Exploring the future hydropower production of a run-of-river type plant in the source region of the Tigris Basin (Türkiye) under CMIP6 scenarios

Year 2024, Volume: 9 Issue: 3, 463 - 491, 18.09.2024

Emrah Yalçın

https://doi.org/10.58559/ijes.1491603

Abstract

This assessment presents a framework for exploring the changing climate impacts on the energy production capacity of a run-of-river type plant, using the Basoren Weir and Hydropower Plant (HPP) as a case study. The Basoren Project is planned considering historical streamflow records in the source region of the Euphrates-Tigris River Basin (ETRB), which is a prominent hotspot warming at nearly double the global average rate. The quantification is built on precipitation and maximum/minimum temperature datasets from 24 Global Climate Models (GCMs) belonging to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under the moderate- and high-end Shared Socioeconomic Pathway (SSP) scenarios of SSP2-4.5 and SSP5-8.5, as well as the CMIP6 historical experiment (HEXP) scenario. The distribution mapping method is employed to adjust the raw GCM datasets for systematic biases. The Soil and Water Assessment Tool (SWAT) is preferred in producing daily runoff time series for the bias-adjusted simulations of each GCM over the historical (1988-2009) and three future (2025-2049, 2050-2074, and 2075-2099) periods. The ramifications of the changing climate on the Basoren HPP's energy production capacity are assessed based on the medians of the operational results reached for each GCM under the future societal development scenarios of SSP2-4.5 and SSP5-8.5, considering the medians achieved under the HEXP scenario as the reference case. The results indicate potential reductions in the mean yearly energy production of the Basoren HPP by 7.9%, 5.5%, and 5.3% under the SSP2-4.5 scenario, and by 5.8%, 8.0%, and 17.3% under the SSP5-8.5 scenario for the periods 2025-2049, 2050-2074, and 2075-2099, respectively. While declining spillway releases are expected to partly offset the impact of decreasing streamflow rates on energy production, the shift from a snow-dominated to a rain-dominated hydrologic regime necessitates re-optimizing the power capacities of the ETRB plants to maintain effective use of hydropower potential.

