Determining the Uncertainty of Evaporation from Reservoir by Considering the Climate Change Conditions (Case Study: Dez Dam Reservoir)

Document Type : Research Paper

Authors

1 Department of Water Resources, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahwaz, Ahwaz, Iran .Email: Aligorgizade@gmail.com

2 Department of Hydrology and Water Resources, Faculty of Water Engineering, Shahid Chamran University of Ahvaz, Ahwaz, Iran

3 Faculty of Water Science and Engineering, Shahid Chamran University, Ahvaz, Iran

4 Faculty of Civil Engineering, Jondi-Shapour University, Dezful, Iran

Abstract

Human activities have led to increased greenhouse gas emissions in the atmosphere area and it caused internal climate changes. These influences are effective on the climate parameters, which increases the temperature rate and, consequently, elevates the rate of evaporation from the free surfaces. The reservoirs of dams are influenced directly by this temperature rise as the main place of water storage, causing the annual loss of a large amount of water in them due to the evaporation phenomenon. In this research, the effect of climate change on the evaporation from Dez dam reservoir was studied considering the uncertainty of climate change scenarios. Also, the changes occurring in temperature ranges and evaporation rates in future periods were examined under climate change scenarios. The results suggested that in the coming period of 2020-2044, the annual evaporation rate will increase in all three greenhouse gas emissions scenarios, and with a probability of occurrence of 90%, the highest evaporation rate would occur in May under the A1 scenario.

