability to Environmental Hazards,” Social Science Quarterly , 84: 242-261 Cutter SL, Mitchell J, Scott M (2000) “Revealing the Vulnerability of People and Places: A Case Study of Georgetown County, South Carolina,” Annals of the Association of American Geographers, 90 (4): 713-737 Davidson, R (1997) “A Multidisciplinary Urban Earthquake Disaster Risk Index,” Earthquake Spectra , 13(2): 211-223 Fekete, A (2009) “Validation of a Social Vulnerability Index in Context to River-floods in Germany,” Natural Hazards and Earth Systems Sciences , 9: 393-403 Fernandez J, Mattingly S, Bendimerad F, Cardona OD (2006) Application of Indicators in Urban and Megacities Disaster Risk Management, A Case Study of Metro Manila, EMI Topical Report TR-07-01 Freudenberg M (2008) Composite Indicators of Country Performance: A Critical Assessment , OECD, Paris Hewitt K and Burton I (1971) The Hazardousness of a Place: A Regional Ecology of Damaging Events, University of Toronto Press, Toronto Khazai B and Bendimerad F. (2011) Risk and Resiliency Indicators, EMI Topical Report TR-1 1-03 Khazai B, Kilic O, Basmaci A, Konukcu B, Sungay B, Zeidan A, Wenzel F (2008) Megacity Indicators System for Disaster Risk Management - Implementation in Istanbul, in M ...
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At the forefront of the risk assessment sciences is the development of standards, data, and tools for the assessment of earthquake risk. Countries such as Portugal have been targets of extensive earthquake risk assessments to communicate damage potential and to improve methodologies. Few studies, however, have gone beyond the estimation of direct p...
Citations
... Interpreted as the direct danger to the presence of societies, environmental system and properties, and the extent of the geographical context that could be adversely affected by disaster risk occurrence [4,11]. Exposure is measured through an integrated understanding of how relevant factors can be combined to determine a community's level of resilience [14,15]. These techniques include methods for assessing the vulnerability of local societies, which are generally based on statistical data obtained from national censuses and supplemented data sources, in order to determine how they are likely to respond in the face of natural disasters. ...
Due to the complex nature of seismic vulnerability assessment, different approaches and data are required, based on the country. Alternatively, seismic vulnerability assessment can be categorized into two common techniques, the conventional and holistic methods, the use of which depends on the region's conditions. Generally, conventional methods concern the consequences of an earthquake by estimating the potential loss caused by the structural inventory damage and the number of casualties. Meanwhile, holistic methods focus on the different primary factors that contribute to seismic vulnerability, which are represented by the social, economic, physical, and environmental elements of a community or structure in a region. However, less attention has been given to the quantitative evaluation of holistic seismic vulnerability in Malaysia compared to hazard-related research. Therefore, the aim of this study was to identify the holistic seismic vulnerability indicators in the context of an earthquake in Malaysia. Analysis is critical for understanding the numerous indicators of causes of earthquakes to define their relative relationships and the disaster risk probability. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting method, a comprehensive review of the Scopus and Web of Science databases was undertaken to search for indicators with a substantial impact on the aforementioned dimensions of earthquake vulnerability. This article concludes that there are three major elements of vulnerability (exposure, resilience, and coping capacity), comprising eighteen indicators of seismic vulnerability, in the context of earthquakes in Malaysia.
... i. Exposure, is a crucial element of vulnerability risk that defines the extent of societies and properties under assessment in the geographical context of risk occurrence UNISDR 2016). Measuring exposure demands an integrated understanding of components and how these factors can be amalgamated to contribute to the resilience of communities (Burton and Silva 2014;Carreno et al. 2016). These approaches include methods that use predominantly integral statistical data gathered from national census to assess the vulnerability of local populations. ...
