Download or read book Optimal Calibration Uncertainty Assessment and Long term Monitoring Using Computationally Expensive Groundwater Models written by Pradeep Mugunthan and published by . This book was released on 2005 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Effective Groundwater Model Calibration written by Mary C. Hill and published by John Wiley & Sons. This book was released on 2006-08-25 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Calibration of Watershed Models written by Qingyun Duan and published by John Wiley & Sons. This book was released on 2003-01-10 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. These models are based on general mathematical descriptions of the watershed processes that transform natural forcing (e.g., rainfall over the landscape) into response (e.g., runoff in the rivers). The user of a watershed hydrology model must specify the model parameters before the model is able to properly simulate the watershed behavior.

Download or read book Calibration and Reliability in Groundwater Modelling written by Jens Christian Refsgaard and published by . This book was released on 2008 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Assessment of Parametric and Model Uncertainty in Groundwater Modeling written by Dan Lu and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Groundwater systems are open and complex, rendering them prone to multiple conceptual interpretations and mathematical descriptions. When multiple models are acceptable based on available knowledge and data, model uncertainty arises. One way to assess the model uncertainty is postulating several alternative hydrologic models for a site and using model selection criteria to (1) rank these models, (2) eliminate some of them, and/or (3) weight and average predictions statistics generated by multiple models based on their model probabilities. This multimodel analysis has led to some debate among hydrogeologists about the merits and demerits of common model selection criteria such as AIC, AICc, BIC, and KIC. This dissertation contributes to the discussion by comparing the abilities of the two common Bayesian criteria (BIC and KIC) theoretically and numerically. The comparison results indicate that, using MCMC results as a reference, KIC yields more accurate approximations of model probability than does BIC. Although KIC reduces asymptotically to BIC, KIC provides consistently more reliable indications of model quality for a range of sample sizes. In the multimodel analysis, the model averaging predictive uncertainty is a weighted average of predictive uncertainties of individual models. So it is important to properly quantify individual model's predictive uncertainty. Confidence intervals based on regression theories and credible intervals based on Bayesian theories are conceptually different ways to quantify predictive uncertainties, and both are widely used in groundwater modeling. This dissertation explores their differences and similarities theoretically and numerically. The comparison results indicate that given Gaussian distributed observation errors, for linear or linearized nonlinear models, linear confidence and credible intervals are numerically identical when consistent prior parameter information is used. For nonlinear models, nonlinear confidence and credible intervals can be numerically identical if parameter confidence and credible regions based on approximate likelihood method are used and intrinsic model nonlinearity is small; but they differ in practice due to numerical difficulties in calculating both confidence and credible intervals. Model error is a more vital issue than differences between confidence and credible intervals for individual models, suggesting the importance of considering alternative models. Model calibration results are the basis for the model selection criteria to discriminate between models. However, how to incorporate calibration data errors into the calibration process is an unsettled problem. It has been seen that due to the improper use of the error probability structure in the calibration, the model selection criteria lead to an unrealistic situation in which one model receives overwhelmingly high averaging weight (even 100%), which cannot be justified by available data and knowledge. This dissertation finds that the errors reflected in the calibration should include two parts, measurement errors and model errors. To consider the probability structure of the total errors, I propose an iterative calibration method with two stages of parameter estimation. The multimodel analysis based on the estimation results leads to more reasonable averaging weights and better averaging predictive performance, compared to those with considering only measurement errors. Traditionally, data-worth analyses have relied on a single conceptual-mathematical model with prescribed parameters. Yet this renders model predictions prone to statistical bias and underestimation of uncertainty and thus affects the groundwater management decision. This dissertation proposes a multimodel approach to optimum data-worth analyses that is based on model averaging within a Bayesian framework. The developed multimodel Bayesian approach to data-worth analysis works well in a real geostatistical problem. In particular, the selection of target for additional data collection based on the approach is validated against actual data collected. The last part of the dissertation presents an efficient method of Bayesian uncertainty analysis. While Bayesian analysis is vital to quantify predictive uncertainty in groundwater modeling, its application has been hindered in multimodel uncertainty analysis because of computational cost of numerous models executions and the difficulty in sampling from the complicated posterior probability density functions of model parameters. This dissertation develops a new method to improve computational efficiency of Bayesian uncertainty analysis using sparse-grid method. The developed sparse-grid-based method for Bayesian uncertainty analysis demonstrates its superior accuracy and efficiency to classic importance sampling and MCMC sampler when applied to a groundwater flow model.

Download or read book Calibration and Reliability in Groundwater Modelling written by Marc F. P. Bierkens and published by . This book was released on 2006 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several of the papers here deal with decision making under uncertainty.

