Cabot Institute, University of Bristol
Cabot Institute, Royal Fort House, University of Bristol,
Bristol, BS8 1UJ, United Kingdom
http://www.bris.ac.uk/cabot/

Outline
The University of Bristol has been at the forefront of natural disaster risk and mitigation researchfor over 20 years. With the inception of BRISK (Bristol Environmental Risk Centre) in 2009, which
was subsequently folded into the Cabot Institute in 2012, the University made a commitment tosupporting novel, multidisciplinary research that sought to tackle the risks and challenges of the
21st century. The Cabot Institute realises a vision for a new generation of interdisciplinary, scienceto-practice focussed scholars and fosters engaged research with end-users. The core natural
disaster research areas cover hazard and risk related to volcanic eruptions, earthquakes,
landslides, and floods using the most advanced computational/statistical tools for assessing andcommunicating environmental risk. The Cabot experts advise the UK government about hazards,
such as volcanic ash, and work with agencies, such as the World Bank and the UK Met Office, toreduce disaster risk. The concepts of risk, uncertainty, and resilience underpin all of research
themes and remain central aspects of the Cabot vision, strategy, and expertise portfolio.
The Cabot Institute involves academics of international
standing from the Schools of Earth Sciences,
Geographical Sciences, Experimental Psychology, Policy
Studies, Maths, Engineering Maths, Civil Engineering,Computing, and Sociology, Politics and International
Studies, who undertake research in the fields of risk &uncertainty and natural hazards.
 Volcanic risk and ash cloud: The volcanologicalresearch group has established a high international
reputation, and leads the Global Volcano Model(GVM) to create a sustainable, accessible information
platform on volcanic hazard and risk. It has developed
a strong relationship with the Volcanic Ash Advisory
Centre (e.g. 2010-2011 Icelandic eruptions).
Cabot Core Research Areas Seismic risk : The seismic research group has
focussed upon 1) effective delivery of infrastructure
resilience subject to cascading multi-hazards, and 2) systems’ responses to earthquaketriggered hazards. The group is also specialised in monitoring and evaluating hazard due toinduced seismicity (e.g. hydraulic fracking and carbon capture and storage).
 Hydrometeorological risk: The flood research group has been internationally recognised for: 1)
the development of an efficient hydrodynamic model for floodplain inundation simulation overcomplex topography (LISFLOOD-FP), and 2) the impact assessment of major flood events by
taking into account various sources of uncertainty. LISFLOOD-FP is used by the European Joint
Research Centre, the Environment Agency, and Defra.
 Landslide risk: The landslide research group has developed sophisticated numerical models ofphysical processes of landslides, including the Combined Hydrology And slope Stability Model(CHASM) that dynamically simulates rainfall-triggered landslides, and has applied them topractical situations (e.g. Caribbean islands) to develop a new cross-disciplinary platform formeasuring the effectiveness of landslide mitigation in vulnerable urban communities.
 Other related expertise in hazard areas: climate change, including impact on meteorologicalphenomena and sea level rise, drought, disease and epidemics, food security including parasite
outbreaks, and technology.

Research Achievements and Challenges
The University has recently achieved remarkable success in the 2014 UK Research Excellence
Framework (REF) assessments, coming 1st overall in Geography, 2nd overall in Sociology, 2nd
overall in Earth Sciences, 4th overall in Mathematical Sciences, and 4th overall for Computer
Sciences and Informatics. A vibrant risk community resides within each of these areas, contributing
world-class research in the Cabot Institute. In addition to this academic capacity, the Cabot
researchers have consistently engaged with the government, industry (engineering consultancy
and insurance/reinsurance), and the public to transform research into meaningful impact.

