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The purpose of a flood control reservoir operation is to prevent flood damage downstream of the reservoir and the safety of the reservoir itself. When a single reservoir cannot provide enough storage capacity for certain flood control points downstream, cascade reservoirs should be operated together to protect these areas from flooding. In this stu...
Contexts in source publication
Context 1
... total flood control capacity of both of the two dams are nearly 5.6 billion m 3 . The characteristics of the three dams are summarized in Table 1. ...
Context 2
... Xiluodu and Xiangjiaba reservoirs need to protect the cities Yibin and Luzhou from flooding, when the flood with a 20-year return period occurs, and protect the city Chongqing from flooding, when the 50-year return period flood occurs. The Xiluodu, Xiangjiaba and TGR operate together to protect the Jingjiang area from flooding, when The characteristics of the three dams are summarized in Table 1. ...
Context 3
... order to further testify the reliability of the model, the historical observations, including the flood hydrographs of the years 1954, 1968, and 1998, were considered in this section and taken as the inputs of the current and optimal models. The highest water level of TGR routed by the proposed and current models are shown in Table 10, which indicates that the highest water level of TGR generally is lower based on the optimal model. hydrograph is operated by the current operation model and the other by the Xiluodu and Xiangjiaba cascade optimal operation model. ...
Context 4
... order to further testify the reliability of the model, the historical observations, including the flood hydrographs of the years 1954, 1968, and 1998, were considered in this section and taken as the inputs of the current and optimal models. The highest water level of TGR routed by the proposed and current models are shown in Table 10, which indicates that the highest water level of TGR generally is lower based on the optimal model. In order to further testify the reliability of the model, the historical observations, including the flood hydrographs of the years 1954, 1968, and 1998, were considered in this section and taken as the inputs of the current and optimal models. ...
Context 5
... order to further testify the reliability of the model, the historical observations, including the flood hydrographs of the years 1954, 1968, and 1998, were considered in this section and taken as the inputs of the current and optimal models. The highest water level of TGR routed by the proposed and current models are shown in Table 10, which indicates that the highest water level of TGR generally is lower based on the optimal model. According to the comparisons given in Table 10, it can be seen that the cascade optimal operation model can produce superior results to the current operation model. ...
Context 6
... highest water level of TGR routed by the proposed and current models are shown in Table 10, which indicates that the highest water level of TGR generally is lower based on the optimal model. According to the comparisons given in Table 10, it can be seen that the cascade optimal operation model can produce superior results to the current operation model. Therefore, the flood control capacity of the middle and lower reaches of the Yangtze river can be enhanced. ...
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Citations
... Watersheds are spatially and temporally uneven in terms of rainfall, evaporation, runoff yield, and confluences as well as topography and human activities. In streamflow forecasting, upcoming streamflow is systematically evaluated using historical hydro-meteorological data (Boughton and Droop 2003;Taormina et al. 2015;Cheng and Chau 2004) to provide prearranged preparation and management of water resources, as well as an early warning of natural disasters, such as droughts and floods, streamflow forecasting is essential (Bürger et al. 2007;Chen et al. 2018;Zhou et al. 2018a). Understanding the leading issues of stream capacity, humidity, judgment, and energy input is critical to improving water management in the region. ...
The growing population and the rise in urbanization have made managing water a critical concern around the world in recent years. Globally, flooding is one of the most devastating natural disasters. Flood risk mitigation relies heavily on accurate and consistent streamflow forecasts. Pakistan Upper Indus Basin (UIB) is most vulnerable to flooding. Floods have become more frequent in recent decades. UIB can be divided into sub-regions due to its landscape variability, and its collective impact is most prominent in the Massam region. UIB hydrological and meteorological station observations have been used to study seasonal hydro-meteorological variations. To predict flooding, this study proposes a hybrid model combining artificial neural networks as multi-layer perceptron (MLPs) in feed-forward mode, along with empirical mode decomposition (EMD). Data collected by the surface-water hydrology project and Pakistan Meteorological Department from 1960 to 2012, 1969 to 2012, and 1972 to 2012 have been utilized from 17 locations. Statistical parameters and Nash–Sutcliffe Efficiency were measured to analyze the model’s prowess. As a result, decomposition-based models perform better than AI-based models when it comes to prediction accuracy. MLPQTP-EMD performed exceptionally better than competing AI models. The results are further validated by performing a peak value analysis during the flooding season (June–September) achieving a remarkable 91.3% score adding a 5.6% increase by EMD for input data achieving 39.3–32.3% statistical indices scores.
