Climatic Change

, Volume 112, Issue 3–4, pp 881–899 | Cite as

Will climate change exacerbate water stress in Central Asia?

  • Tobias Siegfried
  • Thomas Bernauer
  • Renaud Guiennet
  • Scott Sellars
  • Andrew W. Robertson
  • Justin Mankin
  • Peter Bauer-Gottwein
  • Andrey Yakovlev
Article

Abstract

Millions of people in the geopolitically important region of Central Asia depend on water from snow- and glacier-melt driven international rivers, most of all the Syr Darya and Amu Darya. The riparian countries of these rivers have experienced recurring water allocation conflicts ever since the Soviet Union collapsed. Will climate change exacerbate water stress and thus conflicts? We have developed a coupled climate, land-ice and rainfall-runoff model for the Syr Darya to quantify impacts and show that climatic changes are likely to have consequences on runoff seasonality due to earlier snow-melt. This will increase water stress in unregulated catchments because less water will be available for irrigation in the summer months. Threats from geohazards, above all glacier lake outbursts, are likely to increase as well. The area at highest risk is the densely populated, agriculturally productive, and politically unstable Fergana Valley. Targeted infrastructural developments will be required in the region. If the current mismanagement of water and energy resources can be replaced with more effective resource allocation mechanisms through the strengthening of transboundary institutions, Central Asia will be able to successfully address these future climate-related challenges.

Supplementary material

10584_2011_253_MOESM1_ESM.pdf (148 kb)
(PDF 147 KB)

