Advertisement

Environmental Earth Sciences

, 75:1484 | Cite as

Spatial heterogeneity of local flood vulnerability indicators within flood-prone areas in Taiwan

  • Hsueh-Sheng Chang
  • Tzu-Ling ChenEmail author
Original Article

Abstract

Global environmental change is bringing extreme precipitation, and the combination of natural and artificial impacts are resulting in serious floods on the west coast of Taiwan. Disparity in social, economic and infrastructure resources contributes to spatial variation in the vulnerability to flood disaster. Owing to the high frequency of torrential rain and serious land subsidence in the study area, this paper attempts to categorize vulnerability indicators under varied assumptions of spatial homogeneity and spatial heterogeneity. The results show that the spatial heterogeneity indeed affects the distribution of flood vulnerability indicators. The core value of this article is that it measures the improvement from using geographically weighted statistics rather than traditional statistics. For the flood vulnerability discussion, this paper demonstrates the importance of considering spatial heterogeneity when allocating resources against floods.

Keywords

Flood vulnerability Spatial homogeneity Spatial heterogeneity 

References

  1. Abdi H, Williams LJ (2010) Principal component analysis. Wiley Interdisciplin Review Comput Stat 2:433–459CrossRefGoogle Scholar
  2. Balica SF (2007) Development and Application of Flood Vulnerability Indices for Various Spatial Scales, United Nations Educational, Scientific and Cultural Organization, Delft, the Netherlands-IHE Institute for Water EducationGoogle Scholar
  3. Balica SF (2012) Applying the flood vulnerability index as a knowledge base for flood risk assessment. Delft University of Technology, DelftGoogle Scholar
  4. Balica SF, Douben N, Wright NG (2009) Flood vulnerability indices at varying spatial scales. W Sci Technol 60(10):2571–2580CrossRefGoogle Scholar
  5. Barnett J, Lambert S, Fry I (2008) The hazards of indicators: insights from the environmental vulnerability index. Ann Assoc Am Geogr 98(1):102–119CrossRefGoogle Scholar
  6. Beek E (2006) Water resources development. UNESCO-IHE Institute, DelftGoogle Scholar
  7. Bizikova L, Bellali J, Habtezion Z, Diakhite M, Pinter L (2009) IEA Training Manual Volume Two: Vulnerability and Impact Assessments for Adaptation to Climate Change (via Module), United Nations Environment Program (United Nations Environment Program), KenyaGoogle Scholar
  8. Bruijn KM, Klijn F (2009) Risky places in the Netherlands: a first approximation for floods. J Flood Risk Manag 7:58–67CrossRefGoogle Scholar
  9. Cardona OD (2003) A need for rethinking the concept of vulnerability and risk from a holistic perspective: a necessary review and criticism for effective risk management. Available at: http://www.la-red.org/public/articulos/2003/nrcvrfhp/nrcvrfhp_ago-04-2003.pdf. Accessed 1 Mar 2016
  10. Connor RF, Hiroki K (2005) Development of a method for assessing flood vulnerability. W Sci Technol 51(5):61–67Google Scholar
  11. Cutter SL, Mitchell JT, Scott MS (1997) Handbook for conducting a GIS-Based hazards assessment at the Local Level. Report, South Carolina Emergency Preparedness Division, and Hazards Research Laboratory, Department of Geography, University of South CarolinaGoogle Scholar
  12. Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Quart 84(2):242–261CrossRefGoogle Scholar
  13. de Leon V, Carlos J (2006) Vulnerability—a conceptual and methodological review, vol 4. UNU Economic History Society, BonnGoogle Scholar
  14. Demšar U, Harris P, Brunsdon C, Fotheringham AS, McLoone S (2013) Principle component analysis on spatial data: an overview. Ann Assoc Am Geogr 103(1):106–128CrossRefGoogle Scholar
  15. Di Nauro C (2006) Regional vulnerability map for supporting policy definitions and implementation. In: Proceedings of the applied multi-risk mapping of natural hazards for impact assessment (ARMONIA), in Barcelona, Spain, pp. 1–12Google Scholar
  16. Dilley M (2005) Natural disaster hotspots: a global risk analysis. World Bank, WashingtonCrossRefGoogle Scholar