Recent Research Achievements

Method development• Consortium on Risk in t he Environment: Diagn ostics, Integration, Benchmarking, Learning andElicitation (CREDIBLE): A £2M project to: 1) introduce statistical techniques to move uncertainty
out of the margin for error, 2) help modellers assess less quantifiable uncertainty, and 3)
improve risk visualisation and communication. Methods are tested in various case studies forflood, windstorm, landslide, earthquake, drought, lahar, and ash dispersal.
Monitoring risk
• Strengthening Resilien ce in Vo lcanic Areas (STREVA): An adaptable risk assessment
framework using satellite data for over 500 volcanoes to establish statistical evidence of theireruption potential based on deformation. This leads to a forecast system for all volcanoes,
including those that are remote and inaccessible.
• Volcanic Un rest in Euro pe and Latin Am erica (VUELCO): The project dissects the science ofmonitoring data and creates global strategies for 1) enhanced monitoring capacity and value, 2)
mechanistic data interpretation, and 3) identification of reliable eruption precursors, all fromgeophysical, geochemical, and geodetic fingerprints of unrest episodes.
• RIFTVOLC: A project in the main Ethiopian Rift improves knowledge of past activities,
establishes baseline monitoring of current states of apparent unrest, and develops reliable
assessments of eruptive potential.
• First indep endent UK research
to m onitor frackin g: A programme to conduct real-timemonitoring of groundwater, regional air quality, seismicity, and ground movements before,
during, and after fracking. The results will support peer-reviewed science on the environmental
effects of shale gas operations in the UK.
Assessing risk
• LISFLOOD-FP: A computationally efficient 2D hydrodynamic model can simulate grids up to 106
cells for dynamic flood events utilising terrain information from remote sensing, and simulate thedynamic propagation of flood waves over fluvial, coastal, and estuarine floodplains. It has majoradvantages in quantifying the uncertainty of hazard/risk predictions.
• Cascading Risk and Uncertainty assessment of earthquake Shaking and Tsunami (CRUST): An
integrated methodology for cascading hazards is developed by: 1) characterising earthquake
slips for future mega-thrust earthquakes, 2) modelling a sequence of mainshock-aftershock
records, and 3) modelling tsunami inundation and damage.
• Seismic loss model for urban city : A probabilistic framework is developed by incorporating: 1)
seismic hazard analysis, 2) realistic spatial correlation of ground motions, 3) seismic
vulnerability model, and 4) seismic loss estimation. The model outputs promote decision-making
related to seismic risk management, including retrofitting and earthquake insurance.
Managing risk
• Management of Slope Stability in Communities (MOSSAIC): A flexible blueprint for landslide
risk reduction is developed to understand the physical risk drivers and reduce the landslide
hazard. It seeks low-cost solutions suitable for local communities, and encourages agovernment-community partnership for ongoing management of slope stability.
• Managing the Risks, I mpacts and Uncertainties of droughts and water Scarcity (MARIUS): A£3.5M project to develop improved models and methods to mitigate the impact of drought onwater quality, agriculture, biodiversity, and the economy. The local impact and the role ofinstitutions, regulation and markets in drought management are investigated using scenario
modelling, case studies at household to national scales, and stakeholder engagement.

