Articles | Volume 18, issue 7
Nat. Hazards Earth Syst. Sci., 18, 2057–2079, 2018
https://doi.org/10.5194/nhess-18-2057-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Nat. Hazards Earth Syst. Sci., 18, 2057–2079, 2018
https://doi.org/10.5194/nhess-18-2057-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 27 Jul 2018
Research article | 27 Jul 2018
Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy)
Francesca Carisi et al.
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Cited
28 citations as recorded by crossref.
- A Robust and Transferable Model for the Prediction of Flood Losses on Household Contents M. Mosimann et al. 10.3390/w10111596
- Are flood damage models converging to “reality”? Lessons learnt from a blind test D. Molinari et al. 10.5194/nhess-20-2997-2020
- Multivariate Flood Loss Estimation of the 2018 Bago Flood in Myanmar W. Zin et al. 10.20965/jdr.2020.p0300
- Structural, dynamic and anthropic conditions that trigger the emergence of the levee effect: insight from a simplified risk-based framework C. D’Angelo et al. 10.1080/02626667.2020.1729985
- Analysis of rainfall extremes in the Ngong River Basin of Kenya: Towards integrated urban flood risk management B. Juma et al. 10.1016/j.pce.2020.102929
- Towards an operationalisation of nature-based solutions for natural hazards P. Kumar et al. 10.1016/j.scitotenv.2020.138855
- Flood Depth‒Damage Curves for Spanish Urban Areas E. Martínez-Gomariz et al. 10.3390/su12072666
- What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices G. Guimarães Nobre et al. 10.1029/2019EF001450
- Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. 10.1029/2019WR025068
- Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia D. D'Ayala et al. 10.5194/nhess-20-2221-2020
- Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. 10.5194/nhess-19-661-2019
- The object-specific flood damage database HOWAS 21 P. Kellermann et al. 10.5194/nhess-20-2503-2020
- The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model H. Lv et al. 10.1016/j.jhydrol.2020.125797
- Levee Breaching: A New Extension to the LISFLOOD-FP Model I. Shustikova et al. 10.3390/w12040942
- Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe D. Paprotny et al. 10.1016/j.scitotenv.2020.140011
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
- The determination of flood damage curve in areas lacking disaster data based on the optimization principle of variation coefficient and beta distribution Z. Wu et al. 10.1016/j.scitotenv.2020.142277
- Invited perspectives: How machine learning will change flood risk and impact assessment D. Wagenaar et al. 10.5194/nhess-20-1149-2020
- Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. 10.1029/2018EF000994
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- Short communication: A model to predict flood loss in mountain areas S. Fuchs et al. 10.1016/j.envsoft.2019.03.026
- Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. 10.1016/j.envsoft.2020.104798
- Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
- Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography I. Shustikova et al. 10.1080/02626667.2019.1671982
- Construction of flood loss function for cities lacking disaster data based on three-dimensional (object-function-array) data processing H. Lv et al. 10.1016/j.scitotenv.2021.145649
- Probabilistic Quantification in the Analysis of Flood Risks in Cross-Border Areas of Poland and Germany Ł. Kuźmiński et al. 10.3390/en13226020
- Probabilistic Flood Loss Models for Companies L. Schoppa et al. 10.1029/2020WR027649
- Empirical flash flood vulnerability functions for residential buildings C. Arrighi et al. 10.1007/s42452-020-2696-1
28 citations as recorded by crossref.
- A Robust and Transferable Model for the Prediction of Flood Losses on Household Contents M. Mosimann et al. 10.3390/w10111596
- Are flood damage models converging to “reality”? Lessons learnt from a blind test D. Molinari et al. 10.5194/nhess-20-2997-2020
- Multivariate Flood Loss Estimation of the 2018 Bago Flood in Myanmar W. Zin et al. 10.20965/jdr.2020.p0300
- Structural, dynamic and anthropic conditions that trigger the emergence of the levee effect: insight from a simplified risk-based framework C. D’Angelo et al. 10.1080/02626667.2020.1729985
- Analysis of rainfall extremes in the Ngong River Basin of Kenya: Towards integrated urban flood risk management B. Juma et al. 10.1016/j.pce.2020.102929
- Towards an operationalisation of nature-based solutions for natural hazards P. Kumar et al. 10.1016/j.scitotenv.2020.138855
- Flood Depth‒Damage Curves for Spanish Urban Areas E. Martínez-Gomariz et al. 10.3390/su12072666
- What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices G. Guimarães Nobre et al. 10.1029/2019EF001450
- Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. 10.1029/2019WR025068
- Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia D. D'Ayala et al. 10.5194/nhess-20-2221-2020
- Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. 10.5194/nhess-19-661-2019
- The object-specific flood damage database HOWAS 21 P. Kellermann et al. 10.5194/nhess-20-2503-2020
- The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model H. Lv et al. 10.1016/j.jhydrol.2020.125797
- Levee Breaching: A New Extension to the LISFLOOD-FP Model I. Shustikova et al. 10.3390/w12040942
- Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe D. Paprotny et al. 10.1016/j.scitotenv.2020.140011
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
- The determination of flood damage curve in areas lacking disaster data based on the optimization principle of variation coefficient and beta distribution Z. Wu et al. 10.1016/j.scitotenv.2020.142277
- Invited perspectives: How machine learning will change flood risk and impact assessment D. Wagenaar et al. 10.5194/nhess-20-1149-2020
- Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. 10.1029/2018EF000994
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- Short communication: A model to predict flood loss in mountain areas S. Fuchs et al. 10.1016/j.envsoft.2019.03.026
- Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. 10.1016/j.envsoft.2020.104798
- Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
- Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography I. Shustikova et al. 10.1080/02626667.2019.1671982
- Construction of flood loss function for cities lacking disaster data based on three-dimensional (object-function-array) data processing H. Lv et al. 10.1016/j.scitotenv.2021.145649
- Probabilistic Quantification in the Analysis of Flood Risks in Cross-Border Areas of Poland and Germany Ł. Kuźmiński et al. 10.3390/en13226020
- Probabilistic Flood Loss Models for Companies L. Schoppa et al. 10.1029/2020WR027649
- Empirical flash flood vulnerability functions for residential buildings C. Arrighi et al. 10.1007/s42452-020-2696-1
Latest update: 01 Mar 2021
Short summary
By analyzing a comprehensive loss dataset of affected private households after a recent river flood event in northern Italy, we tackle the problem of flood damage estimation in Emilia-Romagna (Italy). We develop empirical uni- and multivariable loss models for the residential sector. Outcomes highlight that the latter seem to outperform the former and, in addition, results show a higher accuracy of univariable models based on local data compared to literature ones derived for different contexts.
By analyzing a comprehensive loss dataset of affected private households after a recent river...
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