Risk Analysis and Stochastic Management of Reservoir Systems PDF Download
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Author: Miguel A. Marino
Publisher:
ISBN:
Category : Flood control
Languages : en
Pages : 742
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Book Description
Author: Miguel A. Marino
Publisher:
ISBN:
Category : Flood control
Languages : en
Pages : 742
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Book Description
Author: J.B. Marco
Publisher: Springer Science & Business Media
ISBN: 9401116970
Category : Science
Languages : en
Pages : 470
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Book Description
Stochastic hydrology is an essential base of water resources systems analysis, due to the inherent randomness of the input, and consequently of the results. These results have to be incorporated in a decision-making process regarding the planning and management of water systems. It is through this application that stochastic hydrology finds its true meaning, otherwise it becomes merely an academic exercise. A set of well known specialists from both stochastic hydrology and water resources systems present a synthesis of the actual knowledge currently used in real-world planning and management. The book is intended for both practitioners and researchers who are willing to apply advanced approaches for incorporating hydrological randomness and uncertainty into the simulation and optimization of water resources systems. (abstract) Stochastic hydrology is a basic tool for water resources systems analysis, due to inherent randomness of the hydrologic cycle. This book contains actual techniques in use for water resources planning and management, incorporating randomness into the decision making process. Optimization and simulation, the classical systems-analysis technologies, are revisited under up-to-date statistical hydrology findings backed by real world applications.
Author: Martin Kistenmacher
Publisher:
ISBN:
Category : Forecasting
Languages : en
Pages :
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Book Description
Reservoir systems are subject to several uncertainties that are the result of imperfect knowledge about system behavior and inputs. A major source of uncertainty arises from the inability to predict future inflows. Fortunately, it is often possible to generate probabilistic forecasts of inflow volumes in the form of probability density functions or ensembles. These inflow forecasts can be coupled with stochastic management models to determine reservoir release policies and provide stakeholders with meaningful information of upcoming system responses such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. This information on anticipated system responses is also expressed in the form of forecasts that must reliably represent the actual system behavior when it eventually occurs. The first part of this study presents an assessment methodology that can be used to determine the consistency of ensemble forecasts through the use of relative frequency histograms and minimum spanning trees (MST). This methodology is then used to assess a management model's ability to produce reliable ensemble forecasts. It was found that neglecting to account for hydrologic state variables and improperly modeling the finite management horizon decrease ensemble consistency. Several extensions to the existing management model are also developed and evaluated. The second portion of this study involves the management of the uncertainties in reservoir systems. Traditional management models only find management policies that optimize the expected values of system benefits or costs, thereby not allowing operators and stakeholders to explicitly explore issues related to uncertainty and risk management. A technique that can be used to derive management policies that produce desired probabilistic distributions of reservoir system outputs reflecting stakeholder preferences is developed. This technique can be embedded in a user-interactive framework that can be employed to evaluate the trade-offs and build consensus in multi-objective and multi-stakeholder systems. The methods developed in this dissertation are illustrated in case studies of real reservoir systems, including a seven-reservoir, multi-objective system in California's Central Valley.
Author: Janos J. Bogardi
Publisher: Cambridge University Press
ISBN: 1139432249
Category : Science
Languages : en
Pages : 240
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Book Description
35 leading multi-disciplinary scientists with international reputations provide reviews of topical areas of research on uncertainty and reliability related aspects of water resource systems. The volume will be valuable for graduate students, scientists, consultants, administrators, and practising hydrologists and water managers.
Author: William W-G. Yeh
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 162
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Book Description
Author: Zhong Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Water resources are indispensable for the sustainable development of the human society. A variety of hydrological modeling and water resources management tools based on simulation and optimization have been developed to address the current water issues worldwide. However, there are many challenges arising from climate change, human disturbances and enormous uncertainties and complexities. Thus, there is a global need for advanced methodologies that can support the modeling and management of water resources systems in an effective and efficient way. In this dissertation research, a spectrum of methods have been developed to deal with the stochastic modeling and risk-based management problems for water resources systems. These methods include: (i) a Stepwise Clustered Hydrological Inference (SCHI) model that can establish the complex nonlinear relationships between climatic conditions and streamflow for hydrological forecasting; (ii) a flexible and effective hydro-climatic modeling framework based on the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and stepwise cluster analysis for hydrological modeling under the changing climatic conditions; (iii) a Stepwise-cluster-analysis-based Probabilistic Collocation Expansion (SPCE) method for the stochastic simulation and forecast of hydrologic time series; (iv) a hydrologic frequency analysis framework based on change point analysis and Bayesian parameter estimation to deal with the nonstationarity and uncertainties in hydrological risk analysis; (v) an Interval-parameter Two-stage Fuzzy Stochastic Integer Programming (ITFSIP) model for risk-based flood diversion management under multiple uncertainties. The proposed methods have been applied to the Xiangxi River Watershed in China and the Grand River Watershed in Canada, in order to demonstrate their capabilities and performances in precipitation-runoff modeling, climate change impact analysis, uncertainty quantification, frequency analysis, and systematic water resources and risk management. The major contribution of this research lies in the development of innovative approaches for tackling various uncertainties and complexities in the hydrological cycle and water resources systems. This research can provide scientific and practical bases for robust hydrological modeling and reliable water resources management.
