Advertisement

Water Resources Management

, Volume 32, Issue 8, pp 2847–2866 | Cite as

Investigation of the Behavior of an Agricultural-Operated Dam Reservoir Under RCP Scenarios of AR5-IPCC

  • Umut OkkanEmail author
  • Umut Kirdemir
Article

Abstract

In regions where the Mediterranean climate prevails, the agricultural sector and agricultural-operated dam reservoirs are threatened by climate change. In this respect, the prediction of hydro-meteorological changes that may occur in surface water resources under climate change scenarios is essential to examine the sustainability of reservoirs. In this paper, Demirköprü reservoir in the Gediz Basin/Turkey, a reservoir operated for irrigation purposes, was analyzed against the RCP4.5 and RCP 8.5 scenarios specified in the AR5 report of the IPCC. Projection period was evaluated as 2016-2050 water year period. First, statistical downscaling, Bayesian model averaging and quantile delta mapping bias correction techniques were respectively applied to monthly total precipitation and monthly average temperatures of meteorological stations in the region using 12 GCMs. According to RCP4.5 and RCP8.5, negligible reductions in precipitation are foreseen, while significant increases of 1.3 and 1.8 °C, respectively, are projected for temperatures under the same scenarios. Following the calibration of rainfall-runoff models for the sub-basins feeding the reservoir, streamflow simulations were also performed with projected precipitation and temperatures. In particular, according to the RCP 8.5 scenario, reservoir inflows during the period 2016-2050 could be reduced by 21% compared to the reference scenario results. Finally, the projected crop water demands and hydro-meteorological changes are evaluated together and the reservoir performances are examined using various indices. Assuming that the performance of the past irrigation yields will not change in the future, it is foreseen that reservoir’s sustainability will decrease by 16% under the RCP8.5 scenario. Even if the irrigation efficiency is increased by 40%, the reservoir cannot reach past sustainability characteristics.

Keywords

RCPs Downscaling Quantile delta mapping Reservoir performance indices 

Notes

Acknowledgments

This study was funded by the Scientific and Technological Research Council of Turkey under Grant No.114Y716. The authors also wish to thank the editors and the two anonymous reviewers for their constructive suggestions that improved the quality of our paper.

