Estimating Direct and Indirect Damages from Storm Surges: The Case of Hamburg—Wilhelmsburg

References

• Barredo, J. I. [2009] “Normalised flood losses in Europe 1970–2006,” Nat. Hazards Earth Syst. 9, 97–104.
   Web of Science ®Google Scholar
• Barredo, J. I. , Salamon, P. &; Bódis, K. [2008] Towards an Assessment of Coastal Flood Damage Potential in Europe, JRC Scientific and Technical Reports EUR 23698 EN.
   Google Scholar
• Beniston, M. , Stephenson, D. B. & Christensen, O. B. [2007] “Future extreme events in European climate: An exploration of regional climate model projections,” Climatic Change 81, 71–95.
   Web of Science ®Google Scholar
• Berlemann, M. & Vogt, G. [2007] Kurzfristige Wachstumseffekte von Naturkatastrophen — Eine empirische Analyse der Flutkatastrophe vom August 2002 in Sachsen, Ifo Working Paper No. 52.
   Google Scholar
• Bockarjova, M. , Steenge, A. & van der Veen, A. [2004] “On direct estimation of initial damage in the case of major catastrophe derivation of the basic equation,” Disaster Prevention and Management 13(4), 330–336.
   Google Scholar
• Burzel, A. , Dassanayake, D. R. & Oumeraci, H. [2015] “Spatial modelling of tangible and intangible losses in integrated coastal flood risk analysis,” Coast. Eng. J. 57(1) 1540008.
   Google Scholar
• Burzel, A. , Dassanayake, D. R. , Naulin, M. , Kortenhaus, A. , Oumeraci, H. , Wahl, T. , Mudersbach, C. , Jensen, J. , Gönnert, G. , Sossidi, K. , Ujeyl G. & Pasche E. [2010] “Integrated risk analysis for extreme storm surges (XtremRisk Project),” Proc. 32nd Int. Conf. Coastal Eng. (ICCE) (Shanghai, China).
   Google Scholar
• Burzel, A. , Ujeyl, G. & Oumeraci, H. [2012] “Joint Research Project XtremRisK: Overview and Spatial Damage Modelling in Hamburg-Wilhelmsburg,” Proc. 10th Int. Conf. Hydroinformatics (Hamburg, Germany).
   Google Scholar
• Cavallo, E. & Noy, I. [2009] The Economics of Natural Disasters — A Survey, Inter-American Development Bank Working Paper 124.
   Google Scholar
• Chamber of Commerce Hamburg (2010) Company Database, Hamburg.
   Google Scholar
• European Commission [2008] NACE Rev. 2 — Statistical Classification of Economic Activities in the European Community, Eurostat Methodologies and Working Papers, ISSN 1977–0375.
   Google Scholar
• Flegg, A. T. & Webber, C. D. [1997] “On the appropriate use of location quotients in generating regional input-output tables: Reply,” Reg. Stud. 31(8), 795–805.
   Web of Science ®Google Scholar
• Gönnert, G. L. Gerkensmeier, B. [2015] “A multi-method approach to develop extreme storm surge events to strengthen the resilience of highly vulnerable coastal areas.” Coast. Eng. J. 57(1) 1540002.
   Google Scholar
• Guimaraes, P. et al. [1993] “Wealth and income effects of natural disasters: An econometric analysis of hurricane Hugo,” The Review of Regional Studies 23, 97–114
   Google Scholar
• Haimes, Y. & Jiang, P. [2001] “Leontief-based model of risk in complex interconnected infrastructures,” J. Infrastruct. Syst. 7, 1–12.
   Google Scholar
• Hallegatte, S. [2012] Modelling the Role of Inventories in the Assessment of Natural Disaster Economic Costs: Application on Hurricane Katrina in Louisiana, The World Bank Policy Research Working Paper 6047.
   Google Scholar
• Hallegatte, S. [2008] “An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina,” Risk Analysis 25(3), 779–799.
   Google Scholar
• Hallegatte, S. & Przyluski, V. [2010] The Economics of Natural Disasters — Concepts and Methods, Policy Research Working Paper 5507, World Bank.
   Google Scholar
• Jahn, M. [2013] Economics of Extreme Weather Events in Cities: Terminology and Regional Impact Models, HWWI Research Paper 143, Hamburg.
   Google Scholar
• Kowalewski, J. [2009] Methodology of the Input-Output Analysis, HWWI Research Paper 1–25, Hamburg.
