895 resultados para Optimization of Water Resources Management and Control


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Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

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Mode of access: Internet.

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"Prepared for the Illinois Institute of Natural Resources and the Illinois Environmental Protection Agency"--Cover

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Provides location of monuments installed by the Office of Water Resources which indicate land elevation along Midlothian and Natalie Creeks.

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This paper presents a review of modelling and control of biological nutrient removal (BNR)-activated sludge processes for wastewater treatment using distributed parameter models described by partial differential equations (PDE). Numerical methods for solution to the BNR-activated sludge process dynamics are reviewed and these include method of lines, global orthogonal collocation and orthogonal collocation on finite elements. Fundamental techniques and conceptual advances of the distributed parameter approach to the dynamics and control of activated sludge processes are briefly described. A critical analysis on the advantages of the distributed parameter approach over the conventional modelling strategy in this paper shows that the activated sludge process is more adequately described by the former and the method is recommended for application to the wastewater industry (c) 2006 Elsevier Ltd. All rights reserved.

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As long as governmental institutions have existed, efforts have been undertaken to reform them. This research examines a particular strategy, coercive controls, exercised through a particular instrument, executive orders, by a singular reformer, the president of the United States. The presidents studied-- Johnson, Nixon, Ford, Carter, Reagan, Bush, and Clinton--are those whose campaigns for office were characterized to varying degrees as against Washington bureaucracy and for executive reform. Executive order issuance is assessed through an examination of key factors for each president including political party affiliation, levels of political capital, and legislative experience. A classification typology is used to identify the topical dimensions and levels of coerciveness. The portrayal of the federal government is analyzed through examination of public, media, and presidential attention. The results show that executive orders are significant management tools for the president. Executive orders also represent an important component of the transition plans for incoming administrations. The findings indicate that overall, while executive orders have not increased in the aggregate, they are more intrusive and significant. When the factors of political party affiliation, political capital, and legislative experience are examined, it reveals a strong relationship between executive orders and previous executive experience, specifically presidents who served as a state governor prior to winning national election as president. Presidents Carter, Reagan, and Clinton (all former governors) have the highest percent of executive orders focusing on the federal bureaucracy. Additionally, the highest percent of forceful orders were issued by former governors (41.0%) as compared to their presidential counterparts who have not served as governors (19.9%). Secondly, political party affiliation is an important, but not significant, predictor for the use of executive orders. Thirdly, management strategies that provide the president with the greatest level of autonomy--executive orders--redefine the concept of presidential power and autonomous action. Interviews of elite government officials and political observers support the idea that executive orders can provide the president with a successful management strategy, requiring less expenditure of political resources, less risk to political capital, and a way of achieving objectives without depending on an unresponsive Congress. ^

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Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

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As long as governmental institutions have existed, efforts have been undertaken to reform them. This research examines a particular strategy, coercive controls, exercised through a particular instrument, executive orders, by a singular reformer, the president of the United States. The presidents studied- Johnson, Nixon, Ford, Carter, Reagan, Bush, and Clinton-are those whose campaigns for office were characterized to varying degrees as against Washington bureaucracy and for executive reform. Executive order issuance is assessed through an examination of key factors for each president including political party affiliation, levels of political capital, and legislative experience. A classification typology is used to identify the topical dimensions and levels of coerciveness. The portrayal of the federal government is analyzed through examination of public, media, and presidential attention. The results show that executive orders are significant management tools for the president. Executive orders also represent an important component of the transition plans for incoming administrations. The findings indicate that overall, while executive orders have not increased in the aggregate, they are more intrusive and significant. When the factors of political party affiliation, political capital, and legislative experience are examined, it reveals a strong relationship between executive orders and previous executive experience, specifically presidents who served as a state governor prior to winning national election as president. Presidents Carter, Reagan, and Clinton (all former governors) have the highest percent of executive orders focusing on the federal bureaucracy. Additionally, the highest percent of forceful orders were issued by former governors (41.0%) as compared to their presidential counterparts who have not served as governors (19.9%). Secondly, political party affiliation is an important, but not significant, predictor for the use of executive orders. Thirdly, management strategies that provide the president with the greatest level of autonomy-executive orders redefine the concept of presidential power and autonomous action. Interviews of elite government officials and political observers support the idea that executive orders can provide the president with a successful management strategy, requiring less expenditure of political resources, less risk to political capital, and a way of achieving objectives without depending on an unresponsive Congress.

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Acknowledgements We are grateful to the United Kingdom Economic and Social Research Council Nexus Network for funding this work.

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Acknowledgements We are grateful to the United Kingdom Economic and Social Research Council Nexus Network for funding this work.