  17. Eakin H, Lerner A, Murtinho F (2010) Adaptive capacity in evolving peri-urban spaces: responses to flood risk in the Upper Lerma River Valley, Mexico. Glob Env Chang 20:14–22CrossRefGoogle Scholar
  18. Doubem KJ (2006) Characteristics of river floods and flooding: a global overview, 1985–2003. Irrig Drain 55:S9–S21CrossRefGoogle Scholar
  19. Environment Canada (1997) The Canada country study: climate impacts and adaptation, national summary for policymakers, OttawaGoogle Scholar
  20. Fotheringham AS, Brunsdon C, Charlton ME (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, ChichesterGoogle Scholar
  21. Gallopín GC (2006) Linkages between vulnerability, resilience, and adaptive capacity. Glob Environ Change 16(3):293–303CrossRefGoogle Scholar
  22. Gaume E, Gaál L, Viglione A, Szolgay J, Kohnová S, Blöschl G (2010) Bayesian MCMC approach to regional flood frequency analyses involving extraordinary flood events at ungauged sites. J Hydrol 394(1–2):101–117CrossRefGoogle Scholar
  23. Harris P, Brunsdon C, Charlton M (2011) Geographically weighted principal components analysis. Int J Geogr Inf Sci 25(10):1717–1736CrossRefGoogle Scholar
  24. Harris P, Clarke A, Juggins S, Brunsdon C, Charlton M (2014) Enhancements to a geographically weighted princiap component analysis in the context of an application to an environmental data set. Geogr Anal 47(2):146–172CrossRefGoogle Scholar
  25. Haughton, J (2004) Living with environment change: social vulnerability, adaptation and resilience in Vietnam: Edited by W. Neil Adger, P. Mick Kelly, and Nguyen Huu Ninh. Routledge, London and New York, 2002. XXI + 314 pp., index, $90.00.”, Journal of Comparative Economics Vol. 32 No. 2, pp. 367–369Google Scholar
  26. Hinkel J (2011) Indicators of vulnerability and adaptive capacity: towards a clarification of the science–policy interface. Glob Environ Change 21(1):198–208CrossRefGoogle Scholar
  27. Hotelling H (1933) Analysis of a Complex of Statistical Variables into Principal Components. J Educ Psychol 24:417–441CrossRefGoogle Scholar
  28. Hung HC, Chen LY (2012) An integrated assessment of vulnerability to typhoon and flood hazard in the ta-Chia river basin. J Geogr Sci 65:79–96Google Scholar
  29. IPCC (Intergovernmental Panel on Climate Change) (2014) Climate Change 2014: Impacts, Adaptation, and Vulnerability, A Special Report of Working Groups II of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New YorkGoogle Scholar
  30. Khan S (2012) Vulnerability assessments and their planning implications: a case study of the Hutt Valley. N Z Nat Hazards 64(2):1587–1607CrossRefGoogle Scholar
  31. Klein R (2004) Vulnerability indices—an academic perspective. In: Proceedings of the Expert Meeting, “Developing a Method for Addressing Vulnerability to Climate Change and Climate Change Impact Management: to Index or Not to Index?”, Bonn, GermanyGoogle Scholar
  32. Leichenko RM, O’Brien KL (2002) The dynamics of rural vulnerability to global change: the case of Southern Africa. Mitig Adapt Strateg Glob Change 7(1):1–18CrossRefGoogle Scholar
  33. Li J, Tan S (2015) Nonstationary flood frequency analysis for annual flood peak series, adopting climate indices and check dam index as covariates. W Resour Manag 29(5):5533–5550CrossRefGoogle Scholar
  34. Li JZ, Wang YX, Li SF, Hu R (2015) A nonstationary standardized precipitation index incorporating climate indices as covariates. J Geophys Res Atmos 120(23):12082–12095CrossRefGoogle Scholar
  35. Liverman DM (1990) Vulnerability to Global Change, Clark University, Earth Transformed Program, WorcesterGoogle Scholar
  36. Lloyd CD (2010) Analysing population characteristics using geographically weighted principal components analysis: a case study of Northern Ireland in 2001. Comput Enviro Urban Syst 34(5):389–399CrossRefGoogle Scholar
  37. Mehaffey ML, Wainger T, Wade D, Yankee E, Smith VB, Yarbourgh R (2008) Assessing vulnerability from alternative development patterns. Landsc Urban Plan 87(1):84–95CrossRefGoogle Scholar
  38. Messner F, Meyer V (2005) Flood damage, vulnerability and risk perception–challenges for flood damage research. UFZ-Umweltforschungszentrum, LeipzigGoogle Scholar
