scholarly journals A stochastic approach to analyze trade-offs and risks associated with large-scale water resources systems

2007 ◽  
Vol 43 (6) ◽  
Author(s):  
A. Tilmant ◽  
R. Kelman
Keyword(s):  
Water Resources ◽  
Large Scale ◽  
Stochastic Approach ◽  
Water Resources Systems ◽  
Trade Offs

Optimizing the management of complex water resources systems taking into account the long-term persistence in streamflow

2020 ◽  
Author(s):  
Amaury Tilmant ◽  
Vahid Espanmanesh
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Optimization Techniques ◽  
Irrigated Agriculture ◽  
Water Resources Systems ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Operating Policies ◽  
Dual Dynamic Programming

<p>The operation of multireservoir systems is a challenging decision-making problem due to (i) multiple, often conflicting, objectives (e.g. hydropower generation versus irrigated agriculture), (ii) stochastic variables (e.g. inflows, water demands, commodity prices), (iii) nonlinear relationships, (e.g. hydropower production function) and (iv) trade-offs between immediate and future consequences. Properly capturing the properties of the hydrologic processes responsible for the inflows is of paramount importance to enhance the performance of water resources systems. This becomes all the more relevant since low-frequency climate signals, which affect the hydrology in numerous regions around the globe, has increased in recent years. If traditional time series models generally fail to reproduce this regime-like behavior, so are the optimization models that are used to support multireservoir operation. Hidden Markov Model (HMM) is a class of hydrological models that can accommodate both overdispersion and serial dependence in historical time series, two essential hydrological properties that must be captured when modeling a system where the climate is switching between different states (e.g., dry, normal, wet). In terms of reservoir operation, Stochastic Dual Dynamic Programming (SDDP) is one of the few optimization techniques that can accomodate both system and hydrologic complexity. In SDDP, the hydrologic uncertainty is often captured by a multi-site periodic autoregressive (MPAR) model. However, MPAR models are unable to represent the long-term persistence of the streamflow process found in some regions, which may lead to suboptimal reservoir operating policies. We present an extension of the SDDP algorithm that can handle the long-term persistence and provide reservoir operating policies that explicitly capture regime shifts. To achieve this, the state-space vector now includes a climate variable whose transition is governed by a HMM. The Senegal River Basin (SRB), whose flow regime is characterized by multiyear dry/wet periods, is used as a case study.</p>

scholarly journals Scalable Multiobjective Control for Large-Scale Water Resources Systems Under Uncertainty

2018 ◽  
Vol 26 (4) ◽  
pp. 1492-1499 ◽  
Author(s):  
Matteo Giuliani ◽  
Julianne D. Quinn ◽  
Jonathan D. Herman ◽  
Andrea Castelletti ◽  
Patrick M. Reed
Keyword(s):  
Water Resources ◽  
Large Scale ◽  
Water Resources Systems ◽  
Multiobjective Control

scholarly journals Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

2018 ◽  
Vol 66 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Ali Hojjati ◽  
Mohsen Monadi ◽  
Alireza Faridhosseini ◽  
Mirali Mohammadi
Keyword(s):  
Water Resources ◽  
Flood Control ◽  
Optimization Methods ◽  
Optimal Operation ◽  
Nsga Ii ◽  
Water Resources Systems ◽  
Multi Objective ◽  
Trade Offs ◽  
Reservoir Systems ◽  
Alternative Solutions

Abstract Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.

scholarly journals WRSS: An Object-Oriented R Package for Large-Scale Water Resources Operation

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3037
Author(s):  
Rezgar Arabzadeh ◽  
Parisa Aberi ◽  
Sina Hesarkazzazi ◽  
Mohsen Hajibabaei ◽  
Wolfgang Rauch ◽  
...  
Keyword(s):  
Water Resources ◽  
Single Unit ◽  
Large Scale ◽  
Object Oriented ◽  
R Package ◽  
Planning System ◽  
Return Flow ◽  
Coding System ◽  
Water Resources System ◽  
Water Resources Systems

Water resources systems, as facilities for storing water and supplying demands, have been critically important due to their operational requirements. This paper presents the applications of an R package in a large-scale water resources operation. The WRSS (Water Resources System Simulator) is an object-oriented open-source package for the modeling and simulation of water resources systems based on Standard Operation Policy (SOP). The package provides R users several functions and methods to build water supply and energy models, manipulate their components, create scenarios, and publish and visualize the results. WRSS is capable of incorporating various components of a complex supply–demand system, including numerous reservoirs, aquifers, diversions, rivers, junctions, and demand nodes, as well as hydropower analysis, which have not been presented in any other R packages. For the WRSS’s development, a novel coding system was devised, allowing the water resources components to interact with one another by transferring the mass in terms of seepage, leakage, spillage, and return-flow. With regard to the running time, as a key factor in complex models, WRSS outshone the existing commercial tools such as the Water Evaluation and Planning System (WEAP) significantly by reducing the processing time by 50 times for a single unit reservoir. Additionally, the WRSS was successfully applied to a large-scale water resources system comprising of 5 medium- to large-size dams with 11 demand nodes. The results suggested dams with larger capacity sizes may meet agriculture sector demand but smaller capacities to fulfill environmental water requirement. Additionally, large-scale approach modeling in the operation of one of the studied dams indicated its implication on the reservoirs supply resiliency by increasing 10 percent of inflow compared with single unit operation.

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