Event-based approach for probabilistic flood risk assessment

References

• Anagnos, T., Rojahn, C., and Kiremidjian, A.S., 1995. NCEER-ATC joint study on fragility of buildings. Buffalo, NY: National Center for Earthquake Engineering Research, State University of New York at Buffalo, Technical Report NCEER-95-0003.
   Google Scholar
• Anselmo, V., et al., 1996. Flood risk assessment using an integrated hydrological and hydraulic modelling approach: a case study. Journal of Hydrology, 175, 533–554. doi: 10.1016/S0022-1694(96)80023-0
   Web of Science ®Google Scholar
• Apel, H., et al., 2006. A probabilistic modelling system for assessing flood risks. Natural Hazards, 38 (1–2), 79–100. doi:10.1007/s11069-005-8603-7 doi: 10.1007/s11069-005-8603-7
   Web of Science ®Google Scholar
• Bartosova, A., et al., 2000. Using GIS to evaluate the effects of flood risk on residential property values. EPA conference. Economics Faculty Research and Publications, Milwaukee: Marquette University 1–35.
   Google Scholar
• Benjamin, J.R. and Cornell, C.A., 1970. Probability, statistics and decision for civil engineers. New York: McGraw Hill.
   Google Scholar
• CAPRA, Probabilistic Risk Assessment Program, 2013. Available from: http://www.ecapra.org/
   Google Scholar
• CENAPRED, 2004. Basic guide for elaborating the atlas of hazards and risks of states and municipalities, National System of Civil Protection (in Spanish).
   Google Scholar
• Chapman, T., 1998. Stochastic modelling of daily rainfall: the impact of adjoining wet days on the distribution of rainfall amounts. Environmental Modelling & Software, 13 (3–4), 317–324. doi:10.1016/S1364-8152(98)00036-X doi: 10.1016/S1364-8152(98)00036-X
   Web of Science ®Google Scholar
• Charba, J.P., Harrell III, A.W., and Lackner III, A.C., 1992. A monthly precipitation amount climatology derived from published atlas maps: development of a digital data base. NOAA, U.S. Department of Commerce, TDL Office Note 92-7, 20 pp.
   Google Scholar
• Chubey, M.S. and Hathout, S., 2004. Integration of RADARSAT and GIS modelling for estimating future Red River flood risk. GeoJournal, 59 (3), 237–246. doi:10.1023/B:GEJO.00000 26693.87089.83 doi: 10.1023/B:GEJO.0000026693.87089.83
   Google Scholar
• Correia, F. and Rego, F., 1998. Coupling GIS with hydrologic and hydraulic flood modelling. Water Resources Management, 12, 229–249. doi: 10.1023/A:1008068426567
   Web of Science ®Google Scholar
• Council of European Communities, 2007. Directive on the assessment and management of flood risks (2007/60/EC). Official Journal, L288, 27–34.
   Google Scholar
• Cressman, G.P., 1959. An operational objective analysis system. Monthly Weather Review, 87, 367–374. doi: 10.1175/1520-0493(1959)087<0367:AOOAS>2.0.CO;2
   Google Scholar
• De Risi, R., et al., 2013. Flood risk assessment for informal settlements. Natural Hazards. 69 (1), 1003–1032 doi:10.1007/ s11069-013-0749-0
   Web of Science ®Google Scholar
• Der Kiureghian, A. and Ditlevsen, O., 2009. Aleatory or epistemic? Does it matter?. Structural Safety, 31 (2), 105–112. doi:10.1016/j.strusafe.2008.06.020 doi: 10.1016/j.strusafe.2008.06.020
   Web of Science ®Google Scholar
• Dunkerley, D., 2008. Rain event properties in nature and in rainfall simulation experiments: a comparative review with recommendations for increasingly systematic study and reporting. Hydrological Processes, 22, 4415–4435. doi:10.1002/hyp doi: 10.1002/hyp.7045
   Web of Science ®Google Scholar
• Esteva, L., 1967. Criteria for the construction of seismic design spectra. 3rd Panamerican symposium on structures, Caracas, Venezuela (in Spanish).
