Reducing lake water-level decline by optimizing reservoir operating rule curves: A case study of the Three Gorges Reservoir and the Dongting Lake

Li, Xiao; Liu, Pan; Gui, Zhipeng; Ming, Bo; Zheng, Yang; Xie, Kang; Zhang, Xiaoqi

doi:10.1016/j.jclepro.2020.121676

Cited by 30 publications

(8 citation statements)

References 44 publications

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“…2a). Moreover, the impact of the TGR operation on the hydrological rhythm of Dongting Lake was confirmed by building a river-lake model, where the ecological processes such as nitrogen cycling in the lake were profoundly affected by anthropogenic regulation in hydrology (Li et al, 2020).…”

Section: Long-term Effect Of Hydrological Conditions On Vegetation Stratificationmentioning

confidence: 91%

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland

Liu

Jin

Shi

et al. 2021

Preprint

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Abstract. Hydrological conditions drive the distribution of plant communities in wetlands to form vegetation zones where the material cycling varies with plant species. This mediation effect caused by the distribution of vegetation under hydrological conditions will affect the emission of N2O during the nitrogen migration in wetlands. In this study, five vegetation zones in the second largest wetland of China were investigated in situ during high and low water levels to elucidate the effect mediated by vegetation. With the increase in the rate of change of water levels, the zones of the mud flat, nymphoides, phalaris, carex, and reeds were distributed in sequence in the wetland, and the densities of carbon and nitrogen sequestrated by plants also increased. The carbon and nitrogen densities in each zone during low water level was significantly higher than that during high water level, while the organic carbon and the total nitrogen of sediments during high water level was higher. Sediments converted between source and sink for both carbon and nitrogen, during the annual fluctuation in water level. The flux in N2O emissions showed significant differences between the vegetation zones during each water level period. The emission flux decreased with the increasing C : N ratio in sediments, approximating the threshold at 0.23 μg m−2 h−1 when the C : N ratio > 25. The phylum abundance of Firmicutes, Proteobacteria, and Chloroflexi in sediments increased with flooding. The denitrifying nirS and nirK genes and anammox hzsB gene were significantly affected by water level fluctuation, with the maximal variations of these genes occurring in the mud flat and nymphoides zone. The results indicate that the distribution of plants under hydrological conditions modified the stoichiometric ratio of sediments, resulting in the variations of N2O emission fluxes and microbial communities in vegetation zones. Therefore, hydraulic regulation rather than direct planting would be an effective strategy to reduce greenhouse gas emissions in freshwater wetlands.

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Section: Long-term Effect Of Hydrological Conditions On Vegetation Stratificationmentioning

confidence: 91%

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland

Liu

Jin

Shi

et al. 2021

Preprint

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“…Continuing the generation loop can aid in identifying, optimising, and designing problems. The GA introduced by [ 104 ] is one of those popular EA which was implemented in the optimisation of reservoir due to its simplicity and problem-independent application [ 37 , 38 ]. A simple flowchart of the GA and DE is shown in Fig.…”

Section: Reservoir Operation Optimisation Innovation and Techniquesmentioning

confidence: 99%

A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms

Lai

Huang

Koo

et al. 2022

Arch Computat Methods Eng

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Reservoir operation optimisation secures benefits, such as optimising energy production while minimising the possibility of flooding, operating costs, and water scarcity, at the lowest possible cost. This paper carries reviews of research on reservoir optimisation models and the consequential challenges of optimally operating reservoir operations. An introductory section is given to the background of reservoir operations and the current concerns on the optimal reservoir operations, for the decision-makers and stakeholders. Next, the review covered the recent ten years (between 2011 and 2021), on the recent research developments in innovation and techniques of reservoir operation optimisation. Further reviews on the conventional techniques that are the traditional methods, linear programming, nonlinear programming, and dynamic programming are discussed. Enhancements to the techniques in improving the drawbacks of the traditional techniques in optimisation of reservoir policies are next explained and evaluated. Recent advances in applying metaheuristics optimisation algorithms beneficial to the reservoir operations are explained, including the advantages and hinderances. A comprehensive tabulated and categorised review according to the classification of reservoir models, evaluation methods, and reservoir systems is given.

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“…Alternatively, operation policies can be obtained using direct policy search (Schmidhuber 2001), where the parameters of a pre-defined policy function are directly optimised during the optimisation process based on operation objectives, such as maximisation of hydro-electric energy generated or minimisation of flood risk. Various function forms can be used as the policy function, including simple rule curves (Li et al 2020), complicated hedging rules (Xu et al 2019), mathematical equations such as polynomial functions (Tsoukalas andMakropoulos 2015, Saadatpour et al 2020), or data-driven models such as artificial neural networks (ANNs) (Culley et al 2016, Zatarain Salazar et al 2017. Mathematical equations are commonly used as they are more flexible than simple rule curves and their behaviour is well-understood (Schmidhuber 2001).…”

Section: Reservoir Operation Optimisationmentioning

confidence: 99%

Evolutionary algorithm-based multiobjective reservoir operation policy optimisation under uncertainty

Zhou²,

Leonard³

2022

Environ. Res. Commun.

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Reservoir operation optimisation is a decision support tool to assist reservoir operators with water release decisions to achieve management objectives, such as maximising water supply security, mitigating flood risk, and maximising hydroelectric power generation. The effectiveness of reservoir operation decisions is subject to uncertainty in system inputs, such as inflow and therefore, methods such as stochastic dynamic programming (SDP) have been traditionally used. However, these methods suffer from the three curses of dimensionality, modelling, and multiple objectives. Evolutionary algorithm (EA)-based simulation-optimisation frameworks such as the Evolutionary Multi-Objective Direct Policy Search offer a new paradigm for multiobjective reservoir optimisation under uncertainty, directly addressing the shortcomings of SDP-based methods. They also enable the consideration of input uncertainty represented using ensemble forecasts that have become more accessible recently. However, there is no universally agreed approach to incorporate uncertainty into EA-based multiobjective reservoir operation policy optimisation and it is not clear which approach is more effective. Therefore, this study conducts a comparative analysis to demonstrate the advantages and limitations of different approaches to account for uncertainty in multiobjective reservoir operation policy optimisation via a real-world case study; and provide guidance on the selection of appropriate approaches. Based on the results obtained, it is evident that each approach has both advantages and limitations. A suitable approach needs to be carefully selected based on the needs of the study, e.g., whether a hard constraint is required, or a well-established decision-making process exists. In addition, potential gaps for future research are identified.

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Reducing lake water-level decline by optimizing reservoir operating rule curves: A case study of the Three Gorges Reservoir and the Dongting Lake

Cited by 30 publications

References 44 publications

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland

A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms

Evolutionary algorithm-based multiobjective reservoir operation policy optimisation under uncertainty

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Reducing lake water-level decline by optimizing reservoir operating rule curves: A case study of the Three Gorges Reservoir and the Dongting Lake

Cited by 30 publications

References 44 publications

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N&lt;sub&gt;2&lt;/sub&gt;O emissions in freshwater wetland

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N&lt;sub&gt;2&lt;/sub&gt;O emissions in freshwater wetland

A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms

Evolutionary algorithm-based multiobjective reservoir operation policy optimisation under uncertainty

Contact Info

Product

Resources

About

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland

Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N<sub>2</sub>O emissions in freshwater wetland