| Abstrakt: |
Namely: Floods can inflict significant damage on buildings, particularly in urban areas. Effective flood risk management in such areas relies on the ability to identify potential damages and high-risk locations. In the twenty-first century, this issue has become even more critical due to the rapid urbanization process and the intensification of short-term rainstorms and flash floods caused by climate change. Unfortunately, many developing countries lack accurate models for predicting and estimating flood damages at a national level. This article focuses on assessing the direct damages incurred by floods on buildings and their contents in urban areas, especially in regions with limited field data and unreliable damage functions. Five different models, including Life-Sim, Debo (J Hydraul Div Proc ASCE 108(10):1059–1069, 1982), Dutta et al. (J Hydrol 277:24–49, 2003), Luino et al. (J Geoinformatica 13:339–353, 2009), and Arrighi et al. (J Nat Hazards Earth Syst Sci 13:1375–1391, 2013), are discussed concerning building instability (or destruction) and percentage of damage to remaining buildings based on flood hydraulic characteristics such as depth and flow velocity. The economic damages caused by floods of varying return periods, representing the average long-term risk and expected annual damage (EAD), are examined for buildings in a specific region in Iran using the depth-damage functions from the aforementioned models. Moreover, the first-order variance estimation method (FOVE) is utilized to determine the confidence interval around the EAD, considering the challenge of defining probability density functions for damage across all cells in the basic. The depth-damage curve presented by Arrighi et al. (J Nat Hazards Earth Syst Sci 13:1375–1391, 2013) yields the most accurate estimation when compared to observed flood data on economic losses. An important finding of this research is the potential applicability of functions developed in other countries, despite differences in culture, architecture, and urban infrastructure. The method proposed in this article allows for a rapid estimate of flood damages in the absence of information and historical data, providing an acceptable approximation. Additionally, this research investigates the existence of uncertainty in estimating the expected annual damage, and raster maps. [ABSTRACT FROM AUTHOR] |
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