   Google Scholar
• Forte, F., Pennetta, L., and Strobl, R.O., 2005. Historic records and GIS applications for flood risk analysis in the Salento peninsula (southern Italy). Natural Hazards and Earth System Science, 5 (6), 833–844. doi:10.5194/nhess-5-833-2005 doi: 10.5194/nhess-5-833-2005
   Web of Science ®Google Scholar
• Gambolati, G., Teatini, P., and Gonella, M., 2002. GIS simulations of the inundation risk in the coastal lowlands of the Northern Adriatic Sea. Mathematical and Computer Modelling, 35 (9–10), 963–972. doi:10.1016/S0895-7177(02)00063-8 doi: 10.1016/S0895-7177(02)00063-8
   Web of Science ®Google Scholar
• Glahnm, H.R., et al., 1985. Objective map analysis for the local AFOS MOS program. Silver Spring, MD: Techniques Development Laboratory, NOAA Technical Memorandum NWS TDL 75, 34 p.
   Google Scholar
• Haan, C.T., Allen, D.M., and Street, J.O., 1976. A Markov chain model of daily rainfall. Water Resources Research, 12 (3), 443–449. doi:10.1029/WR012i003p00443 doi: 10.1029/WR012i003p00443
   Web of Science ®Google Scholar
• Hall, J.W., Sayers, P.B., and Dawson, R.J., 2005. National-scale assessment of current and future flood risk in England and wales. Natural Hazards, 36 (1–2), 147–164. doi:10.1007/s11069-004-4546-7 doi: 10.1007/s11069-004-4546-7
   Web of Science ®Google Scholar
• HAZUS 99, 1999. Earthquake loss estimation methodology. Vol. 5, Chap. 5. Washington, DC: Federal Emergency Management Agency, FEMA and National Institute of Building Sciences (NIBS).
   Google Scholar
• Hsu, W.-K., et al., 2011. An integrated flood risk assessment model for property insurance industry in Taiwan. Natural Hazards, 58 (3), 1295–1309. doi:10.1007/s11069-011-9732-9 doi: 10.1007/s11069-011-9732-9
   Web of Science ®Google Scholar
• Huerta, B., Vega, B.E., and Avelar, C.E., 2007. Characterization of damage caused to structures and contents due to fluvial and coastal flooding. XV national congress on structural engineering, Puerto Vallarta, Jalisco (in Spanish).
   Google Scholar
• INEGI, National Institute of Statistics and Geography, 2012. Available from: http://www.inegi.org.mx
   Google Scholar
• Islam, M.M. and Sado, K., 2000. Development of flood hazard maps of Bangladesh using NOAA-AVHRR images with GIS. Hydrological Sciences Journal, 45 (3), 337–355. doi:10.1080/02626660009492334 doi: 10.1080/02626660009492334
   Web of Science ®Google Scholar
• Jaimes, M.A., et al., 2008. Estimation of losses in dwellings of asset poverty as a consequence of earthquakes, flooding and tropical cyclones in the Mexican Republic. XVI national congress on structural engineering Veracruz, Veracruz (in Spanish).
   Google Scholar
• Koivumäki, L., et al., 2010. Uncertainties in flood risk mapping: a case study on estimating building damages for a river flood in Finland. Journal of Flood Risk Management, 3 (2), 166–183. doi:10.1111/j.1753-318X.2010.01064.x doi: 10.1111/j.1753-318X.2010.01064.x
   Web of Science ®Google Scholar
• Kreibich, H., et al., 2009. Is flow velocity a significant parameter in flood damage modeling?. Natural Hazards and Earth Sciences, 9 (5), 1679–1692. doi: 10.5194/nhess-9-1679-2009
   Web of Science ®Google Scholar
• Krishnamurti, T.N. and Bounoua, L., 1996. An introduction to numerical weather prediction techniques. Boca Raton, FL: CRC Press, 293 pp.
