Reducing Irrigation Deficiencies Based Optimizing Model for Multi-Reservoir Systems Utilizing Spider Monkey Algorithm

Continuous droughts and water scarcity have led to the need for optimal exploitation of dams’ reservoirs. Thus, the new meta-heuristic algorithm, spider monkey, is suggested for complex modeling of the multi-reservoir system in Iran with the aim of decreasing irrigation deficiencies. Golestan and Voshmgir dams’ operations are optimized with the spider monkey algorithm. The algorithm based on the exchange of information between local and global leaders with the other monkeys which improves the convergence speed. Average deficiencies for Golestan dam is computed as 2.1 and 1.9 MCM by spider monkey algorithm while it is respectively computed as 6.7, 16.4, 11.1, 4.1, 14.6, 19 MCM by particle swarm algorithm, harmony search algorithm, imperialist competitive algorithm, water cycle algorithm, genetic algorithm, and standards operation policy method. Also, the computation time of the spider monkey algorithm is 50 and 47 s for the Golestan and Voshmgir dams while the genetic algorithm optimizes the problem in 172.6 s and 112 s and the particle swarm algorithm needs 117.4 s and 100 s for the Golestan and Voshmgir, respectively. Also, root means square error (RMSE) and mean absolute error between demand and released water for the spider monkey algorithm have the least values among the applied evolutionary algorithms. Thus, the spider monkey algorithm is suggested as an appropriate method for optimizing the operation policy for the dam and reservoir systems.     

Chaotic Evolutionary Algorithms for Multi-Reservoir Optimization

The water sharing dispute in a multi-reservoir river basin forces the water resources planners to have an integrated operation of multi-reservoir system rather than considering them as a single reservoir system. Thus, optimizing the operations of a multi-reservoir system for an integrated operation is gaining importance, especially in India. Recently, evolutionary algorithms have been successfully applied for optimizing the multi-reservoir system operations. The evolutionary optimization algorithms start its search from a randomly generated initial population to attain the global optimal solution. However, simple evolutionary algorithms are slower in convergence and also results in sub-optimal solutions for complex problems with hardbound variables. Hence, in the present study, chaotic technique is introduced to generate the initial population and also in other search steps to enhance the performance of the evolutionary algorithms and applied for the optimization of a multi-reservoir system. The results are compared with that of a simple GA and DE algorithm. From the study, it is found that the chaotic algorithm with the general optimizer has produced the global optimal solution (optimal hydropower production in the present case) within lesser generations. This shows that coupling the chaotic algorithm with evolutionary algorithm will enrich the search technique by having better initial population and also converges quickly. Further, the performances of the developed policies are evaluated for longer run using a simulation model to assess the irrigation deficits. The simulation results show that the model satisfactorily meets the irrigation demand in most of the time periods and the deficit is very less.     

Generation of Clean Hydropower Energy in Multi-Reservoir Systems Based on a New Evolutionary Algorithm

Lingering droughts and shortage of water sources signify the importance of optimal utilization of water reservoirs such as multi-reservoir systems. These systems could be employed not only as a storage system to manage the water utilization but also as a power generation system. To rise the generated power besides the management of water utilization, an optimization algorithm should be used. In this study, the kidney algorithm in three different scenarios, namely the wet, normal, and dry years is employed to fulfill such an engineering operation in a four-reservoir system in China. Simulations show well compatibility of the water level inside the reservoir with real statistical indices in terms of RMSE and MAE. Results also reveal that using the kidney algorithm not only reduces the required calculation but also increases the convergence pace with respect to other algorithms that have been used (bat, shark, abundance of particles, and genetic algorithms). Moreover, it increases the amount of the generated energy by a factor of 2.2–3.2 with respect to the aforementioned algorithms. Results indicate the capability of the kidney algorithm in the management of water sources and engineering operations.

