Abstract
Thanks to modelling advances and the increase in computational resources in recent years, it is now feasible to perform 2-D urban flood simulations at very high spatial resolutions and to conduct flood risk assessments at the scale of single buildings. In this study, we explore the sensitivity of flood loss estimates obtained in such micro-scale analyses to the spatial representation of the buildings in the 2D flood inundation model and to the hazard attribution methods in the flood loss model. The results show that building representation has a limited effect on the exposure values (i.e. the number of elements at risk), but can have a significant impact on the hazard values attributed to the buildings. On the other hand, the two methods for hazard attribution tested in this work result in remarkably different flood loss estimates. The sensitivity of the predicted flood losses to the attribution method is comparable to the one associated with the vulnerability curve. The findings highlight the need for incorporating these sources of uncertainty into micro-scale flood risk prediction methodologies.
Similar content being viewed by others
References
Abdullah AF, Vojinovic Z, Price RK, Aziz NAA (2012) Improved methodology for processing raw LiDAR data to support urban flood modelling—accounting for elevated roads and bridges. J Hydroinform 14:253–269. https://doi.org/10.2166/hydro.2011.009
Abily M, Bertrand N, Delestre O et al (2016) Spatial global sensitivity analysis of high resolution classified topographic data use in 2D urban flood modelling. Environ Model Softw 77:183–195. https://doi.org/10.1016/J.ENVSOFT.2015.12.002
Álvarez M, Puertas J, Peña E, Bermúdez M (2017) Two-dimensional dam-break flood analysis in data-scarce regions: the case study of Chipembe Dam, Mozambique. Water 9:432. https://doi.org/10.3390/w9060432
Amadio M, Mysiak J, Carrera L, Koks E (2016) Improving flood damage assessment models in Italy. Nat Hazards 82:2075–2088. https://doi.org/10.1007/s11069-016-2286-0
Apel H, Thieken AH, Merz B, Blöschl G (2006) A probabilistic modelling system for assessing flood risks. Nat Hazards 38:79–100. https://doi.org/10.1007/s11069-005-8603-7
Apel H, Merz B, Thieken AH (2008) Quantification of uncertainties in flood risk assessments. Int J River Basin Manag 6:149–162. https://doi.org/10.1080/15715124.2008.9635344
Apel H, Aronica GT, Kreibich H, Thieken AH (2009) Flood risk analyses—how detailed do we need to be? Nat Hazards 49:79–98. https://doi.org/10.1007/s11069-008-9277-8
Arrighi C, Brugioni M, Castelli F et al (2013) Urban micro-scale flood risk estimation with parsimonious hydraulic modelling and census data. Nat Hazards Earth Syst Sci 13:1375–1391. https://doi.org/10.5194/nhess-13-1375-2013
Bellos V, Tsakiris G (2015) Comparing various methods of building representation for 2D flood modelling in built-up areas. Water Resour Manag 29:379–397. https://doi.org/10.1007/s11269-014-0702-3
Bermúdez M, Neal JC, Bates PD et al (2017) Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional-local flood modeling system. Water Resour Res 53:2770–2785. https://doi.org/10.1002/2016WR019903
Bermúdez M, Ntegeka V, Wolfs V, Willems P (2018) Development and comparison of two fast surrogate models for urban pluvial flood simulations. Water Resour Manag. https://doi.org/10.1007/s11269-018-1959-8
Bladé E, Cea L, Corestein G et al (2014) Iber: herramienta de simulación numérica del flujo en ríos. Rev Int Métodos Numéricos para Cálculo y Diseño en Ing 30:1–10. https://doi.org/10.1016/j.rimni.2012.07.004
Bodoque JM, Amérigo M, Díez-Herrero A et al (2016) Improvement of resilience of urban areas by integrating social perception in flash-flood risk management. J Hydrol 541:665–676. https://doi.org/10.1016/j.jhydrol.2016.02.005
Bonasia R, Areu-Rangel OS, Tolentino D et al (2017) Flooding hazard assessment at Tulancingo (Hidalgo, Mexico). J Flood Risk Manag. https://doi.org/10.1111/jfr3.12312
Cammerer H, Thieken AH, Lammel J (2013) Adaptability and transferability of flood loss functions in residential areas. Nat Hazards Earth Syst Sci 13:3063–3081. https://doi.org/10.5194/nhess-13-3063-2013
Cea L, Vázquez-Cendón ME (2009) Unstructured finite volume discretization of two-dimensional depth-averaged shallow water equations with porosity. Int J Numer Methods Fluids. https://doi.org/10.1002/fld.2107
