On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model
| Autor: | Daniela Molinari, Anna Rita Scorzini |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
lcsh:Hydraulic engineering
Scale (ratio) Computer science 0208 environmental biotechnology Geography Planning and Development Flood damage assessment INSYDE Meso-scale Micro-scale Biochemistry Aquatic Science Water Science and Technology flood damage assessment micro-scale meso-scale 0211 other engineering and technologies 02 engineering and technology Civil engineering Footprint lcsh:Water supply for domestic and industrial purposes lcsh:TC1-978 Statistics Limit (mathematics) Block (data storage) Planning and Development 021110 strategic defence & security studies lcsh:TD201-500 Geography Flood myth 020801 environmental engineering Variable (computer science) Data quality Level of detail |
| Zdroj: | Water, Vol 9, Iss 9, p 688 (2017) |
| ISSN: | 2073-4441 |
| Popis: | IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE) is a model for the estimation of flood damage to residential buildings at the micro-scale. This study investigates the sensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters at the scale of individual buildings for a case study, the level of detail of input data is progressively downgraded until the condition in which a representative value is defined for all inputs at the census block scale. The analysis reveals that two conditions are required to limit the errors in damage estimation: the representativeness of representatives values with respect to micro-scale values and the local knowledge of the footprint area of the buildings, being the latter the main extensive variable adopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale, also in different countries, depending on the availability of aggregated building data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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