Download or read book Development of Stochastic Factorial Programming Methods for Water Resources Management Under Uncertainty written by Yang Zhou and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Factorial Multi stage Stochastic Programming Methods for Water Resources Management written by Yang Zhou and published by . This book was released on 2011 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study is a first attempt to integrate multivariate factorial analysis with inexact two- and multi-stage stochastic programming. By introducing multivariate factorial analysis into the inexact optimization process, the developed methods are able to not only tackle uncertainties properly and provide water managers with reasonable solutions, but are also capable of analyzing the detailed effects from individual inputs on system performance and reflecting multi-level interactions among various modeling parameters as well as their combined effects on the system.

Download or read book Development of Factorial Multi Stage Programming Methods for Water Resources Management Under Uncertainty written by Ximan Liu and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid population growth and socio-economic development have caused increasing demands for water resources. In addition, issues of water scarcity and pollution are intensifying. The increasing scarcity of water could spark conflict among water users. It is increasingly important to develop rational and optimum water resources management strategies to support sustainable development at all levels - from national to regional. In water resources management systems, uncertainty exists in many system parameters, and the dynamic features of these systems create more challenges for such management. Therefore, making the best use of limited water resources is desired to facilitate sustainable regional development. In this thesis, a factorial multi-stage chance-constrained programming (FMCCP) approach is developed to support water resources management under uncertainty. A multivariate factorial analysis is introduced to identify the effects of uncertainty parameters and their interactions on system performance. This approach is applied to a hypothetical case study of water resources system analysis. The results could help decision-makers to acquire their desired water-allocation schemes. The model could help to analyze the relationship between the economic objective and the system risk. Moreover, factorial analysis is introduced to identify the interactions between the significant factors and to investigate their effects on system performance. In addition, a multi-stage credibility-constrained water resources management (MCWRM) model is developed for water resources management under uncertainty. This proposed method is applied to a hypothetical case study of water resources management. This method improves upon the existing mathematical methods by integrating fuzzy credibility-constrained programming to measure the satisfaction degrees of the constraints. The model effectively reflects uncertainties expressed as probability distributions, fuzzy membership functions and intervals with random boundaries, as well as the dynamic features of water resources management systems, in a systematic manner. The results could help decision-makers to identify water-allocation patterns over the planning horizon and to examine the relationship between predefined policies and implied economic penalties. To demonstrate its applicability, the proposed MCWRM model is applied to a real-world case study in Guhai Water Distribution System (GWDS), China. The proposed model could help decision-makers to analyze the tradeoffs between economic development and environmental policies. The results indicate that the development of economic crops and industrial activities should be encouraged; in contrast, the development of corn should be restricted. The results also reveal that the credibility level would have an obvious effect on the optimized system revenue. When the credibility level is high, the decision-maker prefers to be conservative, resulting in lower system benefits under low violation risk. In contrast, when the credibility level is low, the decision maker seeks to be optimistic, resulting in higher system benefits under high violation risk. The proposed method could provides scientific basis for local sustainable development and water resources management.

Download or read book Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization written by J.B. Marco and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Factorial Probabilistic Methodologies for Water Resources and Hydrologic Systems Analysis Under Interactive Uncertainties written by Shuo Wang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Water Network Design and Management Via Stochastic Programming written by Weini Zhang and published by . This book was released on 2013 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water is an essential natural resource for life and economic activities. Water resources management is facing major challenges due to increasing demands caused by population growth, increased industrial and agricultural use, and depletion of fresh water sources around the world. In addition to putting stress on our civilization, factors such as water supply availability, spatial population changes, industrial growth, etc. are all sources of major uncertainty in water resources management. There are also uncertainties regarding climate variability and how it affects both water demands and supplies. Stochastic programming is a mathematical tool to help make decisions under uncertainty that models the uncertain parameters using probability distributions and incorporates probabilistic statements in mathematical optimization. This dissertation applies stochastic programming to water resources management. In particular, we focus on reclaimed water distribution network design to effectively reuse water in a municipal system and a water allocation problem in an integrated water system under uncertainty. We first present a two-stage stochastic integer program with recourse for cost- effective reclaimed water network design. Unlike other formulations, uncertain demands, temporal, and spatial population changes are explicitly considered in our model. Selection of pipe and pump sizes are modeled using binary variables in order to linearize the nonlinear hydraulic equations and objective function terms. We then develop preprocessing methods to significantly reduce the problem dimension by exploiting the problem characteristics and network structure. We analyze the sensitivity of the network design under varying model parameters, present computational results, and discuss when the stochastic solution is most valuable. Next, we investigate the use of risk-averse approach in water resources management using the so-called conditional value-at-risk as a risk measure. We develop a multistage risk-averse stochastic program with recourse for long-term water allocation under uncertain demands and water supply variability. We propose a specialized decomposition-based algorithm to solve multistage risk-averse stochastic programs, and present both the single-cut and the multicut version of the algorithm. We then compare the solution methodologies with different ways of decomposing the resulting problem. We solve the multistage risk-averse water allocation problem with different risk aversion levels and model assumptions, present computational results to demonstrate the potential benefits of risk-averse approach, and provide a guideline for risk aversion level selection.