Research Challenges

Emerging research areas• Bridging th e hazard-risk-m anagement gap : The gap between hazard, risk, and risk
management research is pervasive and the Cabot Institute is uniquely placed to carve a nicheat the interface. Cabot plays a catalyst role to fuse natural hazard expertise (science) and
impact/risk management expertise (engineering and social science) to develop an integrated,cross-disciplinary science-into-practice framework for dealing with catastrophic natural disasters(e.g. VUELCO and MOSSAIC).
• Disaster risk reduction : The 2005-2015 Hyogo Framework for Action called for investments inemergency preparedness, climate change adaptation, and resilience to environmental shocks.
Cabot has a significant skillset to contribute, particularly through the integration of natural andsocial sciences.
• Integrated modelling of hazards: The non-stationarity of our environment forces us to move fromempirical (correlation) approaches to mechanistic models (based on process understanding).
Cabot has an opportunity to pool its mechanistic modelling expertise and to lead the research
for integrated empirical-mechanistic hazard assessment.
• Psychology of evidence-based decision-m aking: Public's understanding of science and why
people often embrace beliefs that are sharply at odds with the scientific evidence are criticalfactors in avoiding misinformation and promoting the acceptance of scientific advice on natural
hazards and climate change.
• Risk, society and weather extrem es: Society has the capacity to both drive and mitigate risk to
extreme weather. Collaborations across engineering, climate, behaviour and planning
disciplines have potential to investigate the interaction between society and the environment.
• Risk research at m ultiple decision scales : Much risk research is conducted at a single decisionscale and often strictly top-down or bottom-up in nature. Research with the World Bank has
brokered risk approaches between scales and is now progressing with the Global Network for
Disaster Reduction.
• Risk and fo od supply chains : Natural hazards and climate change pose severe risk to foodsupply and security. In a Defra project, Cabot’s mapping, climate, natural hazard, and foodsecurity experts collaborate to explore risk to supply chains.
Research capacity building and organisational partnershipTo fully exploit emerging opportunities, Cabot needs to address gaps in expertise or areas ofexpertise that have not been fully integrated into natural disaster risk research.
• Developing underpinning expertise in mathematical sciences and Big Data, by building closeinternal links to the Heilbronn Institute and the Bristol Research Initiative for the Dynamic Global
Environment (BRIDGE).
• Developing stronger relationships with the GW4 institutions (Bristol, Bath, Cardiff, and Exeter),e.g. in the fields of experimental psychology.
• Building on existing links with the energy/insurance/reinsurance industry, government
departments and agencies, the city of Bristol (2015 European Green Capital), and NGOs.
• Adding capacity/linking more closely with the international disaster management researchcommunity in Japan (Kyoto), New Zealand, the US, and Europe, in addition to developing
nations.
Maximising the research impact• Create a hazard and risk toolkit (including hazard process modelling, sensitivity analysis,
uncertainty assessment, and visualisation/hazard-mapping tools; e.g. LISFLOOD-FP and
CREDIBLE) publicly accessible for widespread use in industry/government.
• Continue to deliver the Cabot Summer School which attracts 25-30 professional delegates
annually.
• Be increasingly proactive (and responsive) to public outreach and risk communication
opportunities, focussing on evidence-based dialogue, in close collaboration with the Science
Media Centre and risk perception experts.
• Ensure natural hazard, risk, and uncertainty expertise is accessible to the Cabot Corporate
Club.

Research Vision
Effective disaster risk reduction and management (DRR and DRM) require further research infilling current major gaps. Three critical themes are identified: 1) from science/ social science tohazard (understanding hazards), 2) from hazard to lo ss, and 3) from assessm ent to de cisionmaking. Theme 1 achieves better prediction of low-frequency, high-impact hazards, multi-hazards,
scales and cascades of hazards, and complex interactions including climate change impact.
Theme 2 aims to extend the risk assessment not only for direct and tangible loss but also forindirect and intangible loss, including social impact; Big Data can help elucidate such indirect loss.
Theme 3 is focussed upon the challenging issues by addressing how risk is it perceived andculturally contingent, what are the appropriate options and what is the evidence, and how is therisk assessment conveyed and how are end-users engaged.
Gaps in our understanding of hazards: from science to hazard and mitigation• Uncertainty is ubiquitous in environmental science, due the complexity of the Earth system,
limited understanding of its components, and a paucity of observations at relevant spatial andtemporal scales. Moreover, mitigating actions against natural hazards are complicated byimperfect knowledge of future changes. Thus it is crucial that physical research in such complex
and changing environments is integrated with rigorous statistical analyses, both to improveknowledge and understanding of the physical processes and underlying uncertainty, but also to
inform robust decision-making and policy formulation. The application areas/topics include
problems at the interface between natural and social sciences: 1) multi-hazard and correlatedrisk, with probabilistically likely co-occurring phenomena (i.e. tidal surges, strong winds, andlightning associated with some storms), and 2) cascaded hazards through data and modelling
chains (e.g. flood risk to emergency planning and decision support) that are particularly relevantto the social science issues of implementing mitigation methodologies to reduce future
vulnerabilities.
Gaps between hazard and loss: assessment and uncertainty with Big Data
• Understanding the linkages and limitations between data rich (big and broad data) and data
sparse environments and situations is critically important. Essential to this is translatingknowledge, process understanding, and predictive capability from systems that are understoodwell to those that inherently have limited information and are resource limited. This will facilitate
the exploration of the challenges of predicting and understanding extreme behaviour via dataextrapolation methodologies for a variety of natural hazards.
• Disasters are not only devastating as they occur and in their immediate aftermath with respect
to loss of life and destruction of infrastructure. They can lead to social upheaval anddisenfranchisement and disproportionately affect the poorest members of the population.
Disruption of supply chains impact the global economy and disruption of food distribution
networks can prolong the impact of disasters and extend their global impact. Crucially, Big Data
approaches are essential to interrogating the far-flung and sometimes non-intuitive
consequences of disasters.
Gaps between assessment and decision-making• Three components are missing in the delivery of DRR research and DRM practice on the
ground: science-base, community-base, and evidence-base. Specifically required are: 1)
methods for risk analysis and decision support in developing countries, and 2) focus on action
into knowle dge (finding out what works on the ground) to facilitate delivery within local
knowledge in participation approaches. Policy-makers and funders require evidence forinvestment so that they can see what works and replicate it. Innovative science-based andcommunity-based approaches can be powerful policy-changers.
• A critical aspect for scientists engaged in hazard assessment is to communicate the nature ofhazards and their probability of occurrence in a manner that is useful and understandable for
emergency managers and policy makers. The research has highlighted a need to further
investigate the role of different stakeholders in emergency planning and crisis management,
their mutual expectations, the social context of at-risk communities, the legal framework within
which advising scientists operate, and the benefits of visualisation and participation approaches