Cea L, Bermudez M, Puertas J et al (2016) IberWQ: new simulation tool for 2D water quality modelling in rivers and shallow estuaries. J Hydroinform 18:816–830. https://doi.org/10.2166/hydro.2016.235
Chen AS, Evans B, Djordjevi S et al (2012a) A coarse-grid approach to representing building blockage effects in 2D urban flood modelling. J Hydrol. https://doi.org/10.1016/j.jhydrol.2012.01.007
Chen AS, Evans B, Djordjević S, Savić DA (2012b) Multi-layered coarse grid modelling in 2D urban flood simulations. J Hydrol 470:1–11. https://doi.org/10.1016/j.jhydrol.2012.06.022
Davis SA, Skaggs LL (1992) Catalog of residential depth-damage functions used by the army corps of engineers in flood damage estimation. IWR report 92-R-3, Institute for Water Resources, US Army Corps of Engineers, Ft. Belvoir, VA
de Almeida GAM, Bates P, Ozdemir H (2016) Modelling urban floods at sub-metre resolution: challenges or opportunities for flood risk management? J Flood Risk Manag. https://doi.org/10.1111/jfr3.12276
de Moel H, Aerts JCJH (2011) Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates. Nat Hazards 58:407–425. https://doi.org/10.1007/s11069-010-9675-6
Dutta D, Herath S, Musiake K (2003) A mathematical model for flood loss estimation. J Hydrol 277:24–49. https://doi.org/10.1016/S0022-1694(03)00084-2
Environment Agency (2014) The updated flood map for surface water (uFMfSW) property points dataset. Bristol, UK. https://data.gov.uk/dataset/risk-of-flooding-from-surface-water-suitability
Ernst J, Dewals BJ, Detrembleur S et al (2010) Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data. Nat Hazards 55:181–209. https://doi.org/10.1007/s11069-010-9520-y
Fewtrell TJ, Bates PD, Horritt M, Hunter NM (2008) Evaluating the effect of scale in flood inundation modelling in urban environments. Hydrol Process 22:5107–5118. https://doi.org/10.1002/hyp.7148
Fewtrell TJ, Duncan A, Sampson CC et al (2011) Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data. Phys Chem Earth 36:281–291. https://doi.org/10.1016/j.pce.2010.12.011
Freni G, La Loggia G, Notaro V (2010) Uncertainty in urban flood damage assessment due to urban drainage modelling and depth–damage curve estimation. Water Sci Technol 61:2979–2993. https://doi.org/10.2166/wst.2010.177
Fuchs S, Birkmann J, Glade T (2012) Vulnerability assessment in natural hazard and risk analysis: current approaches and future challenges. Nat Hazards 64:1969–1975. https://doi.org/10.1007/s11069-012-0352-9
Fuchs S, Keiler M, Zischg A (2015) A spatiotemporal multi-hazard exposure assessment based on property data. Nat Hazards Earth Syst Sci 15:2127–2142. https://doi.org/10.5194/nhess-15-2127-2015
Fuchs S, Röthlisberger V, Thaler T et al (2017) Natural hazard management from a coevolutionary perspective: exposure and policy response in the European Alps. Ann Am Assoc Geogr 107:382–392. https://doi.org/10.1080/24694452.2016.1235494
Garrote J, Alvarenga FM, Díez-Herrero A (2016) Quantification of flash flood economic risk using ultra-detailed stage—damage functions and 2-D hydraulic models. J Hydrol 541:611–625. https://doi.org/10.1016/j.jhydrol.2016.02.006
González-Aguirre JC, Vázquez-Cendón ME, Alavez-Ramírez J (2016) Simulación numérica de inundaciones en Villahermosa México usando el código IBER. Ing del agua 20:201. https://doi.org/10.4995/ia.2016.5231
Green CH (2003) The handbook of water economics: principles and practice. Wiley, New York
Guinot V (2012) Multiple porosity shallow water models for macroscopic modelling of urban floods. Adv Water Resour 37:40–72. https://doi.org/10.1016/j.advwatres.2011.11.002
Horritt M, Bates PD (2002) Evaluation of 1D and 2D numerical models for predicting river flood inundation. J Hydrol 268:87–99. https://doi.org/10.1016/S0022-1694(02)00121-X
Hydrotec (2001) Hochwasser-Aktionsplan Angerbach (Flood action plan for the river Angerbach). Teil I: Berichte und Anlagen. Studie im Auftrag des Stua Dusseldorf. Aachen, Germany
Jonkman SN, Bočkarjova M, Kok M, Bernardini P (2008) Integrated hydrodynamic and economic modelling of flood damage in the Netherlands. Ecol Econ 66:77–90. https://doi.org/10.1016/j.ecolecon.2007.12.022
Kreibich H, Piroth K, Seifert I et al (2009) Is flow velocity a significant parameter in flood damage modelling? Nat Hazards Earth Syst Sci 9:1679–1692