... According to [4], [5], [6], a reservoir is operated according to a set of rules or guidelines for storing and releasing water depending upon the purposes it, is required to serve. The decisions are made regarding releases in different time periods in accordance with the demands. ...
... Then, there is carried out the evaluation of variables to the daily observed data series. According to [6], [9], due to the model development, the regulation of reservoir impounding operation can be made formularized through the algorithm approach, and the initial period of impounding can be further developed. Based on the argument above, the increasing water level elevation is influenced by inflow discharge to the reservoir (in a stochastic context) and outflow discharge of the reservoir. ...
The impounding stage of the reservoir is a stage after the implementation of dam construction is finished. The process of reservoir impounding is started by closing the tunnel diversion gate and the elevation of the water level will be moving up slowly. The speed of the increasing reservoir water level elevation is affected by the dry season or rainy season, so it is arranged in such a way for obtaining the daily increase is not more than 1.0 m/day, due to dam safety. This research intends to build this modeling, at first by studying which variables are affecting in order to get the safe period of impounding. The methodology consists of a correlation analysis of inflow, outflow, and the ratio between storage volume and inflow volume to the optimal impounding equation. The statistical hydrology approach is used in this modeling that will assess the 7 observed reservoir impounding which is started from base elevation until Full Supply Level (FSL). This modeling will help in decision-making about the selection of the safe and optimal period of reservoir impounding. At the end of impounding, the reservoir will be full and it starts to be allocated regarding the utilization that has been designed.
... Most of these unrecorded reservoirs are medium or small sized and locate in hilly areas with complex underwater topography (Rosenberg et al., 2000). The presence of these reservoirs poses significant impact on the proper allocation of water resources in the basin, as well as on the flood and drought prevention for local governments (Donchyts et al., 2022;Zhou et al., 2018). It is necessary to develop an efficient and robust method to obtain the capacity information of these reservoirs. ...
Reservoir is essential for water resources management and utilization, and its storage capacity is the key information for the scientific and engineering community. Over 95% of the ~100,000 reservoirs constructed in China lack capacity information due to the high cost and difficult accessibility of field measurements. Here we develop models of reservoir capacity estimation based on statistical and machine learning (ML) algorithms for the national-scale reservoirs in China. Based on the collected capacity records of a small portion of reservoirs and surrounding environment factors, we built statistical models by considering their associated variables, as well as ML models with different algorithms to predict the unknown reservoir capacities. The prediction results from different statistical and ML models were evaluated by comparing with the validated samples, and the optimal model was selected to estimate the reservoir capacity for further analyses. Results show that among the four statistical models and six ML models, the ML model using the extreme-gradient-boosting-tree (XGBoost) algorithm performs best in capacity prediction with a correlation coefficient of 0.97, a Nash-Sutcliffe efficiency of 0.95, and a mean absolute percentage error of 22.93%. The estimated capacity of unrecorded reservoirs using XGBoost was 279.28 km3 (254.52–306.47 km3), and the total capacity of Chinese reservoirs was 1,065.19 km3 (1,040.43–1,092.38 km3). The proposed method provides a feasible approach of rapid estimation of reservoir capacity and monitoring of storage variations at large scales, which is critical for the rational conservation and utilization of water resources and the formulation of related policies.
... Uncontrolled overflow of water through the waterfront structures, failures of standard mechanisms, or automation false response can lead to a waterfront structures breach of cascade HPPs. In this connection, the flood control operation of reservoirs in emergency conditions is one of the most important parts of emergency plans for potential incidents [4,5]. ...
Detailed forecasting of the flood flow discharge
makes it possible to avoid the destruction of the reservoir, as well
as to reduce the downstream damages. When single reservoir
cannot provide enough storage capacity for flood control, the
joint operation plan of all cascade reservoirs should be
prepared. The paper deals with the possibility of emergency
operation of hydroelectric power plant (HPP) cascade during
the flood period. The simulation model for HPP cascade optimal
operation planning was proposed and developed in the Matlab
Simulink software package. The model considers the technical
parameters of electric power plants, the control floodgate
efficiency, the water flow discharge capacity for each object, as
well as the wave time-lag between objects. The Kuban HPP
cascade was selected as a case study. Evaluation of the reliability
of the flood discharge by HPPs allows minimizing social and
environmental risks. The developed simulation model allows to
determine the boundaries of pool level fluctuations within the
cascade operation dispatch control. As a result, the
requirements of water management complex and the power
generation schedule are provided. The developed HPP cascade
model allows simulating various repair, emergency and post-accident operating modes, which causing the water flow
discharge capacity decreasing. An analysis of emergency modes
makes it possible to improve the dispatch schedule during a
flood period, to determine the normal operation recovery time
for cascade under various disturbances, to define the boundary
conditions for HPP cascade normal operation, etc.
