Reservoir Control Operation and Water Resources Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 8904

Special Issue Editors


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Guest Editor
Institute of Water Science and Engineering, Civil Engineering, Zhejiang University, Hangzhou 310058, China
Interests: reservoir control operation; water resources management; climate change and adaption; system analysis optimization; hydrological modelling; uncertainty; artificial intelligence

E-Mail Website
Guest Editor
Institute of Water Science and Engineering, Civil Engineering, Zhejiang University, Hangzhou 310058, China
Interests: flood forecasting; hydrological modelling; precipitation prediction; statistical post-processing

Special Issue Information

Dear Colleagues,

Water managers and governments worldwide are facing similar challenges: how to meet the growing demands for water, food, and energy sustainably in a changing environment. Efficient reservoir operation techniques are vital for water resources and energy development and utilization. However, uncertainties have always characterized reservoir operations due to the inevitable uncertainty caused by various factors, such as measurement errors, model structure and parameter diversity, and climatic and hydrologic variability, among others. These uncertainties pose significant risks, particularly in light of current and future uncertainties related to climate change and rapid societal, ecological, and economic changes.

Successful operations of reservoirs and water resources require a comprehensive understanding of modeling-related uncertainties and the integrative application of artificial intelligence technology to generate sustainable solutions for water, food, and energy systems in a changing environment. The main themes of this Special Issue include but are not limited to the following: (I) water, food, and energy systems, (II) reservoir control operation, (III) integrated water resources management, (IV) changing environmental evaluation, (V) modeling uncertainties and their effects, (VI) risk assessment and reduction, (VII) artificial intelligence methods, and (VIII) system optimization analysis.

Original field and experimental research papers, review papers and case studies are invited for submission.

Dr. Yuxue Guo
Dr. Li Liu
Guest Editors

Manuscript Submission Information

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Keywords

  • water, food, and energy
  • reservoir operation
  • water resources management
  • changing environment
  • uncertainty
  • risk
  • artificial intelligence

Published Papers (10 papers)

