Articles | Volume 20, issue 11
https://doi.org/10.5194/nhess-20-2997-2020
© Author(s) 2020. 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-20-2997-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Nov 2020
Research article |
| 09 Nov 2020
| 09 Nov 2020
Are flood damage models converging to “reality”? Lessons learnt from a blind test
Daniela Molinari
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
Anna Rita Scorzini
CORRESPONDING AUTHOR
Department of Civil, Environmental and Architectural Engineering, University of L'Aquila, Via Gronchi 18, 67100 L'Aquila, Italy
Chiara Arrighi
Department of Civil and Environmental Engineering, University of Florence, Piazza San Marco 4, 50121 Florence, Italy
Francesca Carisi
Department of Civil, Chemical, Environmental and Material Engineering, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
Fabio Castelli
Department of Civil and Environmental Engineering, University of Florence, Piazza San Marco 4, 50121 Florence, Italy
Alessio Domeneghetti
Department of Civil, Chemical, Environmental and Material Engineering, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
Alice Gallazzi
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
Marta Galliani
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
Frédéric Grelot
G-EAU, Univ Montpellier, AgroParisTech, CIRAD, IRD, INRAE, Montpellier SupAgro, Montpellier, France
Patric Kellermann
GFZ German Research Centre for Geosciences, Section Hydrology, Telegrafenberg, 14473 Potsdam, Germany
Heidi Kreibich
GFZ German Research Centre for Geosciences, Section Hydrology, Telegrafenberg, 14473 Potsdam, Germany
Guilherme S. Mohor
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany
Markus Mosimann
Institute of Geography, Mobiliar Lab for Natural Risks, Oeschger Centre for Climate Change Research, University of Bern, Hallerstrasse 12, 3012 Bern, Switzerland
Stephanie Natho
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany
Claire Richert
G-EAU, Univ Montpellier, AgroParisTech, CIRAD, IRD, INRAE, Montpellier SupAgro, Montpellier, France
Kai Schroeter
GFZ German Research Centre for Geosciences, Section Hydrology, Telegrafenberg, 14473 Potsdam, Germany
Annegret H. Thieken
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany
Andreas Paul Zischg
Institute of Geography, Mobiliar Lab for Natural Risks, Oeschger Centre for Climate Change Research, University of Bern, Hallerstrasse 12, 3012 Bern, Switzerland
Francesco Ballio
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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42 citations as recorded by crossref.
- Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
- Historical comparison of the damage caused by the propagation of a dam break wave in a pre-alpine valley R. Bonomelli et al. 10.1016/j.ejrh.2023.101467
- Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts E. Duo et al. 10.1016/j.envint.2020.105884
- Influence of urban forms on long-duration urban flooding: Laboratory experiments and computational analysis X. Li et al. 10.1016/j.jhydrol.2021.127034
- Process-based flood damage modelling relying on expert knowledge: a methodological contribution applied to the agricultural sector P. Brémond et al. 10.5194/nhess-22-3385-2022
- Flood damage functions based on a single physics- and data-based impact parameter that jointly accounts for water depth and velocity T. Lazzarin et al. 10.1016/j.jhydrol.2022.127485
- Urban resilience assessment: A multicriteria approach for identifying urban flood-exposed risky districts using multiple-criteria decision-making tools (MCDM) M. Mabrouk & H. Haoying 10.1016/j.ijdrr.2023.103684
- 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. 10.1016/j.cscm.2024.e03004
- Understanding flood risk in urban environments: spatial analysis of building vulnerability and hazard areas in the Lisbon metropolitan area P. Santos et al. 10.1007/s11069-024-06731-w
- Spatial risk assessment for climate proofing of economic activities: The case of Belluno Province (North-East Italy) C. Giupponi et al. 10.1016/j.crm.2024.100656
- A Zero-Order Flood Damage Model for Regional-Scale Quick Assessments A. Pogliani et al. 10.3390/w13091292
- Nature-based solutions as urban adaptation to climate risk: Framework for economic evaluation as decision support tool S. Sahay 10.1016/j.scs.2024.106037
- Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. 10.1016/j.envsoft.2020.104798
- Revisiting Urban Resilience: A Systematic Review of Multiple-Scale Urban Form Indicators in Flood Resilience Assessment M. Mabrouk et al. 10.3390/su16125076
- Integrated Flood Impact and Vulnerability Assessment Using a Multi-Sensor Earth Observation Mission with the Perspective of an Operational Service in Lombardy, Italy M. Righini et al. 10.3390/land13020140
