Articles | Volume 18, issue 5
https://doi.org/10.5194/nhess-18-1297-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-18-1297-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 May 2018
Research article |
| 03 May 2018
| 03 May 2018
Multi-model ensembles for assessment of flood losses and associated uncertainty
Rui Figueiredo
CORRESPONDING AUTHOR
Scuola Universitaria Superiore IUSS Pavia, Pavia, Italy
GFZ German Research Centre for Geosciences, Sect. 5.4: Hydrology, Potsdam, Germany
Kai Schröter
GFZ German Research Centre for Geosciences, Sect. 5.4: Hydrology, Potsdam, Germany
Alexander Weiss-Motz
GFZ German Research Centre for Geosciences, Sect. 5.4: Hydrology, Potsdam, Germany
Mario L. V. Martina
Scuola Universitaria Superiore IUSS Pavia, Pavia, Italy
Heidi Kreibich
GFZ German Research Centre for Geosciences, Sect. 5.4: Hydrology, Potsdam, Germany
Viewed
Total article views: 5,314 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 16 Oct 2017)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,265 | 1,756 | 293 | 5,314 | 496 | 256 | 307 |
- HTML: 3,265
- PDF: 1,756
- XML: 293
- Total: 5,314
- Supplement: 496
- BibTeX: 256
- EndNote: 307
Total article views: 4,338 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 May 2018)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 2,745 | 1,324 | 269 | 4,338 | 261 | 246 | 288 |
- HTML: 2,745
- PDF: 1,324
- XML: 269
- Total: 4,338
- Supplement: 261
- BibTeX: 246
- EndNote: 288
Total article views: 976 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 16 Oct 2017)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 520 | 432 | 24 | 976 | 235 | 10 | 19 |
- HTML: 520
- PDF: 432
- XML: 24
- Total: 976
- Supplement: 235
- BibTeX: 10
- EndNote: 19
Viewed (geographical distribution)
Total article views: 5,314 (including HTML, PDF, and XML)
Thereof 5,037 with geography defined
and 277 with unknown origin.
Total article views: 4,338 (including HTML, PDF, and XML)
Thereof 4,093 with geography defined
and 245 with unknown origin.
Total article views: 976 (including HTML, PDF, and XML)
Thereof 944 with geography defined
and 32 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
45 citations as recorded by crossref.
- 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. https://doi.org/10.1016/j.scitotenv.2020.142277
- Formation Mechanism and Response Strategies for Urban Waterlogging: A Comprehensive Review Y. Nie et al. https://doi.org/10.3390/app15063037
- Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy) F. Carisi et al. https://doi.org/10.5194/nhess-18-2057-2018
- Seamless Estimation of Hydrometeorological Risk Across Spatial Scales T. Sieg et al. https://doi.org/10.1029/2018EF001122
- Developing a multivariable lookup table function for estimating flood damages of rice crop in Vietnam using a secondary research approach N. Nguyen et al. https://doi.org/10.1016/j.ijdrr.2021.102208
- Large-scale flood risk assessment in data-scarce areas: an application to Central Asia P. Ceresa et al. https://doi.org/10.5194/nhess-25-403-2025
- Potential Benefits in Remapping the Special Flood Hazard Area: Evidence from the U.S. Housing Market A. Pollack et al. https://doi.org/10.1016/j.jhe.2023.101956
- Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. https://doi.org/10.1029/2018EF000994
- Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru J. Gomez-Zapata et al. https://doi.org/10.5194/nhess-21-3599-2021
- Capturing Regional Differences in Flood Vulnerability Improves Flood Loss Estimation N. Sairam et al. https://doi.org/10.3389/frwa.2022.817625
- How does the selection of wave hindcast datasets and statistical models influence the probabilistic design of offshore scour protections? R. Figueiredo et al. https://doi.org/10.1016/j.oceaneng.2022.113123
- Probabilistic Flood Loss Models for Companies L. Schoppa et al. https://doi.org/10.1029/2020WR027649
- Preface: Damage of natural hazards: assessment and mitigation H. Kreibich et al. https://doi.org/10.5194/nhess-19-551-2019
- From Hazard to Consequences: Evaluation of Direct and Indirect Impacts of Flooding Along the Emilia-Romagna Coastline, Italy C. Armaroli et al. https://doi.org/10.3389/feart.2019.00203
- A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe S. Lüdtke et al. https://doi.org/10.1029/2019WR026213
- Combining models to generate a consensus effective reproduction numberRfor the COVID-19 epidemic status in England H. Manley et al. https://doi.org/10.1017/S0950268824000347
- A Comparison of Factors Driving Flood Losses in Households Affected by Different Flood Types G. Mohor et al. https://doi.org/10.1029/2019WR025943
- The role of socio-economic and property variables in the establishment of flood depth-damage curve for the data-scarce area in Malaysia S. Sulong & N. Romali https://doi.org/10.1080/1573062X.2022.2099292
- Residential flood loss estimated from Bayesian multilevel models G. Mohor et al. https://doi.org/10.5194/nhess-21-1599-2021
- Are flood damage models converging to “reality”? Lessons learnt from a blind test D. Molinari et al. https://doi.org/10.5194/nhess-20-2997-2020