Keywords

Climate change, CMIP6, SWAT, Hydropower, Türkiye

References

• [1] Haddeland I, Heinke J, Biemans H, Eisner S, Flörke M, Hanasaki N, Konzmann M, Ludwig F, Masaki Y, Schewe J, Stacke T, Tessler ZD, Wada Y, Wisser D. Global water resources affected by human interventions and climate change. Proceedings of the National Academy of Sciences 2014; 111(9): 3251-3256.
• [2] IPCC (Intergovernmental Panel on Climate Change). Climate change 2021: The physical science basis, contribution of working group I to the IPCC sixth assessment report. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds). Cambridge University Press, Cambridge and New York, 2021.
• [3] Konapala G, Mishra AK, Wada Y, Mann ME. Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nature Communications 2020; 11: 3044.
• [4] Piao S, Ciais P, Huang Y, Shen Z, Peng S, Li J, Zhou L, Liu H, Ma Y, Ding Y, Friedlingstein P, Liu C, Tan K, Yu Y, Zhang T, Fang J. The impacts of climate change on water resources and agriculture in China. Nature 2010; 467: 43-51.
• [5] Pokhrel Y, Felfelani F, Satoh Y, Boulange J, Burek P, Gädeke A, Gerten D, Gosling SN, Grillakis M, Gudmundsson L, Hanasaki N, Kim H, Koutroulis A, Liu J, Papadimitriou L, Schewe J, Schmied HM, Stacke T, Telteu C-E, Thiery W, Veldkamp T, Zhao F, Wada Y. Global terrestrial water storage and drought severity under climate change. Nature Climate Change 2021; 11: 226-233.
• [6] Dolan F, Lamontagne J, Link R, Hejazi M, Reed P, Edmonds J. Evaluating the economic impact of water scarcity in a changing world. Nature Communications 2021; 12: 1915.
• [7] Monier E, Paltsev S, Sokolov A, Chen Y-HH, Gao X, Ejaz Q, Couzo E, Schlosser CA, Dutkiewicz S, Fant C, Scott J, Kicklighter D, Morris J, Jacoby H, Prinn R, Haigh M. Toward a consistent modeling framework to assess multi- sectoral climate impacts. Nature Communications 2018; 9: 660.
• [8] Almeida RM, Fleischmann AS, Brêda JPF, Cardoso DS, Angarita H, Collischonn W, Forsberg B, García- Villacorta R, Hamilton SK, Hannam PM, Paiva R, Poff NL, Sethi SA, Shi Q, Gomes CP, Flecker AS. Climate change may impair electricity generation and economic viability of future Amazon hydropower. Global Environmental Change 2021; 71: 102383.
• [9] Ceribasi G, Caliskan M. Short- and long-term prediction of energy to be produced in hydroelectric energy plants of Sakarya Basin in Turkey. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2023; 45(1): 2680-2695.
• [10] Ceribasi G, Ceyhunlu AI, Wałęga A, Młyński D. Investigation of the effect of climate change on energy produced by hydroelectric power plants (HEPPs) by trend analysis method: A case study for Dogancay I–II HEPPs. Energies 2022; 15(7): 2474.
• [11] Gernaat DEHJ, de Boer HS, Daioglou V, Yalew SG, Müller C, van Vuuren DP. Climate change impacts on renewable energy supply. Nature Climate Change 2021; 11: 119-125.
• [12] IHA (International Hydropower Association). Hydropower status report 2018. International Hydropower Association, Paris, 2018.
• [13] Pereira-Cardenal SJ. Water-energy modelling: Adaptation to water scarcity. Nature Energy 2016; 1: 16004.
• [14] Pir H, Ceribasi G, Ceyhunlu AI. The effect of climate change on energy generated at hydroelectric power plants: A case of Sakarya river basin in Turkey. Renewable Energy 2024; 223: 120077.
• [15] van Vliet MTH, Wiberg D, Leduc S, Riahi K. Power-generation system vulnerability and adaptation to changes in climate and water resources. Nature Climate Change 2016; 6: 375-380.
• [16] Yalew SG, van Vliet MTH, Gernaat DEHJ, Ludwig F, Miara A, Park C, Byers E, Cian ED, Piontek F, Iyer G, Mouratiadou I, Glynn J, Hejazi M, Dessens O, Rochedo P, Pietzcker R, Schaeffer R, Fujimori S, Dasgupta S, Mima S, da Silva SRS, Chaturvedi V, Vautard R, van Vuuren DP. Impacts of climate change on energy systems in global and regional scenarios. Nature Energy 2020; 5: 794-802.
• [17] Zhou Q, Hanasaki N, Fujimori S, Masaki Y, Hijioka Y. Economic consequences of global climate change and mitigation on future hydropower generation. Climatic Change 2018; 147: 77-90.
• [18] Carvajal PE, Anandarajah G, Mulugetta Y, Dessens O. Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble - The case of Ecuador. Climatic Change 2017; 144: 611-624.
• [19] Lumbroso DM, Woolhouse G, Jones L. A review of the consideration of climate change in the planning of hydropower schemes in sub-Saharan Africa. Climatic Change 2015; 133: 621-633.
• [20] Mukheibir P. Potential consequences of projected climate change impacts on hydroelectricity generation. Climatic Change 2013; 121: 67-78.
• [21] Natalia P, Silvia F, Silvina S, Miguel P. Climate change in northern Patagonia: Critical decrease in water resources. Theoretical and Applied Climatology 2020; 140: 807-822.
• [22] Sharma N, Mishra BK, Baral S. Climate change impacts on Seti Gandaki River flow from hydropower perspectives, Nepal. Sustainable Water Resources Management 2024; 10: 28.
• [23] Liu X, Tang Q, Voisin N, Cui H. Projected impacts of climate change on hydropower potential in China. Hydrology and Earth System Sciences 2016; 20(8): 3343-3359.
