Luo, J., Wu, W. -M., Carley, J., Fienen, M. N., Cheng, H., Watson, D., C. S. Criddle, C. S., Jardine, P. M., Kitanidis, P. K., 2008, Estimating first-order reaction rate coefficient for transport with nonequilibrium linear mass transfer in heterogeneous media: Journal of Contaminant Hydrology, v. 98, p. 50-60. 10. 1016/j. jconhyd. 2008. 03. 002.
Michael N Fienen
Biography
Mike Fienen is a Research Hydrologist at the USGS Wisconsin Water Science Center, an Assistant Adjunct Professor in the Department of Geoscience at the University of Wisconsin-Madison, and a member of the PhD Advisor Committee in the Civil and Environmental Engineering Department at the University of Parma, Italy (DICATeA – Dipartimento di Ingegneria Civile, dell’Ambiente e Territorio e Architettura – Università degli Studi di Parma).
EDUCATION
Ph.D. Environmental Fluid Mechanics and Hydrology, Department of Civil and Environmental Engineering, Stanford University
M.Sc. Environmental Fluid Mechanics and Hydrology, Department of Civil and Environmental Engineering, Stanford University
B.A. Geology, Macalester College Spring Semester in the Rockies, National Outdoor Leadership School
RESEARCH SUMMARY
My research mission is to provide decision-making support for environmental managers that considers uncertainty in all aspects of decisions and strives to extract the most information from the data. This mission is expressed through the main research threads of model calibration and inference of environmental systems. Specific applications include groundwater quantity and quality; statistical inference and prediction of recreational water quality on beaches; mercury in water and fish; and the groundwater and habitat impacts of sea-level rise. In support of these threads, aspects of computational efficiency, statistical analysis, and data management also play important roles.
EDITORIAL
Associate Editor, Groundwater
REVIEWER
- Water Resources Research
- Groundwater
- Ground Water Monitoring & Remediation
- Journal of Hydrology
- Journal of Contaminant Hydrology
- Advances in Water Resources
- Hydrogeology Journal
- Hydrological Sciences
- Entropy
- Hydrology and Earth Systems Science Discussions
- Journal of Climatology
- Computers and Geosciences
- Stochastic Environmental Research and Risk Assessment
- Journal of Environmental Informatics
- American Geophysical Union Geophysical Monograph Series
- Wisconsin Department of Natural Resources—Groundwater Coordinating Council Joint Solicitation (2010, 2011, 2012)
- United States Geological Survey/National Institutes for Water Resources Competitive Grants Program Panel (2010)
- Deutsche Forschungsgemeinschaft (German Research Foundation)
- National Science Foundation (NSF) Earth Sciences (EAR) – Hydrologic Sciences
- ARISTEIA – National Council for Research and Technology of Greece
Science and Products
Date published: October 1, 2017
Status: Active Flocks of a feather dock together: Using Docker and HTCondor to link high-throughput computing across the USGS
USGS scientists often face computationally intensive tasks that require high-throughput computing capabilities. Several USGS facilities use HTCondor to run their computational pools but are not necessarily connected to the larger USGS pool. This project demonstrated how to connect HTCondor pools by flocking, or coordinating, within the USGS. In addition to flocking the Upper Midwest...
Attribution: Community for Data Integration (CDI)
Date published: October 1, 2017
Status: Active Empowering decision-makers: A dynamic web interface for running Bayesian networks
U.S. Geological Survey (USGS) scientists are at the forefront of research that is critical for decision-making, particularly through the development of models (Bayesian networks, or BNs) that forecast coastal change. The utility of these tools outside the scientific community has been limited because they rely on expensive, technical software and a moderate understanding of statistical...
Attribution: Community for Data Integration (CDI)
Date published: March 29, 2016
Status: Active TC Chamberlin Modeling Center
The TC Chamberlin Modeling Center provides one-stop access to advanced computing so no project is limited by a lack of computer power. The Center can provide hardware access, assistance with migration and implementation, and training. We also develop, test, and disseminate state-of-the-art computational and analytical techniques and tools so models can be more effectively used in decision-...