Various techniques and frameworks for an evaluation of seismic vulnerability have been developed and established in previous studies. However, some techniques demand a significant amount of empirical data currently not readily available in developing countries. Therefore, this study proposes a new seismic risk evaluation method at the local district level. A holistic model was constructed for the purpose of assessing potential seismic vulnerability based on appropriate indices and their relative contribution towards vulnerability and coping capacity. It allowed the estimation of vulnerability in terms of exposure, resilience, and capacity factors. Then, utilization of Geographical Information System (GIS) tools resulted in the generation of a total vulnerability map via integration of the study variables to highlight the socio-economic and physical characteristics of vulnerability for the districts in Pahang, Malaysia. Subsequently, a seismic risk map of the study area was derived by overlying the derived map with the seismic hazard map. Consequently, the study revealed the highest levels of seismic risk were concentrated in the central-west of the Pahang region, namely the Bentong district. In contrast, the least vulnerable areas encompassed the Pekan and Jerantut areas, which were located in the eastern region. In brief, the study findings would serve as the foundation towards reducing the country’s vulnerability to disasters.
... Map of seismic hazard in the Iberian Peninsula. Source: Designed by the authors based on data fromBurton and Silva (2014) and from the Instituto Geogr afico Nacional(2015). ...
This study investigated the importance given by two groups of pre-service teachers of primary education from Spain and Portugal to seismic risk in a framework of different natural risks, both in personal terms and as future teachers. A questionnaire was used for data collection. Some questions about the seismic phenomenon were also included. The sample groups consisted of 110 students from an institution in Spain and 121 from one in Portugal. Both institutions are in cities affected by the historic Lisbon earthquake of 1755. The results showed that the risk of forest fire was the first choice for classroom study in both cases. The Spanish group was also more focused on the importance of other risks like flood and drought. The Portuguese group showed a greater concern with seismic risk, frequently referring to their own historic earthquake of 1755. A few gaps in knowledge concerning earthquake prediction and comparing seismic risk in different regions of their own countries were also found. In accordance with the results, it is suggested that training courses for primary school teachers should include Disaster Risk Education in Science Education for a better understanding of the impact of various hazards and a greater concern with seismic risk due to its particular features, especially in regions where the seismic pattern is characterized by long seismic cycles with major earthquake episodes.
... En esta evaluación, los daños o pérdidas físicas potenciales son agravadas por un conjunto de condiciones socioeconómicas Figura A2-1-. Enfoque holístico a la evaluación probabilista del riesgo (Cardona, 2001;Carreño et al., 2007;Marulanda et al., 2009) • 250 Metodología Esta metodología para dar cuenta del riesgo en forma integral o comprensiva ha sido aplicada con diferentes niveles de resolución ( Daniell et al. 2010; Burton y Silva 2014) y ha sido incluido en manuales y bases de datos para evaluación del riesgo sísmico ( Khazai et al. 2014;Burton et al. 2014). Dado que no siempre se cuenta con la misma información en términos de indicadores útiles disponibles para el área de estudio, cada evaluación representa un reto en cuanto a la selección y en algunos casos al cálculo de los factores o descriptores que dan cuenta del contexto social e institucional. ...
El Atlas tiene como objetivo dar a conocer diversos estudios y avances en relación con la evaluación de las diferentes amenazas de origen natural y tecnológico, desarrollados por entidades públicas y privadas en el país; así como también dar a conocer resultados de la evaluación probabilista del riesgo para diferentes amenazas, basados en métricas del riesgo apropiadas para la toma de decisiones.
Se presentan mapas de amenaza sísmica, inundación, tsunami, ciclones tropicales, incendios forestales, sequía y movimientos en masa a nivel nacional. A nivel departamental se presentan perfiles de riesgo multi-amenaza con mapas de la pérdida anual esperada, para representar el riesgo físico, y los resultados del índice integral del riesgo de desastres para dar cuenta del impacto potencial, teniendo en cuenta factores de agravamiento asociados con la fragilidad socioeconómica y la falta de resiliencia a nivel municipal.