... Current research on the flood control operation of reservoirs has mostly focused on flood season or secondary floods, while less attention has been paid to small and medium-sized floods and non-flood season flood operations (Zhao et al. 2009;Dong Si et al. 2013;Fu et al. 2016;Zhenghe et al. 2018;Zhou et al. 2018;Li et al. 2019). The main reason is that the flow of most rivers is small in non-flood season, and the flood volume is within the capacity range of the conventional operation of reservoirs, so the reservoirs can complete the flood control and power generation operation well, and the water resources are fully utilized. ...
This study aims to investigate the integrated optimization of long-term non-flood season flood dispatching and power generation dispatching and improve the utilization efficiency of non-flood season flood resources. In this study, an artificial bee colony (ABC) algorithm based on a multi-strategy mixed search is supplemented with variable time period characteristics to construct an optimal reservoir operation model with a maximum generating capacity under multiple constraints in a variable time period. The multi-year non-flood season flood operation of the Wanan Reservoir is considered as an example. After optimization, the average annual power generation in the non-flood season was increased by 14.23 million kW·h. The average utilization rate of water resources was increased by 3% over the studied period, and the utilization of flood resources was improved. The ABC optimization algorithm based on a multi-strategy hybrid search could alleviate the contradiction between the selection of the time interval step and the calculation accuracy and convergence speed, and it effectively improved the optimization efficiency and development ability of the standard ABC optimization algorithm. These results can provide suggestions for the improvement of the comprehensive benefits of reservoirs with non-flood floods as an important water resource.
HIGHLIGHTS
The model with maximum power generation in a variable period is constructed.;
Multi-strategy artificial bee colony algorithm is used for reservoir scheduling.;
Combine non-flood dispatching with power generation dispatching.;
Provide theoretical basis for the utilization of non-flood season flood resources.;
... The dynamic FLWL approach was also implemented to derive joint operation schemes for cascade reservoirs (Chen et al., 2013b;Tan et al., 2017;Zhou et al., 2018a, Zhou et al., 2018b and mixed cascade reservoirs Chen et al., 2022). The size of the problem was tackled using aggregation-decomposition technique (Gong et al., 2020a), and dynamic programming . ...
... However, the curse of dimensionality limits its use in optimization of multi-reservoir systems. To overcome this curse, modified DP algorithms like the discrete differential DP (DDDP) (Cheng et al., 2014), and the progressive optimality algorithm (POA) (Zhou et al., 2018b) have been used. Zhou et al. (2018b) used DP-POA in a two-stage model to derive optimal rules for a cascade of reservoirs with multiple control points by sequentially progressing from upstream to downstream. ...
... To overcome this curse, modified DP algorithms like the discrete differential DP (DDDP) (Cheng et al., 2014), and the progressive optimality algorithm (POA) (Zhou et al., 2018b) have been used. Zhou et al. (2018b) used DP-POA in a two-stage model to derive optimal rules for a cascade of reservoirs with multiple control points by sequentially progressing from upstream to downstream. The three-stage operation of flood mitigation proposed by Chou and Wu (2015) was extended to a parallel set of multi-reservoir system by Zhu et al. (2021) who used the stage wise storage compensation method to arrive at the optimal flood routing policy while maximizing the outflow peak reduction rate. ...
Operation of multipurpose reservoirs during flood season is a challenging task if there is a conflict among the purposes. Despite the importance of this theme in water resources management and a large number of relevant studies carried out, a detailed review paper on this topic is missing in the literature. Present paper aims to fill this gap by providing a comprehensive review of the published literature by classifying the articles. The conventional and advanced techniques used in flood control operation of single and multiple reservoirs have been reviewed. For flood control regulation, the best results are obtained by judicious use of current data and forecasts. Since the operators need to maintain a balance between conflicting demands in presence of uncertain inflows, assessment of risks and uncertainties and their management is crucial. Finally, suggestions for future research and development on this topic are provided.
... Wei et al. [17] proposed a multi-objective optimization method and a multi-attribute decision making strategy to balance the objectives involving flood control, power generation, water supply, and ecology in reservoir operation. An optimal flood control operation model of cascaded reservoirs was proposed by Zhou et al. [18] to coordinate the upstream reservoirs to reduce the downstream inflows at some flood control locations. Table 1 shows the summary of abbreviations. ...