Contacts: Randall J Hunt, Ph.D., Michael N Fienen
Attribution: Wisconsin Water Science Center
Date published: March 3, 2016
Status: Active Hunting Invasive Species with HTCondor: High Throughput Computing for Big Data and Next Generation Sequencing
Large amounts of data are being generated that require hours, days, or even weeks to analyze using traditional computing resources. Innovative solutions must be implemented to analyze the data in a reasonable timeframe. The program HTCondor (https://research.cs.wisc.edu/htcondor/) takes advantage of the processing capacity of individual...
Attribution: Community for Data Integration (CDI)
Date published: October 1, 2012
Status: Active A digital crust to advance continental‐scale modeling of subsurface fluid flow in climate, crustal process, and Earth system models
Fluid circulation in the Earth’s crust plays an essential role in surface, near surface, and crustal dynamics. Near the surface, soil water and groundwater interact with each other and with rivers, lakes and wetlands, affecting weathering, soil formation, ecosystem evolution and biogeochemical cycles. Further down (1km), fluid flow affects diagenesis, hydrocarbon maturation and migration, ore...
Attribution: John Wesley Powell Center for Analysis and Synthesis
Year Published: 2018
Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor
Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not...
Erickson, Richard A.; Fienen, Michael N.; McCalla, S. Grace; Weiser, Emily L.; Bower, Melvin L.; Knudson, Jonathan M.; Thain, GregAttribution: Community for Data Integration (CDI), Upper Midwest Environmental Sciences Center, Ecosystems, United States of America
View Citation
Erickson, R.A., Fienen, M.N., McCalla, S.G., Weiser, E.L., Bower, M.L., Knudson, J.M., Thain, G. 2018. Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor. PLoS Computational Biology. 14(10):e1006468. DOI: 10.1371/journal.pcbi.1006468.
Year Published: 2018
A tool for efficient, model-independent management optimization under uncertainty
To fill a need for risk-based environmental management optimization, we have developed PESTPP-OPT, a model-independent tool for resource management optimization under uncertainty. PESTPP-OPT solves a sequential linear programming (SLP) problem and also implements (optional) efficient, “on-the-fly” (without user intervention) first-order, second-...
White, Jeremy; Fienen, Michael N.; Barlow, Paul M.; Welter, Dave E.Attribution: Wisconsin Water Science Center, Water Resources
View Citation
White, J. T., Fienen, M. N., Barlow, P. M., and Welter, D.E. (2017) A tool for efficient, model-independent management optimization under uncertainty. Environmental Modeling and Software. doi:10.1016/j.envsoft.2017.11.019
Year Published: 2018
Depletion mapping and constrained optimization to support managing groundwater extraction
Groundwater models often serve as management tools to evaluate competing water uses including ecosystems, irrigated agriculture, industry, municipal supply, and others. Depletion potential mapping—showing the model-calculated potential impacts that wells have on stream baseflow—can form the basis for multiple potential management approaches in an...
Fienen, Michael N.; Bradbury, Kenneth R.; Kniffin, Maribeth; Barlow, Paul M.Attribution: Wisconsin Water Science Center, Water Resources
View Citation
Fienen, M. N., Bradbury, K. R., Kniffin, M. and Barlow, P. M. (2017), Depletion Mapping and Constrained Optimization to Support Managing Groundwater Extraction. Groundwater. doi:10.1111/gwat.12536
Year Published: 2017
Generalized hydrogeologic framework and groundwater budget for a groundwater availability study for the glacial aquifer system of the United States
The glacial aquifer system groundwater availability study seeks to quantify (1) the status of groundwater resources in the glacial aquifer system, (2) how these resources have changed over time, and (3) likely system response to future changes in anthropogenic and environmental conditions. The glacial aquifer system extends from Maine to Alaska,...
