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Earth's Future An Integrative Research Framework to Unravel the Interplay of Natural Hazards and Vulnerabilities


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Climate change, globalization, urbanization, social isolation, and increased interconnectedness between physical, human, and technological systems pose major challenges to disaster risk reduction (DRR). Subsequently, economic losses caused by natural hazards are increasing in many regions of the world, despite scientific progress, persistent policy action, and international cooperation. We argue that these dramatic figures call for novel scientific approaches and new types of data collection to integrate the two main approaches that still dominate the science underpinning DRR: the hazard paradigm and the vulnerability paradigm. Building from these two approaches, here we propose a research framework that specifies the scope of enquiry, concepts, and general relations among phenomena. We then discuss the essential steps to advance systematic empirical research and evidence‐based DRR policy action.
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Earth’s Future
An Integrative Research Framework to Unravel the Interplay
of Natural Hazards and Vulnerabilities
Giuliano Di Baldassarre1,2,3 , Daniel Nohrstedt1,4, Johanna Mård1,2 , Steffi Burchardt1,2 ,
Cecilia Albin1,5,SaraBondesson
1,4,6, Korbinian Breinl1,2 , Frances M. Deegan1,2 , Diana Fuentes1,2,
Marc Girons Lopez1,7 , Mikael Granberg1,8, Lars Nyberg1,8, Monika Rydstedt Nyman1,8,
Emma Rhodes1,2, Valentin Troll1,2, Stephanie Young1,6 , Colin Walch1,5,9, and Charles F. Parker1,4
1Centre of Natural Hazards and Disaster Science (CNDS), Sweden, 2Department of Earth Sciences, Uppsala University,
Uppsala, Sweden, 3IHE Delft Institute for Water Education, Delft, The Netherlands, 4Department of Government,
Uppsala University, Uppsala, Sweden, 5Department of Peace and Conflict Research, Uppsala University, Uppsala,
Sweden, 6Swedish Defence University, Stockholm, Sweden, 7Department of Geography, University of Zurich,
Switzerland, 8Centre for Climate and Safety, Karlstad University, Karlstad, Sweden, 9Department of Political Science, UC
Berkeley, Berkeley, CA, USA
Abstract Climate change, globalization, urbanization, social isolation, and increased interconnect-
edness between physical, human, and technological systems pose major challenges to disaster risk reduc-
tion (DRR). Subsequently, economic losses caused by natural hazards are increasing in many regions of the
world, despite scientific progress, persistent policy action, and international cooperation. We argue that
these dramatic figures call for novel scientific approaches and new types of data collection to integrate
the two main approaches that still dominate the science underpinning DRR: the hazard paradigm and the
vulnerability paradigm. Building from these two approaches, here we propose a research framework that
specifies the scope of enquiry, concepts, and general relations among phenomena. We then discuss the
essential steps to advance systematic empirical research and evidence-based DRR policy action.
Plain Language Summary The recent deadly earthquake in Iran-Iraq has been yet another
reminder of the topicality of natural hazards, and it has come just after an unprecedented series of catas-
trophic events, including the extensive flooding in South Asia and the string of devastating hurricanes
in the Americas. He we identify three main puzzles in the nexus of natural hazards and vulnerabilities,
and demonstrate how novel approaches are needed to solve them with reference to a flood risk example.
Specifically, we show how a new research framework can guide systematic data collections to advance
the fundamental understanding of socionatural interactions, which is an essential step to improve the
development of policies for disaster risk reduction.
1. Premise
Climate change, globalization, urbanization, social isolation, and increased interconnectedness between
physical, human, and technological systems (Cutteret al., 2015) pose major challenges to disaster risk reduc-
tion (DRR). Subsequently, economic losses caused by natural hazards are increasing in many regions of the
world (Figure 1), despite scientific progress, persistent policy action, and international cooperation (United
Nations [UN], 2015).
