Michael N Fienen
Mike Fienen is a Research Hydrologist with the Upper Midwest Water Science Center.
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.
Education and Certifications
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
Science and Products
A cross-validation package driving Netica with python
Simulation of groundwater flow and interaction of groundwater and surface water on the Lac du Flambeau Reservation, Wisconsin
Virtual Beach 3: user's guide
Effects of sea-level rise on barrier island groundwater system dynamics: ecohydrological implications
Nitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling
Bridging groundwater models and decision support with a Bayesian network
Development of a numerical model to simulate groundwater flow in the shallow aquifer system of Assateague Island, Maryland and Virginia
Simulation of the shallow groundwater-flow system in the Forest County Potawatomi Community, Forest County, Wisconsin
Partial least squares for efficient models of fecal indicator bacteria on Great Lakes beaches
Crowdsourcing to Acquire Hydrologic Data and Engage Citizen Scientists: CrowdHydrology
Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions
Science and Products
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Filter Total Items: 87
A cross-validation package driving Netica with python
Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica isAuthorsMichael N. Fienen, Nathaniel G. PlantSimulation of groundwater flow and interaction of groundwater and surface water on the Lac du Flambeau Reservation, Wisconsin
The Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service are interested in improving the understanding of groundwater flow and groundwater/surface-water interaction on the Lac du Flambeau Reservation (Reservation) in southwest Vilas County and southeast Iron County, Wisconsin, with particular interest in an understanding of the potential for contamination of groundwater supplyAuthorsPaul F. Juckem, Michael N. Fienen, Randall J. HuntVirtual Beach 3: user's guide
Virtual Beach version 3 (VB3) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches. VB3 is primarily designed for beach managers responsible for making decisions regarding beach closures or the issuance of swimming advisories due to pathogen contamination. However, researchers, scientists, engAuthorsMike Cyterski, Wesley Brooks, Mike Galvin, Kurt Wolfe, Rebecca Carvin, Tonia Roddick, Mike Fienen, Steve CorsiEffects of sea-level rise on barrier island groundwater system dynamics: ecohydrological implications
We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and succession of vegetation assemblages and habitat suiAuthorsJohn P. Masterson, Michael N. Fienen, E. Robert Thieler, Dean B. Gesch, Benjamin T. Gutierrez, Nathaniel G. PlantNitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling
DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inversAuthorsRashad Rafique, Michael N. Fienen, Timothy B. Parkin, Robert P. AnexBridging groundwater models and decision support with a Bayesian network
Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability makeAuthorsMichael N. Fienen, John P. Masterson, Nathaniel G. Plant, Benjamin T. Gutierrez, E. Robert ThielerDevelopment of a numerical model to simulate groundwater flow in the shallow aquifer system of Assateague Island, Maryland and Virginia
A three-dimensional groundwater-flow model was developed for Assateague Island in eastern Maryland and Virginia to simulate both groundwater flow and solute (salt) transport to evaluate the groundwater system response to sea-level rise. The model was constructed using geologic and spatial information to represent the island geometry, boundaries, and physical properties and was calibrated using anAuthorsJohn P. Masterson, Michael N. Fienen, Dean B. Gesch, Carl S. CarlsonSimulation of the shallow groundwater-flow system in the Forest County Potawatomi Community, Forest County, Wisconsin
The shallow groundwater system in the Forest County Potawatomi Comminity, Forest County, Wisconsin, was simulated by expanding and recalibrating a previously calibrated regional model. The existing model was updated using newly collected water-level measurements, inclusion of surface-water features beyond the previous near-field boundary, and refinements to surface-water features. The updated modeAuthorsMichael N. Fienen, David A. Saad, Paul F. JuckemPartial least squares for efficient models of fecal indicator bacteria on Great Lakes beaches
At public beaches, it is now common to mitigate the impact of water-borne pathogens by posting a swimmer's advisory when the concentration of fecal indicator bacteria (FIB) exceeds an action threshold. Since culturing the bacteria delays public notification when dangerous conditions exist, regression models are sometimes used to predict the FIB concentration based on readily-available environmentaAuthorsWesley R. Brooks, Michael N. Fienen, Steven R. CorsiCrowdsourcing to Acquire Hydrologic Data and Engage Citizen Scientists: CrowdHydrology
Spatially and temporally distributed measurements of processes, such as baseflow at the watershed scale, come at substantial equipment and personnel cost. Research presented here focuses on building a crowdsourced database of inexpensive distributed stream stage measurements. Signs on staff gauges encourage citizen scientists to voluntarily send hydrologic measurements (e.g., stream stage) via texAuthorsMichael N. Fienen, Chris LowryApproaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions
The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability thAuthorsMichael N. Fienen, Marco D'Oria, John E. Doherty, Randall J. Hunt - Science
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