     

Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System

It is remarkable that several hydrological parameters have a significant effect on the reservoir operation. Therefore, operating the reservoir system is complex issue due to existing the nonlinearity hydrological variables. Hence, determining modern model has high ability in handling reservoir operation is crucial. The present study developed artificial intelligence model, called Shark Machine Learning Algorithm (SMLA) to provide optimal operational rules. The major objective for the proposed model is minimizing the deficit volume between water releases and the irrigation water demand. The current study compared the performance of the SML model with popular evolutionary computing methods, namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The proposed models have been utilized of finding the optimal policies to operate Timah Tasoh Dam, which is located in Malaysia. The study utilized considerable statistical indicators to explore the efficiency of the models. The simulation period showed that SMLA approach outperforms both of conventional algorithms. The SMLA attained high Reliability and Resilience (Rel. = 0.98%, Res. = 50%) and minimum Vulnerability (Vul. = 21.9 of demand). It is demonstrated that shark machine learning algorithm would be a promising tool in handling the long-term optimization problem in operation a reservoir system.     

Multi-Objective Optimization of the Proposed Multi-Reservoir Operating Policy Using Improved NSPSO

Severe water shortage is unacceptable for water-supply reservoir operation. For avoiding single periods of catastrophic water shortage, this paper proposes a multi-reservoir operating policy for water supply by combining parametric rule with hedging rule. In this method, the roles of parametric rule and hedging rule can be played at the same time, which are reducing the number of decision variables and adopting an active reduction of water supply during droughts in advance. In order to maintain the diversity of the non-dominated solutions for multi-objective optimization problem and make them get closer to the optimal trade-off surfaces, the multi-population mechanism is incorporated into the non-dominated sorting particle swarm optimization (NSPSO) algorithm in this study to develop an improved NSPSO algorithm (I-NSPSO). The performance of the I-NSPSO on two benchmark test functions shows that it has a good ability in finding the Pareto optimal set. The water-supply multi-reservoir system located at Taize River basin in China is employed as a case study to verify the effect of the proposed operating policy and the efficiency of the I-NSPSO. The operation results indicate that the proposed operating policy is suitable to handle the multi-reservoir operation problem, especially for the periods of droughts. And the I-NSPSO also shows a good performance in multi-objective optimization of the proposed operating policy.     

Near Real-Time Optimization of Multi-Reservoir during Flood Season in the Fengman Basin of China

This study aims to develop a multi-objective optimization model in a multi-reservoir system during flood season using Numerical Weather Predictions (NWPs) outputs (short forecast). The optimization model was coupled with the Water and Energy Budget-based Distributed Hydrological Model that was used to forecast the reservoir inflows. The model was forced by 8-day lead time global deterministic NWPs by Japan Meteorological Agency. The reservoir objective function was established by considering the reservoir and upstream safety, downstream safety and future water use. The model was applied to the Baishan-Fengman multi-reservoir system of Northeast China. The results have demonstrated the model with high efficiency in optimizing reservoir objectives for all of the reservoirs. The sensitivity of the system to lead time and decision time were investigated. With the decreasing of lead time, the dam release peaks decrease and the end water levels increase. This is mainly due to the fact that the model with longer lead time needs to keep storage capacity for detected floods during long lead time period. The variation amplitude of dam releases and water levels decrease with the increasing of decision time due to the smoothing of floods and dam releases during long decision period. The model is easy to operate and is able to be coupled with other hydrological models or earth system models.     

小湾特高拱坝首蓄期坝体变形特性分析及评价

针对小湾特高拱坝首次蓄水期坝体变形备受关注的几个焦点问题,运用综合过程线对比、数学建模、数值仿真、数理统计分析等定性和定量方法进行分析,结果表明:小湾大坝坝体蓄水早期向上游方向倾斜(主要与库盘下沉有关),库水位是首蓄期坝体变形的最主要影响因素,坝体时效变形已趋于收敛。通过将数值仿真成果与实测值比较、模型分析与实测值比较、设计预警指标与实测值比较、小湾工程与同类工程实测值比较,认为小湾水电站特高拱坝经受了正常蓄水位工况下的综合考验,尽管变形量值较大,但变形规律总体正常,首蓄期大坝处于安全状态。     

Reservoir Optimization in Water Resources: a Review

This paper reviews current optimization technique developed to solve reservoir operation problems in water resources. The application of conventional, especially evolutionary computation, combination of simulation-optimization and multi objectives optimization in reservoir operation will be discussed and investigated. Furthermore, new optimization algorithm from other applications will be presented by focusing on Artificial Bee Colony (ABC) and Gravitational Search Algorithm (GSA) as alternative methods that can be explored by researchers in water resources field. Finally this paper looks into the challenges and issues of climate change in reservoir optimization.     