We argue that these dramatic figures call for novel scientific approaches and new types of data collec-
tion to integrate the two main approaches that still dominate the science underpinning DRR: the hazard
paradigm and the vulnerability paradigm (Blöschl et al., 2013). Building from these two approaches, here we
propose a research framework that specifies the scope of enquiry, concepts, and general relations among
phenomena (Ostrom, 2009). We then discuss the essential steps to advance systematic empirical research
and evidence-based DRR policy action.
Special Section:
Avoiding Disasters:
Strengthening Societal
Resilience to Natural Hazards
Key Points:
• Economic losses caused by natural
hazards are increasing in many
regions of the world
• We propose an integrative research
framework that specifies the scope of
enquiry, concepts, and general
relations among phenomena
• We identify three empirical puzzles as
examples of crucial areas where more
knowledge is needed
Correspondence to:
G. Di Baldassarre, giuliano.dibaldassarre@
Di Baldassarre, G., Nohrstedt, D., Mård,
J., Burchardt, S., Albin, C., Bondesson, S.,
Breinl, K., Deegan, F. M., Fuentes, D.,
Lopez, M. G., Granberg, M., Nyberg, L.,
Nyman, M. R., Rhodes, E., Troll, V.,
Young, S., Walch, C., & Parker, C. F.
(2018). An Integrative Research
Framework to Unravel the Interplay of
Natural Hazards and Vulnerabilities,
Earth’s Future,6.
Received 21 NOV 2017
Accepted 18 FEB 2018
Accepted article online 22 FEB 2018
© 2018 The Authors.
This is an open access article under
the terms of the Creative Commons
License, which permits use and distri-
bution in any medium, provided the
original work is properly cited, the use
is non-commercial and no modifica-
tions or adaptations are made.
Earth’s Future 10.1002/2017EF000764
1966-1975 1976-1985 1986-1995 1996-2005 2006-2015
Economic losses (billion USD)
Storm s
Figure 1. Global trends of economic losses (billion USD) over the past decades.
Data from EM-DAT: The Emergency Events Database— Université catholique de
Louvain (UCL)— CRED, D. Guha-Sapir,, Brussels, Belgium.
The hazard paradigm emphasizes the
study of the natural processes that
trigger disasters. It typically suggests
solutions to reduce their impacts on
exposed people, assets, and critical
infrastructures (Blöschl et al., 2013).
This paradigm underpins quanti-
tative assessments of disaster risk,
broadly defined as a combination of
the probability of extreme events and
their potential adverse consequences.
When estimating the effects of struc-
tural measures to reduce hazard levels,
this paradigm often overlooks societal
responses that can produce unin-
tended consequences. For instance, the safe-development paradox (Burby, 2006) shows that lowering
hazard levels can paradoxically lead to increased risks, as doing so can reduce risk awareness and promote
urban expansion in disaster-prone areas (Kates et al., 2006). In flood risk management, for example, it has
been shown that raising levees can increase the potential adverse consequences of flooding (Di Baldas-
sarre et al., 2015). Catastrophic losses and fatalities in New Orleans (2005), Brisbane (2011), and Houston
(2017) are related to the urbanization of floodplain areas facilitated by the presence of structural flood
The vulnerability paradigm focuses on social and technical factors that shape vulnerability. In this paradigm,
DRR measures target the conditions that make communities more vulnerable, for instance poverty or fragile
infrastructures (Wisner et al., 2003). In this view, exposure to disaster risk is a product of power imbalances
and inequality, affecting predominantly marginalized communities (Gaillard & Mercer, 2013). Proponents
of the vulnerability paradigm avoid hazard predictions, which are associated with known limitations espe-
cially in relation to multihazards with cascading effects or disasters. Examples include the 2011 triple disaster
in Japan, that is, earthquake followed by tsunami and meltdown at the Fukushima power plant (Pescaroli
& Alexander, 2015), and the 1953 Tangiwai rail disaster in New Zealand, that is, collapse of an instable
crater lake wall on Mount Ruapehu led to a mudflow (lahar), which took out a rail bridge and led to a
fatal train derailing (Johnston et al., 2000). Yet, the vulnerability paradigm often overlooks that social and
technical conditions that make individuals, communities and infrastructures vulnerable vary across dif-
ferent types of natural hazards. As a result, this paradigm cannot explain unexpected successes, such as
long-term adaptation processes associated with repeated events. For example, while Bangladesh is one of
the poorest countries in the world with weak infrastructures and fragile political institutions, flood resilience
has been developed through a variety of formal and informal measures, including temporary migration.
