Enhancement of large-scale flood damage assessments using building-material-based vulnerability curves for an object-based approach

Abstract

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.

Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks

“…Third, we quantify the uncertainty surrounding the flood vulnerability of the building 37,38 . Common vulnerability models are depth-damage functions that quantify the damages for a certain depth of water in a house.…”

Characterizing uncertainty of general building stock exposure data

“…The potential uncertainty due to regional exposure data has not been thoroughly studied. There are a few exceptions for flood modeling, including: Englehardt et al (2019), which examines the effect that refined estimates of building exposure have on flood loss estimates based on the assignment of vulnerability and its sensitivity to the designation of ''urban'' and ''rural'' in developing countries, and an examination of using various global population data sets, as with Lim et al (2019) and Tuholske et al (2021).…”