ORIGINAL RESEARCH
Investigating Hydrological Responses and Adaptive Operation of a Hydropower Station under a Climate Change Scenario
 
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Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, China
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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
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
Online publish date: 2018-05-09
Publish date: 2018-05-30
Submission date: 2017-05-28
Final revision date: 2017-07-22
Acceptance date: 2017-10-16
 
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.
eISSN:2083-5906
ISSN:1230-1485