Artificial Life Algorithm for Management of Multi-reservoir River Systems

The design and operation of civil engineering systems, particularly water resources systems, has been pursued from the perspective of minimizing costs and related negative impacts, maximizing benefits, or a combination thereof. Due to the complex, nonlinear nature of the majority of systems, together with an increase in digital computing capabilities, global search algorithms are becoming a common means of meeting these objectives. This paper employs an artificial life algorithm, derived from the artificial life paradigm. The algorithm is evaluated using standard optimization test functions and is subsequently applied to determine optimal dam operations in multi-reservoir river systems. The optimal dam operation scheme is that which indirectly minimizes environmental impacts caused by short-term water level fluctuations. Optimal releases are sought by coupling an artificial life algorithm with FLDWAV, a one-dimensional, steady flow simulation model. The resulting multi-reservoir management model is successfully applied to a portion of the Illinois River Waterway.     

Study on Water Sharing in a Multi-reservoir System Using a Dynamic Programming-Neural Network Model

A dynamic programming-based neural network model is developed for analysing the water sharing between two reservoirs in a multi-reservoir system catering for irrigation. To study the water sharing between two downstream reservoirs from an upstream reservoir, a modified dynamic programming algorithm with three state variables and four decision variables is proposed. The operating policies are derived from the three state variable dynamic programming algorithm using a neural network. The new dynamic programming neural network model gives a very good performance for the multi-reservoir system case study considered. The performance of this model is compared with the improvised standard operating policy and constrained dynamic programming neural network model previously suggested.     

An alternative approach to the operation of multinational reservoir systems: Application to the Amistad &; Falcon system (Lower Rio Grande/Río Bravo)

An optimization approach for the operation of international multi-reservoir systems is presented. The approach uses Stochastic Dynamic Programming (SDP) algorithms – both steady-state and real-time – to develop two models. In the first model, the reservoirs and flows of the system are aggregated to yield an equivalent reservoir, and the obtained operating policies are disaggregated using a non-linear optimization procedure for each reservoir and for each nation's water balance. In the second model a multi-reservoir approach is applied, disaggregating the releases for each country's water share in each reservoir. The non-linear disaggregation algorithm uses SDP-derived operating policies as boundary conditions for a local time-step optimization. Finally, the performance of the different approaches and methods is compared. These models are applied to the Amistad-Falcon International Reservoir System as part of a binational dynamic modeling effort to develop a decision support system tool for a better management of the water resources in the Lower Rio Grande Basin, currently enduring a severe drought.     

钢构拦水坝在城市水生态建设中的应用进程与技术经济比较

随着城市水生态建设的趋势,河道拦水坝的应用需求越来越大,河道拦水坝的结构不仅要满足航运、灌溉、行洪等常规功能,还要满足环境协调、生态水景的要求。由于橡胶坝坝袋易破损、易老化、无法快速截洪泄流、景观融合度低等缺点,钢构拦水坝应运而生。本文介绍了5种钢构拦水坝即升卧式闸门、气动盾形闸、钢坝闸、液压升降坝及合页活动坝,阐述了其工作原理及结构特征,对比分析了其地基要求、土建工程量及安装难度、运行使用、景观生态特点和造价,归纳总结了各自的适用条件,为水利工程钢构拦水坝的应用选择提供参考。     

库底非饱和淤砂层对高拱坝地震反应的影响

采用时域显式有限元方法,将库底非饱和淤砂层近似模拟为不同于库水的流体介质。以小湾拱坝为例,分析可压缩库水条件下库底非饱和淤砂层对高拱坝地震反应的影响。计算结果表明非饱和淤砂层的存在有可能使得坝体地震响应增加。     

