Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam
AbstractVietnam has a long history and experience with floods. Flood risk is expected to increase further due to climatic, land use and other global changes. Can Tho City, the cultural and economic center of the Mekong delta in Vietnam, is at high risk of flooding. To improve flood risk analyses for Vietnam, this study presents novel multi-variable flood loss models for residential buildings and contents and demonstrates their application in a flood risk assessment for the inner city of Can Tho. Cross-validation reveals that decision tree based loss models using the three input variables water depth, flood duration and floor space of building are more appropriate for estimating building and contents loss in comparison with depth–damage functions. The flood risk assessment reveals a median expected annual flood damage to private households of US$3340 thousand for the inner city of Can Tho. This is approximately 2.5% of the total annual income of households in the study area. For damage reduction improved flood risk management is required for the Mekong Delta, based on reliable damage and risk analyses. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Chinh, D.T.; Dung, N.V.; Gain, A.K.; Kreibich, H. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam. Water 2017, 9, 313.
Chinh DT, Dung NV, Gain AK, Kreibich H. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam. Water. 2017; 9(5):313.Chicago/Turabian Style
Chinh, Do T.; Dung, Nguyen V.; Gain, Animesh K.; Kreibich, Heidi. 2017. "Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam." Water 9, no. 5: 313.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.