Author: Ralph Allen Wurbs
Publisher: Prentice Hall
ISBN:
Category : Architecture
Languages : en
Pages : 392
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Book Description
Author: L. Duckstein
Publisher: Springer Science & Business Media
ISBN: 9400935773
Category : Technology & Engineering
Languages : en
Pages : 586
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Book Description
Hydraulic, hydrologic and water resources engineers have been concerned for a long time about failure phenomena. One of the major concerns is the definition of a failure event E, of its probability of occurrence PtE), and of the complementary notion of reliability. However, as the stochastic aspects of hydraulics and water resources engineering were developed, words such as "failure," "reliability," and "risk" took on different meanings for different specialists. For example, "risk" is defined in a Bayesian framework as the expected loss resulting from a precisely defined failure event, while according to the practice of stochastic hydraulics it is the probability of occurrence of a failure event. The need to standardize the various concepts and operational definitions generated numerous exciting discussions between the co-editors of this book during 1983-84 when L. Duckstein, under sponsorship of the Alexander von Humboldt Foundation (FRG), was working with E. Plate at the Institute of Hydrology and Water Resources of the University of Karlsruhe. After consulting with the Scientific Affairs Division of NATO, an organizing committee was formed. This comittee - J. Bernier (France), M. Benedini (Italy), S. Sorooshian (U. S. A. ), and co-directors L. Duckstein (U. S. A. ) and E. J. Plate (F. R. G. ) -- brought into being this NATO Advanced Study Institute (ASI). Precisely stated, the purpose of this ASI was to present a tutorial overview of existing work in the broad area of reliability while also pointing out topics for further development.
Author: Richard J. Hayes
Publisher:
ISBN:
Category : Computer simulation
Languages : en
Pages : 22
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Book Description
The Corps' Hydrologic Engineering Center (HEC) has developed a generalized simulation model capable of analyzing complex river-reservoir systems. The development of the model, 'HEC-5, Simulation of Flood Control and Conservation Systems' (Eichert, 1974, 1975) has been paced by the changing mission of the Corps as well as the evolution of computer systems. HEC-5 development and management, including code development, testing, documentation, training and field application experience, is discussed. (fr).
Author: Yunus Dada Salami
Publisher:
ISBN:
Category :
Languages : en
Pages : 156
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Book Description
Dams and reservoirs with multiple purposes require effective management to fully realize their purposes and maximize efficiency. For instance, a reservoir intended mainly for the purposes of flood control and hydropower generation may result in a system with primary objectives that conflict with each other. This is because higher hydraulic heads are required to achieve the hydropower generation objective while relatively lower reservoir levels are required to fulfill flood control objectives. Protracted imbalances between these two could increase the susceptibility of the system to risks of water shortage or flood, depending on inflow volumes and operational policy effectiveness. The magnitudes of these risks can become even more pronounced when upstream use of the river is unregulated and uncoordinated so that upstream consumptions and releases are arbitrary. As a result, safe operational practices and risk management alternatives must be structured after an improved understanding of historical and anticipated inflows, actual and speculative upstream uses, and the overall hydrology of catchments upstream of the reservoir. One of such systems with an almost yearly occurrence of floods and shortages due to both natural and anthropogenic factors is the dual reservoir system of Kainji and Jebba in Nigeria. To analyze and manage these risks, a methodology that combines a stochastic and deterministic approach was employed. Using methods outlined by Box and Jenkins (1976), autoregressive integrated moving average (ARIMA) models were developed for forecasting Niger river inflows at Kainji reservoir based on twenty-seven-year-long historical inflow data (1970-1996). These were then validated using seven-year inflow records (1997-2003). The model with the best correlation was a seasonal multiplicative ARIMA (2,1,1)x(2,1,2)12 model. Supplementary validation of this model was done with discharge rating curves developed for the inlet of the reservoir using in situ inflows and satellite altimetry data. By comparing net inflow volumes with storage deficit, flood and shortage risk factors at the reservoir were determined based on (a) actual inflows, (b) forecasted inflows (up to 2015), and (c) simulated scenarios depicting undefined competitive upstream consumption. Calculated high-risk years matched actual flood years again suggesting the reliability of the model. Monte Carlo simulations were then used to prescribe safe outflows and storage allocations in order to reduce futuristic risk factors. The theoretical safety levels achieved indicated risk factors below threshold values and showed that this methodology is a powerful tool for estimating and managing flood and shortage risks in reservoirs with undefined competitive upstream consumption.