En el formato original se puede obtener en:
http://repositorio.gestiondelriesgo.gov.co/handle/20.500.11762/27179
... Simple examples are statistical analyses between damages (or fatalities) and a second variable such as the number of buildings in need of large repair in an area as used in the Global Earthquake Model (GEM) (e.g. Burton and Silva, 2014;Silva et al., 2014a, b). Below we give several examples: ...
... For floods, indicators related to increasing resilience such as urban planning institutions (Balica et al., 2009) and investments in precautionary measures (Connor and Hiroki, 2005) are occasionally considered in assessing social vulnerability. For earthquakes, it appears that fewer models take governance-related indicators into account, such as political stability (GEM, 2016) and crime rates (Burton and Silva, 2014). Non-hazard-specific vulnerability assessment models such as the DRI by Peduzzi et al. (2009) use Transparency International's Corruption Perception Index (CPI) as an indicator of corruption, and the Prevalent Vulnerability Index (PVI) incorporates a governance index with the following six indicators: voice and accountability, political stability, absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption (Cardona and Carreño, 2011;IPCC, 2012). ...
In a cross-disciplinary study, we carried out an extensive
literature review to increase understanding of vulnerability indicators used
in the disciplines of earthquake- and flood vulnerability assessments. We
provide insights into potential improvements in both fields by identifying
and comparing quantitative vulnerability indicators grouped into physical
and social categories. Next, a selection of index- and curve-based
vulnerability models that use these indicators are described, comparing
several characteristics such as temporal and spatial aspects. Earthquake
vulnerability methods traditionally have a strong focus on object-based
physical attributes used in vulnerability curve-based models, while flood
vulnerability studies focus more on indicators applied to aggregated land-use
classes in curve-based models. In assessing the differences and similarities
between indicators used in earthquake and flood vulnerability models, we only
include models that separately assess either of the two hazard types. Flood
vulnerability studies could be improved using approaches from earthquake
studies, such as developing object-based physical vulnerability curve
assessments and incorporating time-of-the-day-based building occupation
patterns. Likewise, earthquake assessments could learn from flood studies by
refining their selection of social vulnerability indicators. Based on the
lessons obtained in this study, we recommend future studies for exploring
risk assessment methodologies across different hazard types.
... Simple examples are statistical analyses between damages (or fatalities) and a second variable such as the number of buildings in need of large repair in an area as used in the Global Earthquake Model (GEM) (e.g. Burton and Silva, 2014(Connor and Hiroki, 2005; Balica et al., 2009). A similar index is the country level physical and community risk index for earthquakes and floods in the Asia-Pacific region by Daniell et al. (2010). ...
In a cross-discipline study, we carried out an extensive literature review to increase understanding of vulnerability indicators used in both earthquake- and flood vulnerability assessments. We provide insights into potential improvements in both fields by identifying and comparing quantitative vulnerability indicators. Indicators have been categorised into physical- and social categories, and then, where possible, further subdivided into measurable and comparable indicators. Next, a selection of index- and curve based vulnerability models that use these indicators have been described, comparing several characteristics such as temporal- and spatial aspects. It appears that earthquake vulnerability methods traditionally have a strong focus on object-based physical attributes used in vulnerability curve-based models, while flood vulnerability studies focus more on indicators applied to aggregated land-use classes in curve-based models. Flood risk studies could be improved using approaches from earthquake studies, such as incorporating more detailed physical indicators, developing object-based physical vulnerability curve assessments and incorporating time-of-the-day based building occupation patterns. Likewise, earthquake assessments could learn from flood studies by refining their selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies for exploring risk assessment methodologies cross-different hazard types.
... Efforts to quantify risk have typically considered a limited number of dimensions like the physical dimension (for example, buildings and mortality) and economic aspects of vulnerability, but social vulnerability is poorly understood and difficult to measure. Measuring vulnerability and exposure requires an integrated understanding of components and how these factors combine to contribute to the resilience 27 of communities (Carreño et al. 2007;Burton and Silva 2014). These approaches include methods that use predominantly statistical data gathered from published sources, and approaches that involve surveying local populations. ...
