Technical Papers
Jan 13, 2020

Modeling Framework for Reservoir Capacity Planning Accounting for Fish Migration

Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 3

Abstract

Reservoirs change the environment upstream of dams from lotic to lentic and alter hydrodynamic migration cues, thereby forming barriers to upstream fish migration. Increasing reservoir capacity improves its ability to store water and provide benefits for human water uses but may simultaneously degrade fish migration environment in the reservoir and increase the economic cost for restoring fish migration. Such a tradeoff has been rarely explored. This study develops an integrated hydrodynamic, hydrologic, and economic framework for planning reservoir capacity that accounts for fish migration; water use benefits; and reservoir construction, maintenance, and operation costs. Based on the hydrodynamic simulation of flow velocities along a potential fish migration route in a reservoir, we determine the minimum flow release required to restore migration for different inflow and storage conditions and fish hydrodynamic requirements. The minimum release is then expressed as a constraint in an optimization model that determines the optimal reservoir capacity and a new operating rule curve to maximize reservoir net benefit. Using China’s Danjiangkou Reservoir as a case study, we confirm that increasing reservoir capacity increases the quantity of water abandoned for restoring fish migration. Accounting for fish migration decreases optimal reservoir capacity by 39%, decreases annual costs by 13%, and decreases annual net benefits by 8%–21%, depending on fish hydrodynamic requirements. Large reservoirs may need to sacrifice considerable storage both before and during the migration period, and thus the optimal capacity for a particular reservoir should be decided based on a balance between human water demand and fish migration requirements.

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Data Availability Statement

The Environmental Fluid Dynamics Code used for hydrodynamic simulation can be found at https://www.eemodelingsystem.com/. Meteorological, terrain, and hydrological data used in the case study can be found in the references, and other data are available from the corresponding author by request.

Acknowledgments

This research was supported by the National Natural Science Foundation of China (Grant Nos. 51439001, and 51909036); the Innovative Research Group of the National Natural Science Foundation of China (Grant No. 51721093); and a fellowship provided by the China Scholarship Council.

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Journal of Water Resources Planning and Management
Volume 146Issue 3March 2020

History

Received: Nov 29, 2018
Accepted: Aug 14, 2019
Published online: Jan 13, 2020
Published in print: Mar 1, 2020
Discussion open until: Jun 13, 2020

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Ph.D. Student, State Key Laboratory of Water Environmental Simulation, School of Environment, Beijing Normal Univ., Beijing 100875, China; Visiting Scholar, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, Urbana, IL 61801. Email: [email protected]
Professor, Institute of Environmental and Ecological Engineering, Guangdong Univ. of Technology, Guangzhou, Guangdong 510006, China; Professor, State Key Laboratory of Water Environmental Simulation, School of Environment, Beijing Normal Univ., Beijing 100875, China (corresponding author). ORCID: https://orcid.org/0000-0003-4672-8243. Email: [email protected]
Ximing Cai, M.ASCE [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, Urbana, IL 61801. Email: [email protected]
Professor, State Key Laboratory of Water Environmental Simulation, School of Environment, Beijing Normal Univ., Beijing 100875, China. Email: [email protected]
Yanpeng Cai [email protected]
Professor, State Key Laboratory of Water Environmental Simulation, School of Environment, Beijing Normal Univ., Beijing 100875, China. Email: [email protected]

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