Keywords

References

  1. IPCC IPOCC, (2007). Climate Change 2007 - The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC. Science (80- ). doi: volume
  2. Abbasi F, Babaian I, Malboosi S et al., (2012). Assessment of Iran’s climate change in the future decades (2025-2100) by using micro-scaling of general circulation of atmosphere data. Quarterly journal of geographic research pp:17979–18005.
  3. Montazeri M, Fahmi H, (2003). Impacts of Climate Change on Water Resources of the Country [Iran].
  4. Chattopadhyay N, Hulme M, (1997). Evaporation and potential evapotranspiration in India under conditions of recent and future climate change. Agric For Meteorol. doi: 10.1016/S0168-1923(97)00006-3
  5. Dankers R, Christensen OB, (2005). Climate change impact on snow coverage, evaporation and river discharge in the sub-arctic Tana Basin, Northern Fennoscandia. Clim Change. doi: 10.1007/s10584-005-2533-y
  6. Lenters JD, Kratz TK, Bowser CJ, (2005). Effects of climate variability on lake evaporation: Results from a long-term energy budget study of Sparkling Lake, northern Wisconsin (USA). J Hydrol. doi: 10.1016/j.jhydrol.2004.10.028
  7. Donohue RJ, McVicar TR, Roderick ML, (2010). Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. J Hydrol. doi: 10.1016/j.jhydrol.2010.03.020
  8. Helfer F, Lemckert C, Zhang H, (2012). Impacts of climate change on temperature and evaporation from a large reservoir in Australia. J Hydrol. doi: 10.1016/j.jhydrol.2012.10.008
  9. Yang H, Yang D, (2012). Climatic factors influencing changing pan evaporation across China from 1961 to 2001. J Hydrol. doi: 10.1016/j.jhydrol.2011.10.043
  10. Wu L, Wang S, Bai X et al., (2017). Quantitative assessment of the impacts of climate change and human activities on runoff change in a typical karst watershed, SW China. Sci Total Environ. doi: 10.1016/j.scitotenv.2017.05.288
  11. Reshmidevi T V., Nagesh Kumar D, Mehrotra R, Sharma A, (2018). Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. J Hydrol. doi: 10.1016/j.jhydrol.2017.02.016
  12. Zahiri A, Shafai Bajestan M, Dehghani A, (2011). Estimation of Sediment Volume Due to Clay Flows in Dez Dam Reservoir. Journal of Water and Soil Conservation Studies 18 (1): pp:143–161.
  13. Afshin Y, (1990). Rivers of iran.
  14. Benzaghta MA, Mohammed TA, Ghazali AH, Soom MAM, (2012). Validation of Selected Models for Evaporation Estimation from Reservoirs Located in Arid and Semi-Arid Regions. Arabian Journal for Science and Engineering 37 (3): pp:521–534. doi: 10.1007/s13369-012-0194-5.
  15. Gorjizade A, Akhondali AM, Zarei H, Kaboli HS, (2014). Evaluation of Eight Evaporation Estimation Methods in a Semi-arid Region (Dez reservoir, Iran). Int. J. Adv. Biol. Biomed. Res.
  16. YAO H, (2009). Long-Term Study of Lake Evaporation and Evaluation of Seven Estimation Methods: Results from Dickie Lake, South-Central Ontario, Canada. J Water Resour Prot. doi: 10.4236/jwarp.2009.12010
  17. Winter TC, Rosenberry DO, Sturrock AM, (1995). Evaluation of 11 Equations for Determining Evaporation for a Small Lake in the North Central United States. Water Resour Res. doi: 10.1029/94WR02537
  18. Marengo JA, Chou SC, Torres RR et al., (2014). Climate Change in Central and South America: Recent Trends, Future Projections, and Impacts on Regional Agriculture. CGIAR Res. Progr. Clim. Chang. Agric. Food Secur.
  19. Dashtbozorgi A, Aljani B, Jafarpour Z, Shakiba A, (2015). Simulation of temperature limit indices of Khuzestan province based on RCP scenarios. Geography and environmental hazards pp:301–321.
  20. Masah Bavani A, Morid S, (2005). The effects of climate change on the flow of Zayandehrood River in Isfahan. Agricultural science and technology and natural resources pp:17–27.
  21. Ashofte P, Masah Bavani A, (2010). Impact of Climate Change on Maximum Discharges: Case Study of Aidoghmoush Basin, East Azerbaijan. Journal of Science and Technology of Agriculture and Natural Resources 14 (53): pp:28–38.
  22. Hosseinizade A, (2013). Feasibility of Impact of Future Climate Change on Groundwater Resources Considering Uncertainty Sources.
  23. Ekström M, Fowler HJ, Kilsby CG, Jones PD, (2005). New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 2. Future estimates and use in impact studies. Journal of Hydrology 300 (1–4): pp:234–251. doi: 10.1016/J.JHYDROL.2004.06.019.
  24. Bates BC, Charles SP, Hughes JP, (1998). Stochastic downscaling of numerical climate model simulations. Environmental Modelling & Software 13 (3–4): pp:325–331. doi: 10.1016/S1364-8152(98)00037-1.
  25. Green TR, Taniguchi M, Kooi H et al., (2011). Beneath the surface of global change: Impacts of climate change on groundwater. J Hydrol. doi: 10.1016/j.jhydrol.2011.05.002
  26. Barnett T, Malone R, Pennell W et al., (2004). The effects of climate change on water resources in the west: Introduction and overview. Clim Change. doi: 10.1023/B:CLIM.0000013695.21726.b8
  27. Aerts JCJH, Droogers P, (2004). Climate Change in contrasting river basins. Adaptation strategies for water for food and water for the environment.
  28. Semenov MA, Barrow EM, (1997). Use of a stochastic weather generator in the development of climate change scenarios. Clim Change. doi: 10.1023/A:1005342632279
  29. Qian B, Gameda S, Hayhoe H, (2008). Performance of stochastic weather generators LARS-WG and AAFC-WG for reproducing daily extremes of diverse Canadian climates. Clim Res. doi: 10.3354/cr00755
  30. Hashmi MZ, Shamseldin AY, Melville BW, (2011). Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch Environ Res Risk Assess. doi: 10.1007/s00477-010-0416-x
  31. Manual U, Semenov MA, Barrow EM, (2002). A Stochastic Weather Generator for Use in Climate Impact Studies. Weather
  32. Babaian I, Najafi Nik Z, (2010). Analysis of Climate Change in Khorasan Razavi Province in 2010-2010 Using GCM Model Output Microprojection. Journal of Geography and Regional Development 15 pp:1–19.
  33. Semenov MA, Stratonovitch P, (2010). Use of multi-model ensembles from global climate models for assessment of climate change impacts. Clim Res. doi: 10.3354/cr00836
  34. Pitari G, Ackerman A, Adams P et al., (2001). Aerosols, their Direct and Indirect Effects. Clim. Chang. 2001 Sci. Basis. Contrib. Work. Gr. I to Third Assess. Rep. Intergov. Panel Clim. Chang.
  35. Seyed Kaboli H, (2012). Determination of intensity, duration, and frequency curves under risk levels of climate change impacts in future periods with uncertainty sources.

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