Abstract
The use of different approaches in the development of flood damage models in various countries is expected to affect flood damage modelling at a regional or global scale. Since these models are often used as tools for disaster management and decision making, it is very needful to understand the comparative similarity and differences in countries’ loss models; this can help in the overall integration for developing regional risk models and cross-country risk assessment. In this study, empirically generated generalised loss models in three Asian countries (Sri Lanka, Thailand and Japan) were compared and applied to estimate potential flood damages in two different urban river basins. For each case study, each model was normalised using cost prices and floor areas (as applied to each country) and were integrated within the Geographic Information Systems (GIS) to estimate damages for the flood events. Using the mean vulnerability index of corresponding building types for the selected countries, a single model for regional flood risk assessment was created. However, the study showed that there are variations in the vulnerability and the potential flood damage estimates of similar global building types from the three countries, despite being developed by the same approach. These are attributed to the country’s specific conditions such as building regulations and codes, GDP per capita, cost price of building materials. Our results suggest that the average vulnerability index from the countries however reduced potential errors in the estimates. Moreover, it is proposed that the average regional vulnerability model derived with empirical data inputs from all the countries for regional risk assessment and cross-country comparison. Therefore, it can predict near accurate potential flood damages, which can serve as measures for regional flood disaster risk management plans.
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References
Ahmed M, Suphachalasai S (2014) Assessing the costs of climate change and adaptation in South Asia. Asian Development Bank, Mandaluyong
Carby BE (2014) Natural hazards in the Asia-Pacific region: recent advances and emerging concepts. In: Terry JP, Goff J. Geological Society special publication, vol 361. Geological Society, London, 225 pp. Price: UK£80.00. ISBN 978-1-86239-339-4 (hardback): Geological Journal, 49(2):215–216
Census (2012) Census of Population and Housing: Department of Census and Statistics, Ministry of Finance and Planning
Chormanski J, Okruszko T, Ignar S, Batelaan O, Rebel KT, Wassen MJ (2011) Flood mapping with remote sensing and hydrochemistry: a new method to distinguish the origin of flood water during floods. Ecol Eng 37(9):1334–1349
CIMNE EAI, INGENIAR, and ITEC (2013) Probabilistic modelling of natural risks at the global level: the hybrid loss exceedance curve, background. Paper prepared for the 2013 global assessment report on disaster risk reduction. United Nations Office of Disaster Risk Reduction, Geneva
DMC (2010) Integrated post flood assessment: disaster management centre. Ministry of Disaster Management, Colombo
Dransch D, Fohringer J, Poser KP, Lucas C (2013) Volunteered geographic information for disaster management. In: Silva CN (ed) Citizen E-participation in urban governance: crowdsourcing and collaborative creativity. IGI Global, Hershey, p 353
Dutta D, Herath S (2001) GIS based flood loss estimation modeling in Japan. In: Proceedings of the US-Japan 1st workshop on comparative study on urban disaster management, Port Island, Kobe, Japan, February 2001
Dutta D, Nakayama K (2009) Effects of spatial grid resolution on river flow and surface inundation simulation by physically based distributed modelling approach. Hydrol Process 23(4):534–545
Dutta D, Herath S, Musiake K (2003) A mathematical model for flood loss estimation. J Hydrol 277(1–2):24–49
Fahmida K (2005) Methodology for socio-economic vulnerability assessment for urban flood disaster risk management. Asian Institute of Technology, Khlong Luang
Finance TMO (2012) Thai flood 2011: rapid assessment for resilent recovery and reconstruction planning. The Thai Government and The World Bank, Bangkok
Flo-2D (2009) Flo-2D reference manual. FLO-2D Software Inc., Nutrioso
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 Science Technology WST 61(12):2979–2993
Gallegos HA, Schubert JE, Sanders BF (2012) Structural damage prediction in a high-velocity urban dam-break flood: field-scale assessment of predictive skill. Journal of Engineering Mechanics 138(10):1249–1262
Hanson S, Nicholls R, Ranger N, Hallegatte S, Corfee-Morlot J, Herweijer C, Chateau J (2010) A global ranking of port cities with high exposure to climate extremes. Clim Change 104(1):89–111
Herath S, Wang Y (2009) Incorporating wind damage in potential flood loss estimation. Glob Environ Res 13:151–159
Herath S, Dutta D, Musiake K (1999) Flood damage estimation of an urban catchment using remote sensing and GIS. In: Proceedings international conference on urban storm drainage 1999, vol 4, pp 2177–2185
Hijioka Y, Lin E, Pereirav JJ, Corlett RT, Cui X, Insarov GE, Lasco RD, Lindgren E, Surjanv A (2014) Asia. In: Barros VR, Field CB, Dokken DJ, Mastrandrea MD, Mach KJ, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 1327–1370
IGES Research Report (2015) Effectiveness of insurance for disaster risk reduction and climate change adaptation: challenges and opportunities. In: Prabhakar S, Pereira JJ, Gattineni Srinivasa Rao JMP, Scheyvens H, Cummins J (eds) Effectiveness of insurance for disaster risk reduction and climate change adaptation: challenges and opportunities. Institute for Global Environmental Strategies, Hayama, p 63