Physical and Biological Responses to an Alternative Removal Strategy of a Moderate‐sized Dam in Washington,USA

Dam removal is an increasingly practised river restoration technique, and ecological responses vary with watershed, dam and reservoir properties, and removal strategies. Moderate‐sized dams, like Hemlock Dam (7.9 m tall and 56 m wide), are large enough that removal effects could be significant, but small enough that mitigation may be possible through a modified dam removal strategy. The removal of Hemlock Dam in Washington State, USA, was designed to limit channel erosion and improve fish passage and habitat by excavating stored fine sediment and reconstructing a channel in the former 6‐ha reservoir. Prior to dam removal, summer daily water temperatures downstream from the dam increased and remained warm long into the night. Afterwards, a more natural diel temperature regime was restored, although daily maximum temperatures remained high. A short‐lived turbidity pulse occurred soon after re‐watering of the channel, but was otherwise similar to background levels. Substrate shifted from sand to gravel–cobble in the former reservoir and from boulder to gravel–cobble downstream of the dam. Initially, macroinvertebrate assemblage richness and abundance was low in the project area, but within 2 years, post‐removal reaches upstream and downstream of the dam had diverse and abundant communities. The excavation of stored sediment and channel restoration as part of the dam removal strategy restored river continuity and improved benthic habitat while minimizing downstream sedimentation. This study provides a comparison of ecological effects with other dam removal strategies and can inform expectations of response time and magnitude. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.     

Optimal Reservoir Operation Based on Conjunctive Use of Surface Water and Groundwater Using Neuro-Fuzzy Systems

Reservoir operation cannot be carried out without due heed to surface water and groundwater resources, since neglecting either will have irreversible consequences. Optimal operation of the Zayandehrood Dam which supplies water into the Zayandehrood River basin in the central plateau of Iran is a case in point which warrants due consideration paid to both dam operation and the climate conditions in the region suffering from a history of successive droughts. The main objective of the present research is to develop operation rules for the Zayandehrood reservoir through a combined perspective of both surface and ground water resources using the fuzzy inference system, and adaptive neuro-fuzzy inference system. The objective is to determine the share of the Zayandehrood reservoir in meeting downstream water demands. For this purpose, the water shortage and the dramatic groundwater drawdown in the Zayandehrood River basin faced with in recent years have been studied in an attempt to develop operation models capable of controlling groundwater drawdown. The models indicate that not only can groundwater drawdown be controlled, but that it is also possible to establish a greater sustainability. Different operation models have been compared in terms of their operation criteria. Results show that the ANFIS model composed of optimal data enjoys a higher sustainability compared to others.     

坝体混凝土爆破拆除施工方法探讨

闹德海水库是一座防洪滞沙、农田灌溉、城市供水等综合利用的大（2）型水库,是辽河一级支流柳河上唯一已建的大型控制性工程。始建于1942年,历经了三次加固与改建,依据水利部大坝安全管理中心坝函[2005]989号文,对闹德海水库进行第四次加固。本次加固内容为上游增设检修门槽、坝下消能工等项目。由于闹德海水库承担向阜新日供水8万t任务,且阜新又没有替代水源,工期非常重要,为加快工程施工进度,在大坝主体上采取控制与预裂爆破的方法拆除原闸门槽混凝土。通过仪器检测质点震动速度小于10cm／s,完全满足规范和设计要求,同时也保证了工程质量和工期。     

区域水库群大坝安全评价体系的构建

结合江西省水库群大坝安全评价工作,介绍了区域水库群大坝安全评价体系的构建过程,包括大坝安全评价技术标准的制定、单座水库大坝工程险度评价和风险评估、区域性水库群除险加固全面规划、水库群大坝安全风险排序、大坝病险原因分析及对策研究、除险加固方案的实施效果评价及区域性水库群除险加固动态管理信息系统的建立等内容。该体系在江西省水库群大坝安全评价中的应用效果良好,可为决策者提供科学依据。     

