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Article

Decision Support Model for Ecological Operation of Reservoirs Based on Dynamic Bayesian Network

1
Changjiang River Scientific Research Institute, No. 23 Huangpu Road, Wuhan 430010, China
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College of Hydrology and Water Resources, Hohai University, No. 1 Xikang Road, Nanjing 210098, China
3
College of Civil Engineering and Architecture, Zhejiang University, No. 866 Yuhangtang Road, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Academic Editor: George Arhonditsis
Water 2021, 13(12), 1658; https://doi.org/10.3390/w13121658
Received: 21 March 2021 / Revised: 7 June 2021 / Accepted: 8 June 2021 / Published: 14 June 2021
(This article belongs to the Section Hydrology)
In this study, a model was proposed based on the sustainable boundary approach, to provide decision support for reservoir ecological operation with the dynamic Bayesian network. The proposed model was developed in four steps: (1) calculating and verifying the sustainable boundaries in combination with the ecological objectives of the study area, (2) generating the learning samples by establishing an optimal operation model and a Monte Carlo simulation model, (3) establishing and training a dynamic Bayesian network by learning the examples and (4) calculating the probability of the economic and ecological targets exceeding the set threshold from time to time with the trained dynamic Bayesian network model. Using the proposed model, the water drawing of the reservoir can be adjusted dynamically according to the probability of the economic and ecological targets exceeding the set threshold during reservoir operation. In this study, the proposed model was applied to the middle reaches of Heihe River, the effect of water supply proportion on the probability of the economic target exceeding the set threshold was analyzed, and the response of the reservoir water storage in each period to the probability of the target exceeding the set threshold was calculated. The results show that the risks can be analyzed with the proposed model. Compared with the existing studies, the proposed model provides guidance for the ecological operation of the reservoir from time to time and technical support for the formulation of reservoir operation chart. Compared with the operation model based on the designed guaranteed rate, the reservoir operation model based on uncertainty reduces the variation range of ecological flow shortage or the overflow rate and the economic loss rate by 5% and 6%, respectively. Thus, it can be seen that the decision support model based on the dynamic Bayesian network can effectively reduce the influence of water inflow and rainfall uncertainties on reservoir operation. View Full-Text
Keywords: dynamic Bayesian network; environmental flow threshold; uncertainty; ecology operation dynamic Bayesian network; environmental flow threshold; uncertainty; ecology operation
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MDPI and ACS Style

Zhou, T.; Dong, Z.; Chen, X.; Ran, Q. Decision Support Model for Ecological Operation of Reservoirs Based on Dynamic Bayesian Network. Water 2021, 13, 1658. https://doi.org/10.3390/w13121658

AMA Style

Zhou T, Dong Z, Chen X, Ran Q. Decision Support Model for Ecological Operation of Reservoirs Based on Dynamic Bayesian Network. Water. 2021; 13(12):1658. https://doi.org/10.3390/w13121658

Chicago/Turabian Style

Zhou, Tao, Zengchuan Dong, Xiuxiu Chen, and Qihua Ran. 2021. "Decision Support Model for Ecological Operation of Reservoirs Based on Dynamic Bayesian Network" Water 13, no. 12: 1658. https://doi.org/10.3390/w13121658

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