Jeremy White
Dr. Jeremy White is a Supervisory Hydrologic Technician at the Virginia and West Virginia Water Science Center.
He completed his B.S. in computer science at West Texas A&M, and M.S. and Ph.D. in geology at the University of South Florida. Dr. White has extensive experience with parameter estimation and uncertainty quantification in environmental and geophysical models, as well as simulation of surface water and groundwater interactions and density-dependent groundwater flow. Dr. White also has experience using high-performance computing systems to solve massively and embarrassingly parallel problems.
Science and Products
Filter Total Items: 50
A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty
An open-source tool has been developed to facilitate constrained single- and multi-objective optimization under uncertainty (CMOU) analyses. The tool uses the well-known PEST interface protocols to communicate with the underlying forward simulation, making it non-intrusive. The tool contains a built-in parallel run manager to make use of heterogeneous and distributed computing resources...
Authors
Jeremy White, Matthew Knowling, Michael N. Fienen, Adam Siade, Otis Rea, Guillermo Martinez
A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states
Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of...
Authors
Ayman H. Alzraiee, Jeremy T. White, Matthew Knowling, Randall J. Hunt, Michael N. Fienen
Risk-based wellhead protection decision support: A repeatable workflow approach Risk-based wellhead protection decision support: A repeatable workflow approach
Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty...
Authors
Michael N. Fienen, Nicholas Corson-Dosch, Jeremy T. White, Andrew T. Leaf, Randall J. Hunt
Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff
Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern...
Authors
Wesley Kitlasten, Eric D. Morway, Richard G. Niswonger, Murphy Gardner, Jeremy T. White, Enrique Triana, David J. Selkowitz
Risk-based decision-support groundwater modeling for the lower San Antonio River Basin, Texas, USA Risk-based decision-support groundwater modeling for the lower San Antonio River Basin, Texas, USA
A numerical surface-water/groundwater model was developed for the lower San Antonio River Basin to evaluate the responses of low base flows and groundwater levels within the basin under conditions of reduced recharge and increased groundwater withdrawals. Batch data assimilation through history matching used a simulation of historical conditions (2006-2013); this process included history...
Authors
Linzy K. Foster, Jeremy T. White, Andrew T. Leaf, Natalie A. Houston, Aarin Teague
Evaluating lower computational burden approaches for calibration of large environmental models Evaluating lower computational burden approaches for calibration of large environmental models
Realistic environmental models used for decision making typically require a highly parameterized approach. Calibration of such models is computationally intensive because widely used parameter estimation approaches require individual forward runs for each parameter adjusted. These runs construct a parameter-to-observation sensitivity, or Jacobian, matrix used to develop candidate...
Authors
Randall J. Hunt, Jeremy T. White, Leslie L. Duncan, Connor J. Haugh, John E. Doherty
Non-USGS Publications**
White, J.T., Fienen, M.N, and Doherty,J.E. 2016. A python framework for environmental model uncertainty analysis, Environmental Modelling & Software, Volume 85, Pages 217-228, ISSN 1364-8152
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
Filter Total Items: 50
A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty
An open-source tool has been developed to facilitate constrained single- and multi-objective optimization under uncertainty (CMOU) analyses. The tool uses the well-known PEST interface protocols to communicate with the underlying forward simulation, making it non-intrusive. The tool contains a built-in parallel run manager to make use of heterogeneous and distributed computing resources...
Authors
Jeremy White, Matthew Knowling, Michael N. Fienen, Adam Siade, Otis Rea, Guillermo Martinez
A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states
Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of...
Authors
Ayman H. Alzraiee, Jeremy T. White, Matthew Knowling, Randall J. Hunt, Michael N. Fienen
Risk-based wellhead protection decision support: A repeatable workflow approach Risk-based wellhead protection decision support: A repeatable workflow approach
Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty...
Authors
Michael N. Fienen, Nicholas Corson-Dosch, Jeremy T. White, Andrew T. Leaf, Randall J. Hunt
Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff
Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern...
Authors
Wesley Kitlasten, Eric D. Morway, Richard G. Niswonger, Murphy Gardner, Jeremy T. White, Enrique Triana, David J. Selkowitz
Risk-based decision-support groundwater modeling for the lower San Antonio River Basin, Texas, USA Risk-based decision-support groundwater modeling for the lower San Antonio River Basin, Texas, USA
A numerical surface-water/groundwater model was developed for the lower San Antonio River Basin to evaluate the responses of low base flows and groundwater levels within the basin under conditions of reduced recharge and increased groundwater withdrawals. Batch data assimilation through history matching used a simulation of historical conditions (2006-2013); this process included history...
Authors
Linzy K. Foster, Jeremy T. White, Andrew T. Leaf, Natalie A. Houston, Aarin Teague
Evaluating lower computational burden approaches for calibration of large environmental models Evaluating lower computational burden approaches for calibration of large environmental models
Realistic environmental models used for decision making typically require a highly parameterized approach. Calibration of such models is computationally intensive because widely used parameter estimation approaches require individual forward runs for each parameter adjusted. These runs construct a parameter-to-observation sensitivity, or Jacobian, matrix used to develop candidate...
Authors
Randall J. Hunt, Jeremy T. White, Leslie L. Duncan, Connor J. Haugh, John E. Doherty
Non-USGS Publications**
White, J.T., Fienen, M.N, and Doherty,J.E. 2016. A python framework for environmental model uncertainty analysis, Environmental Modelling & Software, Volume 85, Pages 217-228, ISSN 1364-8152
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.