As a result, flood fatalities have been significantly reduced in Bangladesh over the past 40years (Kreibich
et al., 2017).
2. Key Puzzles
Here we identify three empirical puzzles as examples of crucial areas where more fundamental knowledge
is needed to advance evidence-based DRR.
2.1. Variability in Learning
The experience of Bangladesh and other unexpected successes (Kreibich et al., 2017) suggest that repeated
events, such as floods or cyclones, can promote higher levels of preparedness, or trigger policy change,
thereby decreasing fatalities and increasing resilience. Understanding these learning dynamics is important
if we are to improve the impact of international cooperative efforts, such as the UN International Strategy
for DRR (UN, 2015).
Earth’s Future 10.1002/2017EF000764
2.2. Diminishing Returns and Unintended Consequences
Effective DRR is often attributed to multistakeholder collaboration, functioning institutions, adaptation, or
implementation of risk reduction measures. However, these qualities are difficult to obtain in practice and
they can produce unintended effects, such as the safe-development paradox discussed above. These qual-
ities can also generate diminishing returns where efforts to enhance collaboration, for example, do not
enhance performance or even lead to negative consequences (Pierce & Aguinis, 2013). Calkin et al. (2015),
for instance, have argued that the current wildfire management strategy in the United States can paradoxi-
cally increase the risk of future wildfires. Thus, there is a need to understand why these qualities for efficient
DRR do not always generate desired outcomes.
2.3. Increase the Visibility of Prevention
Much knowledge of DRR builds from dystopian failure cases, such as hurricane Katrina, where societies have
failed to mitigate hazards and risks. Yet, although failure is a potential source of lesson-drawing, history also
offers success stories that deserve more rigorous assessment (Adger et al., 2005). Potential cases include
positive experiences, such as the empirical evidence of flood risk reduction in multiple sites around the
world presented by Kreibich et al. (2017).
3. Elements of a New Framework
We argue that one essential step to further strengthen evidence-based DRR policy-making, and to solve
the three puzzles identified above, is to advance the understanding of the feedback mechanisms between
natural and social processes by integrating the hazard and vulnerability paradigms. We therefore propose
a research framework (Figure 2a) that builds from social-ecological systems (Adger et al., 2005), community
resilience (Cutter et al., 2008), climate change adaptation (Birkmann & von Teichman, 2010), and sociohy-
drology (Sivapalan et al., 2012).
The integrative framework specifies how the impacts and perceptions of natural hazards influence
sociotechnical vulnerabilities, governance, and institutions, while at the same time social behavior, techni-
cal measures, and policy interventions alter the frequency, magnitude, and spatial distribution of natural
hazards (Figure 2a). Reciprocal effects at the local scale are also influenced by global drivers. Climate and
environmental change can alter the frequency and severity of extreme weather events, while socioeco-
nomic trends (including population growth, urbanization, and interdependent infrastructures) can increase
exposure to natural hazards.
4. Flood Risk Example
To illustrate the underlying logic of the proposed framework, and show how it can help guide empirical
and modeling studies to address the three puzzles above, we present an example application in a flood risk
Figure 2b depicts an explanatory model of human-flood interactions, with positive and negative feedback
mechanisms between a specific natural hazard, that is, flooding, and elements of vulnerabilities, that is,
exposure, risk awareness, wealth, and structural protection measures (levees). This model can be seen as
a specification of the more general framework depicted in Figure 2a. Technical, social, demographic, eco-
nomic, and natural factors influence each other and gradually change overtime, while going through more
abrupt change in the wake of flood events (Figure 2b). The model uses change in risk awareness, among
policymakers and communities, as a primary mechanism to explain the dynamics of risk. Influenced by the
theory of availability heuristics (Tversky & Kahneman, 1973), the model posits that awareness is enhanced
immediately after the occurrence of catastrophic events, but then decays overtime (Di Baldassarre et al.,
This model of human-flood interactions can help address the three puzzles as follows.