• [24] Ali SA, Aadhar S, Shah HL, Mishra V. Projected increase in hydropower production in India under climate change. Scientific Reports 2018; 8: 12450.
• [25] Hurford AP, Harou JJ, Bonzanigo L, Ray PA, Karki P, Bharati L, Chinnasamy P. Efficient and robust hydropower system design under uncertainty - A demonstration in Nepal. Renewable and Sustainable Energy Reviews 2020; 132: 109910.
• [26] Meng Y, Liu J, Leduc S, Mesfun S, Kraxner F, Mao G, Qi W, Wang Z. Hydropower production benefits more from 1.5°C than 2°C climate scenario. Water Resources Research 2020; 55: e2019WR025519.
• [27] O’Neill BC, Tebaldi C, van Vuuren DP, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J-F, Lowe J, Meehl GA, Moss R, Riahi K, Sanderson BM. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development 2016; 9(9): 3461-3482.
• [28] Riahi K, van Vuuren DP, Kriegler E, Edmonds J, Neill BCO, Fujimori S, Bauer N, Calvin K, Dellink R, Fricko O, Lutz W, Popp A, Cuaresma JC, Samir KC, Leimbach M, Jiang L, Kram T, Rao S, Emmerling J, Ebi K, Hasegawa T, Havlik P, Humpenöder F, Da Silva LA, Smith S, Stehfest E, Bosetti V, Eom J, Gernaat D, Masui T, Rogelj J, Strefler J, Drouet L, Krey V, Luderer G, Harmsen M, Takahashi K, Baumstark L, Doelman JC, Kainuma M, Klimont Z, Marangoni G, Lotze-Campen H, Obersteiner M, Tabeau A, Tavoni M. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change 2017; 42: 153- 168.
• [29] Cook BI, Mankin JS, Marvel K, Williams AP, Smerdon JE, Anchukaitis KJ. Twenty-first century drought projections in the CMIP6 forcing scenarios. Earth's Future 2020; 8(6): e2019EF001461.
• [30] Dosio A, Jury MW, Almazroui M, Ashfaq M, Diallo I, Engelbrecht FA, Klutse NAB, Lennard C, Pinto I, Sylla MB, Tamoffo AT. Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models. Climate Dynamics 2021; 57: 3135-3158.
• [31] Turner AG, Annamalai H. Climate change and the South Asian summer monsoon. Nature Climate Change 2012; 2: 587-595.
• [32] Lee D-K, Cha D-H. Regional climate modeling for Asia. Geoscience Letters 2020; 7: 13.
• [33] Daggupati P, Srinivasan R, Ahmadi M, Verma D. Spatial and temporal patterns of precipitation and stream flow variations in Tigris-Euphrates river basin. Environmental Monitoring and Assessment 2017; 189(2): 50.
• [34] Giorgi F. Climate change hot‐spots. Geophysical Research Letters 2006; 33(8): L08707.
• [35] Lelieveld J, Hadjinicolaou P, Kostopoulou E, Chenoweth J, El Maayar M, Giannakopoulos C, Hannides C, Lange MA, Tanarhte M, Tyrlis E, Xoplaki E. Climate change and impacts in the Eastern Mediterranean and the Middle East. Climatic Change 2012; 114(3-4): 667-687.
• [36] Zittis G, Almazroui M, Alpert P, Ciais P, Cramer W, Dahdal Y, Fnais M, Francis D, Hadjinicolaou P, Howari F, Jrrar A, Kaskaoutis DG, Kulmala M, Lazoglou G, Mihalopoulos N, Lin X, Rudich Y, Sciare J, Stenchikov G, Xoplaki E, Lelieveld J. Climate change and weather extremes in the Eastern Mediterranean and Middle East. Reviews of Geophysics 2022; 60(3): e2021RG000762.
• [37] Bozkurt D, Sen OL. Climate change impacts in the Euphrates-Tigris Basin based on different model and scenario simulations. Journal of Hydrology 2013; 480: 149-161.
• [38] Bozkurt D, Sen OL, Hagemann S. Projected river discharge in the Euphrates-Tigris Basin from a hydrological discharge model forced with RCM and GCM outputs. Climate Research 2015; 62(2): 131-147.
• [39] Sen OL, Unal A, Bozkurt D, Kindap T. Temporal changes in the Euphrates and Tigris discharges and teleconnections. Environmental Research Letters 2011; 6(2): 024012.
• [40] Yucel I, Güventürk A, Sen OL. Climate change impacts on snowmelt runoff for mountainous transboundary basins in eastern Turkey. International Journal of Climatology 2015; 35(2): 215-228.
• [41] Chenoweth J, Hadjinicolaou P, Bruggeman A, Lelieveld J, Levin Z, Lange MA, Xoplaki E, Hadjikakou M. Impact of climate change on the water resources of the eastern Mediterranean and Middle East region: Modeled 21st century changes and implications. Water Resources Research 2011; 47(6): W06506.
• [42] Kitoh A, Yatagai A, Alpert P. First super-high-resolution model projection that the ancient “Fertile Crescent” will disappear in this century. Hydrological Research Letters 2008; 2: 1-4.
• [43] Nohara D, Kitoh A, Hosaka M, Oki T. Impact of climate change on river discharge projected by multimodel ensemble. Journal of Hydrometeorology 2006; 7(5): 1076-1089.
• [44] Özdoğan M. Climate change impacts on snow water availability in the Euphrates-Tigris basin. Hydrology and Earth System Sciences 2011; 15(9): 2789-2803.
• [45] Şen Z. Climate change expectations in the upper Tigris River basin, Turkey. Theoretical and Applied Climatology 2019; 137: 1569-1585.
• [46] Şensoy A, Uysal G, Doğan YO, Civelek HS. The future snow potential and snowmelt runoff of Mesopotamian water tower. Sustainability 2023; 15(8): 6646.
• [47] Yalcin E. Assessing future changes in flood frequencies under CMIP6 climate projections using SWAT modeling: A case study of Bitlis Creek, Turkey. Journal of Water and Climate Change 2024; jwc2024646.
