Using a fish entrainment model assistant in a reservoir operation in China

Autor: Meixia Bao, Pengcheng Li, Yu Han, Wenming Zhang, Yike Li, Weiwei Yao
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Hydroinformatics, Vol 24, Iss 4, Pp 765-782 (2022)
Druh dokumentu: article
ISSN: 1464-7141
1465-1734
DOI: 10.2166/hydro.2022.147
Popis: Individual fish are vulnerable in hydropower reservoirs due to spillway and intake operations. It is essential to understand how reservoir forebay fish ecosystems respond to water levels, intake, and spillway regulation. This study aims to explore the fish entrainment risk of the Dawei Reservoir operation on the Dadu River in Sichuan, China, accounting for both intake and spillway operations under wet, normal, and dry seasonal reservoir water levels. Hydrodynamic variables, reservoir operation scenarios, and two fish species were used as indexes to analyze the fish entrainment risk. The simulation results showed that the fish entrainment risk was low under the Dawei intake operation schemes ranging from 0.84 × 103 to 5.97 × 103 m2. The results also showed that the fish entrainment risk was very high under the Dawei spillway operation in fish entrainment areas ranging from 3.90 × 104 to 2.08 × 105 m2. Based on the simulation results, the lowest fish entrainment risk happened with two intakes open and the reservoir water level at 2,640 m. The highest fish entrainment risk happened with five intakes open and the reservoir water level at 2,670 m. The results indicate that the long-term Dawei Reservoir regulation would not modify the fish entrainment risk at significant levels under the Dawei Reservoir operation schemes. HIGHLIGHTS A model was proposed to determine the fish entrainment risk.; The fish entrainment risk was low during the seasonal operation of intakes.; The maximum and minimum fish entrainment risks were established.; The fish entrainment risk was high under the spillway operation.; The long-term reservoir operation would not significantly affect the fish entrainment risk.;
Databáze: Directory of Open Access Journals
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