ORIGINAL RESEARCH
Investigating Hydrological Responses and Adaptive
Operation of a Hydropower Station under
a Climate Change Scenario
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1
Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, China
2
Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan
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Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore, Pakistan
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Department of Agricultural Engineering, Bahauddin Zakariya University, Multan, Pakistan
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Department of Structures and Environmental Engineering, University of Agriculture, Faisalabad, Pakistan
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State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources,
Chinese Academy of Sciences (CAS), Lanzhou, China
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State key laboratory of Crysopheric Science, Northwest institute of eco-Environment and Resources,
Chinese Academy of Sciences, Lanzhou 730000, China
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School of Environment and Safety Engineering, Jiangsu University, Zhenjiang, China
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College of Environmental Science and Engineering, Ocean University of China, Qingdao, China
Submission date: 2017-05-28
Final revision date: 2017-07-22
Acceptance date: 2017-10-16
Online publication date: 2018-05-09
Publication date: 2018-05-30
Corresponding author
Muhammad Sultan
Department of Agricultural Engineering, Bahauddin Zakariya University, Bosan Road, Multan 60800, Pakistan, Dept. of Agricultural Engineering, Bahauddin Zakariya University, 60800 Multan, Pakistan
Pol. J. Environ. Stud. 2018;27(5):2337-2348
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ABSTRACT
In this study we investigated the projections of climate change and its impacts on the water resources
of the Xin’anjiang watershed and optimal hydropower production using future run-offs (the decades of the
2020s, 2050s, and 2080s). The arc SWAT hydrological model and change factor downscaling technique
were integrated to detect the run-offs and to downscale CMIP5 future climate variables, respectively.
Optimal hydropower generation using future runoff was predicted by developing a mathematical model
and by applying the particle swarm optimization technique within its paradigm. The results depict an
increase of up to 5.9ºC in monthly mean maximum temperature, and 5.58ºC in minimum temperature
until the 2080s. There will be a 63% increase in flow magnitudes more than the base year flow during
the 2020s, whereas up to 70% and 31.40% increments have been observed for the 2050s and 2080s,
respectively. The results revealed potential hydropower generation of 19.23*108 kWh using 2020s runoff
of rainy years. Similarly, 19.35*108 kWh and 14.23*108 kWh were estimated from the flows during
the 2050s and 2080s, respectively.