• [48] Yalcin E. Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model. Hydrological Sciences Journal 2023; 68(13): 1915-1936.
• [49] AE SU (AE SU Engineering Limited Company). Basoren Weir and HPP feasibility report. AE SU Engineering Limited Company, Ankara, 2009.
• [50] DSI (General Directorate of State Hydraulic Works). Electrical Power Resources Survey and Development Administration (EIE) - Stream gauging yearbooks (1935-2011). General Directorate of State Hydraulic Works, Ankara, 2022.
• [51] MGM (Turkish State Meteorological Service). Long-term all parameters bulletin for the Bitlis (Station ID: 17207) and Siirt (Station ID: 17210) weather stations. Turkish State Meteorological Service, Ankara, 2022.
• [52] MGM (Turkish State Meteorological Service). Daily precipitation, maximum and minimum air temperature, wind speed, solar radiation, and relative humidity records of the Bitlis (Station ID: 17207) and Siirt (Station ID: 17210) weather stations. Turkish State Meteorological Service, Ankara, 2022.
• [53] Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL. SWAT 2012 input/output documentation. Texas Water Resources Institute, Texas, 2013.
• [54] Neitsch SL, Arnold JG, Kiniry JR, Williams JR. Soil and Water Assessment Tool theoretical documentation version 2009. Texas Water Resources Institute, Texas, 2011.
• [55] USGS (United States Geological Survey). Shuttle Radar Topography Mission (SRTM): 1 arc-second global elevation database. United States Geological Survey, 2014. https://earthexplorer.usgs.gov/ (Accessed 28 June 2022).
• [56] EC-JRC (European Commission - Joint Research Centre). The Global Land Cover 2000 (GLC2000) products. European Commission - Joint Research Centre, 2006. https://forobs.jrc.ec.europa.eu/products/glc2000/products.php (Accessed 28 June 2022).
• [57] FAO (Food and Agriculture Organization of the United Nations). Digital Soil Map of the World (DSMW). Food and Agriculture Organization of the United Nations, 2007. https://www.fao.org/geonetwork/srv/en/metadata.show?id=14116 (Accessed 28 June 2022).
• [58] Abbaspour KC. SWAT-CUP2: SWAT calibration and uncertainty programs - A user manual. Eawag - Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, 2015.
• [59] Abbaspour KC, Johnson CA, van Genuchten MT. Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone Journal 2004; 3(4): 1340-1352.
• [60] Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology 2007; 333(2-4): 413-430.
• [61] Abbaspour KC, Rouholahnejad E, Vaghefi S, Srinivasan R, Yang H, Kløve B. A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. Journal of Hydrology 2015; 524: 733-752.
• [62] Yalcin E. Estimation of irrigation return flow on monthly time resolution using SWAT model under limited data availability. Hydrological Sciences Journal 2019; 64(13): 1588-1604.
• [63] Nash JE, Sutcliffe JV. River flow forecasting through conceptual models part I - A discussion of principles. Journal of Hydrology 1970; 10(3): 282-290.
• [64] ESGF (Earth System Grid Federation). WCRP Coupled Model Intercomparison Project (Phase 6). Earth System Grid Federation, 2022. https://esgf-node.llnl.gov/projects/cmip6/ (Accessed 15 May 2022).
• [65] Jones PW. First- and second-order conservative remapping schemes for grids in spherical coordinates. Monthly Weather Review 1999; 127(9): 2204-2210.
• [66] Rathjens H, Bieger K, Srinivasan R, Chaubey I, Arnold JG. CMhyd user manual: Documentation for preparing simulated climate change data for hydrologic impact studies. Purdue University, United States Department of Agriculture - Agricultural Research Service, Texas A&M AgriLife, and Texas A&M University, 2016. https://swat.tamu.edu/media/115265/bias_cor_man.pdf (Accessed 25 May 2022).
• [67] Legates DR, McCabe GJ. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resources Research 1999; 35(1): 233-241.
• [68] Almeida MP, Perpiñán O, Narvarte L. PV power forecast using a nonparametric PV model. Solar Energy 2015; 115: 354-368.
• [69] Gupta HV, Kling H, Yilmaz KK, Martinez GF. Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of Hydrology 2009; 377(1-2): 80-91.
• [70] Roberts NM, Lean HW. Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Monthly Weather Review 2008; 136(1): 78-97.
• [71] Moriasi DN, Gitau MW, Pai N, Daggupati P. Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE 2015; 58(6): 1763-1785.
• [72] Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 2007; 50(3): 885- 900.
• [73] Ahmed K, Sachindra DA, Shahid S, Demirel MC, Chung E-S. Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics. Hydrology and Earth System Sciences 2019; 23(11): 4803-4824.
• [74] Bağçaci SÇ, Yucel I, Duzenli E, Yilmaz MT. Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: A Mediterranean hot spot case, Turkey. Atmospheric Research 2021; 256: 105576.
• [75] Seker M, Gumus V. Projection of temperature and precipitation in the Mediterranean region through multi- model ensemble from CMIP6. Atmospheric Research 2022; 280: 106440.