- Cloudburst-disaster modelling. A new open-source catastrophe model D. Knös et al. 10.1016/j.ijdrr.2021.102679
- The role of residual risk on flood damage assessment: A continuous hydrologic-hydraulic modelling approach for the historical city of Rome, Italy A. Fiori et al. 10.1016/j.ejrh.2023.101506
- A Global Scale Analysis of River Flood Risk of UNESCO World Heritage Sites C. Arrighi 10.3389/frwa.2021.764459
- Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy A. Taramelli et al. 10.5194/nhess-22-3543-2022
- Cost–benefit analysis of flood mitigation measures: a case study employing high-performance hydraulic and damage modelling D. Molinari et al. 10.1007/s11069-021-04814-6
- Improvements and Operational Application of a Zero-Order Quick Assessment Model for Flood Damage: A Case Study in Italy L. Manselli et al. 10.3390/w14030373
- INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium) A. Scorzini et al. 10.5194/nhess-22-1743-2022
- Residential building and sub-building level flood damage analysis using simple and complex models R. Paulik et al. 10.1007/s11069-024-06756-1
- Residential flood loss estimated from Bayesian multilevel models G. Mohor et al. 10.5194/nhess-21-1599-2021
- Developing a framework for the assessment of current and future flood risk in Venice, Italy J. Schlumberger et al. 10.5194/nhess-22-2381-2022
- Flood risk assessment through large-scale modeling under uncertainty L. Pavesi et al. 10.5194/nhess-24-4507-2024
- Residential building flood damage: Insights on processes and implications for risk assessments R. Paulik et al. 10.1111/jfr3.12832
- Toward an adequate level of detail in flood risk assessments T. Sieg et al. 10.1111/jfr3.12889
- CERCA (Cascading Effects in Risk Consequences Assessment): An operational tool for geo-hydrological scenario risk assessment and cascading effects evaluation D. Biondi et al. 10.2166/nh.2023.088
- A framework for building climate storylines based on downward counterfactuals: The case of the European Union Solidarity fund A. Ciullo et al. 10.1016/j.crm.2021.100349
- Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview V. Bigi et al. 10.3390/cli9010012
- Modeling flood susceptibility zones using hybrid machine learning models of an agricultural dominant landscape of India S. Saini et al. 10.1007/s11356-023-29049-9
- Enhancing Flood Management Through Machine Learning: A Comprehensive Analysis of the CatBoost Application O. O. I. et al. 10.38124/ijisrt/IJISRT24JUN1770
- Geospatial modelling of floods: a literature review E. Avila-Aceves et al. 10.1007/s00477-023-02505-1
- The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0 M. Di Bacco et al. 10.5194/nhess-24-1681-2024
- Evaluating the spatial application of multivariable flood damage models R. Paulik et al. 10.1111/jfr3.12934
- Estimating direct economic impacts of severe flood events in Turkey (2015–2020) G. Koç et al. 10.1016/j.ijdrr.2021.102222
- Urban flood drifters (UFD): Identification, classification and characterisation A. Bayón et al. 10.1111/jfr3.13002
- Hydrodynamic Modelling of Floods and Estimating Socio-economic Impacts of Floods in Ugandan River Malaba Sub-catchment A. Mubialiwo et al. 10.1007/s41748-021-00283-w
- Multi-risk assessment in a historical city C. Arrighi et al. 10.1007/s11069-021-05125-6
- A Revised Approach to Flood Damage Estimation in Flood Risk Maps and Flood Risk Management Plans, Poland I. Godyń 10.3390/w13192713
- Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data P. Costabile et al. 10.1029/2023WR034599
4 citations as recorded by crossref.
- Brief Communication: Simple-INSYDE, development of a new tool for flood damage evaluation from an existing synthetic model M. Galliani et al. 10.5194/nhess-20-2937-2020
- Tidal Flood Risk on Salt Farming: Evaluation of Post Events in the Northern Part of Java Using a Parametric Approach A. Nirwansyah & B. Braun 10.3390/geosciences11100420
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Latest update: 25 Dec 2024
Short summary
Flood risk management requires a realistic estimation of flood losses. However, the capacity of available flood damage models to depict real damages is questionable. With a joint effort of eight research groups, the objective of this study was to compare the performances of nine models for the estimation of flood damage to buildings. The comparison provided more objective insights on the transferability of the models and on the reliability of their estimations.
Flood risk management requires a realistic estimation of flood losses. However, the capacity of...
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