| Title | Probabilistic depth-damage curves for assessment of flood-induced building losses |
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| Author | McGrath, H ; Abo
El Ezz, A; Nastev, M |
| Thesis | Springer |
| Source | Natural Hazards vol. 97, issue 1, 2019 p. 1-14, https://doi.org/10.1007/s11069-019-03622-3 |
| Image |  |
| Year | 2019 |
| Alt Series | Natural Resources Canada, Contribution Series 20180306 |
| Publisher | Springer Science and Business Media LLC |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf (Adobe® Reader®); html |
| Subjects | hydrogeology; Science and Technology; floods; water levels; Methodology; Buildings; Costs |
| Illustrations | plots; tables; bar graphs; pie charts; sketch maps |
| Program | Public Safety Geoscience Quantitative risk assessment project |
| Released | 2019 05 28 |
| Abstract | The most common and internationally accepted method of assessing building damage due to flooding is through the application of a depth-damage curve (DDC). A DDC relates the percent damage or estimated
economic loss to a buildings' structural integrity and/or contents directly to a given water level (depth). The DDC generally represents an average structure within a given building category, e.g. one-storey single-family residence. Given the great
variability across any given structural category, the variation in building materials, construction quality across communities and the singular focus on depth for estimation of losses, it is important to communicate the uncertainty and potential
variability of the expected losses in any assessment. In this paper, probabilistic depth-damage curves (PDDCs) are developed based on synthetically derived DDCs from communities in southern Ontario. The generated PDDCs are based on assumed loss
thresholds for minor and major loss levels, as spent in Canadian dollars. The economic loss estimates obtained in this way and their likelihood of being exceeded at any given flood depth express more transparently the potential building losses. An
applied example of this method is included for both aggregate and building-by-building loss estimation. |
| Summary | (Plain Language Summary, not published)
Generally, a depth-damage curve (DDC) is used to assess building damage from flooding. These depict a one-to-one relationship between flood depth and
economic loss. A new method to convey the probability of economic losses due to flooding in a more transparent way is introduced through the development of probabilistic DDC. These are generated from the DDC and loss thresholds (e.g., $10,000 and
$25,000) to assign building losses to different damage class states: affected, minor and major. |
| GEOSCAN ID | 313142 |
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