Vulnerability assessment of Guyanese sugar to floods

  • Sasenarine Tomby
  • Jing ZhangEmail author


Climate change is an ongoing process that has profound impacts on global environment and economy. This study focused on floods impacting Guyanese sugar industry. The study developed a conceptual framework representing an agriculture system’s vulnerability to a climate change stimulus/stimuli to assist in selecting indicators that can more accurately and realistically represent vulnerability. The development of a conceptual framework followed the IPCC (2007) framework composing of three vulnerability factors, that is, exposure, sensitivity, and adaptive capacity; however, it added some novelty as to how each of these factors is defined, their relationships, sequence of their occurrences, and their attributes. This study uses an impact-based approach to identify sensitivity indicators by investigating the impacts of floods on Guyanese sugar. This methodology resulted in indicators that can realistically measure an agriculture system’s vulnerability to a climate change stimulus/stimuli. Multiple indicators were used to measure sugar vulnerability with experts’ opinions used to assign weights (by the Analytical Hierarchy Process) to both the vulnerability factors and their indicators to arrive at annual sugar vulnerability indexes for the period 2003 to 2016. The study showed that Guyanese sugar was highly vulnerable to floods and adaptation measures were identified to target specific indicators.



  1. Aleksandrova M, Gain KA, Giupponi C (2016) Assessing agricultural systems vulnerability to climate change to inform adaptation planning: an application in Khorezm, Uzbekistan. Mitig Adapt Strateg Glob Chang 21:1263–1287CrossRefGoogle Scholar
  2. Baldos ULC, Hertel TW (2014) Global food security in 2050: the role of agricultural productivity and climate change. Aust J Agric Resour Econ 58:554–570CrossRefGoogle Scholar
  3. Balica S, Wright NG (2009) A network of knowledge on applying an indicator-based methodology for minimizing flood vulnerability. Hydrol Process 23:2983–2986CrossRefGoogle Scholar
  4. Birkmann J, Cardona OD, Carreño ML, Barbat AH, Pelling M, Schneiderbauer S et al (2013) Framing vulnerability, risk and societal responses: the MOVE framework. Nat Hazards 67:193–212CrossRefGoogle Scholar
  5. Brito MM, Evers M, Höllermann B (2017) Prioritization of flood vulnerability, coping capacity and exposure indicators through the Delphi technique: a case study in Taquari-Antas basin, Brazil. Int J Disaster Risk Reduct 24:119–128CrossRefGoogle Scholar
  6. Calzadilla A, Rehdanz K, Betts R, Falloon P, Wiltshire A, Tol RS (2013) Climate change impacts on global agriculture. Clim Chang 120:357–374CrossRefGoogle Scholar
  7. Chang SE, Yip JZ, van Zijll de Jong SL, Chaster R, Lowcock A (2015) Using vulnerability indicators to develop resilience networks: a similarity approach. Nat Hazards 78:1827–1841CrossRefGoogle Scholar
  8. Eriksen SH, Kelly PM (2007) Developing credible vulnerability indicators for climate adaptation policy assessment. Mitig Adapt Strateg Glob Change 12:495–524CrossRefGoogle Scholar
  9. Fellmann T (2012) The assessment of climate change-related vulnerability in the agricultural sector: reviewing conceptual frameworks. In: Meybeck A, Lankoski J, Redfern S, Azzu N, Gitz V (eds) Building resilience for adaptation to climate change in the agriculture sector. Rome, Food and Agriculture Organization of the United Nations (FAO) and the Organization for Economic Co-operation and Development (OECD), (pp 37–61) Google Scholar
  10. Füssel H-M (2009) Review and quantitative analysis of indices of climate change exposure, adaptive capacity, sensitivity, and impacts. World Bank, Washington DCGoogle Scholar
  11. Füssel HM, Klein R (2006) Climate change vulnerability assessments: an evolution of conceptual thinking. Clim Chang 75(3):301–329CrossRefGoogle Scholar
  12. Goepel KD (2013) Implementing the analytic hierarchy process as a standard method for multi-criteria decision making in corporate enterprises – a new AHP excel template with multiple inputs. Proceedings of the International Symposium on the Analytic Hierarchy Process. Kuala LumpurGoogle Scholar
  13. Hinkel J (2011) “Indicators of vulnerability and adaptive capacity”: towards a clarification of the science–policy interface. Glob Environ Chang 21:198–208CrossRefGoogle Scholar
