Claire R Tiedeman (Former Employee)
Science and Products
Filter Total Items: 45
Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty
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...
Authors
Mary C. Hill, Claire R. Tiedeman
USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015 USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015
In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years...
Authors
Thomas M. Brocher, Michael D. Carr, David L. Halsing, David A. John, Victoria E. Langenheim, Margaret T. Mangan, Mark C. Marvin-DiPasquale, John Y. Takekawa, Claire R. Tiedeman
By
Natural Hazards Mission Area, Water Resources Mission Area, Ecosystems Mission Area, Volcano Hazards Program, Earthquake Hazards Program, Volcano Science Center, Earthquake Science Center, Western Ecological Research Center (WERC), Alaska Science Center, Geology, Minerals, Energy, and Geophysics Science Center
Guidelines 13 and 14—Prediction uncertainty Guidelines 13 and 14—Prediction uncertainty
An advantage of using optimization for model development and calibration is that optimization provides methods for evaluating and quantifying prediction uncertainty. Both deterministic and statistical methods can be used. Guideline 13 discusses using regression and post-audits, which we classify as deterministic methods. Guideline 14 discusses inferential statistics and Monte Carlo...
Authors
Mary C. Hill, Claire R. Tiedeman
Appendix D: Selected statistical tables Appendix D: Selected statistical tables
No abstract available.
Authors
Mary C. Hill, Claire R. Tiedeman
Calibrating transient and transport models and recalibrating existing models Calibrating transient and transport models and recalibrating existing models
The methods presented in Chapters 3 to 8 are applicable to models of any system. However, there are special considerations when applying the methods to certain types of models. This chapter discusses three types of models that are of special interest to many scientific and engineering fields: transient models, transport models, and existing models that are to be recalibrated.
Authors
Mary C. Hill, Claire R. Tiedeman
Appendix B: Calculation details of the modified Gauss-Newton Method Appendix B: Calculation details of the modified Gauss-Newton Method
No abstract available.
Authors
Mary C. Hill, Claire R. Tiedeman
Evaluation of longitudinal dispersivity estimates from simulated forced‐ and natural‐gradient tracer tests in heterogeneous aquifers Evaluation of longitudinal dispersivity estimates from simulated forced‐ and natural‐gradient tracer tests in heterogeneous aquifers
We simulate three types of forced‐gradient tracer tests (converging radial flow, unequal strength two well, and equal strength two well) and natural‐gradient tracer tests in multiple realizations of heterogeneous two‐dimensional aquifers with a hydraulic conductivity distribution characterized by a spherical variogram. We determine longitudinal dispersivities (αL) by analysis of forced...
Authors
Claire R. Tiedeman, Paul A. Hsieh
A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system
We develop a new observation‐prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is...
Authors
Claire R. Tiedeman, D. Matthew Ely, Mary C. Hill, Grady M. O’Brien
Evaluating observations in the context of predictions for the death valley regional groundwater system Evaluating observations in the context of predictions for the death valley regional groundwater system
When a model is calibrated by nonlinear regression, calculated diagnostic and inferential statistics provide a wealth of information about many aspects of the system. This work uses linear inferential statistics that are measures of prediction uncertainty to investigate the likely importance of continued monitoring of hydraulic head to the accuracy of model predictions. The measurements...
Authors
D.M. Ely, M. C. Hill, C. R. Tiedeman, G. M. O’Brien
Using sensitivity analysis in model calibration efforts Using sensitivity analysis in model calibration efforts
In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of...
Authors
Claire R. Tiedeman, Mary C. Hill
Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system
Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about...
Authors
C. R. Tiedeman, M. C. Hill, F. A. D’Agnese, C.C. Faunt
Evaluation of longitudinal dispersivity estimates from forced-gradient tracer tests in heterogeneous aquifers Evaluation of longitudinal dispersivity estimates from forced-gradient tracer tests in heterogeneous aquifers
Converging radial-flow and two-well tracer tests are simulated in two-dimensional aquifers to investigate the effects of heterogeneity and forced-gradient test configuration on longitudinal dispersivity (??L) estimates, and to compare ??L estimates from forced-gradient tests with ??L values that characterize solute spreading under natural-gradient flow. Results indicate that in both...