Download or read book Calibration and Reliability in Groundwater Modelling written by Fritz Stauffer and published by . This book was released on 2000 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Uncertainty Analysis and the Identification of the Contaminant Transport and Source Parameters for a Computationally Intensive Groundwater Simulation written by Yong Yin and published by . This book was released on 2009 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transport parameter estimation and contaminant source identification are critical steps in the development of a physically based groundwater contaminant transport model. Due to the irreversibility of the dispersion process, the calibration of a transport model of interest is inherently ill-posed, and very sensitive to the simplification employed in the development of the lumped models. In this research, a methodology for the calibration of physically based computationally intensive transport models was developed and applied to a case study, the Reich Farm Superfund site in Toms River, New Jersey.

Download or read book Comparing Methods for Bioremediation Policy Cost Optimization written by José Antonio Aponte and published by . This book was released on 2006 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2006 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Prediction Uncertainty Analysis to Design Hydrologic Monitoring Networks written by Michael N Fienen and published by CreateSpace. This book was released on 2014-08-01 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of monitoring networks for resource-management decisions is becoming more recognized, in both theory and application. Quantitative computer models provide a science-based framework to evaluate the efficacy and efficiency of existing and possible future monitoring networks. In the study described herein, two suites of tools were used to evaluate the worth of new data for specific predictions, which in turn can support efficient use of resources needed to construct a monitoring network. The approach evaluates the uncertainty of a model prediction and, by using linear propagation of uncertainty, estimates how much uncertainty could be reduced if the model were calibrated with addition information (increased a priori knowledge of parameter values or new observations). The theoretical underpinnings of the two suites of tools addressing this technique are compared, and their application to a hypothetical model based on a local model inset into the Great Lakes Water Availability Pilot model are described. Results show that meaningful guidance for monitoring network design can be obtained by using the methods explored. The validity of this guidance depends substantially on the parameterization as well; hence, parameterization must be considered not only when designing the parameter-estimation paradigm but also-importantly-when designing the prediction-uncertainty paradigm.

Download or read book Calibration and Reliability in Groundwater Modelling written by Yanxin Wang and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The usefulness of the predictive simulations obtained with groundwater models is often hampered by the inability to indicate and preferably quantify the reliability of the model results. Uncertainty in model predictions stems primarily from a number of errors relating to the model formulation such as: inadequate concept of processes and interactions; inadequate description of processes and interactions; inadequate sense of spatial and temporal variability; inadequate description of the state of the system; incorrect coefficient values and improper specification of the error bounds. In recent years much research has been carried out resulting in a variety of approaches that can be followed to incorporate the information about these errors into modelling process. Various techniques have been developed to assess the confidence levels of model predictions so that users can account for uncertainties in the decision-making process. This publication contains 52 papers the ModelCARE 90 conference held in The Hague, September 1990.

Download or read book Comparison of Stochastic Radial Basis Function and PEST for Automatic Calibration of Computationally Expensive Groundwater Models with Application to Miyun Huai Shun Aquifer written by Ying Wan and published by . This book was released on 2013 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: Groundwater numerical models have been widely used as effective tools to analyze and manage water resources. However, the accuracy and reliability of a groundwater numerical model largely depends on model parameters calibration, which is extremely computationally expensive. Therefore, it is highly desirable that efficient optimization algorithms be applied to automatic calibration problems. In this study, we compare the performance of three optimization algorithms and propose a new hybrid method. The algorithms are applied to calibration of a model for part of Beijing water supply. We first outline the three algorithms and briefly describe our hybrid method. The first algorithm referred as PEST in this paper is the Gauss-Marquardt-Levenberg (GML) method including truncated singular value decomposition, which is widely applied in the field of model parameter calibration. As the second one, CMAES_P is a "PEST compatible" implementation of CMA-ES (Covariance Matrix Adaptation Evolution Strategy) global optimization algorithm. PEST derivative-based algorithm and CMAES_P are both encapsulated in the automated parameter optimization software PEST, which has advanced predictive analysis and regularization features to minimize user-specified objective functions. The third one, called Stochastic Radial Basis Function (Stochastic RBF) method, is developed by Regis and Shoemaker (2007), which utilizes radial basis function as the response surface model to approximate the expensive objective function. Our new hybrid method combines Stochastic RBF and PEST derivative-based algorithm, which provides PEST derivative-based algorithm with the starting points found by Stochastic RBF. This paper compares the performances of the aforementioned four algorithms for automatic parameter calibration of a groundwater model on three 28-parameter cases and two synthetic test function calibration problems. We employ the following characteristics as our comparison criteria on all the cases: (1) efficiency in giving good objective function for a given number of function evaluations; (2) performance for different statistical criteria; (3) variability of solutions in multiple trials; (4) improvements if more function evaluations are performed. On the basis of 20 trials, the results indicate that Stochastic RBF is best among the three and CMAES_P is superior to PEST. In addition, our hybrid method still failed to beat Stochastic RBF in highly computationally expensive nonlinear cases. To sum up, our results show that Stochastic RBF method is a more efficient alternative to PEST for automatic parameter calibration of computationally expensive groundwater models. ii.

