Developing Efficient Strategies For Automatic Calibration Of Computationally Intensive Environmental Models
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| Author | : Seyed Saman Razavi |
| Publisher | : |
| Total Pages | : 191 |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
Environmental simulation models have been playing a key role in civil and environmental engineering decision making processes for decades. The utility of an environmental model depends on how well the model is structured and calibrated. Model calibration is typically in an automated form where the simulation model is linked to a search mechanism (e.g., an optimization algorithm) such that the search mechanism iteratively generates many parameter sets (e.g., thousands of parameter sets) and evaluates them through running the model in an attempt to minimize differences between observed data and corresponding model outputs. The challenge rises when the environmental model is computationally intensive to run (with run-times of minutes to hours, for example) as then any automatic calibration attempt would impose a large computational burden. Such a challenge may make the model users accept sub-optimal solutions and not achieve the best model performance. The objective of this thesis is to develop innovative strategies to circumvent the computational burden associated with automatic calibration of computationally intensive environmental models.
| Author | : Seiyon Lee |
| Publisher | : |
| Total Pages | : |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Computer model calibration is a major component in projecting sea level rise and developing coastal flood-risk management strategies. Hierarchical spatial models have been used extensively to model spatially dependent observations across many fields such as climate science, ecology, public health, and epidemiology. The computational methods presented here have wide ranging applications in environmental sciences such as quantifying uncertainties in future sea level rise which are then used to formulate coastal risk management policies and providing researchers from various fields with a fast and readily extendable approach to fit complex hierarchical spatial models of their choice. My dissertation research focuses on developing statistical and computational methods to address pressing issues in the environmental sciences. My contributions are as follows: (1) a fast particle-based approach for calibrating a three-dimensional Antarctic ice sheet model. I developed a sequential Monte Carlo method that leverages the massive parallelization inherent to modern high-performance computing systems; (2) an efficient and extendable approach for fitting high-dimensional hierarchical spatial models. I propose a discretized and dimension-reduced representation of the underlying spatial random field using empirical basis functions on a triangular mesh; and (3) a computationally efficient method for modeling high-dimensional zero-inflated spatial observations.
| Author | : Pierre-Luc Huot |
| Publisher | : |
| Total Pages | : |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
| Author | : David Butler |
| Publisher | : CRC Press |
| Total Pages | : 552 |
| Release | : 2018-04-09 |
| Genre | : Technology & Engineering |
| ISBN | : 1498750591 |
This new edition of a well-established textbook covers the environmental and engineering aspects of the management of rainwater and wastewater in areas of human development. Urban Drainage deals comprehensively not only with the design of new systems, but also the analysis and upgrading of existing infrastructure. Keeping its balance of principles, practice and research, this new edition has significant new material on modelling, resilience, smart systems, and the global and local context. The two new authors bring further research and practice-based experience. This is an essential text for undergraduate and graduate students, lecturers and researchers in water engineering, environmental engineering, public health engineering, engineering hydrology, and related non-engineering disciplines. It also serves as a dependable reference for drainage engineers in water service providers, local authorities, and for consulting engineers. Extensive examples are used to support and demonstrate the key issues throughout the text.
| Author | : Mary C. Hill |
| Publisher | : John Wiley & Sons |
| Total Pages | : 475 |
| Release | : 2006-08-25 |
| Genre | : Technology & Engineering |
| ISBN | : 0470041072 |
Methods and guidelines for developing and using mathematical models Turn to Effective Groundwater Model Calibration for a set of methods and guidelines that can help produce more accurate and transparent mathematical models. The models can represent groundwater flow and transport and other natural and engineered systems. Use this book and its extensive exercises to learn methods to fully exploit the data on hand, maximize the model's potential, and troubleshoot any problems that arise. Use the methods to perform: Sensitivity analysis to evaluate the information content of data Data assessment to identify (a) existing measurements that dominate model development and predictions and (b) potential measurements likely to improve the reliability of predictions Calibration to develop models that are consistent with the data in an optimal manner Uncertainty evaluation to quantify and communicate errors in simulated results that are often used to make important societal decisions Most of the methods are based on linear and nonlinear regression theory. Fourteen guidelines show the reader how to use the methods advantageously in practical situations. Exercises focus on a groundwater flow system and management problem, enabling readers to apply all the methods presented in the text. The exercises can be completed using the material provided in the book, or as hands-on computer exercises using instructions and files available on the text's accompanying Web site. Throughout the book, the authors stress the need for valid statistical concepts and easily understood presentation methods required to achieve well-tested, transparent models. Most of the examples and all of the exercises focus on simulating groundwater systems; other examples come from surface-water hydrology and geophysics. The methods and guidelines in the text are broadly applicable and can be used by students, researchers, and engineers to simulate many kinds systems.
| Author | : Andrea Saltelli |
| Publisher | : John Wiley & Sons |
| Total Pages | : 304 |
| Release | : 2008-02-28 |
| Genre | : Mathematics |
| ISBN | : 9780470725177 |
Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
| Author | : |
| Publisher | : |
| Total Pages | : 378 |
| Release | : 2008 |
| Genre | : Dissertations, Academic |
| ISBN | : |
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 286 |
| Release | : 2007-08-25 |
| Genre | : Political Science |
| ISBN | : 0309110009 |
Many regulations issued by the U.S. Environmental Protection Agency (EPA) are based on the results of computer models. Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy. Given the critical role played by models, the EPA asked the National Research Council to assess scientific issues related to the agency's selection and use of models in its decisions. The book recommends a series of guidelines and principles for improving agency models and decision-making processes. The centerpiece of the book's recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency's ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.
| Author | : Keith J. Beven |
| Publisher | : John Wiley & Sons |
| Total Pages | : 489 |
| Release | : 2012-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 047071459X |
Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and authoritative text, first published in 2001. The book provides both a primer for the novice and detailed descriptions of techniques for more advanced practitioners, covering rainfall-runoff models and their practical applications. This new edition extends these aims to include additional chapters dealing with prediction in ungauged basins, predicting residence time distributions, predicting the impacts of change and the next generation of hydrological models. Giving a comprehensive summary of available techniques based on established practices and recent research the book offers a thorough and accessible overview of the area. Rainfall-Runoff Modelling: The Primer Second Edition focuses on predicting hydrographs using models based on data and on representations of hydrological process. Dealing with the history of the development of rainfall-runoff models, uncertainty in mode predictions, good and bad practice and ending with a look at how to predict future catchment hydrological responses this book provides an essential underpinning of rainfall-runoff modelling topics. Fully revised and updated version of this highly popular text Suitable for both novices in the area and for more advanced users and developers Written by a leading expert in the field Guide to internet sources for rainfall-runoff modelling software
| Author | : Charles Audet |
| Publisher | : Springer |
| Total Pages | : 307 |
| Release | : 2017-12-02 |
| Genre | : Mathematics |
| ISBN | : 3319689134 |
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I. Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead). Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region). Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures. Benchmarking techniques are also presented in the appendix.