  39. Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Stationarity is dead: whither water management? Science 319(5863):573–574CrossRefGoogle Scholar
  40. Nandi D, Ashour AS, Samanta S, Chakraborty S, Salem MAM, Dey N (2015) Principle component analysis in medical image processing: a study. Int J Image Min 1(1):65–86CrossRefGoogle Scholar
  41. Obeysekera J, Salas JD (2014) Quantifying the uncertainty of design floods under nonstationary conditions. J Hydrol Eng 19(7):1438–1446CrossRefGoogle Scholar
  42. Pelling M (2003) The vulnerability of cities. In: Pelling M (ed) Natural disaster and social resilience. Earthscan Publications, SterlingGoogle Scholar
  43. Shi Y (2013) Population vulnerability assessment based on scenario simulation of rainstorm-induced waterlogging: a case study of Xuhui District, Shanghai City. Nat Hazard 66(2):1189–1203CrossRefGoogle Scholar
  44. Smit B, Wandel J (2006) Adaptation, adaptive capacity and vulnerability. Glob Environ Change 16(3):282–292CrossRefGoogle Scholar
  45. Smith K (2001) Environmental hazards: assessing risk and reducing disaster. Routledge, LondonGoogle Scholar
  46. Sterr RK, Klein RJ, Reese S (2003) Climate change and costal zones: an overview of the state-of-the-art on regional and local vulnerability assessment. In: Giupponi C, Shechlter M (eds) Climate change in the Mediterranean socio-economic perspective of impacts vulnerability and adaptation. Edward Elgar Publishing House, Cheltenham, pp 245–278Google Scholar
  47. Strupczewski WG, Kochanek KM, Bogdanowicz E, Markiewicz I, Feluch W (2016) Comparison of two nonstationary flood frequency analysis methods within the context of the variable regime in the representative Polish rivers. Acta Geophys 64(1):206–236CrossRefGoogle Scholar
  48. Sun AL, Shi C, Shi Y (2009) The preliminary inquiry of flood vulnerability space changes in coastal provinces and autonomous regions. Environ Sci Manag 34(3):36–40Google Scholar
  49. Sun X, Lall U, Merz B, Dung NV (2015) Hierarchical Bayesian clustering for nonstationary flood frequency analysis: application to trends of annual maximum flow in Germany. W Resour Res 51(8):6586–6601CrossRefGoogle Scholar
  50. Tabachnick BG, Fidell LS (2006) Using multivariate statistics, 5th edn. Allyn & Bacon, NeedhamGoogle Scholar
  51. Tobler WR (1970) A computer movie simulating urban growth in the Detroit region. Econ Geogr 46(Supplement):234–240CrossRefGoogle Scholar
  52. Turner BL, Kasperson RE, Matson PA, McCarthy JJ, Corell RW, Christensen L, Eckley N, Kasperson JX, Luers A, Martello ML, Polsky C, Pulsipher A, Schiller A (2003) A framework for vulnerability analysis in sustainability science. Proc Nat Acad Sci USA 100(14):8074–8079CrossRefGoogle Scholar
  53. UN (2015) Sendai framework for disaster risk reduction 2015–2030. United Nations Office for Disaster Risk ReductionGoogle Scholar
  54. UN/ISDR (2007) Hyogo framework for action 2005–2015: building the resilience of nations and communities to disasters. UN/ISDR, GenevaGoogle Scholar
  55. UNESCO-IHE (2007) Annual Report 2007. UNESCO-IHE Institute for Water EducationGoogle Scholar
  56. Villagrán C, Hazle G, Barrera F (2005) Hepáticas y Antocerotes del Archipiélago de Chile. Ediciones Museo Nacional de Historia NaturalGoogle Scholar
  57. Villarini G, Smith JA, Serinaldi F, Bales J, Bates PD, Krajewski WF (2009) Flood frequency analysis for nonstationary annual peak records in an urban drainage basin”. Adv W Resour 32(8):1255–1266CrossRefGoogle Scholar
  58. Walker G, Burningham K (2011) Flood risk, vulnerability and environmental justice: evidence and evaluation of inequality in a UK context. Crit Soc Polic 31(2):216–240CrossRefGoogle Scholar
  59. Wong DWS, Lee J (2008) Statistical analysis of geographic information with ArcView GIS and ArcGIS. Wiley, ChichesterGoogle Scholar
  60. Wu ZP, Hsiung KH (2009) Spatial analysis of urban fire risk. Chung Hua J Archit 3(3):1–12Google Scholar
  61. Wu JY, Huang YS (2011) The establishment of vulnerability evaluation indexed: the case of Shueili township, Nantou Taiwan. City Plan 38(2):195–218Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Urban PlanningNational Cheng-Kung UniversityTainanTaiwan

Personalised recommendations