4.1. Variability in Learning
Adaptation dynamics, such as the one manifested by decreasing flood damage in Bangladesh, are explained
by the model as an increase in risk awareness generated by frequent events, which tends to decrease expo-
sure to flooding, and therefore losses (Figure 2b). Yet, there is evidence in other contexts that frequent
Earth’s Future 10.1002/2017EF000764
Figure 2. (a) Analytical framework focusing on the dynamics produced by the (local) interplay of natural hazards and vulnerabilities
under (global) environmental change and socioeconomic trends. (b) Flood risk example at the local scale: explanatory model based on
Di Baldassarre et al. (2013) emphasizing hypothetical feedbacks between five key variables that are assumed to influence each other and
change gradually overtime (thin arrows), while being abruptly altered by the sudden occurrence of flooding (thick arrows). Dashed
arrows indicate control mechanisms: wealth influences how flood exposure can potentially change overtime and also determines
whether levees can be built or not, while levees reduce the frequency of flooding. (c) Hypothetical wealth trajectories in relation to
disaster occurrences: bouncing back, forward or collapsing after a major disaster. (d) Ranges of availability of systematic times eries
across decades in the study of flood risk dynamics. The fuzzy classification highlights the limited availability of data to carry out empirical
studies about socionatural interactions.
events can also gradually generate damage (Moftakhari et al., 2017), which erodes community resilience
and sustains a negative spiral toward significant loss of social and economic capital, as seen for example in
parts of Southern Africa (Rockström, 2003). The integrative framework can help specify competing hypothe-
ses, alternative to the one depicted in Figure 2b, explaining why some communities learn from frequent and
severe hazards while others do not.
4.2. Diminishing Returns and Unintended Consequences
Negative effects of risk reduction measures, such as the safe-development paradox, are explained by the
model as a decrease of risk awareness produced by the prevention of frequent flooding caused by higher
levees, which contributes to increasing exposure, and therefore higher losses (Figure 2b). This explanatory
model also suggests the need of empirical studies about change in risk awareness across decades. Unfor-
tunately, systematic monitoring of these variables, that is, longitudinal studies and comparable surveys of
risk perception, is almost never available (Figure 2d).
4.3. Increase the Visibility of Prevention
Our framework can also provide guidance to identify, and systematically investigate, DRR bright spots
emphasizing the social and natural factors that underlay different recovery trajectories (Figure 2c). After
the occurrence of a major disaster, will the socionatural system bounce back or even forward? Or will
it collapse? Viglione et al. (2014), for example, used an explanatory model similar to the one depicted
in Figure 2b to uncover the socionatural conditions in which different trajectories are produced. The
outcomes highlighted the major role of attitudes toward risk, trust in DRR authorities, and the capacity to
maintain high levels of risk awareness.
To advance systematic empirical research, we propose the following essential steps. The integrative frame-
work, which emphasizes the interplay of natural hazards and vulnerabilities (Figure 2a), can be used to
Earth’s Future 10.1002/2017EF000764
derive one or more explanatory models (as alternative hypotheses) about the way in which social, tech-
nical, and natural variables influence each other (Figure 2b). These models can then be tested by evaluating
their capability to capture emerging tendencies, such as adaptation dynamics or safe-development para-
doxes, or used to explore the socionatural factors triggering different trajectories (Figure 2c). Lastly, these
explanatory models can guide empirical studies as they can inform about the type of data we need to col-
lect (Figure 2d) to better support evidence-based DRR. Empirical studies will in turn allow evaluating the
explanatory power of alternative models. While the application example presented here is about flood risk,
the framework can also specify the scope of enquiry and guide data collections for other natural hazards.