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Research

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19 pages, 1324 KiB  
Article
Assessment of Hydrological and Meteorological Composite Drought Characteristics Based on Baseflow and Precipitation
by Saihua Huang, Heshun Zhang, Yao Liu, Wenlong Liu, Fusen Wei, Chenggang Yang, Feiyue Ding, Jiandong Ye, Hui Nie, Yanlei Du and Yuting Chen
Water 2024, 16(11), 1466; https://doi.org/10.3390/w16111466 - 21 May 2024
Viewed by 183
Abstract
Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the [...] Read more.
Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the standardized precipitation index (SPI) and the standardized baseflow index (SBI) for the Jiaojiang River Basin (JRB) using the copula function. The prediction model was established by training random forests on past data, and the driving force behind the combined drought index was explored through the LIME algorithm. The results show that the established composite drought index combines the advantages of SPI and SBI in drought forecasting. The monthly and annual droughts in the JRB showed an increasing trend from 1991 to 2020, but the temporal characteristics of the changes in each subregion were different. The accuracies of the trained random forest model for heavy drought in Baizhiao (BZA) and Shaduan (SD) stations were 83% and 88%, respectively. Furthermore, the Local Interpretable Model-Agnostic Explanations (LIME) interpretation identified the essential precipitation, baseflow, and evapotranspiration features that affect drought. This study provides reliable and valid multivariate indicators for drought monitoring and can be applied to drought prediction in other regions. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
18 pages, 9889 KiB  
Article
Spatial and Temporal Assessment of Baseflow Based on Monthly Water Balance Modeling and Baseflow Separation
by Huawei Xie, Haotian Hu, Donghui Xie, Bingjiao Xu, Yuting Chen, Zhengjie Zhou, Feizhen Zhang and Hui Nie
Water 2024, 16(10), 1437; https://doi.org/10.3390/w16101437 - 17 May 2024
Viewed by 326
Abstract
Baseflow is the part of streamflow that is mainly replenished by groundwater. The protection of the biological environment and the growth of its water resources greatly depend on the spatial and temporal evolution of baseflow. Therefore, the Baizhiao (BZA) and Shaduan (SD) catchments [...] Read more.
Baseflow is the part of streamflow that is mainly replenished by groundwater. The protection of the biological environment and the growth of its water resources greatly depend on the spatial and temporal evolution of baseflow. Therefore, the Baizhiao (BZA) and Shaduan (SD) catchments of the Jiaojiang River Basin (JRB) in the Zhejiang province of China were selected as study areas. The ABCD model and Eckhardt method were used to calculate baseflow and baseflow index (BFI). The temporal and spatial evolution patterns of baseflow were analyzed through statistical analysis and the Mann–Kendall test. The results showed that the ABCD model performs well in simulating overall hydrological processes on the monthly streamflow at BAZ and SD stations with NSE (Nash–Sutcliffe Efficiency) values of 0.82 and 0.83 and Pbias (Percentage Bias) values of 9.2% and 8.61%, respectively. The spatial–temporal distribution of the BFI indicates the higher baseflow contribution in upstream areas compared to downstream areas at both stations. The baseflow and BFI had significant upward trends at the BZA and SD stations in the dry season, while their trends were not uniform during the wet period. These findings are essential guidance for water resource management in the JRB regions. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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17 pages, 4217 KiB  
Article
Joint Optimal Use of Sluices of a Group of Cascade Hydropower Stations under High-Intensity Peak Shaving and Frequency Regulation
by Shiyu Mou, Tian Qu, Jia Li, Xin Wen and Yu Liu
Water 2024, 16(2), 275; https://doi.org/10.3390/w16020275 - 12 Jan 2024
Viewed by 818
Abstract
With the large-scale development and grid connection of renewable energy, hydropower faces more intense and frequent peak shaving and frequency regulation, giving rise to water level fluctuations and frequently forced sluice adjustments at hydropower stations. This paper proposes a model that combines “offline [...] Read more.
With the large-scale development and grid connection of renewable energy, hydropower faces more intense and frequent peak shaving and frequency regulation, giving rise to water level fluctuations and frequently forced sluice adjustments at hydropower stations. This paper proposes a model that combines “offline calculation” and “online search”. First, feasible sluice opening combinations for different water levels at each hydropower station are calculated offline, and a sluice operation strategy table is constructed. Subsequently, an optimal sluice operation strategy is searched online according to the real-time water level and various regulatory requirements. As an example, we select three hydropower stations in the middle reach of the Dadu River in China, namely, Pubugou, Shenxigou, and Zhentouba. The results show that the total number of adjustments of the sluices of the cascade hydropower stations was reduced from 1195 to 675, a reduction of 43.5%, and the leading hydropower station, Pubugou, met water level control requirements, whereas the fluctuations in the water level of the two downstream daily regulating hydropower stations, Shenxigou and Zhentouba, were reduced by 1.38 m and 0.55 m, respectively. The results indicate that the sluices of hydropower stations were optimally used under high-intensity peak shaving and frequency regulation. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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23 pages, 11382 KiB  
Article
Development and Deployment of a Virtual Water Gauge System Utilizing the ResNet-50 Convolutional Neural Network for Real-Time River Water Level Monitoring: A Case Study of the Keelung River in Taiwan
by Jui-Fa Chen, Yu-Ting Liao and Po-Chun Wang
Water 2024, 16(1), 158; https://doi.org/10.3390/w16010158 - 30 Dec 2023
Viewed by 1235
Abstract
Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, traditional methods relying on physical river gauges are becoming progressively [...] Read more.
Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, traditional methods relying on physical river gauges are becoming progressively unreliable. This paper presents an innovative methodology that leverages ResNet-50, a Convolutional Neural Network (CNN) model, to identify distinct water level features in Closed-Circuit Television (CCTV) river imagery of the Chengmei Bridge on the Keelung River in Neihu District, Taiwan, under various weather conditions. This methodology creates a virtual water gauge system for the precise and timely detection of water levels, thereby eliminating the need for dependable physical gauges. Our study utilized image data from 1 March 2022 to 28 February 2023. This river, crucial to the ecosystems and economies of numerous cities, could instigate a range of consequences due to rapid increases in water levels. The proposed system integrates grid-based methods with infrastructure like CCTV cameras and Raspberry Pi devices for data processing. This integration facilitates real-time water level monitoring, even without physical gauges, thus reducing deployment costs. Preliminary results indicate an accuracy range of 83.6% to 96%, with clear days providing the highest accuracy and heavy rainfall the lowest. Future work will refine the model to boost accuracy during rainy conditions. This research introduces a promising real-time river water level monitoring solution, significantly contributing to flood control and disaster management strategies. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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16 pages, 13658 KiB  
Article
Research on Flood Risk Control Methods and Reservoir Flood Control Operation Oriented towards Floodwater Utilization
by Liwei Zhou, Ling Kang, Shuai Hou and Jinlei Guo
Water 2024, 16(1), 43; https://doi.org/10.3390/w16010043 - 21 Dec 2023
Viewed by 849
Abstract
Since improving floodwater utilization may increase flood risk, flood risk control methods for trade-offs between these factors have research value. This study presented a flood risk control method oriented towards floodwater utilization which considers multiple main flood risk factors. The proposed method not [...] Read more.
