How much does an extreme rainfall event cost? Material damage and relationships between insurance, rainfall, land cover and urban flooding

References

• Aerts, J.C.J.H. and Botzen, W.J.W., 2011. Climate change impacts on pricing long-term flood insurance: a comprehensive study for the Netherlands. Global Envrionmental Change, 21 (3), 1045–1060. Elsevier Ltd. doi:10.1016/j.gloenvcha.2011.04.005
   Web of Science ®Google Scholar
• André, C., et al., 2013. Contribution of insurance data to cost assessment of coastal flood damage to residential buildings: insights gained from Johanna (2008) and Xynthia (2010) storm events. Natural Hazards and Earth System Sciences, 13 (8), 2003–2012. doi:10.5194/nhess-13-2003-2013
   Web of Science ®Google Scholar
• Archetti, R., et al., 2011. Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach. Hydrology and Earth System Sciences, 15 (10), 3115–3122. doi:10.5194/hess-15-3115-2011
   Web of Science ®Google Scholar
• Aronica, G.T. and Lanza, L.G., 2005. Drainage efficiency in urban areas: a case study. Hydrological Processes, 19 (5), 1105–1119. doi:10.1002/hyp.5648
   Web of Science ®Google Scholar
• Atreya, A., Ferreira, S., and Michel-Kerjan, E., 2015. What drives households to buy flood insurance? New evidence from Georgia. Ecological Economics, 117, 153–161. doi:10.1016/j.ecolecon.2015.06.024
   Web of Science ®Google Scholar
• Barnolas, M. and Llasat, M.C., 2007. A flood geodatabase and its climatological applications: the case of Catalonia for the last century. Natural Hazards and Earth System Sciences, 7 (2), 271–281. doi:10.5194/nhess-7-271-2007
   Web of Science ®Google Scholar
• Barredo, J.I., 2009. Normalised flood losses in Europe: 1970–2006. Natural Hazards and Earth System Sciences, 9, 97–104. doi:10.5194/nhess-9-97-2009
   Web of Science ®Google Scholar
• Barrera, A., Llasat, M.C., and Barriendos, M., 2006. Estimation of extreme flash flood evolution in Barcelona County from 1351 to 2005. Natural Hazards and Earth System Sciences, 6 (4), 505–518. doi:10.5194/nhess-6-505-2006
   Web of Science ®Google Scholar
• Barthel, F. and Neumayer, E., 2012. A trend analysis of normalized insured damage from natural disasters. Climatic Change, 113 (2), 215–237. doi:10.1007/s10584-011-0331-2
   Web of Science ®Google Scholar
• Bernet, D.B., Prasuhn, V., and Weingartner, R., 2017. Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time. Natural Hazards and Earth System Sciences, 17 (9), 1659–1682. doi:10.5194/nhess-17-1659-2017
   Web of Science ®Google Scholar
• Botzen, W.J.W. and van den Bergh, J.C., 2008. Insurance against climate change and flooding in the Netherlands: present, future, and comparison with other countries. Risk Analysis, 28 (2), 413–426. doi:10.1111/j.1539-6924.2008.01035.x
   PubMed Web of Science ®Google Scholar
• Botzen, W.J.W. and van den Bergh, J.C., 2012. Risk attitudes to low-probability climate change risks: WTP for flood insurance. Journal of Economic Behaviour and Organization, 82 (1), 151–166. doi:10.1016/j.jebo.2012.01.005
   Web of Science ®Google Scholar
• Botzen, W.J.W., van den Bergh, J.C., and Bouwer, L.M., 2010. Climate change and increased risk for the insurance sector: a global perspective and an assessment for the Netherlands. Natural Hazards, 52 (3), 577–598. doi:10.1007/s11069-009-9404-1
   Web of Science ®Google Scholar
• Bouwer, L.M., 2011. Have disaster losses increased due to anthropogenic climate change? Bulletin of the American Meteorological Society, 92 (1), 39–46. doi:10.1175/2010BAMS3092.1
   Web of Science ®Google Scholar
• Brandão, C., Rodrigues, R., and Costa, J.P., 2001. Análise de fenómenos extremos: precipitações intensas em Portugal Continental. Lisboa: Direcção dos Serviços de Recursos Hídricos.