Authors
C. R. Tiedeman, P. A. Hsieh
Science and Products
Filter Total Items: 45
Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty Effective groundwater model calibration: With analysis of data, sensitivities, predictions, and uncertainty
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...
Authors
Mary C. Hill, Claire R. Tiedeman
USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015 USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015
In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years...
Authors
Thomas M. Brocher, Michael D. Carr, David L. Halsing, David A. John, Victoria E. Langenheim, Margaret T. Mangan, Mark C. Marvin-DiPasquale, John Y. Takekawa, Claire R. Tiedeman
By
Natural Hazards Mission Area, Water Resources Mission Area, Ecosystems Mission Area, Volcano Hazards Program, Earthquake Hazards Program, Volcano Science Center, Earthquake Science Center, Western Ecological Research Center (WERC), Alaska Science Center, Geology, Minerals, Energy, and Geophysics Science Center
Guidelines 13 and 14—Prediction uncertainty Guidelines 13 and 14—Prediction uncertainty
An advantage of using optimization for model development and calibration is that optimization provides methods for evaluating and quantifying prediction uncertainty. Both deterministic and statistical methods can be used. Guideline 13 discusses using regression and post-audits, which we classify as deterministic methods. Guideline 14 discusses inferential statistics and Monte Carlo...
Authors
Mary C. Hill, Claire R. Tiedeman
Appendix D: Selected statistical tables Appendix D: Selected statistical tables
No abstract available.
Authors
Mary C. Hill, Claire R. Tiedeman
Calibrating transient and transport models and recalibrating existing models Calibrating transient and transport models and recalibrating existing models
The methods presented in Chapters 3 to 8 are applicable to models of any system. However, there are special considerations when applying the methods to certain types of models. This chapter discusses three types of models that are of special interest to many scientific and engineering fields: transient models, transport models, and existing models that are to be recalibrated.
Authors
Mary C. Hill, Claire R. Tiedeman
Appendix B: Calculation details of the modified Gauss-Newton Method Appendix B: Calculation details of the modified Gauss-Newton Method
No abstract available.
Authors
Mary C. Hill, Claire R. Tiedeman
Evaluation of longitudinal dispersivity estimates from simulated forced‐ and natural‐gradient tracer tests in heterogeneous aquifers Evaluation of longitudinal dispersivity estimates from simulated forced‐ and natural‐gradient tracer tests in heterogeneous aquifers
We simulate three types of forced‐gradient tracer tests (converging radial flow, unequal strength two well, and equal strength two well) and natural‐gradient tracer tests in multiple realizations of heterogeneous two‐dimensional aquifers with a hydraulic conductivity distribution characterized by a spherical variogram. We determine longitudinal dispersivities (αL) by analysis of forced...
Authors
Claire R. Tiedeman, Paul A. Hsieh
A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system
We develop a new observation‐prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is...
Authors
Claire R. Tiedeman, D. Matthew Ely, Mary C. Hill, Grady M. O’Brien
Evaluating observations in the context of predictions for the death valley regional groundwater system Evaluating observations in the context of predictions for the death valley regional groundwater system
When a model is calibrated by nonlinear regression, calculated diagnostic and inferential statistics provide a wealth of information about many aspects of the system. This work uses linear inferential statistics that are measures of prediction uncertainty to investigate the likely importance of continued monitoring of hydraulic head to the accuracy of model predictions. The measurements...
Authors
D.M. Ely, M. C. Hill, C. R. Tiedeman, G. M. O’Brien
Using sensitivity analysis in model calibration efforts Using sensitivity analysis in model calibration efforts
In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of...
Authors
Claire R. Tiedeman, Mary C. Hill
Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system
Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about...
Authors
C. R. Tiedeman, M. C. Hill, F. A. D’Agnese, C.C. Faunt
Evaluation of longitudinal dispersivity estimates from forced-gradient tracer tests in heterogeneous aquifers Evaluation of longitudinal dispersivity estimates from forced-gradient tracer tests in heterogeneous aquifers
Converging radial-flow and two-well tracer tests are simulated in two-dimensional aquifers to investigate the effects of heterogeneity and forced-gradient test configuration on longitudinal dispersivity (??L) estimates, and to compare ??L estimates from forced-gradient tests with ??L values that characterize solute spreading under natural-gradient flow. Results indicate that in both...
Authors
C. R. Tiedeman, P. A. Hsieh