Islam MM, Ado KS (2000) Flood damage and management modelling using satellite remote sensing data with GIS: case study of Bangladesh. In: Proceedings remote sensing and hydrology 2000 (proceedings of a symposium held at April 2000). IAHS publ. no. 267, Santa Fe, New Mexico
Jaiswal k, Wald D, D’Ayala D (2011) Developing empirical collapse fragility functions for global building types. Earthquake Spectra 27(3):775–775
James L, Hall B (1986) Risk information for floodplain management. J Water Resour Plan Manag 112(4):485–499
JAXA (2014) ALOS research project—landuse landcover. Japan Aerospace Exploration Agency, Tsukuba
Jongman B, Kreibich H, Apel H, Barredo JI, Bates PD, Feyen L, Gericke A, Neal J, Aerts JCJH, Ward PJ (2012) Comparative flood damage model assessment: towards a European approach. Nat Hazards Earth Syst Sci 12:3733–3752
Jonkman SN, Bočkarjova M, Kok M, Bernardini P (2008) Integrated hydrodynamic and economic modelling of flood damage in the Netherlands. Ecol Econ 66(1):77–90
Komolafe AA, Herath S, Avtar R (2018a) Development of generalized loss functions for rapid estimation of flood damages: a case study in Kelani River basin, Sri Lanka. Appl Geomat 10(1):13–30
Komolafe AA, Herath S, Avtar R (2018b) Methodology to assess potential flood damages in urban areas under the influence of climate change. Nat Hazards Rev 19(2):05018001
Komolafe AA, Herath S, Avtar R (2018c) Sensitivity of flood damage estimation to spatial resolution. J Flood Risk Manag 11:S370–S381
Kreibich H, Piroth K, Seifert I, Maiwald H, Kunert U, Schwarz J, Merz B, Thieken AH (2009) Is flow velocity a significant parameter in flood damage modelling? Nat Hazards Earth Syst Sci 9(5):1679–1692
Mahagamage MGYL, Manage PM (2015) Mapping spatial distribution of water quality parameters of groundwater in the Kelani river basin in Sri Lanka using GIS. In: Proceeding of 11th international academic conference on development in science and technology (IACDST-2015), pp 3–5
Masqsood T, Wehner MHR, Edwards M, Dale K, Miller V (2013) GAR 15 regional vulnerability functions: reporting on the UNISDR/GA SE Asian regional workshop on structural vulnerability models for GAR global risk assessment, 11–14 November 2013, Geoscience Australia
Merz B, Kreibich H, Schwarze R, Thieken AH (2010) Assessment of economic flood damage. Nat Hazards Earth Syst Sci 10:1697–1724
MLITT (2001) Construction statistics guidebook: construction research and statistics office. Policy Bureau, Ministry of Land, Infracture, Transport and Tourism, Tokyo
MOC (1996) Flood damage statistics in Japan. Technical report. River Engineering Bureau, Ministry of Construction, Tokyo
Notaro V, De Marchis M, Fontanazza CM, La Loggia G, Puleo V, Freni G (2014) The effect of damage functions on urban flood damage appraisal. Procedia Eng 70:1251–1260
Penning-Rowsell EC, Chatterton JB (1979) The benefits of flood alleviation: a manual of assessment techniques. Gower Technical Press, Aldershot
Richard D (2014) UN report: 2014 Asia and Pacific Region Floods Cost US$16 Billion. http://floodlist.com/asia/report-asia-pacific-region-floods-cost-us16-billion-2014
Salimi S, Ghanbarpour MR, Solaimani K, Ahmadi MZ (2008) Floodplain mapping using hydraulic simulation model in GIS. J Appl Sci 8:660–665
Smith DI, Greeaway M (1988) Floohe computer assessment of urban flood damage. ANUFLOOD technical report. Desktop Planning, Melborne
Su MD, Kang J-L, Chang L-F, Chen AS (2005) A grid-based GIS approach to regional flood damage assessment. J Mar Sci Technol 13(3):184–192
Tang JS, Vongvisessomjai S, Sahasakmontri K (1992) Estimation of flood damage cost for Bangkok. Water Resour Manag 6(1):47–56
Tapia-Silva F-O, Itzerott S, Foerster S, Kuhlmann B, Kreibich H (2011) Estimation of flood losses to agricultural crops using remote sensing. Phys Chem Earth A/B/C 36(7–8):253–265
UN DESA Population Division (2012) World urbanization prospects: the 2011 revision. ESA/P/WP/224. United Nations Department of Economic and Social Affairs (UN DESA) Population Division, New York
UNESCO (2003) Chao Phraya River Basin, Thailand. World water assessment programme, 2003. UN world water development report 1: water for people, water for life, Chap. 16. UNESCO, Paris, pp 387–400
UNISDR (2009) Risk and power in a changing climate: invest today for a safer tomorrow. United Nations International Strategy for Disaster Reduction (UNISDR), Geneva
UNISDR (2013a) Global assessment report on disaster risk reduction: from shared risk to shared value: the business case for disaster risk reduction. United Nations Office of Disaster Risk Reduction (UNISDR), Geneva
UNISDR (2013b) Loss data and extensive/intensive risk analysis. United Nations office of Disaster Risk Reduction (UNISDR), Geneva
Walliman N, Ogden R, Baiche B, Tagg A, Escarameia M (2012) Development of a tool to estimate individual building vulnerability to floods. In: Pacetti M, Passerini G, Brebbia CA, Latini G (eds) The Sustainable City VII. WIT Press, New Forest National Park
White GF (1964) Choice of adjustment to floods: research paper, vol 93. Department of Geography, University of Chicago, Chicago
Acknowledgements
The authors appreciate the efforts of the Irrigation Department, Sri Lanka and the Asia Institute of Technology, Thailand for their active involvement in damage data acquisition. The authors thank the Japan Foundation for United Nations University (JFUNU) for awarding scholarship for this research. The authors thank the anonymous reviewer who contributed to enhance the clarity of the manuscript and expand the discussions.
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Komolafe, A.A., Herath, S., Avtar, R. et al. Comparative analyses of flood damage models in three Asian countries: towards a regional flood risk modelling. Environ Syst Decis 39, 229–246 (2019). https://doi.org/10.1007/s10669-018-9716-3
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DOI: https://doi.org/10.1007/s10669-018-9716-3