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Keywords = yearly drawdown level

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17 pages, 2975 KB  
Article
Dynamic Control of Yearly Drawdown Level of Overyear Regulation Reservoir in Cascade System
by Zongye Chang, Zhiqiang Jiang and Xiaohui Yuan
Water 2023, 15(4), 665; https://doi.org/10.3390/w15040665 - 8 Feb 2023
Viewed by 2328
Abstract
Based on the joint scheduling model of cascade reservoirs and a dynamic programming (DP) algorithm, this paper studies the optimal control of the yearly drawdown level of an overyear regulation reservoir considering the influence of inflow uncertainty. An innovative dynamic control method has [...] Read more.
Based on the joint scheduling model of cascade reservoirs and a dynamic programming (DP) algorithm, this paper studies the optimal control of the yearly drawdown level of an overyear regulation reservoir considering the influence of inflow uncertainty. An innovative dynamic control method has been put forward, and the corresponding technical route is provided. In case study, the seven reservoirs of the Yalong River are used as the research object, the proposed dynamic control method is verified by a detailed case study, and yearly drawdown level dynamic control bounds of the Lianghekou reservoir under two inflow series are constructed. Based on a long series of historical inflows, the simulation calculation and detailed comparative analysis are carried out. It is found that the dynamic control bound constructed by the selected inflow series has little impact on the fluctuation of scheduling results and can well cope with the impact of inflow uncertainty on the scheduling results. In addition, compared with the traditional fixed-yearly-drawdown-level control mode, the proposed dynamic control method can consider the interannual difference of inflow, which can increase the total power generation of the cascade system by more than 94 billion kWh at maximum and realize 63.4%~76.3% of the benefits of the lifting space of yearly drawdown level optimization. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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17 pages, 5320 KB  
Article
Simulation-Optimization Model for Conjunctive Management of Surface Water and Groundwater for Agricultural Use
by Agbortoko Bate Ashu and Sang-Il Lee
Water 2021, 13(23), 3444; https://doi.org/10.3390/w13233444 - 4 Dec 2021
Cited by 13 | Viewed by 4029
Abstract
The conjunctive management of surface water and groundwater resources is essential to sustainably manage water resources. The target study is the Osan watershed, in which approximately 60–70% of rainfall occurs during the summer monsoon in Central South Korea. Surface water resources are overexploited [...] Read more.
The conjunctive management of surface water and groundwater resources is essential to sustainably manage water resources. The target study is the Osan watershed, in which approximately 60–70% of rainfall occurs during the summer monsoon in Central South Korea. Surface water resources are overexploited six times as much as groundwater resources in this region, leading to increasing pressure to satisfy the region’s growing agricultural water demand. Therefore, a simulation-optimization (S-O) model at the sub-basin scale is required to optimize water resource allocation in the Osan watershed. An S-O model based on an artificial neural network (ANN) model coupled with Jaya algorithm optimization (JA) was used to determine the yearly conjunctive supply of agricultural water. The objective was to minimize the water deficit in the watershed subject to constraints on the cumulative drawdown in each subarea. The ANN model could predict the behaviour of the groundwater level and facilitate decision making. The S-O model could minimize the water deficit by approximately 80% in response to the gross water demand, thereby proving to be suitable for a conjunctive management model for water resource management and planning. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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