References

  1. Aizen VB, Aizen EM, Melack JM, Kreutz KJ, Cecil LDW (2004) Association between atmospheric circulation patterns and firn-ice core records from the Inilchek glacierized area, central Tien Shan, Asia. J Geophys Res 109(10.1029):D08304CrossRefGoogle Scholar
  2. Aizen VB, Aizen EM, Kuzmichonok VA (2007) Glaciers and hydrological changes in the Tien Shan: simulation and prediction. Environ. Res. Lett. 2:045019CrossRefGoogle Scholar
  3. Allen RG (2000) Using the FAO-56 dual crop coefficient method over an irrigated region as part of an evapotranspiration intercomparison study. J Hydrol 229(1–2):27–41CrossRefGoogle Scholar
  4. Armstrong R, Raup B, Khalsa SJS, Barry R, Kargel J, Helm C, Kieffer H (2005) GLIMS glacier database. Boulder, Colorado USA: National Snow and Ice Data Center. Digital mediaGoogle Scholar
  5. Bagla P (2009) No sign yet of Himalayan meltdown, Indian report finds. Science 326(5955):924CrossRefGoogle Scholar
  6. Bagla P (2010) Climate science leader Rajendra Pachauri confronts the critics. Science 327(5965):510CrossRefGoogle Scholar
  7. Barnett TP, Adam JC, Lettenmaier DP (2005) Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 438(7066):303–309CrossRefGoogle Scholar
  8. Bernauer T, Siegfried T (2011) Climate change and international water conflict in central asia. J Peace Res (forthcoming)Google Scholar
  9. Bucknall J, Klytchnikova I, Lampietti J, Lundell M, Scatasta M, Thurman M (2003) Irrigation in Central Asia—social, economic and environmental considerations. Tech. rep., The World BankGoogle Scholar
  10. Center for International Earth Science Information Network (CIESIN) (2010) Columbia University; United Nations Food and Agriculture Programme (FAO); and Centro Internacional de Agricultura Tropical (CIAT). Gridded Population of the World: Future Estimates (GPWFE)Google Scholar
  11. Cogley JG, Kargel JS, Kaser G, van der Veen CJ (2010) Tracking the source of glacier misinformation. Science 327(5965):522CrossRefGoogle Scholar
  12. Dyurgerov M, Meier MF, Bahr DB (2009) A new index of glacier area change: a tool for glacier monitoring. J Glaciol 55(192):710–716CrossRefGoogle Scholar
  13. ECMF (2009) Operational surface analysis datasetGoogle Scholar
  14. Giorgi F, Christensen J, Hulme M, von Storch H, Whetton P, Jones R, Mearns L, Fu C, Arritt R, Bates B, Benestad R, Boer G, Buishand A, Castro M, Chen D, Cramer W, Crane R, Crossly J, Dehn M, Dethloff K, Dippner J, Emori S, Francisco R, Fyfe J, Gerstengarbe F, Gutowski W, Gyalistras D, Hanssen-Bauer I, Hantel M, Hassell D, Heimann D, Jack C, Jacobeit J, Kato H, Katz R, Kauker F, Knutson T, Lal M, Landsea C, Laprise R, Leung L, Lynch A, May W, McGregor J, Miller N, Murphy J, Ribalaygua J, Rinke A, Rummukainen M, Semazzi F, Walsh K, Werner P, Widmann M, Wilby R, Wild M, Xue Y (2001) Climate change 2001: the scientific basis. Contribution of working group to the third assessment report of the intergouvernmental panel on climate change, chap. Regional Climate Information- Evaluation and Projections. Cambridge University Press, Cambridge, United Kingdom and New York, USAGoogle Scholar
  15. Gleditsch NP, Nordås R (2007) Climate change and conflict. Polit Geogr 26(6):627–638 (special issue)CrossRefGoogle Scholar
  16. Greene AM, Robertson AW, Smyth P, Triglia S (2011) Downscaling forecasts of Indian monsoon rainfall using a nonhomogeneous hidden Markov model. Q. J. R. Meteorol. Soc. doi:10.1002/qj.788
  17. Greuell W, Smeets P (2001) Variations with elevation in the surface energy balance on the Pasterze (Austria). J Geophys Res 106(D23):31717CrossRefGoogle Scholar
  18. Haeberli W, Beniston M (1998) Climate change and its impacts on glaciers and permafrost in the Alps. Ambio 27(4):258–265Google Scholar
  19. Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55CrossRefGoogle Scholar
  20. Immerzeel WW, van Beek LPH, Bierkens MFP (2010) Climate change will affect the asian water towers. Science 328:1382–1385CrossRefGoogle Scholar
  21. Kirshner S (2005) Modeling of multivariate time series using hidden Markov models. Ph.D. thesis, University of California, IrvineGoogle Scholar
  22. Malone EL (2010) Changing glaciers and hydrology in Asia—addressing vulnerabilities to glacier melt impacts. Tech. rep., USAIDGoogle Scholar
  23. Mearns R, Norton A (2010) Social dimensions of climate change: equity and vulnerability in a warming world. World Bank PublicationsGoogle Scholar
  24. Merton RK (1995) The Thomas theorem and the Matthew effect. Soc Forces 74(2):379–422Google Scholar
  25. MetzCanziani O, Palutikof J, Van Der Linden P, Hanson C B (2007) Climate change 2007: mitigation of climate change: contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change, illustrated edn. Cambridge University Press, CambridgeGoogle Scholar
  26. Micklin P (2007) The aral sea disaster. Annu Rev Earth Planet Sci 35:47–72CrossRefGoogle Scholar