to a range of actors. Therefore, research should be conducted in a framework that
amalgamates various disciplines, such as natural/social sciences, emergency management,
computer visualisation techniques, and the law.
Broader Perspectives
Bristol University and the Cabot Institute play crucial roles within the UKDC-Resilience (Bristol,
Durham, King’s College, and UCL), which is an alliance of the leading UK centres of excellence fordisaster risk and resilience research and learning. A collective perspective of the UKDC-Resilienceon future disaster science agendas is illustrated below by identifying five key research priorities
and three novel mechanisms for better connecting science to policy and society. Contemporary
science is called to be increasingly impact-oriented, to embrace co-design or co-production
through engagement with stakeholders beyond the science community, and to be transdisciplinary.
Priorities

Participatory
Visualisation

Organisational
Partnerships

Integrated Science
Training

Extremes
CascadesRelativity
Uncertainty
Balance

UKCD-Resilience Research Vision
The UCKCD-Resilience calls for integrated science organised around five research and threecapacity-building priorities. Research and capacity-building are envisioned to cross-cut and offer avision of academic engagement in disaster studies that is current, grounded, and reflexive.
• Extremes: Extremes exist at both ends of a frequency distribution, highlighting rare/large
events and common/small events. Future research should address integrated risk management
approaches that cover a range of small to large events.
• Cascades: Disaster events need to be conceptualised as cascades, involving
phased/concurrent multi-hazard interactions. Applied disaster research on economic impact
requires empirical/theoretical work to take into account systemic and indirect disaster impact.
• Relativity: Time, space, and scale are relative concepts that shape the conditions throughwhich physical, social, and combined social-environmental systems move, and potentiallycascade. Science needs to work to better understand how social-environmental systems learn
and change behaviour over time, space, and scale.
• Uncertainty: Uncertainty cannot be taken out of science but it can be made more transparent.
This requires collaboration between modellers, social scientists, and research users in science
design and implementation.
• Balance: Improving decision-making to strike the best possible balance between risk reduction
and risk response incrementally adjusts existing social-environmental systems (e.g. technology
and culture). This is an agenda for enhancing critical reflexivity in decision-making at all scales.
• Participatory Visualisation : A wide range of modelling and scenario techniques increasinglyoffers new opportunities for engaging stakeholders, including the public, to better understandunderlying natural and social properties shaping disaster risk and loss. The next step in thisagenda is to internationalise knowledge sharing.
• Organisational Partnerships: The organisational level support is necessary to overcome brain
drain effects of highly qualified/trained individuals of key agencies in the UK government andoverseas. This is important for transdisciplinarity that calls for far more embedded andinterconnected science-policy relationships.
• Integrated Science Training : Training a new generation of integrated disaster scientists
requires a reorientation in support for postgraduate learning. Any initiative needs to build in not
only traditional PhD but also professional training and reach out to integrate natural as well associal science into the humanitarian sector, civil defence, and development sectors.