The effect of Keepit Dam on the temperature regime of the Namoi River,Australia

Modifications to water temperature caused by the release of hypolimnetic water from thermally stratified reservoirs pose a major threat to the aquatic biota of lowland rivers in Australia's Murray–Darling basin. Keepit Dam is earmarked as one of several deep‐release structures in the basin causing ecologically significant temperature modification over a large length of river. This study utilized discrete and continuously monitored historical water temperature data from stream gauging stations, together with reservoir thermal profile data, to assess the impacts of Keepit Dam on the thermal regime of the Namoi River. Modifications to selected components of the river's annual temperature cycle were quantified in relation to a pre‐dam temperature regime estimated from statistical models incorporating catchment, hydrological and sample attributes. Keepit Dam has modified the thermal regime of the Namoi River. The effect was greatest immediately downstream from the dam where the annual maximum daily temperature was approximately 5.0 °C lower and occurred three weeks later than the pre‐dam condition. This change was sufficient to disrupt thermal spawning cues for selected Australian native fish species. The magnitude of disturbance progressively diminished with distance from the dam. Key aspects of the river's annual temperature cycle were largely restored to the pre‐dam condition within 100 river km downstream from the dam, which is closer than previous estimates. However, there was marked inter‐annual variation in the magnitude of thermal modification and ecological impact as a result of year to year changes in tributary flow and reservoir behaviour. Copyright © 2002 John Wiley & Sons, Ltd.     

Reservoir water effects on earthquake performance evaluation of Torul Concrete-Faced Rockfill Dam

This study presents earthquake performance analysis of the Torul Concrete-Faced Rockfill (CFR) Dam with two-dimensional dam-soil and dam-soil-reservoir finite element models. The Lagrangian approach was used with fluid elements to model impounded water. The interface elements were used to simulate the slippage between the concrete face slab and the rockfill. The horizontal component of the 1992 Erzincan earthquake, with a peak ground acceleration of 0.515g, was considered in time-history analysis. The Drucker-Prager model was preferred in nonlinear analysis of the concrete slab, rockfill and foundation soil. The maximum principal stresses and the maximum displacements in two opposite directions were compared by the height of the concrete slab according to linear time-history analysis to reveal the effect of reservoir water. The changes of critical displacements and principal stresses with time are also shown in this paper. According to linear and nonlinear time-history analysis, the effect of the reservoir water on the earthquake performance of the Torul CFR Dam was investigated and the possible damage situation was examined. The results show that the hydrodynamic pressure of reservoir water leads to an increase in the maximum displacements and principal stresses of the dam and reduces the earthquake performance of the dam. Although the linear time-history analysis demonstrates that the earthquake causes a momentous damage to the concrete slab of the Torul CFR Dam, the nonlinear time-history analysis shows that no evident damage occurs in either reservoir case.     

A simplified water temperature model for the Colorado River below Glen Canyon Dam

Glen Canyon Dam, located on the Colorado River in northern Arizona, has affected the physical, biological and cultural resources of the river downstream in Grand Canyon. One of the impacts to the downstream physical environment that has important implications for the aquatic ecosystem is the transformation of the thermal regime from highly variable seasonally to relatively constant year‐round, owing to hypolimnetic releases from the upstream reservoir, Lake Powell. Because of the perceived impacts on the downstream aquatic ecosystem and native fish communities, the Glen Canyon Dam Adaptive Management Program has considered modifications to flow releases and release temperatures designed to increase downstream temperatures. Here, we present a new model of monthly average water temperatures below Glen Canyon Dam designed for first‐order, relatively simple evaluation of various alternative dam operations. The model is based on a simplified heat‐exchange equation, and model parameters are estimated empirically. The model predicts monthly average temperatures at locations up to 421 km downstream from the dam with average absolute errors less than 0.5°C for the dataset considered. The modelling approach used here may also prove useful for other systems, particularly below large dams where release temperatures are substantially out of equilibrium with meteorological conditions. We also present some examples of how the model can be used to evaluate scenarios for the operation of Glen Canyon Dam. Published in 2008 by John Wiley & Sons, Ltd.