Abstract. In this study, we developed an enhanced approach for large-scale flood damage and risk assessments that uses characteristics of buildings and the built environment as object-based information to represent exposure and vulnerability to flooding. Most current large-scale assessments use an aggregated land-use category to represent the exposure, treating all exposed elements the same. For large areas where previously only coarse information existed such as in Africa, more detailed exposure data are becoming available. For our approach, a direct relation between the construction type and building material of the exposed elements is used to develop vulnerability curves. We further present a method to differentiate flood risk in urban and rural areas based on characteristics of the built environment. We applied the model to Ethiopia and found that rural flood risk accounts for about 22 % of simulated damage; rural damage is generally neglected in the typical land-use-based damage models, particularly at this scale. Our approach is particularly interesting for studies in areas where there is a large variation in construction types in the building stock, such as developing countries.

Traditionally, building-level risk reduction measures aim to address the risk of a single hazard type, for instance, through building codes (Cutter et al., 2015; Daniell, 2015; Shreve & Kelman, 2014). However, many countries face the risk of multiple disasters (Cutter et al., 2015; De Ruiter et al., 2020). Floods and earthquakes are often the hazard types with the highest economic damages, especially in developing countries (Zorn, 2018), and their damages are likely to continue to increase in the future (Bilham, 2009; Cutter et al., 2015; Winsemius et al., 2016). The increase in the damages in the future is due to both a projected increase in the frequency of (climate-driven) hazards (in the case of floods), and also due to increasing exposure in vulnerable areas (Balica et al., 2015). This is expected to continue in the future, with projections estimating that the world's population will have doubled between 1950 and 2050, which requires the construction of an additional 1 billion housing units (Bilham, 2009). Moreover, social inequalities cause developing countries and the poor to suffer disproportionally from the impacts of natural hazards (

Abstract. In this study, we developed an enhanced approach for large-scale flood damage and risk assessments that uses characteristics of buildings and the built environment as object-based information to represent exposure and vulnerability to flooding. Most current large-scale assessments use an aggregated land-use category to represent the exposure, treating all exposed elements the same. For large areas where previously only coarse information existed such as in Africa, more detailed exposure data is becoming available. For our approach, a direct relation between the construction type and building material of the exposed elements is used to develop vulnerability curves. We further present a method to differentiate flood risk in urban and rural areas based on characteristics of the built environment. We applied the model to Ethiopia, and found that rural flood risk accounts for about 22 % of simulated damages; rural damages are generally neglected in the typical land-use-based damage models particularly at this scale. Our approach is particularly interesting for studies in areas where there is a large variation in construction types in the building stock, such as developing countries. It also enables comparison across different natural hazard types that also use material-based vulnerability, paving the way to the enhancement of multi-risk assessments.

<p>Many countries face the risk of multiple hazards. The UNDRR’s Global Platform for Disaster Risk Reduction have called upon the science community for an increased understanding of the complexities of multi-hazard risk (UNDRR 2019). Nonetheless, in the currently prevailing risk assessment paradigm, risk is often represented as static and fragmented in terms of hazard types. While positively influencing the risk of one hazard, DRR measures can have adverse effects on the risk of another hazard type thereby increasing the vulnerability of the built environment, exacerbating impacts and potentially causing compound or cascading disasters. For example, wood-frame buildings tend to perform well under ground shaking but are likely to sustain higher damages due to an inundation than concrete buildings. We refer to these negative impacts between hazards as the asynergy of a DRR measure. Due to the predominantly single-hazard approach, the potential asynergies of DRR measures remain poorly understood.</p><p>In a case study of Afghanistan, we calculate the asynergies of building level DRR measures for floods and earthquakes. To this extent, we develop two increased-resilience scenarios where a decrease in flood and earthquake vulnerability are mimicked. These scenarios are used to assess the asynergies and to illustrate to what degree a risk reduction of one risk may actually be offset by an increase of the other risk. This can then be used to show which type of measure is worthwhile in which area.</p><p>An improved capability of understanding risk more holistically would strongly benefit first responders, aid organizations, urban planners and decision makers in designing sustainable DRR measures. We discuss several key potential asynergies of building level DRR measures for floods and earthquakes tailored to decrease the risk of one hazard on the risk of the other hazard. Finally, we outline a roadmap highlighting key future research and policy directions, and possible ways to strengthen coherent policies for DRR.</p>