A monthly hydropower scheduling determines the monthly flows, storage, and power generation of each reservoir/hydropower plant over a planning horizon to maximize the total revenue or minimize the total operational cost. The problem is typically a complex and nonlinear optimization that involves equality and inequality constraints including the water balance, hydraulic coupling between cascaded hydropower plants, bounds on the reservoir storage, etc. This work applied the Zoutendijk algorithm for the first time to a medium/long-term hydropower scheduling of cascaded reservoirs, where the generating discharge capacity is handled with an iterative procedure, while the other head-related nonlinear constraints are represented with exponential functions fitting to discrete points. The procedure starts at an initial feasible solution, from which it finds a feasible improving direction, along which a better feasible solution is sought with a one-dimensional search. The results demonstrate that the Zoutendijk algorithm, when applied to six cascaded hydropower reservoirs on the Lancang River, worked very well in maximizing the hydropower production while ensuring the highest firm power output to be secured.
... Therefore, considering the different interests that may exist in decision-making for the operation of reservoirs, as well as the mutual conflicts that these interests may present, finding operating policies to which all the involved parties will agree is not an easy task. For flood control objective, for instance, it is better if there is less water in the reservoir, allowing to accumulate a large additional volume of water during the flood season (Zhou et al., 2018), while more water in the reservoir is better for irrigation purposes (Scola et al., 2014). Regarding hydropower production, the stored energy in the reservoir gradually increases with the rise in water level (Jansen et al., 2013), and outflows might support irrigation, however, there are also well-known cases where hydropower production reduces water availability for irrigation (Ruijie, Cai, Ringler, & Zhu, 2017). ...
... Some researches also focused on flood control modeling and solution algorithms . C. Zhou et al. (2018) for instance, established a flood control model where the cascade reservoirs were divided into two subsystems, handled in two stages to minimize: the peak flow first, the highest water level second and then the flood water diversion third. Karbowski (1993) formulated an optimal flood control problem including multiple cascade reservoirs with inflow assumed being forecasted with certainty, which was solved by aggregating the storage capacities with the natural inflows to the system. ...
This paper presents a multireservoir flood control model that incorporates operating rules to alleviate the risk that results from traditional flood control models. The model is accurately reformulated into one that can be solved with the mixed integer linear programming (MILP) and approximated with a two‐stage linear programming (TSLP) to speed up the solution by excluding all the binary variables. A scroll decision‐making strategy is proposed by assuming only a few days of future inflows being predicted with certainty. With 10 historical and 30 designed floods in different magnitudes, the models and methods are applied to the Yangtze River basin, which includes 11 cascade reservoirs. The results on average show the MILP reduces the rule violation by 17%, while the TSLP is more than 150 times faster in CPU time. Excluding one of the reservoirs from the simulation reveals that the Three Gorges (TG) contributes the most in flood detention, accounting for 76% on average for once‐in‐a‐century floods. Interestingly, with the scroll decision‐making strategy implemented, the change from 3 to 7 days of certain forecasting has the most significant reduction in both the rule violation and flood detention, indicating that the forecasting accuracy of more recent inflows is more valuable for flood control.
... Design discharge is a discharge value that is available in flow at a certain time and is calculated to have an existence that exceeds or equals a value based on specific probabilities and distributions that represent the characteristics of the flow [20] [21]. This research uses the Weibull method (calculating 80% probability for R5 design discharge and 95% probability for R20 design discharge). ...
Cascade Citarum Reservoirs, located in the western part of the island of Java in Indonesia country, cover the main building dams, hydropower, irrigation facilities and other supporting facilities. The study aimed to evaluate the characteristics of the existing condition of the downstream reservoir, including the relation of the water quality and quantity, by using a conceptual model of the Citarum Cascade Reservoir management. The study mostly used the secondary data acquired from Indonesia Power, the Management Bureau of Cirata Dam (BPWC), Perum Jasa Tirta II (PJT) Jatiluhur, the Management Bureau of the Citarum-Ciliwung River Basin (BPDAS Citarum-Ciliwung), and the Water Resource Management Agency of the West Java Province. This research aims to predict the discharge plans R5 and R20 using the Weibull method and the uncertainty of future discharge using the continuous model approach. Furthermore, the multivariate statistical test will analyse the linkage of water quality in reservoir management. To solve the problem of the allocation of the raw water discharge to fulfil the water requirement in the downstream area was developed proportionally in this study, in which the raw water discharge allocations were 46.92 m3/sec, 91.9 m3 /sec and 97.95 m3/sec for Saguling, Cirata, and Jatiluhur, respectively. The tests to determine the relationship between the discharge and water quality using the Discriminant test indicated that the discharge correlates strongly with the parameters such as NH3. BOD and COD.