   Google Scholar
• Lane, S.N., Landström, C., and Whatmore, S.J., 2011. Imagining flood futures: risk assessment and management in practice. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 369 (1942), 1784–1806. doi:10.1098/rsta.2010.0346 doi: 10.1098/rsta.2010.0346
   PubMed Web of Science ®Google Scholar
• Lascelles, B., et al., 2000. Spatial and temporal variation in two rainfall simulators: implications for spatially explicit rainfall simulation experiments. Earth Surface Processes and Landforms, 25, 709–721. doi: 10.1002/1096-9837(200007)25:7<709::AID-ESP126>3.0.CO;2-K
   Web of Science ®Google Scholar
• Melchers, R.E., 1999. Structural reliability analysis and prediction. 2nd ed. Chichester: John Wiley & Sons, 437 pp.
   Google Scholar
• Menabde, M., et al., 1997. Self-similar random fields and rainfall simulation. Journal of Geophysical Research, 102 (D12), 509–513.
   Google Scholar
• Merz, B. and Thieken, A.H., 2005. Separating natural and epistemic uncertainty in flood frequency analysis. Journal of Hydrology, 309, 114–132. doi:10.1016/j.jhydrol.2004.11.015 doi: 10.1016/j.jhydrol.2004.11.015
   Web of Science ®Google Scholar
• Merz, B. and Thieken, A.H., 2009. Flood risk curves and uncertainty bounds. Natural Hazards, 51 (3), 437–458. doi:10.1007/s11069–009-9452-6 doi: 10.1007/s11069-009-9452-6
   Web of Science ®Google Scholar
• Merz, B., Kreibich, H., and Schmidtke, R., 2004. Estimation uncertainty of direct monetary flood damage to buildings. Natural Hazards and Earth System Science, 4, 153–163. doi: 10.5194/nhess-4-153-2004
   Web of Science ®Google Scholar
• Meyer, V. and Messner, F., 2005. National flood damage evaluation methods: a review of applied methods in England, the Netherlands, the Czech Republic and Germany, UFZ-Discussion Papers, Department of Economics.
   Google Scholar
• Meyer, V., Haase, D., and Scheuer, S., 2007. GIS-based multicriteria analysis as decision support in flood risk management, UFZ-Diskussionspapiere, p. 60.
   Google Scholar
• Meyer, V., Haase, D., and Scheuer, S., 2009. Flood risk assessment in European river basins – concept, methods, and challenges exemplified at the Mulde River. Integrated Environmental Assessment and Management, 5 (1), 17–26. doi: 10.1897/IEAM_2008-031.1
   PubMedGoogle Scholar
• Morel-Seytoux, H.J., 1976. Optimization and uncertainty. Stochastic Approaches to Water Resources, 1. pp. 9–37
   Google Scholar
• Mostert, E. and Junier, S.J., 2009. The European flood risk directive: challenges for research. Hydrology and Earth System Sciences, 6, 4961–4988 ( Discussions 6). doi: 10.5194/hessd-6-4961-2009
   Google Scholar
• Murphy, C., Gardoni, P., and Harris, C.E., 2011. Classification and moral evaluation of uncertainties in engineering modeling. Science and Engineering Ethics, 17 (3), 553–570. doi:10.1007/s11948-010-9242-2 doi: 10.1007/s11948-010-9242-2
   PubMed Web of Science ®Google Scholar
• Nascimento, N., et al., 2005. Flood-damage curves: methodological development for the Brazilian context. 10th international conference on urban drainage, 21–26 August, Copenhagen, Denmark.
   Google Scholar
• Ologunorisa, T.E. and Abawua, M.J., 2005. Flood risk assessment: a review. Journal of Applied Sciences and Environmental Management, 9 (1), 57–63.
