Flood Risk Management: Research and Practice 2008
DOI: 10.1201/9780203883020.ch203
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Synthetic water level building damage relationships for GIS-supported flood vulnerability modeling of residential properties

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Cited by 14 publications
(17 citation statements)
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“…For this reason, the same groundwater inundation is assumed to lead to similar damage to buildings of the same type. This approach is set in line with the results of damage analysis on residential buildings due to surface water flood, referred in Neubert et al (2008), Naumann et al (2009), andPistrika andJonkman (2010). The identification of building types is based on field surveys or by an analysis of geoinformation, using the Urban-Structure-Type (UST) approach.…”
Section: Module Groundwater Dynamicsmentioning
confidence: 78%
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“…For this reason, the same groundwater inundation is assumed to lead to similar damage to buildings of the same type. This approach is set in line with the results of damage analysis on residential buildings due to surface water flood, referred in Neubert et al (2008), Naumann et al (2009), andPistrika andJonkman (2010). The identification of building types is based on field surveys or by an analysis of geoinformation, using the Urban-Structure-Type (UST) approach.…”
Section: Module Groundwater Dynamicsmentioning
confidence: 78%
“…However, a supplementary assessment of flood losses inside the flooded area is not available here and an interpretation about general effects of the measurements is therefore pretty difficult. A suitable way for a complementary damage calculation due to surface water floods has been presented by Neubert et al (2008Neubert et al ( , 2012) with the damage model HOWAD. The combination of both models is feasible because of the same architecture and the comparable level of detail.…”
Section: Results Of the Modellingmentioning
confidence: 99%
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“…ER = engineering regulation. Roo, 2010;Steinebach, 1999;Steinebach et al, 2004;Nujic, 1995;Neubert, Naumann, and Deilmann, 2009. Motivation for development • Target users are local water managers.…”
Section: Input Data Requirementsmentioning
confidence: 99%