Integrated Reservoir Operation Considering Real-Time Hydrological Prediction for Adaptive Water Resources Management

2016 ◽  
pp. 101-132 ◽  
Author(s):  
Daisuke Nohara ◽  
Tomoharu Hori
Keyword(s):  
Water Resources ◽  
Real Time ◽  
Water Resources Management ◽  
Reservoir Operation ◽  
Resources Management ◽  
Hydrological Prediction

scholarly journals Optimization of Water-Supply and Hydropower Reservoir Operation Using the Charged System Search Algorithm

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 5 ◽  
Author(s):  
Behzad Asadieh ◽  
Abbas Afshar
Keyword(s):  
Water Resources ◽  
Water Supply ◽  
Water Resources Management ◽  
Reservoir Operation ◽  
Big Bang ◽  
Alternative Methods ◽  
Resources Management ◽  
Charged System Search ◽  
Non Linear ◽  
Charged System

The Charged System Search (CSS) metaheuristic algorithm is introduced to the field of water resources management and applied to derive water-supply and hydro-power operating policies for a large-scale real-world reservoir system. The optimum algorithm parameters for each reservoir operation problems are also obtained via a tuning procedure. The CSS algorithm is a metaheuristic optimization method inspired by the governing laws of electrostatics in physics and motion from the Newtonian mechanics. In this study, the CSS algorithm’s performance has been tested with benchmark problems, consisting of highly non-linear constrained and/or unconstrained real-valued mathematical models, such as the Ackley’s function and Fletcher–Powell function. The CSS algorithm is then used to optimally solve the water-supply and hydropower operation of “Dez” reservoir in southern Iran over three different operation periods of 60, 240, and 480 months, and the results are presented and compared with those obtained by other available optimization approaches including Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Constrained Big Bang–Big Crunch (CBB–BC) algorithm, as well as those obtained by gradient-based Non-Linear Programming (NLP) approach. The results demonstrate the robustness and superiority of the CSS algorithm in solving long term reservoir operation problems, compared to alternative methods. The CSS algorithm is used for the first time in the field of water resources management, and proves to be a robust, accurate, and fast convergent method in handling complex problems in this filed. The application of this approach in other water management problems such as multi-reservoir operation and conjunctive surface/ground water resources management remains to be studied.

scholarly journals Optimisation of Multipurpose Reservoir Operation by coupling SWAT and Genetic Algorithm for Optimal Operating Policy (Case Study: Ganga River basin)

2018 ◽  
Author(s):  
Jatin Anand ◽  
A K Gosain ◽  
R Khosa
Keyword(s):  
Genetic Algorithm ◽  
Water Resources ◽  
Water Resources Management ◽  
Reservoir Operation ◽  
Integrated Water Resources Management ◽  
Optimal Operating ◽  
Resources Management ◽  
Decision Variables ◽  
Operating Policies

Reservoirs are recognized as one of the most efficient infrastructure components in integrated water resources management and development. At present, with the ongoing advancement of social economy and requirement of water, the water resources shortage problem has worsened, and the operation of reservoirs, in terms of consumption of flood water, has become significantly important. Reservoirs perform both regulation of flood and integrated water resources management, in which the flood limited water level is considered as the most important parameter for trade-off between regulation of flood and conservation. To achieve optimal operating policies for reservoirs, large numbers of simulation and optimization models have been developed in the course of recent decades, which vary notably in their applications and working. Since each model has their own limitations, the determination of fitting model for derivation of reservoir operating policies is challenging and most often there is always a scope for further improvement as the selection of model depends on availability of data. Subsequently, assessment and evaluation associated with the operation of reservoir stays conventional. In the present study, the Soil and Water Assessment Tool (SWAT) models and a Genetic Algorithm model has been developed and applied to two reservoirs in Ganga River basin, India to derive the optimal operational policies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. As a result, a simulation-based optimization model was recommended for optimal reservoir operation, such as allocation of water, flood regulation, hydropower generation, irrigation demands and navigation and e-flows using a definite combination of decision variables. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on simulated result, in the present case study it is concluded that GA-derived policies are promising and competitive and can be effectively used operation of the reservoir.

scholarly journals Proposition of New Metaphor-Less Algorithms for Reservoir Operation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Vartika Paliwal ◽  
Aniruddha D. Ghare ◽  
Ashwini B. Mirajkar ◽  
Neeraj Dhanraj Bokde ◽  
Zaher Mundher Yaseen
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Reservoir Operation ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Computational Time ◽  
Benchmark Problems ◽  
Operation System ◽  
Resources Management ◽  
Operation Optimization