References

  1. Aich V, Liersch S, Vetter T et al (2014) Comparing impacts of climate change on streamflow in four large African river basins. Hydrol Earth Syst Sci 18:1305–1321CrossRefGoogle Scholar
  2. Akkuzu E, Unal HB, Karatas BS, Avci M, Asik S (2007) General irrigation planning performance of water user associations in the Gediz Basin in Turkey. J Irrig Drain Eng 133(1):17–26CrossRefGoogle Scholar
  3. Brekke LD, Maurer EP, Anderson JD et al (2009) Assessing reservoir operations risk under climate change. Water Resour Res 45:1–16CrossRefGoogle Scholar
  4. Cannon AJ, Sobie SR, Murdock TQ (2015) Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes? J Clim 28:6938–6959CrossRefGoogle Scholar
  5. Dibike YB, Gachon P, St-Hilaire A et al (2007) Uncertainty analysis of statistically downscaled temperature and precipitation regimes in Northern Canada. Theor Appl Climatol 91:149–170CrossRefGoogle Scholar
  6. DSİ (2006) Marmara Gölü Fizibilite Raporu (in Turkish, General Directorate of State Hydraulic Works-Marmara Lake Feasibility Report)Google Scholar
  7. Fischer G, Tubiello FN, Velthuizen H, Wiberg DA (2007) Climate change impacts on irrigation water requirements: effects of mitigation, 1990–2080. Technol Forecast Soc Chang 74:1083–1107CrossRefGoogle Scholar
  8. Fistikoglu O, Okkan U (2011) Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River basin in Turkey. J Hydrol Eng 16:157–164CrossRefGoogle Scholar
  9. Knutti R, Abramowitz G, Collins M, et al (2010) Good practice guidance paper on assessing and combining multi model climate projections. IPCC Expert Meet Assess Comb Multi Model Clim Proj 15ppGoogle Scholar
  10. Koirala S, Hirabayashi Y, Mahendran R, Kanae S (2014) Global assessment of agreement among streamflow projections using CMIP5 model outputs. Environ Res Lett 9(6):1–12CrossRefGoogle Scholar
  11. Kwon W, Baek H, Park E (2010) Probabilistic regional climate change projections using Bayesian model averaging. In: IPCC Expert Meeting on Assessing and Combining Multi Model Climate Projections. Boulder, Colorado, USA, p 69–70Google Scholar
  12. Li L, Xu H, Chen X, Simonovic SP (2010) Streamflow forecast and reservoir operation performance assessment under climate change. Water Resour Manag 24:83–104CrossRefGoogle Scholar
  13. Loucks DP (1997) Quantifying trends in system sustainability. Hydrol Sci J 42(4):513–530CrossRefGoogle Scholar
  14. McMahon TA, Adeloye AJ, Sen-Lin Z (2006) Understanding performance measures of reservoirs. J Hydrol 324:359–382CrossRefGoogle Scholar
  15. Moriasi DN, Arnold JG, Van Liew MW et al (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50:885–900CrossRefGoogle Scholar
  16. Okkan U, Fistikoglu O (2014) Evaluating climate change effects on runoff by statistical downscaling and hydrological model GR2M. Theor Appl Climatol 117:343–361CrossRefGoogle Scholar
  17. Okkan U, Inan G (2015) Statistical downscaling of monthly reservoir inflows for Kemer watershed in Turkey: use of machine learning methods, multiple GCMs and emission scenarios. Int J Climatol 35:3274–3295CrossRefGoogle Scholar
  18. Okkan U, Kirdemir U (2016) Downscaling of monthly precipitation using CMIP5 climate models operated under RCPs. Meteorol Appl 23:514–528CrossRefGoogle Scholar
  19. Olesen JE, Bindi M (2002) Consequences of climate change for European agricultural productivity, land use and policy. Eur J Agron 16:239–262CrossRefGoogle Scholar
  20. Parry ML, Rosenzweig C, Iglesias A et al (2004) Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Glob Environ Chang 14:53–67CrossRefGoogle Scholar
  21. Raftery AE, Gneiting T, Balabdaoui F, Polakowski M (2005) Using Bayesian model averaging to calibrate forecast ensembles. Mon Weather Rev 133:1155–1174CrossRefGoogle Scholar
  22. Raje D, Mujumdar PP (2010) Reservoir performance under uncertainty in hydrologic impacts of climate change. Adv Water Resour 33:312–326CrossRefGoogle Scholar
  23. Sachindra DA, Huang F, Barton A, Perera BJC (2014) Statistical downscaling of general circulation model outputs to precipitation-part 2: bias-correction and future projections. Int J Climatol 34:3282–3303CrossRefGoogle Scholar
  24. Satterthwaite D (2009) The implications of population growth and urbanization for climate change. Environ Urban 21(2):545–567CrossRefGoogle Scholar
  25. Solis SS, McKinney DC, Loucks DP (2011) Sustainability index for water resources planning and management. J Water Res Plan and Manag 137(5):381–390Google Scholar
  26. Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J (2013) Climate change 2013. The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate ChangeGoogle Scholar
  27. Vuuren DPV, Edmonds J, Kainuma M, Riahi K, Thomson et al (2011) The representative concentration pathways: an overview. Clim Chang 109:5–31CrossRefGoogle Scholar
  28. Wilby RL, Dawson CW, Barrow EM (2002) SDSM- a decision support tool for the assessment of regional climate change impacts. Environ Model Softw 17:145–157CrossRefGoogle Scholar
  29. Xu CY, Singh VP (2001) Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrol Process 15:305–319CrossRefGoogle Scholar
  30. Zhang L, Potter N, Hickel K et al (2008) Water balance modeling over variable time scales based on the Budyko framework - model development and testing. J Hydrol 360:117–131CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Civil Engineering, Hydraulic DivisionBalikesir UniversityBalikesirTurkey

Personalised recommendations