   Google Scholar
• Brázdil, R., Kundzewicz, Z.W., and Benito, G., 2006. Historical hydrology for studying flood risk in Europe. Hydrological Sciences Journal, 51 (October), 739–764. doi:10.1623/hysj.51.5.739
   Web of Science ®Google Scholar
• Bruni, G., et al., 2015. On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution. Hydrology and Earth System Sciences, 19 (2), 691–709. doi:10.5194/hess-19-691-2015
   Web of Science ®Google Scholar
• Butler, D. and Davies, J.W., 2004. Urban drainage. 2nd ed. London; Spon Press. doi:10.1017/CBO9781107415324.004
   Google Scholar
• Chen, W.B. and Liu, W.C., 2014. Modeling flood inundation induced by river flow and storm surges over a river basin. Water (Switzerland), 6 (10), 3182–3199. doi:10.3390/w6103182
   Google Scholar
• Cherqui, F., et al., 2015. Assessing urban potential flooding risk and identifying effective risk-reduction measures. Science of the Total Environment, 514, 418–425. doi:10.1016/j.scitotenv.2015.02.027
   PubMed Web of Science ®Google Scholar
• CNT, 2014. The Prevalence and Cost of Urban Flooding: A Case Study of Cook County, IL. Available from: http://www.cnt.org/sites/default/files/publications/CNT_PrevalenceAndCostOfUrbanFlooding2014.pdf [Accessed 18 Oct 2017].
   Google Scholar
• Condon, A.J. and Sheng, Y.P., 2012. Evaluation of coastal inundation hazard for present and future climates. Natural Hazards, 62 (2), 345–373. doi:10.1007/s11069-011-9996-0
   Web of Science ®Google Scholar
• Cortès, M., et al., 2018. The relationship between precipitation and insurance data for flood damages in a region of the Mediterranean (Northeast Spain). Natural Hazards and Earth System Sciences, Discuss, 18, 857–868. doi:10.5194/nhess-2017-278
   Web of Science ®Google Scholar
• Crompton, R.P. and McAneney, K.J., 2008. Normalised Australian insured losses from meteorological hazards: 1967-2006. Environmental Science and Policy, 11 (5), 371–378. doi:10.1016/j.envsci.2008.01.005
   Web of Science ®Google Scholar
• Dee, D.P., et al., 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137 (656), 553–597. doi:10.1002/qj.828
   Web of Science ®Google Scholar
• Diakakis, M., et al., 2016. Factors controlling the spatial distribution of flash flooding in the complex environment of a metropolitan urban area. The case of Athens 2013 flash flood event. International Journal of Disaster Risk Reduction, 18, 171–180. doi:10.1016/j.ijdrr.2016.06.010
   Web of Science ®Google Scholar
• Diakakis, M., Priskos, G., and Skordoulis, M., 2018. Public perception of flood risk in flash flood prone areas of Eastern Mediterranean: the case of Attica Region in Greece. International Journal of Disaster Risk Reduction, 28 (March), 404–413. doi:10.1016/j.ijdrr.2018.03.018
   Web of Science ®Google Scholar
• Douben, K.J., 2006. Characteristics of river floods and flooding: a global overview, 1985-2003. Irrigation and Drainage, 55 (SUPPL. 1), 25–27. doi:10.1002/ird.239
   Web of Science ®Google Scholar
• Elmer, F., et al., 2010. A Delphi method expert survey to derive standards for flood damage data collection. Risk Analysis, 30 (1), 107–124. doi:10.1111/j.1539-6924.2009.01325.x
   PubMed Web of Science ®Google Scholar
• Fragoso, M., et al., 2011. Assessment of frequency-magnitude of extreme rainfall events and flooding—Portugal. N1.2 Report WP1. Secoa—Solutions for Environmental contrasts in Coastal Areas, Project: 244251 FP7-ENV.2009.2.1.5.
