(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 time series 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.

Contexts in source publication

Context 1

... 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 ), community resilience ( Cutter et al., 2008), climate change adaptation (Birkmann & von Teichman, 2010), and sociohydrology ( Sivapalan et al., 2012). ...

Context 2

... integrative framework specifies how the impacts and perceptions of natural hazards influence sociotechnical vulnerabilities, governance, and institutions, while at the same time social behavior, technical 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. ...

Context 3

... 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 setting. 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. ...

Context 4

... 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, economic, and natural factors influence each other and gradually change overtime, while going through more abrupt change in the wake of flood events (Figure 2b). ...

Context 5

... model can be seen as a specification of the more general framework depicted in Figure 2a. Technical, social, demographic, economic, 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. ...

Context 6

... 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 exposure to flooding, and therefore losses (Figure 2b). Yet, there is evidence in other contexts that frequent (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). ...

Context 7

... 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 hypotheses, alternative to the one depicted in Figure 2b, explaining why some communities learn from frequent and severe hazards while others do not. ...

Context 8

... 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. ...

Context 9

... explanatory model also suggests the need of empirical studies about change in risk awareness across decades. Unfortunately, systematic monitoring of these variables, that is, longitudinal studies and comparable surveys of risk perception, is almost never available (Figure 2d). ...

Context 10

... 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? ...

Context 11

... 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. ...

Context 12

... advance systematic empirical research, we propose the following essential steps. The integrative framework, which emphasizes the interplay of natural hazards and vulnerabilities (Figure 2a), can be used to DI BALDASSARRE ET AL.derive one or more explanatory models (as alternative hypotheses) about the way in which social, technical, 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 paradoxes, or used to explore the socionatural factors triggering different trajectories (Figure 2c). ...

Context 13

... advance systematic empirical research, we propose the following essential steps. The integrative framework, which emphasizes the interplay of natural hazards and vulnerabilities (Figure 2a), can be used to DI BALDASSARRE ET AL.derive one or more explanatory models (as alternative hypotheses) about the way in which social, technical, 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 paradoxes, or used to explore the socionatural factors triggering different trajectories (Figure 2c). ...

Context 14

... integrative framework, which emphasizes the interplay of natural hazards and vulnerabilities (Figure 2a), can be used to DI BALDASSARRE ET AL.derive one or more explanatory models (as alternative hypotheses) about the way in which social, technical, 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 paradoxes, 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 collect (Figure 2d) to better support evidence-based DRR. ...

Context 15

... models can then be tested by evaluating their capability to capture emerging tendencies, such as adaptation dynamics or safe-development paradoxes, 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 collect (Figure 2d) to better support evidence-based DRR. Empirical studies will in turn allow evaluating the explanatory power of alternative models. ...