Kumar M, Bhatt G, Duffy CJ (2009) An efficient domain decomposition framework for accurate representation of geodata in distributed hydrologic models. Int J Geogr Inf Sci 23:1569–1596. https://doi.org/10.1080/13658810802344143
McGrath H, Stefanakis E, Nastev M (2015) Sensitivity analysis of flood damage estimates: a case study in Fredericton, New Brunswick. Int J Disaster Risk Reduct 14:379–387. https://doi.org/10.1016/J.IJDRR.2015.09.003
Merz B, Thieken AH (2009) Flood risk curves and uncertainty bounds. Nat Hazards 51:437–458. https://doi.org/10.1007/s11069-009-9452-6
Merz B, Kreibich H, Schwarze R, Thieken A (2010) Assessment of economic flood damage. Nat Hazards Earth Syst Sci 10:1697–1724. https://doi.org/10.5194/nhess-10-1697-2010
Notaro V, De Marchis M, Fontanazza CM et al (2014) The effect of damage functions on urban flood damage appraisal. Procedia Eng 70:1251–1260. https://doi.org/10.1016/J.PROENG.2014.02.138
Ozdemir H, Sampson CC, de Almeida GAM, Bates PD (2013) Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data. Hydrol Earth Syst Sci 17:4015–4030. https://doi.org/10.5194/hess-17-4015-2013
Papathoma-Köhle M, Zischg A, Fuchs S et al (2015) Loss estimation for landslides in mountain areas—an integrated toolbox for vulnerability assessment and damage documentation. Environ Model Softw 63:156–169. https://doi.org/10.1016/J.ENVSOFT.2014.10.003
Papathoma-Köhle M, Gems B, Sturm M, Fuchs S (2017) Matrices, curves and indicators: a review of approaches to assess physical vulnerability to debris flows. Earth Sci Rev 171:272–288. https://doi.org/10.1016/J.EARSCIREV.2017.06.007
Qi H, Altinakar MS (2011) Simulation-based decision support system for flood damage assessment under uncertainty using remote sensing and census block information. Nat Hazards 59:1125–1143. https://doi.org/10.1007/s11069-011-9822-8
Röthlisberger V, Zischg AP, Keiler M (2017) Identifying spatial clusters of flood exposure to support decision making in risk management. Sci Total Environ 598:593–603. https://doi.org/10.1016/j.scitotenv.2017.03.216
Sampson CC, Fewtrell TJ, Duncan A et al (2012) Use of terrestrial laser scanning data to drive decimetric resolution urban inundation models. Adv Water Resour 41:1–17. https://doi.org/10.1016/j.advwatres.2012.02.010
Sampson CC, Fewtrell TJ, O’Loughlin F et al (2014) The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model. Hydrol Earth Syst Sci 18:2305–2324. https://doi.org/10.5194/hess-18-2305-2014
Schubert JE, Sanders BF (2012) Building treatments for urban flood inundation models and implications for predictive skill and modeling efficiency. Adv Water Resour 41:49–64. https://doi.org/10.1016/j.advwatres.2012.02.012
Staffler H, Pollinger R, Zischg A, Mani P (2008) Spatial variability and potential impacts of climate change on flood and debris flow hazard zone mapping and implications for risk management. Nat Hazards Earth Syst Sci 8:539–558. https://doi.org/10.5194/nhess-8-539-2008
Totschnig R, Sedlacek W, Fuchs S (2011) A quantitative vulnerability function for fluvial sediment transport. Nat Hazards 58:681–703. https://doi.org/10.1007/s11069-010-9623-5
Zischg A, Schober S, Sereinig N et al (2013) Monitoring the temporal development of natural hazard risks as a basis indicator for climate change adaptation. Nat Hazards 67:1045–1058. https://doi.org/10.1007/s11069-011-9927-0
Zischg AP, Mosimann M, Bernet DB, Röthlisberger V (2018) Validation of 2D flood models with insurance claims. J Hydrol 557:350–361. https://doi.org/10.1016/J.JHYDROL.2017.12.042
Acknowledgements
The authors thank the Swiss Federal Office for Statistics for providing the residential register, the Swiss Federal Office for Topography for providing the building dataset and the Canton of Bern, Switzerland for providing the Lidar terrain model. María Bermúdez gratefully acknowledges financial support from the Spanish Regional Government of Galicia (postdoctoral Grant reference ED481B 2014/156-0). Andreas Paul Zischg gratefully acknowledges financial support from the Swiss National Foundation (Grant No. IZK0Z2_170478/1).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
Bermúdez, M., Zischg, A.P. Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling. Nat Hazards 92, 1633–1648 (2018). https://doi.org/10.1007/s11069-018-3270-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-018-3270-7