The first international conference for the post-2015 United Nations landmark agreements (Sendai Framework for Disaster Risk Reduction 2015–2030, Sustainable Development Goals, and Paris Agreement on Climate Change) was held in January 2016 to discuss the role of science and technology in implementing the Sendai Framework for Disaster Risk Reduction 2015–2030. The UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 aimed to discuss and endorse plans that maximize science’s contribution to reducing disaster risks and losses in the coming 15 years and bring together the diversity of stakeholders producing and using disaster risk reduction (DRR) science and technology. This article describes the evolution of the role of science and technology in the policy process building up to the Sendai Framework adoption that resulted in an unprecedented emphasis on science in the text agreed on by 187 United Nations member states in March 2015 and endorsed by the United Nations General Assembly in June 2015. Contributions assembled by the Conference Organizing Committee and teams including the conference concept notes and the conference discussions that involved a broad range of scientists and decision makers are summarized in this article. The conference emphasized how partnerships and networks can advance multidisciplinary research and bring together science, policy, and practice; how disaster risk is understood, and how risks are assessed and early warning systems are designed; what data, standards, and innovative practices would be needed to measure and report on risk reduction; what research and capacity gaps exist and how difficulties in creating and using science for effective DRR can be overcome. The Science and Technology Conference achieved two main outcomes: (1) initiating the UNISDR Science and Technology Partnership for the implementation of the Sendai Framework; and (2) generating discussion and agreement regarding the content and endorsement process of the UNISDR Science and Technology Road Map to 2030.
... We refer to this convolution as an integrated risk assessment. This work was conducted as part of a test case and proof of concept needed for the development of Opensource software that will be utilized for end-to-end earthquake risk assessment within the Global Earthquake Model (GEMS's) OpenQuake framework (Burton and Silva 2014). ...
At the forefront of the risk assessment sciences is the development of standards, data, and tools for the assessment of earthquake risk. Countries such as Portugal have been targets of extensive earthquake risk assessments to communicate damage potential and to improve methodologies. Few studies, however, have gone beyond the estimation of direct physical impacts by integrating estimates of physical risk (i.e. human or economic losses) with quantified metrics of socioeconomic characteristics of populations. The purpose of this paper is to describe an end-to-end assessment of earthquake risk for mainland Portugal that accounts for physical and social attributes using the Global Earthquake Model (GEM's) suite of risk assessment tools. The results indicate that the potential adverse effects from earthquakes in Portugal are related to interacting conditions, some conditional on geography, some due to the characteristics of the building stock, and some having to do with the social characteristics of populations.
... Efforts to quantify risk have typically considered a limited number of dimensions like the physical dimension (for example, buildings and mortality) and economic aspects of vulnerability, but social vulnerability is poorly understood and difficult to measure. Measuring vulnerability and exposure requires an integrated understanding of components and how these factors combine to contribute to the resilience 27 of communities (Carreño et al. 2007;Burton and Silva 2014). These approaches include methods that use predominantly statistical data gathered from published sources, and approaches that involve surveying local populations. ...
Executive Summary
The year 2015 presents an unparalleled opportunity
to unify UN policy efforts through the convergence of
three landmark UN frameworks: the post-2015 Framework
for Disaster Risk Reduction (March 2015), the Sustainable
Development Goals (September 2015) and the
Climate Change Agreements (December2015). There is
an urgent need to align policy and efface institutional
and financial barriers that obstruct the development
of resilient communities and enable access to relevant
knowledge, equitable participation and sustainable development.
Science and technology have shown that we can reduce
or prevent the impact from disasters, and it is an opportunity
for governments to work together with national
and international policy and science and technology
communities in an effort to reduce disaster risk and
prevent disasters where possible.