  14. Iglesias A, Garrote L, Quiroga S et al (2012) A regional comparison of the effects of climate change on agricultural crops in Europe. Climate Change 112(1):29–46CrossRefGoogle Scholar
  15. IPCC (2007) Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the International Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  16. Kelly PM, Adger WN (2000) Theory and practice in assessing vulnerability to climate change and facilitating adaptation. Climate Change 47(4):325–352CrossRefGoogle Scholar
  17. Khan S (2012) Vulnerability assessments and their planning implications: a case study of the Hutt Valley, New Zealand. Climate Change 64(2):1587–1607Google Scholar
  18. Klein RJ, Nicholls RJ (1999) Assessment of coastal vulnerability to climate change. Ambio 28(2):182–187Google Scholar
  19. Li Y, Xiong W, Hu W, Berry P, Ju H, Lin E et al (2015) Integrated assessment of China’s agricultural vulnerability to climate change: a multi-indicator approach. Clim Chang 128:355–366CrossRefGoogle Scholar
  20. Luers AL (2005) The surface of vulnerability: an analytical framework for examining environmental change. Glob Environ Chang 15:214–223CrossRefGoogle Scholar
  21. Mahato A (2014) Climate change and its impact on agriculture. Int J Sci Res Publ 4(4):1–6Google Scholar
  22. Malla G (2009) Climate change and its impact on nepalese agriculture. J Agric Environ 9:62–71.
  23. Mallari AE (2016) Climate change vulnerability assessment in the agriculture sector: typhoon Santi experience. Procedia Soc Behav Sci 216:440–451CrossRefGoogle Scholar
  24. Næss LO, Norland IT, Lafferty WM, Aall C (2006) Data and processes linking vulnerability assessment to adaptation decision-making on climate change in Norway. Glob Environ Chang 16:221–233CrossRefGoogle Scholar
  25. Pearson LJ, Nelson R, Crimp S, Langridge J (2011) Interpretive review of conceptual frameworks and research models that inform Australia’s agricultural vulnerability to climate change. Environ Model Softw 26:113–123CrossRefGoogle Scholar
  26. Perry LG, Andersen DC, Reynolds LV, Nelson SM, Shafroth PB (2012) Vulnerability of riparian ecosystems to elevated CO2 and climate change in arid and semiarid western North America - review. Glob Chang Biol 18:821–842CrossRefGoogle Scholar
  27. Schumann RA, Meyer JH, Van Antwerpen R (2000) A review of green manuring practices in sugarcane production. Proc South Africa Sugar Technol Assess 74:93–100Google Scholar
  28. Sivakumar MV, Das HP, Brunini O (2005) Impacts of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics. Climate Change 70(1–2):31–72CrossRefGoogle Scholar
  29. Smit B, Pilifosova O, Burton I, Challenger B, Huq S, Klein RJ et al (2001) Adaptation to climate change in the context of sustainable development and equity. Climate change 2001: impacts, adaptation, and vulnerability. In: McCarthy JJ, Canziani O, Leary NA, Dokken DJ, White KS (eds) Contribution of the Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 877–912Google Scholar
  30. Stephenson TS et al (2014) Changes in extreme temperature and precipitation in the Caribbean region, 1961–2010. Int J Climatol 34:2957–2971Google Scholar
  31. Stern N (2007) The economics of climate change: the Stern review. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  32. Tomby S, ZHANG J (2018) Impacts of climate change: floods and Guyana sugar industry. Int J Sci Res Publ 8(2):479–486Google Scholar
  33. UNFCCC (2007) Impacts, vulnerabilities and adaptation in developing countries. United Nations Framework Convention on Climate Change, GermanyGoogle Scholar
  34. WWF. (2004). Sugar and the environment: encouraging better management practices in sugar production. WWF, Zeist, The Netherlands: WWF Global Freshwater ProgrammeGoogle Scholar
  35. Xiong W, Lin E, Ju H et al (2007) Climate change and critical thresholds in China’s food security. Climate Change 81(2):205–221CrossRefGoogle Scholar
  36. Yankson PW, Owusu AB, Owusu G, Boakye-Danquah J, Tetteh JD (2017) Assessment of coastal communities’ vulnerability to floods using indicator-based approach: a case study of Greater Accra Metropolitan Area, Ghana. Nat Hazards 89:661–689CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Tongji Institute of Environment for Sustainable Development, College of Environmental Science and EngineeringTongji UniversityShanghaiChina
  2. 2.College of Environmental Science and EngineeringTongji UniversityShanghaiChina

Personalised recommendations