   Google Scholar
• Pappenberger, F. and Beven, K.J., 2006. Ignorance is bliss: or seven reasons not to use uncertainty analysis. Water Resources Research, 42 (5), 1–8. doi:10.1029/2005WR004820 doi: 10.1029/2005WR004820
   Web of Science ®Google Scholar
• Peterson, T.C., et al., 1998. Global Historical Climatology Network (GHCN) quality control of monthly temperature data. International Journal of Climatology, 18, 1169–1179. doi: 10.1002/(SICI)1097-0088(199809)18:11<1169::AID-JOC309>3.0.CO;2-U
   Web of Science ®Google Scholar
• Reese, S., Markau, H.J., and Sterr, H., 2003. MERK; Micro-Scale risk evaluation of flood-prone coastal lowlands, Research project on commission of the Federal Ministry of Research and the State of Schleswig-Holstein Government.
   Google Scholar
• Reeve, D.E., 2009. Risk and reliability: coastal and hydraulic engineering. London: SPON Press, 304 pp., ISBN 13: 978-0-415-46755-1.
   Google Scholar
• Roca, M. and Glasgow, G., 2010. Flood risk attribution to river defences. River Flow 2010, 8–9 September 2010, Germany.
   Google Scholar
• Ross, M.A. and Tara, P.D., 1993. Integrated hydrologic modeling with geographic information systems. Journal of Water Resources Planning and Management, 119 (2), 129–140. doi:10.1061/(ASCE)0733-9496(1993)119:2(129) doi: 10.1061/(ASCE)0733-9496(1993)119:2(129)
   Web of Science ®Google Scholar
• SCS (Soil Conservation Service), 1957. Use of storm and watershed characteristics in synthetic hydrograph analysis and application: V Mockus. Washington, DC: U.S. Dept. of Agriculture.
   Google Scholar
• Sharma, A. and Lall, U., 1999. A nonparametric approach for daily rainfall simulation. Mathematics and Computers in Simulation, 48 (4–6), 361–371. doi:10.1016/S0378-4754(99)00016-6 doi: 10.1016/S0378-4754(99)00016-6
   Web of Science ®Google Scholar
• Simm, J., et al., 2009. Representing fragility of flood and coastal defences: getting into the detail. Proceedings of the European conference on flood risk management research into practice (Floodrisk 2008), 30 September–2 October 2008, Oxford.
   Google Scholar
• Taggart, M. and Van de Lindt, J., 2009. Performance-based design of residential wood-frame buildings for flood based on manageable loss. Journal of Performance of Constructed Facilities, 23 (2), 56–64. doi: 10.1061/(ASCE)0887-3828(2009)23:2(56)
   Web of Science ®Google Scholar
• Teo, C.-K. and Grimes, D.I.F., 2007. Stochastic modelling of rainfall from satellite data. Journal of Hydrology, 346 (1–2), 33–50. doi:10.1016/j.jhydrol.2007.08.014 doi: 10.1016/j.jhydrol.2007.08.014
   Web of Science ®Google Scholar
• Thumerer, T., Jones, A., and Brown, D., 2000. A GIS based coastal management system for climate change associated flood risk assessment on the east coast of England. International Journal of Geographical Information Science, 14 (3), 265–281. doi: 10.1080/136588100240840
   Web of Science ®Google Scholar
• Tran, P., et al., 2009. GIS and local knowledge in disaster management: a case study of flood risk mapping in Vietnam. Disasters, 33 (1), 152–169. doi:10.1111/j.1467-7717.2008.01067.x doi: 10.1111/j.1467-7717.2008.01067.x
   PubMed Web of Science ®Google Scholar
• UNISDR, United Nations Office for Disaster Risk Reduction, 2011. Global assessment report on disaster risk reduction. Geneva: United Nations International Strategy for Disaster Reduction.