The UNISDR Scientific and Technical Advisory Group
(STAG) and partners have been working to embed a
broader approach to disasters and disaster risks which
includes prevention, mitigation, preparedness, response
and recovery. It is no longer sufficient to react
once a disaster has occurred, because even if disasters
are well managed, the impacts on people, society and
the economy can be devastating and felt over the long
term. With disasters increasing in frequency and severity,
the International Panel on Climate Change Assessment
Report 5 (2014) recognised the urgent need to
focus on sustainable development.
Throughout the post-2015 Framework for Disaster Risk
Reduction negotiations and discussions process, the
STAG and the Major Group on Science and Technology
in partnership with Regional and Global Platforms
have identified priority areas for action. This supportive
work has been met with acall to actively strengthen
the relationship between science, technology, innovation,
knowledge development and research to assist in
informing policy making and practice. While there are
many challenges including the complexity of the risks
associated with disasters, terminology that is diverse
and often overlapping, the difficulty in prioritisation of
targets and issues in aligning global, national and local
indicators there is a clear case for the continuing uptake
and integration of science into practice to deliver more
effective policies that truly benefit human societies and
their ecosystem.
While political leadership and community partnerships
are required for the successful implementation
of effective, science-informed initiatives, the research
community has a responsibility to formulate applicable
methodologies and tools that respond to real-word
challenges, but communities that need these have limited
resources to acquire or the capacity to make use
of these. Ensuring that research addresses the full cycle
of prevention, mitigation, preparedness, response and
recovery for those who need it the most is key, while
national and international partnerships and networks
can ensure the dissemination and sharing of good practice
and scientific findings.
To assist this process the STAG has endeavoured,
through the process of writing this report, Science is
Used for Disaster Risk Reduction, and the publications
of case studies1
to create a repository of good practice
on the integration of science2
and technology into disaster
risk reduction.
The repository has gathered applicable case studies
through inviting scientists and professionals of all disciplines
around the world to demonstrate how technology
and science can improve areas such as early warning
systems, safer building practices, more relevant education
and a greater emphasis on communication and
community engagement. We asked partners contributing
case studies to explain the problem they were trying
to address in reducing disaster risk, how they used
science to inform an initiative or policy and whether this
made a difference.
As with their predecessors in 2013, the case studies
included within this report and on the website (http://
www.preventionweb.net/english/professional/networks/public/stag/)
identified some common themes
for success including more inclusive community participation
in the development of science-informed initiatives,
clear leadership and high-level commitment to
implement and sustain interventions in the long term.
The science and technology communities have stated,
through voluntary commitments formulated for the
Third UN World Conference on Disaster Risk Reduction,
a wish to strengthen the dialogue and collaboration
with policy-makers and disaster risk reduction (DRR)
practitioners at local, national, regional and global levels
to identify needs and knowledge gaps, co-design,
co-produce and co-deliver new knowledge, and make
science more readily available and accessible. In order
to achieve this, science and technology communities
and networks will mobilise and strengthen existing capacities
and initiatives to support the implementation
of the post-2015 framework for DRR from the local to
the global scale, and in particular deliver outputs in the
following six areas:
(1) Assessment of the current state of data, scientific
knowledge and technical availability on disaster
risks and resilience (what is known, what is
needed, what are the uncertainties, etc.);
1. STAG publications of case studies “Using Sciences for Disaster Risk Reduction” are available at www.unisdr.org and www.preventionweb.net
2. Science in this context refers to knowledge obtained through systematic observation, recording, testing, evaluation and dissemination and includes physical, geographical,
engineering, environmental, social, health, psychological, management and economic sciences to name but a few.
5
SCIENCE IS USED FOR DISASTER RISK REDUCTION
(2) Synthesis of scientific evidence in a timely, accessible
and policy-relevant manner;
(3) Scientific advice to decision-makers through
close collaboration and dialogue to identify
knowledge needs including at national and local
levels, and review policy options based on scientific
evidence; and
(4) Monitoring and review to ensure that new
and up-to-date scientific information is used in
data collection and monitoring progress towards
disaster risk reduction and resilience building.