Based on the current water crisis scenario, effective water resources management can play an essential role. Reservoir operation optimization is part of water resources management. Reservoir operation optimization is difficult as it involves a large number of variables and constraints to achieve this goal. The present study aims at exploring the performance of recently developed heuristic algorithms—Rao algorithms as applied to the reservoir operation studies for the first time. Rao algorithms are metaphor-less algorithms that require only basic parameters—population size and function evaluations. In the present study, Rao algorithms have been applied to two case studies: discrete four-reservoir operation system problem and continuous four-reservoir operation system problem (benchmark problems) for the assessment of their performance vis-à-vis other algorithms from the literature. The results showed that the Rao-1 algorithm provided the optimal solution with the least function evaluations when compared to Rao-2, Rao-3, and other algorithms applied in the past to the same benchmark problem. Consequently, the Rao-1 model is found to be superior to these approaches by taking less computational time. Hence, the Rao-1 algorithm can be considered suitable for application to reservoir operation optimization problems.

scholarly journals Open storm: a complete framework for sensing and control of urban watersheds

2018 ◽  
Vol 4 (3) ◽  
pp. 346-358 ◽  
Author(s):  
Matthew Bartos ◽  
Brandon Wong ◽  
Branko Kerkez
Keyword(s):  
Water Resources ◽  
Internet Of Things ◽  
Real Time ◽  
Water Resources Management ◽  
Water Systems ◽  
Urban Watersheds ◽  
Resources Management ◽  
Smart Water ◽  
And Control ◽  
Complete Framework

Leveraging recent advances in technologies surrounding the Internet of Things, “smart” water systems are poised to transform water resources management by enabling ubiquitous real-time sensing and control.

scholarly journals Development of multi-objective reservoir operation rules for integrated water resources management

2009 ◽  
Vol 12 (2) ◽  
pp. 185-200 ◽  
Author(s):  
T. S. Cheong ◽  
I. Ko ◽  
J. W. Labadie
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Reservoir Operation ◽  
Integrated Water Resources Management ◽  
Optimization Models ◽  
Resources Management ◽  
Operating Rules ◽  
Operation Rules ◽  
Optimal Network ◽  
Reservoir Conditions

Real-time monitoring, databases, optimization models and visualization tools have been integrated into a Decision Support System (DSS) for optimal water resources management of two water supply reservoirs, the Daechung Reservoir and the Yongdam Reservoir of the Geum River basin, Daejeon, Korea. The KModSim as a DSS has been designed to provide information on current reservoir conditions to operational staff and to help in making decisions for short- and long-term management. For the physical calibration, the network simulations in seasonal water allocation of both reservoirs are performed for 23 years from January 1 1983 to June 30 2006. Linear and nonlinear operating rules are developed by using the actual reservoir operation data obtained from both reservoirs which are then used in KModSim by the hydrologic state method to estimate optimized target storages of both reservoirs. For validation of hydrologic states in KModSim and scenario testing for the management simulations, the optimal network simulation for the seasonal water allocations from October 1 2002 to June 30 2006 were also performed. The results' simulation by new rules fit the measured actual reservoir storage and represent well the various outflow discharge curves measured at the gauging stations of Geum River. The developed operating rules are proven to be superior in explaining actual reservoir operation as compared to the simulated target storages by existing optimization models.

scholarly journals Quantification of resilience to water scarcity, a dynamic measure in time and space

2016 ◽  
Vol 373 ◽  
pp. 13-17 ◽  
Author(s):  
S. P. Simonovic ◽  
R. Arunkumar
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Water Resources ◽  
Global Change ◽  
Water Resources Management ◽  
Water Scarcity ◽  
Reservoir Operation ◽  
Spatial Dynamics ◽  
Direct Interaction ◽  
Resources Management

Abstract. There are practical links between water resources management, climate change adaptation and sustainable development leading to reduction of water scarcity risk and re-enforcing resilience as a new development paradigm. Water scarcity, due to the global change (population growth, land use change and climate change), is of serious concern since it can cause loss of human lives and serious damage to the economy of a region. Unfortunately, in many regions of the world, water scarcity is, and will be unavoidable in the near future. As the scarcity is increasing, at the same time it erodes resilience, therefore global change has a magnifying effect on water scarcity risk. In the past, standard water resources management planning considered arrangements for prevention, mitigation, preparedness and recovery, as well as response. However, over the last ten years substantial progress has been made in establishing the role of resilience in sustainable development. Dynamic resilience is considered as a novel measure that provides for better understanding of temporal and spatial dynamics of water scarcity. In this context, a water scarcity is seen as a disturbance in a complex physical-socio-economic system. Resilience is commonly used as a measure to assess the ability of a system to respond and recover from a failure. However, the time independent static resilience without consideration of variability in space does not provide sufficient insight into system's ability to respond and recover from the failure state and was mostly used as a damage avoidance measure. This paper provides an original systems framework for quantification of resilience. The framework is based on the definition of resilience as the ability of physical and socio-economic systems to absorb disturbance while still being able to continue functioning. The disturbance depends on spatial and temporal perspectives and direct interaction between impacts of disturbance (social, health, economic, and other) and adaptive capacity of the system to absorb disturbance. Utility of the dynamic resilience is demonstrated through a single-purpose reservoir operation subject to different failure (water scarcity) scenarios. The reservoir operation is simulated using the system dynamics (SD) feedback-based object-oriented simulation approach.

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