  27. NAM Technical Reference and Model Documentation (2000) DHI - Water & Environment, DenmarkGoogle Scholar
  28. Nayar A (2009) When ice melts. Nature 461:1042–1046CrossRefGoogle Scholar
  29. Oerlemans J (2001) Glaciers and climate change. Taylor & FrancisGoogle Scholar
  30. Oerlemans J (2005) Extracting a climate signal from 169 glacier records. Science 308(5722):675CrossRefGoogle Scholar
  31. Parry ML, Canziani OF, Palutikof JP, Van Der Linden PJ, Hanson CE (2007) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University PressGoogle Scholar
  32. Pereira-Cardenal S, Riegels N, Berry PA, Smith R, Yakovlev A, Siegfried T, Bauer-Gottwein P (2011) Real-time remote sensing driven river basin modeling using radar altimetry. Hydrol Earth Syst Sci 15:241–254CrossRefGoogle Scholar
  33. Rabus B, Eineder M, Roth A, Bamler R (2003) The shuttle radar topography mission–a new class of digital elevation models acquired by spaceborne radar. ISPRS J Photogramm Remote Sens 57(4):241–262CrossRefGoogle Scholar
  34. Raskin P, Hansen E, Zhu Z, Stavsky D (1992) Simulation of water-supply and demand in the aral sea region. Water Int 17(2):55–67CrossRefGoogle Scholar
  35. Robertson AW, Kirshner S, Smyth P (2004) Downscaling of daily rainfall occurrence over Northeast Brazil using a hidden Markov model. J Clim 17(22):4407–4424CrossRefGoogle Scholar
  36. Robertson AW, Kirshner S, Smyth P, Charles SP, Bates BC (2006) Subseasonal-to-interdecadal variability of the Australian monsoon over North Queensland. Q J Royal Meteorol Soc 132(615):519–542CrossRefGoogle Scholar
  37. Robertson AW, Moron V, Swarinoto Y (2009) Seasonal predictability of daily rainfall statistics over Indramayu district, Indonesia. Int J Climatol 29:1449–1462CrossRefGoogle Scholar
  38. Schaefer JM, Denton GH, Barrell DJA, Ivy-Ochs S, Kubik PW, Andersen BG, Phillips FM, Lowell TV, Schluchter C (2006) Near-synchronous interhemispheric termination of the last glacial maximum in mid-latitudes. Science 312(5779):1510CrossRefGoogle Scholar
  39. Siegfried T, Bernauer T (2007) Estimating the performance of international regulatory regimes. Water Resour Res 43:W11406. doi:10.1029/2006WR005738 CrossRefGoogle Scholar
  40. Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M, Miller HL (2007) IPCC, 2007: Climate change 2007: the physical science basis. contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. New York, Cambridge University PressGoogle Scholar
  41. Swarup A (2010) Oxfam. Tech. rep., Oxfam International, Dushanbe, TajikistanGoogle Scholar
  42. The MathWorks (2003) MATLAB version R2011a, Natick, Massachusetts: The MathWorks IncGoogle Scholar
  43. The World Bank (2004) Water energy nexus in Central Asia: improving regional cooperation in the Syr Darya basin. Tech. rep., The World BankGoogle Scholar
  44. Timbal B, Hope P, Charles S (2008) Evaluating the consistency between statistically downscaled and global dynamical model climate change projections. J Clim 21:6052–6059CrossRefGoogle Scholar
  45. United Nations Department of Economic and Social Affairs (2007) World population Prospect—the 2006 Revision. Tech. rep., United NationsGoogle Scholar
  46. United Nations Department of Economic and Social Affairs (2011) Population Division, World Population Prospects: The 2010 Revision, New YorkGoogle Scholar
  47. Verbist K, Robertson AW, Cornelis W, Gabriëls D (2010) Seasonal predictability of daily rainfall characteristics in central-northern Chile for dry-land management. J Appl Meteoratol Clim 49(9):1938–1955CrossRefGoogle Scholar
  48. Wilby RL, Hay LE, Leavesley GH (1999) A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River basin, Colorado. J Hydrol 225(1–2):67–91CrossRefGoogle Scholar
  49. Wilson L (1973) Variations in mean annual sediment yield as a function of mean annual precipitation. Am J Sci 273(4):335CrossRefGoogle Scholar
  50. Yip S, Ferro CAT, Stephenson DB, Hawkins E (2010) A simple, coherent framework for partitioning uncertainty in climate predicitionsGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Tobias Siegfried
    • 1
  • Thomas Bernauer
    • 2
  • Renaud Guiennet
    • 3
  • Scott Sellars
    • 4
  • Andrew W. Robertson
    • 5
  • Justin Mankin
    • 6
  • Peter Bauer-Gottwein
    • 7
  • Andrey Yakovlev
    • 8
  1. 1.Hydrosolutions GmbHZurichSwitzerland
  2. 2.ETH Zurich, Center for International StudiesZurichSwitzerland
  3. 3.Department of Environmental EngineeringDTULyngbyDenmark
  4. 4.Center for Hydrometeorology and Remote SensingUniversity of CaliforniaIrvineUSA
  5. 5.International Research Institute for Climate and Society (IRI)Columbia UniversityPalisadesUSA
  6. 6.School of Earth SciencesStanford UniversityStanfordUSA
  7. 7.Department of Environmental EngineeringDTULyngbyDenmark
  8. 8.Uzbek Scientific Investigation and Survey Institute (UzGIP)Ministry of Agriculture and Water ResourcesTashkentUzbekistan

Personalised recommendations