Since improving floodwater utilization may increase flood risk, flood risk control methods for trade-offs between these factors have research value. This study presented a flood risk control method oriented towards floodwater utilization which considers multiple main flood risk factors. The proposed method not only achieves the boundaries of the flood limited water level (FLWL) under various acceptable risks but also dynamically controls the water level to enhance floodwater utilization. A case study conducted on the Danjiangkou reservoir yielded the following results: (1) The proposed method provides FLWL dynamic control boundaries under various acceptable risks. (2) The proposed method reveals the potential to raise the FLWL, with a possibility to raise it by 1.00 m above the present FLWL under the absence of flood risk. (3) The available flood resources in both the wet and dry seasons increase, on average, by 0.83 and 0.81 billion m3, and the flood risk remains within the acceptable range after raising the FLWL by 1.00 m, which contributes to enhancing floodwater utilization. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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14 pages, 2779 KiB  
Article
Evolutionary Trends and Coordinated Development Analysis of Water Resources Systems and High-Quality Economic Growth in the Yangtze River Delta
by Di Liu, Qin Dai and Guanghui Yuan
Water 2023, 15(22), 4030; https://doi.org/10.3390/w15224030 - 20 Nov 2023
Cited by 1 | Viewed by 904
Abstract
This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination [...] Read more.
This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination coefficient, we investigate spatiotemporal evolutionary trends and overarching harmonious development states between the two systems. Results indicate: (1) Throughout the research period, mean values of high-quality economic development indices fluctuated within the range of 0.05 to 0.68, while water resource carrying capacity indices oscillated between 0.18 and 0.81. (2) The epicenter of high-quality economic development indices is situated in the periphery of Lake Tai, whereas the fulcrum of the water resource system indices is located in Huzhou City, both displaying a northwest-southeast orientation. (3) Coupling coordination development exhibits a propitious advancement trajectory, with certain locales attaining exemplary coordinated growth. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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20 pages, 3588 KiB  
Article
Sedimentation Characteristics of the Fluctuating Backwater Area at the Tail of Cascade Reservoirs: A Case Study of the Three Gorges Reservoir
by Jun Li, Hua Ge, Yanrong Ping, Xianyong Dong, Lingling Zhu and Yaochang Ma
Water 2023, 15(22), 4011; https://doi.org/10.3390/w15224011 - 19 Nov 2023
Viewed by 864
Abstract
The construction of cascade reservoirs is associated with considerable uncertainty in sedimentation in the fluctuating backwater area of the terminal reservoir and poses challenges to water safety. The sedimentation characteristics under the influence of multiple factors in the main urban area of the [...] Read more.
The construction of cascade reservoirs is associated with considerable uncertainty in sedimentation in the fluctuating backwater area of the terminal reservoir and poses challenges to water safety. The sedimentation characteristics under the influence of multiple factors in the main urban area of the Chongqing river section were analyzed as a case study for the operation of cascade reservoirs in the Jinsha River via the utilization of a large dataset spanning back to the normal storage of the Three Gorges Reservoir. The results of this study indicate that, owing to factors such as upstream water, sediment inflow, reservoir operation, and river sand mining, this river section experienced deposition on the sand bars and erosion in the main channel. The rate of sedimentation increased with sediment inflow, peak flow rate, and duration, while the location of sedimentation shifted as the concentration ratio changed. These results may provide technical support not only for the operation of the Three Gorges Reservoir, but also for the governance of the fluctuating backwater areas of other cascade reservoirs. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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18 pages, 13660 KiB  
Article
Optimization of Reservoir Level Scheduling Based on InSAR-LSTM Deformation Prediction Model for Rockfill Dams
by Zhigang Fang, Rong He, Haiyang Yu, Zixin He and Yaming Pan
Water 2023, 15(19), 3384; https://doi.org/10.3390/w15193384 - 27 Sep 2023
Viewed by 961
Abstract
The Xiaolangdi reservoir has a storage capacity of more than 10 billion cubic meters, and the dam has significant seasonal deformation. Predicting the deformation of the dam during different periods is important for the safe operation of the dam. In this study, a [...] Read more.
The Xiaolangdi reservoir has a storage capacity of more than 10 billion cubic meters, and the dam has significant seasonal deformation. Predicting the deformation of the dam during different periods is important for the safe operation of the dam. In this study, a long short-term memory (LSTM) model based on interferometric synthetic aperture radar (InSAR) deformation data is introduced to predict dam deformation. First, a time series deformation model of the Xiaolangdi Dam for 2017–2023 was established using Sentinel-1A data with small baseline subset InSAR (SBAS-InSAR), and a cumulative deformation accuracy of 95% was compared with the on-site measurement data at the typical point P. The correlation between reservoir level and dam deformation was found to be 0.81. Then, a model of reservoir level and dam deformation predicted by neural LSTM was established. The overall deformation error of the dam was predicted to be within 10 percent. Finally, we used the optimized reservoir level to simulate the deformation at the measured point P of the dam, which was reduced by about 36% compared to the real deformation. The results showed that the combination of InSAR and LSTM could predict dam failure and prevent potential failure risks by adjusting the reservoir levels. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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14 pages, 2044 KiB  
Article
Optimization of Multi-Reservoir Flood Control Operating Rules: A Case Study for the Chaobai River Basin in China
by Wenhua Wan, Yueyi Liu, Hang Zheng, Jianshi Zhao, Fei Zhao and Yajing Lu
Water 2023, 15(15), 2817; https://doi.org/10.3390/w15152817 - 4 Aug 2023
Cited by 1 | Viewed by 1085
Abstract
Reservoirs are susceptible to interference from inter-basin water transfer projects intended to relieve serious water shortages. The Central Route of the South-to-North Water Division Project in China has altered the hydrological conditions and water storage status of the terminal reservoir, the Miyun Reservoir, [...] Read more.
Reservoirs are susceptible to interference from inter-basin water transfer projects intended to relieve serious water shortages. The Central Route of the South-to-North Water Division Project in China has altered the hydrological conditions and water storage status of the terminal reservoir, the Miyun Reservoir, thereby affecting the flood control reliability in the Chaobai River Basin. In this study, a dual-objective five-reservoir operation model was developed, in which reservoir releases are obtained through piecewise linear operating rules. The model considers the flooding risks both downstream of the basin and in the Miyun reservoir area. A parameterization-simulation-optimization approach was employed to obtain the Pareto-optimal front, providing decision-makers with a list of optimal rule parameters to select and match their own risk preferences. All optimized rules could ensure safe operation during the designed floods to be expected once (or more than once) every thousand years. In contrast, the current flood operation schemes largely ignore the water transfer between basins but primarily concentrate on storing water from floods. Thus, the Miyun Reservoir, whose design return period is 1000 years, can easily become filled during a 100-year flood, impeding the system’s flood control capacity. Compared to the operating rule optimized in this study, the current schemes result in a 10.5% higher upstream inundation loss and an unsatisfactory 17 million CNY of equivalent water transfer loss. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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Review

