게재연도 | 2022 |
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논문집명 | Sustainability |
논문명 | Flood Damage Assessment: A Review of Microscale Methodologies for Residential Buildings |
저자 | Oluwatofunmi Deborah Aribisala, Sang-Guk Yum, Manik Das Adhikari, Moon-Soo Song |
구분 | 국외저널 |
요약 | Flood damage assessment (FDA) is an essential tool for evaluating flood damage, vulnerability, and risk to civil systems such as residential buildings. The outcome of an FDA depends on the
spatial limits of the study and the complexity of the data. For microscale FDA, a high level of detail
is required to assess flood damage. This study reviewed the existing methodologies in microscale
FDA based on empirical and synthetic data selection methods for model development. The merits
and challenges of these approaches are discussed. This review also proposes an integrated step for
assessing the stages of FDA. This study contributes to the literature by providing insights into the
methodologies adopted, particularly on a microscale basis, which has not been comprehensively
discussed in the previous reviews. The findings of this study reveal that univariate modeling of flood
damage is nevertheless popular among researchers. New advanced approaches, such as advanced
machine learning and 3D models, are yet to gain prominence when compared with the univariate
modeling that has recorded a high success. This review concludes that there is a need to adopt
a combined empirical–synthetic approach in the selection of data for developing damage models.
Further research is required in the areas of multivariate modeling (advanced machine learning), 3D
BIM-GIS modeling, 3D visualization of damages, and projection of probabilities in flood damage
predictions to buildings. These are essential for performance flood-based building designs and for
promoting building resilience to flood damage. |
핵심어 | flood damage assessment; microscale; damage model; vulnerability function; building damage; 3D BIM-GIS modeling |