5. Future Directions and Priorities
Rethinking the foundations of DRR research brings significant analytical challenges. Our framework rec-
ognizes the importance of systematic monitoring across decades to get new insights about the tempo-
ral development and effectiveness of alternative actions. Valid outcome measures are urgently needed to
assess DRR performance overtime and across contexts. Combining information about the interaction of
social and natural systems opens new exciting avenues to assess whether and how diverse forms of com-
munity organization and behavior give rise to different outcomes.
Over the past decades, DRR research and practice has benefitted from exploiting systematic information
about physical processes, population census, economic data, and disaster losses. Yet, to explore both unin-
tended consequences and unexpected successes, we need to make better use of other sources of data to
track feedback mechanisms between natural hazards and sociotechnical vulnerabilities overtime. Flood risk
is merely one example where more systematic time series on risk perception, trust in authorities, awareness,
and preparedness are urgently needed.
The proposed framework integrates the current paradigms to solve empirical puzzles in DRR, and provide
guidance for empirical studies to unravel the nexus between physical, human, and technological systems.
These are critical steps to generate deeper knowledge about the interplay between these interconnected
systems, which is essential for making wise decisions about DRR.
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Over the last two decades wildfire activity, damage, and management cost within the US have increased substantially. These increases have been associated with a number of factors including climate change and fuel accumulation due to a century of active fire suppression. The increased fire activity has occurred during a time of significant ex-urban development of the Wildland Urban Interface (WUI) along with increased demand on water resources originating on forested landscapes. These increased demands have put substantial pressure on federal agencies charged with wildfire management to continue and expand the century old policy of aggressive wildfire suppression. However, aggressive wildfire suppression is one of the major factors that drive the increased extent, intensity, and damage associated with the small number of large wildfires that are unable to be suppressed. In this paper we discuss the positive feedback loops that lead to demands for increasing suppression response while simultaneously increasing wildfire risk in the future. Despite a wealth of scientific research that demonstrates the limitations of the current management paradigm pressure to maintain the existing system are well entrenched and driven by the existing social systems that have evolved under our current management practice. Interestingly, US federal wildland fire policy provides considerable discretion for managers to pursue a range of management objectives; however, societal expectations and existing management incentive structures result in policy implementation that is straining the resilience of fire adapted ecosystems and the communities that reside in and adjacent to them.
This chapter reviews methods of flood and drought risk management and emerging approaches of how to prioritize the implementation of these methods in a changing world. Prioritization can follow two paths. The top-down approach is based on climate projections and has an economic motivation; recent focus has been on quantifying the uncertainty of future hazard probabilities. The bottom-up approach is vulnerability or resilience centered and has a social motivation; recent focus has been on exploring the full range of possibilities from a local risk management perspective. The bottom-up approach is less dependent on climate projections and may be more suitable for dealing with surprising high-impact (Black Swan) events. It is suggested that the primary approach to hydrological risk management in a changing world should be a bottom-up approach, which may be complemented by top-down (scenario) approaches.
The risk coping culture of a community plays a major role in the development of urban floodplains. In this paper we analyse, in a conceptual way, the interplay of community risk coping culture, flooding damage and economic growth. We particularly focus on three aspects: (i) collective memory, i.e., the capacity of the community to keep risk awareness high; (ii) risk-taking attitude, i.e., the amount of risk the community is collectively willing to be exposed to; and (iii) trust of the community in risk reduction measures. To this end, we use a dynamic model that represents the feedback between the hydrological and social system components. Model results indicate that, on the one hand, by under perceiving the risk of flooding (because of short collective memory and too much trust in flood protection structures) in combination with a high risk-taking attitude, community development is severely limited because of high damages caused by flooding. On the other hand, overestimation of risk (long memory and lack of trust in flood protection structures) leads to lost economic opportunities and recession. There are many scenarios of favourable development resulting from a trade-off between collective memory and trust in risk reduction measures combined with a low to moderate risk-taking attitude. Interestingly, the model gives rise to situations in which the development of the community in the floodplain is path dependent, i.e., the history of flooding may lead to community growth or recession.