- Flood risk assessment of cultural heritage at large spatial scales: Framework and application to mainland Portugal R. Figueiredo et al. https://doi.org/10.1016/j.culher.2019.11.007
- Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification T. Sieg et al. https://doi.org/10.1371/journal.pone.0212932
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. https://doi.org/10.1007/s11069-020-04413-x
- Evaluating targeted heuristics for vulnerability assessment in flood impact model chains A. Zischg et al. https://doi.org/10.1111/jfr3.12736
- Index-based insurance to mitigate current and future extreme events financial losses for water utilities G. Gesualdo et al. https://doi.org/10.1016/j.ijdrr.2023.104218
- Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. https://doi.org/10.1029/2019WR025068
- Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. https://doi.org/10.1016/j.envsoft.2020.104798
- What drives uncertainty surrounding riverine flood risks? I. Hosseini-Shakib et al. https://doi.org/10.1016/j.jhydrol.2024.131055
- INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium) A. Scorzini et al. https://doi.org/10.5194/nhess-22-1743-2022
- Extreme Flood Disasters: Comprehensive Impact and Assessment Q. Yu et al. https://doi.org/10.3390/w14081211
- Scalable flood inundation mapping using deep convolutional networks and traffic signage B. Alizadeh & A. Behzadan https://doi.org/10.1007/s43762-023-00090-1
- Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS A. Sebastian et al. https://doi.org/10.1007/s11069-021-04922-3
- Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. https://doi.org/10.5194/nhess-19-661-2019
- A hazard-human coupled model (HazardCM) to assess city dynamic exposure to rainfall-triggered natural hazards Q. Dai et al. https://doi.org/10.1016/j.envsoft.2020.104684
- Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts E. Duo et al. https://doi.org/10.1016/j.envint.2020.105884
- Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems L. Wang et al. https://doi.org/10.2166/wst.2024.212
- Evolution of flood protection levels and flood vulnerability in Europe since 1950 estimated with vine-copula models D. Paprotny et al. https://doi.org/10.1007/s11069-024-07039-5
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. https://doi.org/10.5194/nhess-21-643-2021
- Flood risk assessment through large-scale modeling under uncertainty L. Pavesi et al. https://doi.org/10.5194/nhess-24-4507-2024
- Innovative Vulnerability and Risk Assessment of Urban Areas against Flood Events: Prognosis of Structural Damage with a New Approach Considering Flow Velocity H. Maiwald et al. https://doi.org/10.3390/w14182793
- Characterization of damages in buildings after floods in Vega Baja County (Spain) in 2019. The case study of Almoradí municipality R. Moya Barbera et al. https://doi.org/10.1016/j.cscm.2024.e03004
- A model taxonomy for flood fragility and vulnerability assessment of buildings C. Galasso et al. https://doi.org/10.1016/j.ijdrr.2020.101985
- Model parameter influence on probabilistic flood risk analysis R. Paulik et al. https://doi.org/10.1016/j.ijdrr.2023.104215
- Emerging strategies for addressing flood-damage modeling issues: A review S. Redondo-Tilano et al. https://doi.org/10.1016/j.ijdrr.2024.105058
- Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines E. Duo et al. https://doi.org/10.5194/nhess-25-13-2025
45 citations as recorded by crossref.
- 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. https://doi.org/10.1016/j.scitotenv.2020.142277
- Formation Mechanism and Response Strategies for Urban Waterlogging: A Comprehensive Review Y. Nie et al. https://doi.org/10.3390/app15063037
- Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy) F. Carisi et al. https://doi.org/10.5194/nhess-18-2057-2018
- Seamless Estimation of Hydrometeorological Risk Across Spatial Scales T. Sieg et al. https://doi.org/10.1029/2018EF001122
- Developing a multivariable lookup table function for estimating flood damages of rice crop in Vietnam using a secondary research approach N. Nguyen et al. https://doi.org/10.1016/j.ijdrr.2021.102208
- Large-scale flood risk assessment in data-scarce areas: an application to Central Asia P. Ceresa et al. https://doi.org/10.5194/nhess-25-403-2025
- Potential Benefits in Remapping the Special Flood Hazard Area: Evidence from the U.S. Housing Market A. Pollack et al. https://doi.org/10.1016/j.jhe.2023.101956
- Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. https://doi.org/10.1029/2018EF000994
- Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru J. Gomez-Zapata et al. https://doi.org/10.5194/nhess-21-3599-2021
- Capturing Regional Differences in Flood Vulnerability Improves Flood Loss Estimation N. Sairam et al. https://doi.org/10.3389/frwa.2022.817625
- How does the selection of wave hindcast datasets and statistical models influence the probabilistic design of offshore scour protections? R. Figueiredo et al. https://doi.org/10.1016/j.oceaneng.2022.113123
- Probabilistic Flood Loss Models for Companies L. Schoppa et al. https://doi.org/10.1029/2020WR027649
- Preface: Damage of natural hazards: assessment and mitigation H. Kreibich et al. https://doi.org/10.5194/nhess-19-551-2019