Download or read book Stochastic Water Resources Technology written by N. T Kottegoda and published by Springer. This book was released on 1980-06-18 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Selected Water Resources Abstracts written by and published by . This book was released on 1970 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Modeling and Risk Management for Water Resources Systems Under Changing Climatic Conditions written by Zhong Li and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Control of Water Resources Systems Under Uncertainty written by Roko Andričević and published by . This book was released on 1988 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Inexact Two Stage Stochastic Optimization written by G. H. Huang (D. P. Loucks, S.-C. Yeh, and B. Bass) and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Optimization and Simulation Techniques for Management of Regional Water Resource Systems written by Texas Water Development Board. Systems Engineering Division and published by . This book was released on 1970 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Driven Methods for Optimization Under Uncertainty with Application to Water Allocation written by David Keith Love and published by . This book was released on 2013 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic programming is a mathematical technique for decision making under uncertainty using probabilistic statements in the problem objective and constraints. In practice, the distribution of the unknown quantities are often known only through observed or simulated data. This dissertation discusses several methods of using this data to formulate, solve, and evaluate the quality of solutions of stochastic programs. The central contribution of this dissertation is to investigate the use of techniques from simulation and statistics to enable data-driven models and methods for stochastic programming. We begin by extending the method of overlapping batches from simulation to assessing solution quality in stochastic programming. The Multiple Replications Procedure, where multiple stochastic programs are solved using independent batches of samples, has previously been used for assessing solution quality. The Overlapping Multiple Replications Procedure overlaps the batches, thus losing the independence between samples, but reducing the variance of the estimator without affecting its bias. We provide conditions under which the optimality gap estimators are consistent, the variance reduction benefits are obtained, and give a computational illustration of the small-sample behavior. Our second result explores the use of phi-divergences for distributionally robust optimization, also known as ambiguous stochastic programming. The phi-divergences provide a method of measuring distance between probability distributions, are widely used in statistical inference and information theory, and have recently been proposed to formulate data-driven stochastic programs. We provide a novel classification of phi-divergences for stochastic programming and give recommendations for their use. A value of data condition is derived and the asymptotic behavior of the phi-divergence constrained stochastic program is described. Then a decomposition-based solution method is proposed to solve problems computationally. The final portion of this dissertation applies the phi-divergence method to a problem of water allocation in a developing region of Tucson, AZ. In this application, we integrate several sources of uncertainty into a single model, including (1) future population growth in the region, (2) amount of water available from the Colorado River, and (3) the effects of climate variability on water demand. Estimates of the frequency and severity of future water shortages are given and we evaluate the effectiveness of several infrastructure options.

Download or read book Stochastic Optimization and Simulation Techniques for Management of Regional Water Resources Systems written by and published by . This book was released on 1971 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligence Systems in Environmental Management Theory and Applications written by Cengiz Kahraman and published by Springer. This book was released on 2016-09-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspects of classical environmental solution techniques to its intelligent counterpart, the book presents a dynamic snapshot on the field that is expected to stimulate new directions and stimulate new ideas and developments.

Download or read book A Stochastic Programming Model Applied to Water Resources Management written by János Pintér and published by . This book was released on 1975 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Planning Under Uncertainty written by Gerd Infanger and published by . This book was released on 1992 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: