Advertisement

Using a fuzzy approach to assess adaptive capacity for urban water resources

  • J. Z. Zhang
  • L. W. Li
  • Y. N. Zhang
  • Y. F. Liu
  • W. L. Ma
  • Z. M. Zhang
Original Paper
  • 12 Downloads

Abstract

Adaptive capacity has become the focus of current research on climate change. A complete set of methods to assess the adaptive capacity for Beijing water resources was established in this study. Risk factors for water resources were identified by overlapping climate change, urbanization issues, and urban water resources, and a three-dimensional framework comprising 12 indicators specific to each risk factor was built to assess the adaptive capacity of the water resource systems. These three dimensions represent the three pillars of a sustainable water resource system: water supply, water demand, and water quality. An analytic hierarchy process was used to determine the weight for each indicator. Then a fuzzy version of the technique for order preference by similarity to an ideal solution was applied to calculate the ranking for the 11 districts in Beijing and quantify the adaptive capacity for water resources in these areas. The fuzzy approach results revealed that three indicators are key: comprehensive management capabilities for water supply, control capability for water demand, and management capabilities for water quality. Finally, adaptability proposals are proposed in accordance with the ranking results obtained.

Keywords

Adaptive capacity Analytic hierarchy process Climate change Technique for order preference by similarity to an ideal solution Triangular fuzzy number Water resources 

Notes

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (51408022), Major Science and Technology Program for Water Pollution Control and Treatment (No. 2015ZX07406001), Beijing Municipal Excellent Talent Training Foundation (No. 2013D005017000009) and Beijing Municipal Natural Science Foundation (No. 8154044).

References

  1. Adger WN, Vincent K (2005) Uncertainty in adaptive capacity. CR Geosci 337:399–410CrossRefGoogle Scholar
  2. Afshar A, Mariño MA, Saadatpour M, Afshar A (2011) Fuzzy TOPSIS multi-criteria decision analysis applied to Karun reservoirs system. Water Resour Manag 25(2):545–563CrossRefGoogle Scholar
  3. Adger WN, Brooks N, Bentham G, Agnew, M, Eriksen S (2004) New Indicators of vulnerability and adaptive capacity. Tyndall Centre Climate Change ResGoogle Scholar
  4. Arnell NW (1999) Climate Change And Global Water Resources. Global Environmental Change 9((suppl 1)):S31–S49CrossRefGoogle Scholar
  5. Barclay P (2013) Climate change adaptation in great lakes Cities. The University Of Michigan, Ann ArborGoogle Scholar
  6. Bergsma E, Gupta J, Jong P (2012) Does individual responsibility increase the adaptive capacity of society? The case of local water management in The Netherlands. Resour Conserv Recycl 64:13–22CrossRefGoogle Scholar
  7. Chen J-F, Hsieh H-N, Do QH (2015) Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Appl Soft Comput 28:100–108CrossRefGoogle Scholar
  8. Chitsaz N, Banihabib ME (2015) Comparison of different multi criteria decision-making models in prioritizing flood management alternatives. Water Res Manag 29:2503–2525CrossRefGoogle Scholar
  9. Culley S, Noble S, Yates A, Timbs M, Westra S, Maier HR, Giuliani M, Castelletti A (2016) A bottom-up approach to identifying the maximum operational adaptive capacity of water resource systems to a changing climate. Water Resour Res 52:6751–6768CrossRefGoogle Scholar
  10. El-Zein A, Tonmoy FN (2015) Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney. Ecol Ind 48:207–217CrossRefGoogle Scholar
  11. Engle NL (2011) Adaptive capacity and its assessment. Glob Environ Change 21:647–656CrossRefGoogle Scholar
  12. Giupponi C (2014) Decision support for mainstreaming climate change adaptation in water resources management. Water Resour Manage 28:4795–4808CrossRefGoogle Scholar
  13. Gogate NG, Kalbar PP, Raval PM (2017) Assessment of stormwater management options in urban contexts using multiple attribute decision-making. J Clean Prod 142(2):2046–2059CrossRefGoogle Scholar
  14. Gupta J, Termeer C, Klostermann J, Meijerink S, Van Den Brink M, Jong P, Nooteboom S, Bergsma E (2010) The adaptive capacity wheel: a method to assess the inherent characteristics of institutions to enable the adaptive capacity of society. Environ Sci Policy 13:459–471CrossRefGoogle Scholar
  15. Hao X, Xia J, Wang R (2010) influence of climate change on surface water environment. J China Hydrol 30:67–72Google Scholar
  16. Ioris AAR, Hunter C, Walker S (2008) The development and application of water management sustainability indicators in Brazil And Scotland. J Environ Manag 88:1190–1201CrossRefGoogle Scholar
  17. Junior FRL, Osiro L, Carpinetti LCR (2014) A comparison between fuzzy ahp and fuzzy topsis methods to supplier selection. Appl Soft Comput 21:194–209CrossRefGoogle Scholar
  18. Khazai B, Merz M, Schulz C, Borst D (2013) An integrated indicator framework for spatial assessment of industrial and social vulnerability to indirect disaster losses. Nat Hazards 67:145–167CrossRefGoogle Scholar
  19. Khir-Eldien K, Zahran SA (2016) Climate changes vulnerability and adaptive capacity. Springer, ChamCrossRefGoogle Scholar
  20. Kusangaya S, Warburton ML, Archer Van Garderen E, Jewitt GPW (2014) Impacts of climate change on water resources in Southern Africa: a review. Phys Chem Earth, Parts A/B/C 67:47–54CrossRefGoogle Scholar
  21. Li C, Li A (1999) The application of topsis method to comprehensive asse-ssment of environmental quality. J Geol Hazards Environ Preserv 10:10–14Google Scholar
  22. Li J, Zhang Y, Liu T (2013) Assessment method for cleaner production of vanadium extraction from stone coal. Environ Sci Technol 36:191–194Google Scholar
  23. Mosadeghi R, Warnken J, Tomlinson R, Mirfenderesk H (2015) Comparison of fuzzy-ahp and ahp in a spatial multi-criteria decision making model for urban land-use planning. Comput Environ Urban Syst 49:54–65CrossRefGoogle Scholar
  24. Olmstead SM (2014) Climate change adaptation and water resource management: a review of the literature. Energy Econ 46:500–509CrossRefGoogle Scholar
  25. Pahl-Wostl C, Knieper C (2014) The capacity of water governance to deal with the climate change adaptation challenge: using fuzzy set qualitative comparative analysis to distinguish between polycentric, fragmented and centralized regimes. Glob Environ Change 29:139–154CrossRefGoogle Scholar
  26. Pandey VP, Babel MS, Shrestha S, Kazama F (2011) A framework to assess adaptive capacity of the water resources system in Nepalese River Basins. Ecol Ind 11:480–488CrossRefGoogle Scholar
  27. Pelling M, High C (2005) Understanding adaptation: what can social capital offer assessments of adaptive capacity? Glob Environ Change 15:308–319CrossRefGoogle Scholar
  28. Pires A, Chang N-B, Martinho G (2011) An Ahp-based fuzzy interval topsis assessment for sustainable expansion of the solid waste management system in Setúbal Peninsula, Portugal. Resour Conserv Recycl 56:7–21CrossRefGoogle Scholar
  29. Pires A, Morato J, Peixoto H, Botero V, Zuluaga L, Figueroa A (2017) Sustainability assessment of indicators for integrated water resources management. Sci Total Environ 578:139–147CrossRefGoogle Scholar
  30. Rouillard JJ, Benson D, Gain AK (2014) Evaluating iwrm implementation success: are water policies in bangladesh enhancing adaptive capacity to climate change impacts? Int J Water Resour Dev 30:515–527CrossRefGoogle Scholar
  31. Schipper L, Burton I (2009) Understanding adaptation: origins, concepts, practice and policy. In: Schipper L, Burton I (eds) Adaptation to climate change. Earthscan, London, pp 1–8Google Scholar
  32. Shi Y, Gao XJ, Wu J, Giorgi F (2010) Simulating future climate changes over North China with a high resolution regional climate model. J Appl Meteorol Sci 21(5):580–589Google Scholar
  33. Simha P, Mutiara ZZ, Gaganis P (2017) Vulnerability assessment of water resources and adaptive management approach for Lesvos Island, Greece. Sustain Water Resour Manag 3:283–295CrossRefGoogle Scholar
  34. Wade AA, Hand BK, Kovach RP, Luikart G, Whited DC, Muhlfeld CC (2016) Accounting for adaptive capacity and uncertainty in assessments of species—climate change vulnerability. Conserv Biol 31:136–149CrossRefGoogle Scholar
  35. Widener JM, Gliedt TJ, Hartman P (2017) Visualizing dynamic capabilities as adaptive capacity for municipal water governance. Sustain Sci 12:203–219CrossRefGoogle Scholar
  36. Chen SJ, Hwang CL (1992) Fuzzy multiple attribute decision making methods. Fuzzy multiple attribute decision making: methods and applications. Berlin, HeidelbergGoogle Scholar
  37. Zeng Y, Li J, Cai Y, Tan Q (2017) Equitable and reasonable freshwater allocation based on a multi-criteria decision making approach with hydrologically constrained bankruptcy rules. Ecol Ind 73:203–213CrossRefGoogle Scholar
  38. Zhang D, Shi Y (2012) Numerical simulation of climate changes over North China by the regcm3 model. Chin J Geophys 55:2854–2866CrossRefGoogle Scholar
  39. Zhu L, Xu L (2011) analysis of effects of global change on terrestrial ecosystem. areal research and development. Areal Res Dev 30:161–165Google Scholar

Copyright information

© Islamic Azad University (IAU) 2018

Authors and Affiliations

  • J. Z. Zhang
    • 1
  • L. W. Li
    • 1
  • Y. N. Zhang
    • 2
  • Y. F. Liu
    • 1
    • 3
  • W. L. Ma
    • 1
  • Z. M. Zhang
    • 1
  1. 1.Beijing Climate Change Response Research and Education CenterBeijing University of Civil Engineering and ArchitectureBeijingChina
  2. 2.Research Institute of Petroleum Exploration and DevelopmentBeijingChina
  3. 3.China Academy of Urban Planning and DesignBeijingChina

Personalised recommendations