   Google Scholar
• Fragoso, M., et al., 2010. The exceptional rainfall event in Lisbon on 18 February 2008. Weather, 65 (2), 31–35. doi:10.1002/wea.513
   Web of Science ®Google Scholar
• Freni, G., Loggia, G.L., and Notaro, V., 2010. Uncertainty in urban flood damage assessment due to urban drainage modelling and depth-damage curve estimation. Water Science Technology, 61 (12), 2979–2993. doi:10.2166/wst.2010.177
   PubMed Web of Science ®Google Scholar
• Goudenhoofdt, E. and Delobbe, L., 2013. Statistical characteristics of convective storms in Belgium derived from volumetric weather radar observations. Journal of Applied Meteorology and Climatology, 52 (4), 918–934. doi:10.1175/JAMC-D-12-079.1
   Web of Science ®Google Scholar
• Grahn, T. and Nyberg, L., 2017. Assessment of pluvial flood exposure and vulnerability of residential areas. International Journal of Disaster Risk Reduction, 21 (January), 367–375. Elsevier Ltd. doi:10.1016/j.ijdrr.2017.01.016
   Web of Science ®Google Scholar
• Guzzetti, F. and Tonelli, G., 2004. Information system on hydrological and geomorphological catastrophes in Italy (SICI): a tool for managing landslide and flood hazards. Natural Hazards and Earth System Sciences, 4 (2), 213–232. doi:10.5194/nhess-4-213-2004
   Web of Science ®Google Scholar
• Hoeppe, P., 2016. Trends in weather related disasters - Consequences for insurers and society. Weather and Climate and Extremes, 11, 70–79. Elsevier. doi:10.1016/j.wace.2015.10.002
   Web of Science ®Google Scholar
• Hung, H.C., 2009. The attitude towards flood insurance purchase when respondents’ preferences are uncertain: a fuzzy approach. Journal of Risk Research, 12 (2), 239–258. doi:10.1080/13669870802497702
   Web of Science ®Google Scholar
• Hurford, A.P., et al., 2012. The effectiveness of extreme rainfall alerts in predicting surface water flooding in England and Wales. International Journal of Climatology, 32 (11), 1768–1774. doi:10.1002/joc.2391
   Web of Science ®Google Scholar
• Jha, A.K., Bloch, R., and Lamond, J., 2012. Cities and flooding: a Guide to integrated urban flood risk management for the 21st century. World Bank. doi:10.1596/978-0-8213-8866-2
   Google Scholar
• Jongman, B., et al., 2014. Increasing stress on disaster-risk finance due to large floods. Nature Climate Change, 4 (4), 1–5. doi:10.1038/NCLIMATE2124
   Web of Science ®Google Scholar
• Lamond, J. and Penning-Rowsell, E., 2014. The robustness of flood insurance regimes given changing risk resulting from climate change. Climate Risk Management, 2, 1–10. Elsevier B.V. doi:10.1016/j.crm.2014.03.001
   Google Scholar
• Lave, T.R. and Lave, L.B., 1991. Public Perception of the Risks of Floods: implications for Communication. Risk Analysis, 11 (2), 255–267. doi:10.1111/j.1539-6924.1991.tb00602.x
   PubMed Web of Science ®Google Scholar
• Leal, M. and Ramos, C., 2013. Susceptibilidade às cheias na Área Metropolitana De Lisboa Norte: factores de predisposição e impactes das mudanças de uso do solo. Finisterra, 95, 17–40. doi:10.18055/Finis3129
   Google Scholar
• Leal, M., Ramos, C., and Pereira, S., 2018. Different types of flooding lead to different human and material damages: the case of the Lisbon Metropolitan Area. Natural Hazards, 91 (2), 735–758. Springer Netherlands. doi:10.1007/s11069-017-3153-3
   Web of Science ®Google Scholar
• Liberato, M.L.R., et al., 2012. Moisture sources and large-scale dynamics associated with a flash flood event. Geophysical Monographs Series, 200 (November), 111–126. doi:10.1029/2012GM001244
   Google Scholar