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13 pages, 3216 KiB  
Review
A Scientometric Review for Uncertainties in Integrated Simulation–Optimization Modeling System
by Congcong Li, Lulu He, Dan Liu and Zhiyong Feng
Water 2024, 16(2), 285; https://doi.org/10.3390/w16020285 - 14 Jan 2024
Cited by 1 | Viewed by 992
Abstract
Water resources management is a challenging task caused by huge uncertainties and complexities in hydrological processes and human activities. Over the last three decades, various scholars have carried out the study on hydrological simulation under complex conditions and quantitatively characterized the associated uncertainties [...] Read more.
Water resources management is a challenging task caused by huge uncertainties and complexities in hydrological processes and human activities. Over the last three decades, various scholars have carried out the study on hydrological simulation under complex conditions and quantitatively characterized the associated uncertainties for water resources systems. To keep abreast of the development of the collective knowledge in this field, a scientometric review and metasynthesis of the existing uncertainty analysis research for supporting hydrological modeling and water resources management has been conducted. A total of 2020 publications from 1991 to 2018 were acquired from the Web of Science. The scientific structure, cooperation, and frontiers of the related domain were explored using the science mapping software CiteSpace V5.4.R3. Through co–citation, collaboration, and co–occurrence network study, the results present the leading contributors among all countries and hotspots in the research domain. In addition, synthetical uncertainty management for hydrological models and water resource systems under climatic and land use change will continue to be focused on. This study comprehensively evaluates various aspects of uncertainty analysis in hydrologic simulation–optimization systems, showcasing advanced data analysis and artificial intelligence technologies. It focuses on current research frontiers, aiding decision–makers in better understanding and managing the complexity and uncertainties of water resource systems, thereby enhancing the sustainability and efficiency of responses to environmental changes. Full article
(This article belongs to the Special Issue Reservoir Control Operation and Water Resources Management)
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