   Google Scholar
• Kron, W. [2011] “Increasing weather losses in Europe: What they cost the insurance industry?” CESifo Forum 12(2), 73–87.
   Google Scholar
• Leiter, A. M. , Oberhofer, H. & Raschky, P. A. [2009] “Creative Disasters? Flooding effects on capital, labour and productivity within European firms,” Environmental Resource Economics 43, 333–350.
   Web of Science ®Google Scholar
• Ludwig, U. & Brautzsch, H. U. [2002] “The catastrophic flood at the social product in Germany,” Wirtschaft im Wandel 12, 353–359.
   Google Scholar
• Naulin, M. , Kortenhaus, A. & Oumeraci, H. [2015] “Reliability-based flood defense analysis in an integrated risk assessment,” Coast. Eng. J. 57(1) 1540005.
   Google Scholar
• Okuyama, Y. [2004] “Modeling spatial economic impacts of an earthquake: Input-output approaches,” Disaster Prevention and Management 13(4), 297–306.
   Google Scholar
• Okuyama, Y. , Hewings, G. & Sonis, M. [2004] “Measuring the economic impacts of disasters: Interregional input-output analysis using the sequential interindustry model,” in Modeling Spatial and Economic Impacts of Disasters , eds. Okuyama, Y. & Chang, S. (Springer, Heidelberg).
   Google Scholar
• Rath, S. [2007] Model Discretisation in 2D Hydroinformatics based on High Resolution Remote Sensing Data and the Feasibility of Automated model Parameterization, Ph.D Thesis, HamburgHarburg University of Technology, Hamburg, Germany.
   Google Scholar
• Rose, A. [2004] “Economic principles, issues, and research priorities in hazard loss estimation,” in Modelling Spatial and Economic Impacts of Disasters , eds. Okuyama, Y. and Chang, S. , pp. 13–36 (Springer, New York).
   Google Scholar
• Rose, A. & Liao, S.-Y. [2005] “Modelling regional economic resilience to disasters: A computable general equilibrium analysis of water service disruptions,” Journal of Regional Science 45, 75–112.
   Web of Science ®Google Scholar
• Rose, A. , Oladosu, G. & Liao, S.-Y. [2007] “Business interruption impacts of a terrorist attack on the electric power system of Los Angeles: Customer resilience to a total blackout,” Risk Anal. 23, 513–531.
   Google Scholar
• Santos, J. R. & Haimes, Y. Y. [2004] “Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures,” Risk Anal. 24, 1437–1451.
   PubMed Web of Science ®Google Scholar
• Statistical Office of Hamburg and Schleswig-Holstein [2011] District Database , http://www.statistik-nord.de/fileadmin/regional/regional.php.
   Google Scholar
• Statistical Office of Hamburg and Schleswig-Holstein [2010] Gross domestic product and value added at current prices for Hamburg.
   Google Scholar
• Sterr, H. , Klein, R. J. & Reese, S. [2000] Climate Change and Coastal Zones: An Overview of the State-of-the-art on Regional and Local Vulnerability Assessment, FEEM Working Paper 38.
   Google Scholar
• The European Parliament and the Council of the European Union [2007] Directive 2007/60/EC of the European Parliament and the Council of 23 October 2007 on the assessmtent and management of flood risks (Text with EE A relevance), Official Journal of the European Union L288/27.
   Google Scholar
• Ujevl, G. , Pasche, E. & Gershovich, I. [2010] Determination of significant waterstage and wave heights of the Elbe estuary in the area of Hamburg using a hydrodynamic 2D model, Presentation on the Storm Surge congress, Hamburg, Germany.
   Google Scholar
• Ujeyl et al. [2012] “Evaluating direct damages of residential and commercial assets on a micro scale — Results of the XtremRisK Project,” in Proc. 2nd European Conf. FLOODrisk Management Rotterdam.
   Google Scholar
• van der Veen, A. & Logtmeijer, C. [2005] “Economic hotspots: Visualizing vulnerability to flooding,” Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards , 36, 65–80.
   Web of Science ®Google Scholar
• Wahl, T. , Mudersbach, C. , Jensen, J. [2015] “Statistical assessment of storm surge scenarios within integrated risk analyses,” Coast. Eng. J. 57(1) 1540003.
   Google Scholar
• West, C. T. & Lenze, D. G. [1994] Modelling the Regional Impact of Natural Disasters and Recovery: A General Framework and an Application to Hurricane Andrew, International Regional Science Review 17, 121–150.
   Google Scholar