- From Hazard to Consequences: Evaluation of Direct and Indirect Impacts of Flooding Along the Emilia-Romagna Coastline, Italy C. Armaroli et al. https://doi.org/10.3389/feart.2019.00203
- A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe S. Lüdtke et al. https://doi.org/10.1029/2019WR026213
- Combining models to generate a consensus effective reproduction numberRfor the COVID-19 epidemic status in England H. Manley et al. https://doi.org/10.1017/S0950268824000347
- A Comparison of Factors Driving Flood Losses in Households Affected by Different Flood Types G. Mohor et al. https://doi.org/10.1029/2019WR025943
- The role of socio-economic and property variables in the establishment of flood depth-damage curve for the data-scarce area in Malaysia S. Sulong & N. Romali https://doi.org/10.1080/1573062X.2022.2099292
- Residential flood loss estimated from Bayesian multilevel models G. Mohor et al. https://doi.org/10.5194/nhess-21-1599-2021
- Are flood damage models converging to “reality”? Lessons learnt from a blind test D. Molinari et al. https://doi.org/10.5194/nhess-20-2997-2020
- Flood risk assessment of cultural heritage at large spatial scales: Framework and application to mainland Portugal R. Figueiredo et al. https://doi.org/10.1016/j.culher.2019.11.007
- Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification T. Sieg et al. https://doi.org/10.1371/journal.pone.0212932
- A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. https://doi.org/10.1007/s11069-020-04413-x
- Evaluating targeted heuristics for vulnerability assessment in flood impact model chains A. Zischg et al. https://doi.org/10.1111/jfr3.12736
- Index-based insurance to mitigate current and future extreme events financial losses for water utilities G. Gesualdo et al. https://doi.org/10.1016/j.ijdrr.2023.104218
- Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. https://doi.org/10.1029/2019WR025068
- Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. https://doi.org/10.1016/j.envsoft.2020.104798
- What drives uncertainty surrounding riverine flood risks? I. Hosseini-Shakib et al. https://doi.org/10.1016/j.jhydrol.2024.131055
- INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium) A. Scorzini et al. https://doi.org/10.5194/nhess-22-1743-2022
- Extreme Flood Disasters: Comprehensive Impact and Assessment Q. Yu et al. https://doi.org/10.3390/w14081211
- Scalable flood inundation mapping using deep convolutional networks and traffic signage B. Alizadeh & A. Behzadan https://doi.org/10.1007/s43762-023-00090-1
- Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS A. Sebastian et al. https://doi.org/10.1007/s11069-021-04922-3
- Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. https://doi.org/10.5194/nhess-19-661-2019
- A hazard-human coupled model (HazardCM) to assess city dynamic exposure to rainfall-triggered natural hazards Q. Dai et al. https://doi.org/10.1016/j.envsoft.2020.104684
- Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts E. Duo et al. https://doi.org/10.1016/j.envint.2020.105884
- Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems L. Wang et al. https://doi.org/10.2166/wst.2024.212
- Evolution of flood protection levels and flood vulnerability in Europe since 1950 estimated with vine-copula models D. Paprotny et al. https://doi.org/10.1007/s11069-024-07039-5
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. https://doi.org/10.5194/nhess-21-643-2021
- Flood risk assessment through large-scale modeling under uncertainty L. Pavesi et al. https://doi.org/10.5194/nhess-24-4507-2024
- Innovative Vulnerability and Risk Assessment of Urban Areas against Flood Events: Prognosis of Structural Damage with a New Approach Considering Flow Velocity H. Maiwald et al. https://doi.org/10.3390/w14182793
- Characterization of damages in buildings after floods in Vega Baja County (Spain) in 2019. The case study of Almoradí municipality R. Moya Barbera et al. https://doi.org/10.1016/j.cscm.2024.e03004
- A model taxonomy for flood fragility and vulnerability assessment of buildings C. Galasso et al. https://doi.org/10.1016/j.ijdrr.2020.101985
- Model parameter influence on probabilistic flood risk analysis R. Paulik et al. https://doi.org/10.1016/j.ijdrr.2023.104215
- Emerging strategies for addressing flood-damage modeling issues: A review S. Redondo-Tilano et al. https://doi.org/10.1016/j.ijdrr.2024.105058
- Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines E. Duo et al. https://doi.org/10.5194/nhess-25-13-2025
Saved (final revised paper)
Latest update: 14 Nov 2026
Short summary
Flood loss modelling is subject to large uncertainty that is often neglected. Most models are deterministic, and large disparities exist among them. Adopting a single model may lead to inaccurate loss estimates and sub-optimal decision-making. This paper proposes the use of multi-model ensembles to address such issues. We demonstrate that this can be a simple and pragmatic approach to obtain more accurate loss estimates and reliable probability distributions of model uncertainty.
Flood loss modelling is subject to large uncertainty that is often neglected. Most models are...
Altmetrics
Final-revised paper
Preprint