Reeves, Howard W.; Bayless, E. Randall; Dudley, Robert W.; Feinstein, Daniel T.; Fienen, Michael N.; Hoard, Christopher J.; Hodgkins, Glenn A.; Qi, Sharon L.; Roth, Jason L.; Trost, Jared J.Attribution: Water, Colorado Water Science Center, Minnesota Water Science Center, New England Water Science Center, Ohio Kentucky Indiana Water Science Center, Upper Midwest Water Science Center, Wisconsin Water Science Center, Michigan Water Science Center, Michigan-Ohio Water Science Center, Water Resources, Ohio, United States of America
View Citation
Reeves, H.W., Bayless, E.R., Dudley, R.W., Feinstein, D.T., Fienen, M.N., Hoard, C.J., Hodgkins, G.A., Qi, S.L., Roth, J.L., and Trost, J.J., 2017, Generalized hydrogeologic framework and groundwater budget for a groundwater availability study for the glacial aquifer system of the United States: U.S. Geological Survey Scientific Investigations Report 2017–5015, 49 p., https://doi.org/10.3133/sir20175015.
Year Published: 2017
Community for Data Integration 2016 annual report
The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working...
Langseth, Madison L.; Hsu, Leslie; Amberg, Jon J.; Bliss, Norman; Bock, Andrew R.; Bolus, Rachel T.; Bristol, R. Sky; Chase, Katherine J.; Crimmins, Theresa M.; Earle, Paul S.; Erickson, Richard; Everette, A. Lance; Falgout, Jeff T.; Faundeen, John L.; Fienen, Michael N.; Griffin, Rusty; Guy, Michelle R.; Henry, Kevin D.; Hoebelheinrich, Nancy J.; Hunt, Randall; Hutchison, Vivian B.; Ignizio, Drew A.; Infante, Dana M.; Jarnevich, Catherine; Jones, Jeanne M.; Kern, Tim; Leibowitz, Scott; Lightsom, Francis L.; Marsh, R. Lee; McCalla, S. Grace; McNiff, Marcia; Morisette, Jeffrey T.; Nelson, John C.; Norkin, Tamar; Preston, Todd M.; Rosemartin, Alyssa; Sando, Roy; Sherba, Jason T.; Signell, Richard P.; Sleeter, Benjamin M.; Sundquist, Eric T.; Talbert, Colin B.; Viger, Roland J.; Weltzin, Jake F.; Waltman, Sharon; Weber, Marc; Wieferich, Daniel J.; Williams, Brad; Windham-Myers, LisamarieAttribution: Community for Data Integration (CDI), Science Analytics and Synthesis (SAS), United States of America
View Citation
Langseth, M.L., Hsu, Leslie, Amberg, Jon, Bliss, Norman, Bock, A.R., Bolus, R.T., Bristol, R.S., Chase, K.J., Crimmins, T.M., Earle, P.S., Erickson, Richard, Everette, A.L., Falgout, Jeff, Faundeen, J.L., Fienen, Michael, Griffin, Rusty, Guy, M.R., Henry, K.D., Hoebelheinrich, N.J., Hunt, Randall, Hutchison, V.B., Ignizio, D.A., Infante, D.M., Jarnevich, Catherine, Jones, J.M., Kern, Tim, Leibowitz, Scott, Lightsom, F.L., Marsh, R.L., McCalla, S.G., McNiff, Marcia, Morisette, J.T., Nelson, J.C., Norkin, Tamar, Preston, T.M., Rosemartin, Alyssa, Sando, Roy, Sherba, J.T., Signell, R.P., Sleeter, B.M., Sundquist, E.T., Talbert, C.B., Viger, R.J., Weltzin, J.F., Waltman, Sharon, Weber, Marc, Wieferich, D.J., Williams, Brad, Windham-Myers, Lisamarie, 2017, Community for Data Integration 2016 annual report: U.S. Geological Survey Open-File Report 2017–1053, 40 p., https://doi.org/10.3133/ofr20171053.
Year Published: 2017
Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands
The Little Plover River is a groundwater-fed stream in the sand plains region of central Wisconsin. In this region, sandy sediment deposited during or soon after the last glaciation forms an important unconfined sand and gravel aquifer. This aquifer supplies water for numerous high-capacity irrigation, municipal, and industrial wells that support...
Ken Bradbury; Fienen, Michael N.; Kniffin, Maribeth; Jacob Krause; Westenbroek, Stephen M.; Leaf, Andrew T.; Barlow, Paul M.Attribution: Wisconsin Water Science Center, Water Resources
View Citation
Bradbury, K.R., Fienen, M.N., Kniffin, M.L., Krause, J.J., Westenbroek, S.M., Leaf, A.T., and Barlow, P.M., 2017, Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands: Wisconsin Geological and Natural History Survey Bulletin 111, 82 p.
