Balancing social, economic and ecological benefits of reservoir operation during the flood season: A case study of the Three Gorges Project, China
dc.contributor.author | Huang, Lei | |
dc.contributor.author | Li, Xiang | |
dc.contributor.author | Fang, Hongwei | |
dc.contributor.author | Yin, Dong Qin | |
dc.contributor.author | Si, Yuan | |
dc.contributor.author | Wei, Jiahua | |
dc.contributor.author | Liu, Jiahong | |
dc.contributor.author | Hu, Xiaoyong | |
dc.contributor.author | Zhang, Li | |
dc.date.accessioned | 2020-05-04T23:05:17Z | |
dc.date.issued | 2019 | |
dc.date.updated | 2019-11-25T08:03:14Z | |
dc.description.abstract | Balancing the multiple purposes of reservoir operation, including the social, economic, and ecological aspects, has become one of the most complicated problems facing the managers and operators worldwide. This paper formulates a detailed mathematical model to optimize the reservoir operation during the flood season, considering the three major operational purposes, i.e. flood control (social purpose), energy production (economic purpose), and management of sediment transport (ecological purpose). The entire formulations conform to a nonlinear programming (NLP) model, which can be solved effectively and efficiently by the Multi-Start Solver from the LINGO software through equivalent transformation. This model is applied to the Three Gorges Project (TGP) in China, which is the world’s largest and most complex hydraulic engineering in operation. Three typical flood hydrographs (i.e. dry, normal, and wet scenarios) are selected as model inputs under the three strategies (i.e. design operating rules, increasing the flood control water level (FCWL), and impounding in advance). The trade-offs among these three major operational purposes are quantitatively analyzed. Moreover, phosphorus (P), one of the sediment-associated environmental factors, is introduced for exploring its responses to various scenarios and strategies. Results indicate that a higher fore-bay water level leads to a greater energy production, a smaller flood peak but less sediment and P transports to the downstream. Under the design operating rules, the maximum energy production of the TGP can reach 560, 620, and 699 × 108 KWh, respectively, in dry, normal, and wet scenarios, corresponding to a flood peak of 25000–27500 m3/s, a sediment load of 1517–1999 × 104 t, and a P load of 3152–3740 × 104 kg to the downstream. Whereas, the maximum sediment loads are 2796, 4640, and 5377 × 104 t, and the maximum P loads are 4021, 5345, and 5784 × 104 kg, respectively, in dry, normal, and wet scenarios, corresponding to an energy production of 500–588 × 108 KWh, and a flood peak of 38600–52500 m3/s to the downstream. In terms of achieving the comprehensive benefits of the TGP, impounding in advance is a better choice than both the design operating rules and increasing the FCWL, for it can increase the energy production and the probability of full refill with almost no increase in flood risk to both the dam and the middle and lower reaches of the Yangtze River as well as smaller reduction in the sediment and P transports. The formulated detailed mathematical model is a general one that is applicable to a variety of reservoirs owning multiple operational purposes. Moreover, the achievements gained from this paper will provide important references for the managers and operators. | en_AU |
dc.description.sponsorship | The authors are very grateful to the Hydrology Bureau of the Changjiang Water Resources Commission and the China Three Gorges Corporation for supplying the valuable data. This study is supported by the National Key Research and Development Program of China (2016YFC0401401, and 2016YFC0402506), the National Natural Science Foundation of China (91647210, 51609256, 51609122, 51522907, 51739011, 51479213, and 11802158), and the Research Foundations of the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (2016ZY02), the State Key Laboratory of Lake Science and Environment (2016SKL012), the State Key Laboratory of Hydro-science and Engineering (2018-KY-03), and the 111 Project (B18031). Partial support is also supported by the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (2017QNRC001). | en_AU |
dc.format.mimetype | application/pdf | en_AU |
dc.identifier.issn | 0022-1694 | en_AU |
dc.identifier.uri | http://hdl.handle.net/1885/203757 | |
dc.language.iso | en_AU | en_AU |
dc.publisher | Elsevier | en_AU |
dc.rights | © 2019 Elsevier B.V | en_AU |
dc.source | Journal of Hydrology | en_AU |
dc.title | Balancing social, economic and ecological benefits of reservoir operation during the flood season: A case study of the Three Gorges Project, China | en_AU |
dc.type | Journal article | en_AU |
local.bibliographicCitation.lastpage | 434 | en_AU |
local.bibliographicCitation.startpage | 422 | en_AU |
local.contributor.affiliation | Huang, Lei, Tsinghua University | en_AU |
local.contributor.affiliation | Li, Xiang, China Institute of Water Resources and Hydropower Research | en_AU |
local.contributor.affiliation | Fang, Hongwei, Tsinghua University | en_AU |
local.contributor.affiliation | Yin, Dong Qin, College of Science, ANU | en_AU |
local.contributor.affiliation | Si, Yuan, China Institute of Water Resources and Hydropower Research | en_AU |
local.contributor.affiliation | Wei, Jiahua, Tsinghua University | en_AU |
local.contributor.affiliation | Liu, Jiahong, China Institute of Water Resources and Hydropower Research | en_AU |
local.contributor.affiliation | Hu, Xiaoyong, China Three Gorges Corporation | en_AU |
local.contributor.affiliation | Zhang, Li, Tsinghua University | en_AU |
local.contributor.authoremail | repository.admin@anu.edu.au | en_AU |
local.contributor.authoruid | Yin, Dong Qin, u5457650 | en_AU |
local.description.embargo | 2037-12-31 | |
local.description.notes | Imported from ARIES | en_AU |
local.identifier.absfor | 040699 - Physical Geography and Environmental Geoscience not elsewhere classified | en_AU |
local.identifier.absseo | 970105 - Expanding Knowledge in the Environmental Sciences | en_AU |
local.identifier.ariespublication | u5786633xPUB790 | en_AU |
local.identifier.citationvolume | 572 | en_AU |
local.identifier.doi | 10.1016/j.jhydrol.2019.03.009 | en_AU |
local.identifier.scopusID | 2-s2.0-85062912127 | |
local.identifier.uidSubmittedBy | u5786633 | en_AU |
local.publisher.url | https://www.elsevier.com/ | en_AU |
local.type.status | Published Version | en_AU |
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