![]() ![]() This study develops a bottom-up approach to simulating dynamic processes of flood exposure and vulnerability, as well as the resulting future riverine flood risk, by considering factors that may attract or repel settlement in flood-prone areas. A more accurate assessment of developments in flood exposure requires a coupling of human and environmental subsystems 26. Importantly, these spatial projections represent a static view of human decision-making in relation to environmental processes, particularly regarding flood risk. ![]() ![]() Several population projection models 22, 23 that are used in high-impact flood risk studies 2, 3, 5, 24, 25 assess the suitability of areas to capacitate population growth by identifying geographical features that are likely to encourage or discourage populations to settle, such as elevation, steepness of the terrain, distance from urban centres, and distance from the coast. However, projecting future flood exposure in these assessments requires a downscaling method where high-level (SSP-)scenarios can be applied to forecast exposure on a local scale. Large-scale flood risk assessments commonly use generic (top-down) scenarios of population growth, largely because population development is complex and depends on many external factors. For large-scale climate risk models, it is useful to combine a top-down approach, for example to assess climate hazards, with a bottom-up approach that accounts for behavioural responses to changing hazards. For example, bottom-up approaches are used to project the evacuation behaviour of individuals in the face of disasters 16, analyse adaptation behaviour in response to floods and insurance incentives 17, 18, 19, 20, and assess migration flows away from high-risk areas 15, 21. Instead of top-down methods, which use static exposure and vulnerability input data to project climate impacts on global or regional scales, bottom-up assessments focus on human behaviour and how individuals dynamically respond in time and space to certain (environmental) conditions 9. ![]() Recent scientific developments address the dynamic interplay between climate hazards, exposure, and vulnerability. Settling in floodplains may also become more attractive when this area provides aesthetic or recreational amenities 13, 14, when flood protection infrastructure is improved 15, or when governments or insurers provide financial compensation after floods 12. Households may, for example, move away from or avoid settling in areas at high risk of flooding 10, 11, 12 or apply flood risk reduction measures if they do reside in these areas 1. Although these assumptions simplify large-scale (global) climate risk models, they disregard the fact that exposure and vulnerability are intrinsically dynamic 8 and should be modelled as such 9. Besides exposure, the vulnerability of communities to flooding is also often assumed to remain constant over time 1. These large-scale flood risk models consider exposure growth in floodplains based on story lines such as ’shared socio-economic pathways’ (SSPs), which are based on several generic scenarios of global developments such as economic growth, political stability, and technological development 7. For example, global flood risk modelling studies have found that socio-economic growth is the dominant driver of increasing riverine flood risk in some regions across the world 5, 6. Recent research recognises the dynamic nature of exposure and vulnerability with respect to climate risks, and it emphasises the need to apply these dynamics in models. Traditionally, climate change risk has been assessed with models that mainly focus on changing hazard conditions due to biophysical processes and climate change, exogenous projections of exposed assets and people, and assuming constant vulnerability to project the potential damage of climate hazard 4. It is imperative that climate risk assessments guide climate adaptation policies 1, 2, 3. ![]()
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