• Lo, A.Y., 2013. The likelihood of having flood insurance increases with social expectations. Area, 45 (1), 70–76. doi:10.1111/area.12002
   Web of Science ®Google Scholar
• Loster, T., 1999. Flood Trends and Global Change. Global Change Catastrophe Management, 1–7. Available from: http://fp.arizona.edu/kkh/hwrs/pdfs/trends/T-loster-Flood-Trends-summary-Reinsureance-Co.pdf
   Google Scholar
• McGrane, S.J., 2016. Impacts of urbanisation on hydrological and water quality dynamics, and urban water management: a review. Hydrological Sciences Journal, 61 (13), 2295–2311. doi:10.1080/02626667.2015.1128084
   Web of Science ®Google Scholar
• Merz, B., Elmer, F., and Thieken, A.H., 2009. Significance of ‘high probability/low damage’ versus ‘low probability/high damage’ flood events”. Natural Hazards and Earth System Sciences, 9, 1033–1046. doi:10.5194/nhess-10-3-2010
   Web of Science ®Google Scholar
• Merz, B., et al., 2004. Estimation uncertainty of direct monetary flood damage to buildings. Natural Hazards and Earth System Sciences, 4, 153–163. doi:10.5194/nhess-4-153-2004
   Web of Science ®Google Scholar
• Mills, E., 2005. Insurance in a Climate of Change. Science, 309 (5737), 1040–1044. doi:10.1126/science.1112121
   PubMed Web of Science ®Google Scholar
• Moncoulon, D., et al., 2014. Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff. Natural Hazards and Earth System Sciences, 14 (9), 2469–2485. doi:10.5194/nhess-14-2469-2014
   Web of Science ®Google Scholar
• Moreira, N., et al., 2008. Cheias de 18 de Fevereiro de 2008. Relatório DMC/CIME-01/2008. Lisbon, Portugal: Instituto de Meteorologia.
   Google Scholar
• Norbiato, D., et al., 2008. Flash flood warning based on rainfall thresholds and soil moisture conditions: an assessment for gauged and ungauged basins. Journal of Hydrology, 362 (3–4), 274–290. doi:10.1016/j.jhydrol.2008.08.023
   Web of Science ®Google Scholar
• Notaro, V., et al., 2014. The effect of damage functions on urban flood damage appraisal. Procedia Engineering, 70, 1251–1260. doi:10.1016/j.proeng.2014.02.138
   Google Scholar
• Oliveira, P.E. and Ramos, C., 2002. Inundações na cidade de Lisboa durante o século XX e seus factores agravantes. Finisterra, 37 (74), 33–54. doi:10.18055/Finis1589
   Google Scholar
• Patton, P., 1988. Drainage basin morphometry and floods. In: V. Baker, R.C. Kocher, and P. Patton, eds. Flood geomorphology. New York: Wiley, 51–65.
   Google Scholar
• Paudel, Y., Botzen, W.J.W., and Aerts, J.C.J.H., 2015. Influence of climate change and socio-economic development on catastrophe insurance: a case study of flood risk scenarios in the Netherlands. Regional Environmental Change, 15 (8), 1717–1729. doi:10.1007/s10113-014-0736-3
   Web of Science ®Google Scholar
• Petrucci, O., 2013. Brief communication the assessment of damage caused by historical landslide events. Natural Hazards and Earth System Sciences, 13 (3), 755–761. doi:10.5194/nhess-13-755-2013
   Web of Science ®Google Scholar
• Ramos, C. and Reis, E., 2002. Floods in southern Portugal : their physical and human causes. Mitigation and Adaptation Strategies for Global Change, 7 (3), 267–284. doi:10.1023/A:1024475529524
   Google Scholar
• Rashid, H., 2011. Interpreting flood disasters and flood hazard perceptions from newspaper discourse: tale of two floods in the Red River valley, Manitoba, Canada. Applied Geography, 31 (1), 35–45. doi:10.1016/j.apgeog.2010.03.010
   Web of Science ®Google Scholar
• Smith, K. and Ward, R., 1998. Floods: physical processes and human impacts. Chichester: Wiley.