   Google Scholar
• USACE (U.S. Army Corps of Engineers), 2010. Hydrologic engineering centers river analysis system (HEC-RAS 4.1). Available from: http://www.hec.usace.army.mil/software/hec-ras/
   Google Scholar
• USACE (U.S. Army Corps of Engineers), 2013. Available from: http://www.nfrmp.us/frm_terminology.cfm#def40
   Google Scholar
• Van Manen, S.E. and Brinkhuis, M., 2005. Quantitative flood risk assessment for polders. Reliability Engineering & System Safety, 90 (2–3), 229–237. doi:10.1016/j.ress.2004. 10.002 doi: 10.1016/j.ress.2004.10.002
   Web of Science ®Google Scholar
• Vorogushyn, S., et al., 2010. A new methodology for flood hazard assessment considering dike breaches. Water Resources Research, 46, W08541 pp 1–17. doi: 10.1029/2009WR008475
   Web of Science ®Google Scholar
• Wang, Y., et al., 2011. A GIS-based spatial multi-criteria approach for flood risk assessment in the Dongting Lake Region, Hunan, Central China. Water Resources Management, 25 (13), 3465–3484. doi:10.1007/s11269-011-9866-2 doi: 10.1007/s11269-011-9866-2
   Web of Science ®Google Scholar
• Wen, Y.K. and Ellingwood, B.R., 2005. The role of fragility in consequence-based engineering. Earthquake Spectra, 21 (3), 861–877. doi: 10.1193/1.1979502
   Web of Science ®Google Scholar
• Wen, Y.K., Ellingwood, B.R., and Bracci, J., 2004. Vulnerability function framework for consequence-based engineering. Urbana, IL: Mid-America Earthquake Center, University of Illinois at Urbana Champaign, Report DS-4.
   Google Scholar
• West Jr, L. and Hess, T., 2002. Metadata as a knowledge management tool: supporting intelligent agent and end user access to spatial data. Decision Support Systems, 32, 247–264. doi: 10.1016/S0167-9236(01)00102-6
   Web of Science ®Google Scholar
• World Bank, 2005. Natural disaster hotspots: a global risk analysis. Disaster Risk Management Series No. 5, Hazard Management Unit, The World Bank.
   Google Scholar
• World Bank, 2012a. A guide to integrated urban flood risk management for the 21st century. (J. Abhas, R. Bloch, and J. Lamond, eds.) Washington, DC: The World Bank, p. 631.
   Google Scholar
• World Bank, 2012b. FONDEN: Mexico's natural disaster fund – a review. Washington, DC: The World Bank, p. 78.
   Google Scholar
• Xu, Z., et al., 2001. Integrated hydrologic modeling and GIS in water resources management. Journal of Computing in Civil Engineering, 15, 217–223. doi: 10.1061/(ASCE)0887-3801(2001)15:3(217)
   Web of Science ®Google Scholar
• Yang, C., et al., 2005. Spatial–temporal rainfall simulation using generalized linear models. Water Resources Research, 41 (W11415) pp 1–13. doi:10.1029/2004WR003739
   PubMedGoogle Scholar
• Youssef, A.M., Pradhan, B., and Hassan, A.M., 2011. Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environmental Earth Sciences, 62 (3), 611–623. doi:10.1007/ s12665-010-0551-1 doi: 10.1007/s12665-010-0551-1
   Web of Science ®Google Scholar
• Zerger, A., 2002. Examining GIS decision utility for natural hazard risk modelling. Environmental Modelling & Software, 17 (3), 287–294. doi:10.1016/S1364-8152(01)00071-8 doi: 10.1016/S1364-8152(01)00071-8
   Web of Science ®Google Scholar
• Zerger, A. and Smith, D.I., 2003. Impediments to using GIS for real-time disaster decision support. Computers, Environment and Urban Systems, 27 (2), 123–141. doi:10.1016/S0198-9715(01)00021-7 doi: 10.1016/S0198-9715(01)00021-7
   Google Scholar