This article analyzes the direct damage to residential buildings caused by the flooding of New Orleans after hurricane Katrina in the year 2005. A public dataset has been analyzed that contains information on the economic damage levels for approximately 95,000 residential buildings in the flooded area. The relationship between the flood characteristics and economic damage to residential buildings has been investigated. Results of hydrodynamic flood simulations have been used that give insight in water depths and flow velocities in the study area. In general, differences between the three polders in the observed distributions of damage estimates are related to differences in flood conditions. The highest damage percentages and structural damage mainly occurred in areas where higher flow velocities occurred, especially near the breaches in the Lower 9th Ward neighborhood. Further statistical analysis indicated that there is not any strong one-to-one relationship between the damage percentage and the water depth or the depth-velocity product. This suggests that there is considerable uncertainty associated with stage-damage functions, especially when they are applied to individual structures or smaller clusters of buildings. Based on the data, a more general approach has been proposed that could be used to distinguish different damage zones based on water depth and flow velocity for an area that is affected by flooding due to breaching of flood defenses. Further validation of existing damage models with the dataset and further inclusion of information on building type in the analysis of damage levels is recommended.
A conventional approach for the economic estimation of direct flood damage to buildings is using the method of depth-damage functions. However, there are few publications that describe in detail the derivation of depth-damage functions based on actual flood damage data. It still remains an open issue whether a site-specific depthdamage function can be applied to another region with similar climate and building conditions. This paper aims at demonstrating a step-by-step methodology for devising depth-damage functions using data from a flood event which occurred in Moschato, a suburb of Athens, Greece in July 2002. It also compares the developed depth-damage functions to functions from other areas with similar conditions. In the case study, the damage percentage is calculated per category of flood-affected property on the basis of relief payments. The replacement cost of the affected components of a building structure and the market value of each category of flood-affected property are estimated in order to develop depth-damage relationships for building structures. The local depth-damage function for residential use is compared to generalized functions and a site-specific function developed for the urban area of Palermo, Italy. Differences and similarities in damage datasets are examined and explained by related causative factors such as structural or architectural features of buildings. Finally, the application of both of the above functions to a third case (the Erasinos river basin in Attica, Greece) resulted in a fair difference (9 %) in the estimation of the expected average annual direct damage to residential buildings.
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