Year Published: 2016
MODFLOW-NWT model used to evaluate groundwater/surface-water interactions in the Bad River Watershed, Wisconsin
A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW–NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The model was calibrated to groundwater levels and base...
Leaf, Andrew T.; Fienen, Michael N.; Hunt, Randall J.; Buchwald, Cheryl A.Attribution: Wisconsin Water Science Center
View Citation
Andrew T. Leaf, Michael N. Fienen, Randall J. Hunt, Cheryl Buchwald, 2016, MODFLOW-NWT model used to evaluate groundwater/surface-water interactions in the Bad River Watershed, Wisconsin: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7Z0368H
Year Published: 2016
HESS Opinions: Repeatable research: what hydrologistscan learn from the Duke cancer research scandal
In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were...
Fienen, Michael; Bakker, MarkAttribution: Wisconsin Water Science Center, Water Resources
View Citation
Fienen, M. N. and Bakker, M.: HESS Opinions: Repeatable research: what hydrologists can learn from the Duke cancer research scandal, Hydrol. Earth Syst. Sci., 20, 3739–3743, 2016
Year Published: 2016
A python framework for environmental model uncertainty analysis
We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses...
White, Jeremy; Fienen, Michael N.; Doherty, John E.Attribution: Texas Water Science Center, Water Resources
Year Published: 2016
Assessment of groundwater availability in the Northern Atlantic Coastal Plain aquifer system From Long Island, New York, to North Carolina
Executive SummaryThe U.S. Geological Survey began a multiyear regional assessment of groundwater availability in the Northern Atlantic Coastal Plain (NACP) aquifer system in 2010 as part of its ongoing regional assessments of groundwater availability of the principal aquifers of the Nation. The goals of this national assessment are to document...
Masterson, John P.; Pope, Jason P.; Fienen, Michael N.; Monti, Jr., Jack; Nardi, Mark R.; Finkelstein, Jason S.View Citation
Masterson, J.P., Pope, J.P., Fienen, M.N., Monti, Jack, Jr., Nardi, M.R., and Finkelstein, J.S., 2016, Assessment of groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina: U.S. Geological Survey Professional Paper 1829, 76 p., http://dx.doi.org/10.3133/pp1829.
Year Published: 2016
Documentation of a groundwater flow model developed to assess groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina
The U.S. Geological Survey developed a groundwater flow model for the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to northeastern North Carolina as part of a detailed assessment of the groundwater availability of the area and included an evaluation of how these resources have changed over time from stresses related...
Masterson, John P.; Pope, Jason P.; Fienen, Michael N.; Monti, Jr., Jack; Nardi, Mark R.; Finkelstein, Jason S.View Citation
Masterson, J.P., Pope, J.P., Fienen, M.N., Monti, Jack Jr., Nardi, M.R., and Finkelstein, J.S., 2016, Documentation of a groundwater flow model developed to assess groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina (ver. 1.1, December 2016): U.S. Geological Survey Scientific Investigations Report 2016–5076, 70 p., http://dx.doi.org/10.3133/sir20165076.
Year Published: 2016
Potential effects of sea-level rise on the depth to saturated sediments of the Sagamore and Monomoy flow lenses on Cape Cod, Massachusetts
In 2014, the U.S. Geological Survey, in cooperation with the Association to Preserve Cape Cod, the Cape Cod Commission, and the Massachusetts Environmental Trust, began an evaluation of the potential effects of sea-level rise on water table altitudes and depths to water on central and western Cape Cod, Massachusetts. Increases in atmospheric and...
Walter, Donald A.; McCobb, Timothy D.; Masterson, John P.; Fienen, Michael N.Attribution: New England Water Science Center, Water Resources
View Citation
Walter, D.A., McCobb, T.D., Masterson, J.P., and Fienen, M.N., 2016, Potential effects of sea-level rise on the depth to saturated sediments of the Sagamore and Monomoy flow lenses on Cape Cod, Massachusetts (ver. 1.1, October 18, 2016): U.S. Geological Survey Scientific Investigations Report 2016–5058, 55 p., http://dx.doi.org/10.3133/sir20165058.