Native Fish Need A Natural Flow Regime

Fisheries ◽  
2021 ◽  
Author(s):  
Casey A. Pennock ◽  
Phaedra Budy ◽  
William W. Macfarlane ◽  
Justin Jimenez ◽  
John C. Schmidt
2012 ◽  
Vol 22 (5) ◽  
pp. 1472-1482 ◽  
Author(s):  
Joseph D. Kiernan ◽  
Peter B. Moyle ◽  
Patrick K. Crain

Energy ◽  
2020 ◽  
Vol 190 ◽  
pp. 116260 ◽  
Author(s):  
Jeff Opgrand ◽  
Paul V. Preckel ◽  
F.T. Sparrow ◽  
Gregory Thomas ◽  
Daniel P. Loucks

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Daren M. Carlisle ◽  
James Falcone ◽  
David M. Wolock ◽  
Michael R. Meador ◽  
Richard H. Norris

2016 ◽  
Vol 573 ◽  
pp. 1492-1502 ◽  
Author(s):  
Konstantinos Stefanidis ◽  
Yiannis Panagopoulos ◽  
Alexandros Psomas ◽  
Maria Mimikou

2013 ◽  
Vol 10 (12) ◽  
pp. 15841-15869
Author(s):  
X. A. Yin ◽  
Z. F. Yang ◽  
C. L. Liu

Abstract. In deregulated electricity markets, hydropower portfolio design has become an essential task for producers. The previous research on hydropower portfolio optimisation focused mainly on the maximisation of profits but did not take into account riverine ecosystem protection. Although profit maximisation is the major objective for producers in deregulated markets, protection of riverine ecosystems must be incorporated into the process of hydropower portfolio optimisation, especially against a background of increasing attention to environmental protection and stronger opposition to hydropower generation. This research seeks mainly to remind hydropower producers of the requirement of river protection when they design portfolios and help shift portfolio optimisation from economically oriented to ecologically friendly. We establish a framework to determine the optimal portfolio for a hydropower reservoir, accounting for both economic benefits and ecological needs. In this framework, the degree of natural flow regime alteration is adopted as a constraint on hydropower generation to protect riverine ecosystems, and the maximisation of mean annual revenue is set as the optimisation objective. The electricity volumes assigned in different electricity sub-markets are optimised by the noisy genetic algorithm. The proposed framework is applied to China's Wangkuai Reservoir to test its effectiveness. The results show that the new framework could help to design eco-friendly portfolios that can ensure a planned profit and reduce alteration of the natural flow regime.


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