In addition, two cross-cutting capabilities need to be
strengthened:
(5) Communication and engagement among policy-makers,
stakeholders in all sectors and in the
science and technology domains themselves to
ensure useful knowledge is identified and needs
are met, and scientists are better equipped to
provide evidence and advice;
(6) Capacity development to ensure that all countries
can produce, have access to and effectively
use scientific information.
Scientific data and information and the tangible application
of technology are critical to the development of
well-informed policies and decisions across the public,
private and voluntary sectors. Much scientific evidence
exists but better links to decision-making in policy and
planning are needed to continuously enhance our ability
to forecast, reduce and respond to disaster risks
thereby building resilience.
Science and technology can assist in identifying a problem,
developing understanding from research, informing
policy and practice and making a difference that can
be objectively demonstrated when evaluated.
The post-2015 Framework for Disaster Risk Reduction
negotiations and process discussions as well as the UNISDR
STAG and the Major Group on Science and Technology
in partnership with the Regional and Global platforms
identified priority areas for action. The following
recommendations are made to help strengthen DRR
policies and practices:
1. Share knowledge for action
Greater priority should be put on sharing and disseminating
scientific information, including technological
advances and translating them into practical methods
that can readily be integrated into policies, regulations
and implementation plans concerning disaster
risk reduction. Cross-disciplinary exchange will identify
interdependencies which can help to identify findings
for application to complex problems. Capacity development
at all levels of society, comprehensive knowledge
management and the involvement of science in public
awareness-raising, media communication, behaviour
change, and education campaigns should be strengthened.
Specific tools should be developed to facilitate science,
technology and innovation outputs to help inform policy-making
and practice. Additionally institutions and
individuals at risk of disasters should be invited to participate
in scientific research (surveys, vulnerability assessments
and other activities ) to collect local knowledge
and create reliable databases should be created
and so that information can be used to tailor initiatives
to the local context while enabling global comparisons
and assessments.
2. Use a multidisciplinary approach to research
An all-hazard, risk-based, problem-solving, results-oriented
approach should be used in DRR research to address
the multifactorial and interdependent nature of
the disaster risk chain and to identify relevant solutions
and optimize the use of resources. Synergies with the
climate change and sustainable development agenda
should continue to be articulated and leveraged. This
requires collaboration and communication across the
scientific disciplines and technical fields, and with all
stakeholders including representatives of governmental
institutions, communities of policy making, scientific
and technical specialists, the technology sector and
members of the communities at risk to guide scientific
research, set research agendas and support scientific
education and training. The potential contribution of
affected and vulnerable communities in generating research
questions, and in performing research collaboratively
or independently, should be valued and facilitated.
3. Build systems resilience through local, national,
regional and international partnerships
Science and technology communities wish to strengthen
the dialogue and collaboration with policy-makers
and DRR practitioners at local, national, regional and
global levels to identify needs and knowledge gaps,
co-design, co-produce and co-deliver new knowledge,
and make science more readily available and accessible.
To this end, science and technology communities and
networks will mobilise and strengthen existing capacities
and initiatives, including national platforms/bodies,
to support the implementation of the post-2015 framework
for DRR from the local to the global scale, and in
particular deliver outputs.
The objective of the holistic risk assessment is to evaluate risk from a comprehensive perspective, integrating physical risk, or potential physical damage, linked to the happening of hazard events and socio-economic and environmental factors, non-hazard-dependent. This approach seeks to capture how these latter have an incidence on physical risk, exacerbating the negative impacts of a dangerous event, as well as affecting the capacity of the society to anticipate or resist or to respond and recover from adverse impacts. This article presents the results of the holistic evaluation obtained at the subnational level in Colombia in the framework of the Risk Atlas of Colombia of the National Unit for Disaster Risk Management (UNGRD, its Spanish acronym). The evaluation was performed using the probabilistic physical risk results derived from a multi-hazard risk assessment, with 16 socio-economic indicators available for the 1123 municipalities of Colombia. These results are relevant for comparison purposes and are also useful to identify the risk drivers associated not only with the current risk conditions but also those shaping future risk.