   Google Scholar
• Sörensen, J. and Mobini, S., 2017. Pluvial, urban flood mechanisms and characteristics – assessment based on insurance claims. Journal of Hydrology, 555, 51–67. doi:10.1016/j.jhydrol.2017.09.039
   Web of Science ®Google Scholar
• Spekkers, M.H., Clemens, F.H.L.R., and Veldhuis, J.A.E.T., 2015. On the occurrence of rainstorm damage based on home insurance and weather data. Natural Hazards and Earth System Sciences, 15 (2), 261–272. doi:10.5194/nhess-15-261-2015
   Web of Science ®Google Scholar
• Spekkers, M.H., et al., 2013a. A statistical analysis of insurance damage claims related to rainfall extremes. Hydrology and Earth System Sciences, 17 (3), 913–922. doi:10.5194/hess-17-913-2013
   Web of Science ®Google Scholar
• Spekkers, M.H., et al., 5-7 September 2013b. Correlations between rainfall data and insurance damage data related to sewer flooding for the case of Aarhus, Denmark. In International Conference on Flood Resilience, Exp. Asia Eur, Exet, UK.
   Google Scholar
• Surminski, S., et al., 2015. Reflections on the current debate on how to link flood insurance and disaster risk reduction in the European Union. Natural Hazards, 79 (3), 1451–1479. doi:10.1007/s11069-015-1832-5
   Web of Science ®Google Scholar
• Thieken, A.H., et al., 2008. Methods for the evaluation of direct and indirect flood losses. In Fourth International Symposium on Flood Defence, Toronto, Canada, 1–10.
   Google Scholar
• Thieken, A.H., et al., 2007. Coping with floods: preparedness, response and recovery of flood-affected residents in Germany in 2002. Hydrological Sciences Journal, 52 (5), 1016–1037. doi:10.1623/hysj.52.5.1016
   Web of Science ®Google Scholar
• Thieken, A.H., et al., 2006. Insurability and mitigation of flood losses in private households in Germany. Risk Analysis, 26 (2), 383–395. doi:10.1111/j.1539-6924.2006.00741.x
   PubMed Web of Science ®Google Scholar
• Torgersen, G., et al., 2015. Correlation between extreme rainfall and insurance claims due to urban flooding – case study fredrikstad, Norway. Journal of Urban Environmental Engineering, 9 (2), 127–138. doi:10.4090/juee.2015.v9n2.127138
   Google Scholar
• Trigo, R.M., et al., 2016. The deadliest storm of the 20th century striking Portugal: flood impacts and atmospheric circulation. Journal of Hydrology, 541 (November), 597–610. doi:10.1016/j.jhydrol.2015.10.036
   Web of Science ®Google Scholar
• UNISDR, 2002. Guidelines for reducing flood losses. United Nations. Available from: https://www.unisdr.org/files/558_7639.pdf
   Google Scholar
• Yu, D. and Coulthard, T.J., 2015. Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model. Journal of Hydrology, 524, 385–400. doi:10.1016/j.jhydrol.2015.02.040
   Web of Science ®Google Scholar
• Zhou, Q., et al., 2013. Verification of flood damage modelling using insurance data. Water Science Technology, 68 (2), 425–432. doi:10.2166/wst.2013.268
   PubMed Web of Science ®Google Scholar