Download or read book Models in Environmental Regulatory Decision Making written by National Research Council and published by National Academies Press. This book was released on 2007-08-25 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Using Analytical and Numerical Modeling to Assess Deep Groundwater Monitoring Parameters at Carbon Capture Utilization and Storage Sites written by Sean Laurids Porse and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon Dioxide (CO2) Enhanced Oil Recovery (EOR) is becoming an important bridge to commercialize geologic sequestration (GS) in order to help reduce anthropogenic CO2 emissions. Current U.S. environmental regulations require operators to monitor operational and groundwater aquifer changes within permitted bounds, depending on the injection activity type. We view one goal of monitoring as maximizing the chances of detecting adverse fluid migration signals into overlying aquifers. To maximize these chances, it is important to: (1) understand the limitations of monitoring pressure versus geochemistry in deep aquifers (i.e., >450 m) using analytical and numerical models, (2) conduct sensitivity analyses of specific model parameters to support monitoring design conclusions, and (3) compare the breakthrough time (in years) for pressure and geochemistry signals. Pressure response was assessed using an analytical model, derived from Darcy's law, which solves for diffusivity in radial coordinates and the fluid migration rate. Aqueous geochemistry response was assessed using the numerical, single-phase, reactive solute transport program PHAST that solves the advection-reaction-dispersion equation for 2-D transport. The conceptual modeling domain for both approaches included a fault that allows vertical fluid migration and one monitoring well, completed through a series of alternating confining units and distinct (brine) aquifers overlying a depleted oil reservoir, as observed in the Texas Gulf Coast, USA. Physical and operational data, including lithology, formation hydraulic parameters, and water chemistry obtained from field samples were used as input data. Uncertainty evaluation was conducted with a Monte Carlo approach by sampling the fault width (normal distribution) via Latin Hypercube and the hydraulic conductivity of each formation from a beta distribution of field data. Each model ran for 100 realizations over a 100 year modeling period. Monitoring well location was varied spatially and vertically with respect to the fault to assess arrival times of pressure signals and changes in geochemical parameters. Results indicate that the pressure-based, subsurface monitoring system provided higher probabilities of fluid migration detection in all candidate monitoring formations, especially those closest (i.e., 1300 m depth) to the possible fluid migration source. For aqueous geochemistry monitoring, formations with higher permeabilities (i.e., greater than 4 x 10-13 m2) provided better spatial distributions of chemical changes, but these changes never preceded pressure signal breakthrough, and in some cases were delayed by decades when compared to pressure. Differences in signal breakthrough indicate that pressure monitoring is a better choice for early migration signal detection. However, both pressure and geochemical parameters should be considered as part of an integrated monitoring program on a site-specific basis, depending on regulatory requirements for longer term (i.e., >50 years) monitoring. By assessing the probability of fluid migration detection using these monitoring techniques at this field site, it may be possible to extrapolate the results (or observations) to other CCUS fields with different geological environments.

Download or read book Review of the New York City Watershed Protection Program written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-12-04 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: New York City's municipal water supply system provides about 1 billion gallons of drinking water a day to over 8.5 million people in New York City and about 1 million people living in nearby Westchester, Putnam, Ulster, and Orange counties. The combined water supply system includes 19 reservoirs and three controlled lakes with a total storage capacity of approximately 580 billion gallons. The city's Watershed Protection Program is intended to maintain and enhance the high quality of these surface water sources. Review of the New York City Watershed Protection Program assesses the efficacy and future of New York City's watershed management activities. The report identifies program areas that may require future change or action, including continued efforts to address turbidity and responding to changes in reservoir water quality as a result of climate change.

Download or read book Hydrogeophysics written by Yorum Rubin and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This ground-breaking work is the first to cover the fundamentals of hydrogeophysics from both the hydrogeological and geophysical perspectives. Authored by leading experts and expert groups, the book starts out by explaining the fundamentals of hydrological characterization, with focus on hydrological data acquisition and measurement analysis as well as geostatistical approaches. The fundamentals of geophysical characterization are then at length, including the geophysical techniques that are often used for hydrogeological characterization. Unlike other books, the geophysical methods and petrophysical discussions presented here emphasize the theory, assumptions, approaches, and interpretations that are particularly important for hydrogeological applications. A series of hydrogeophysical case studies illustrate hydrogeophysical approaches for mapping hydrological units, estimation of hydrogeological parameters, and monitoring of hydrogeological processes. Finally, the book concludes with hydrogeophysical frontiers, i.e. on emerging technologies and stochastic hydrogeophysical inversion approaches.