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
Development and application of a groundwater/surface-water flow model using MODFLOW-NWT for the Upper Fox River Basin, southeastern Wisconsin
Regression modeling of particle size distributions in urban stormwater: Advancements through improved sample collection methods
Social.Water - A crowdsourcing tool for environmental data acquisition
MODFLOW-style parameters in underdetermined parameter estimation
Simulation of the shallow groundwater-flow system near Mole Lake, Forest County, Wisconsin
Using models for the optimization of hydrologic monitoring
cloudPEST - A python module for cloud-computing deployment of PEST, a program for parameter estimation
MODFLOW-style parameters in underdetermined parameter estimation
Approaches to highly parameterized inversion: Pilot-point theory, guidelines, and research directions
Inverse modeling with RZWQM2 to predict water quality
Simulation of groundwater flow and effects of groundwater irrigation on stream base flow in the Elkhorn and Loup River basins, Nebraska, 1895-2055: Phase Two
Using prediction uncertainty analysis to design hydrologic monitoring networks: Example applications from the Great Lakes water availability pilot project
Science and Products
- Publications
Filter Total Items: 87
Development and application of a groundwater/surface-water flow model using MODFLOW-NWT for the Upper Fox River Basin, southeastern Wisconsin
The Fox River is a 199-mile-long tributary to the Illinois River within the Mississippi River Basin in the states of Wisconsin and Illinois. For the purposes of this study the Upper Fox River Basin is defined as the topographic basin that extends from the upstream boundary of the Fox River Basin to a large wetland complex in south-central Waukesha County called the Vernon Marsh. The objectives forAuthorsD. T. Feinstein, M.N. Fienen, J.L. Kennedy, C.A. Buchwald, M.M. GreenwoodRegression modeling of particle size distributions in urban stormwater: Advancements through improved sample collection methods
A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution atAuthorsWilliam R. Selbig, Michael N. FienenSocial.Water - A crowdsourcing tool for environmental data acquisition
Remote telemetry has a long history of use for collection of environmental measurements. With the rise of mobile phones and SMS text-messaging capacity, many members of the general pubic carry communications equipment in their pockets at all times. Enabling the general public to provide environmental data through text messages has the potential both to provide additional data to scientific projectAuthorsMichael N. Fienen, Christopher LowryMODFLOW-style parameters in underdetermined parameter estimation
In this article, we discuss the use of MODFLOW-Style parameters in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package. Parameters are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the parameterAuthorsMarco D. D'Oria, Michael N. FienenSimulation of the shallow groundwater-flow system near Mole Lake, Forest County, Wisconsin
The shallow groundwater system near Mole Lake, Forest County, Wis. was simulated using a previously calibrated regional model. The previous model was updated using newly collected water-level measurements and refinements to surface-water features. The updated model was then used to calculate the area contributing recharge for one existing and two proposed pumping locations on lands of the SokaogonAuthorsMichael N. Fienen, Paul F. Juckem, Randall J. HuntUsing models for the optimization of hydrologic monitoring
Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interestAuthorsMichael N. Fienen, Randall J. Hunt, John E. Doherty, Howard W. ReevescloudPEST - A python module for cloud-computing deployment of PEST, a program for parameter estimation
This report documents cloudPEST-a Python module with functions to facilitate deployment of the model-independent parameter estimation code PEST on a cloud-computing environment. cloudPEST makes use of low-level, freely available command-line tools that interface with the Amazon Elastic Compute Cloud (EC2(TradeMark)) that are unlikely to change dramatically. This report describes the preliminary seAuthorsMichael N. Fienen, Thomas C. Kunicki, Daniel E. KesterMODFLOW-style parameters in underdetermined parameter estimation
In this article, we discuss the use of MODFLOW‐Style parameters in the numerical codes MODFLOW_2005 and MODFLOW_2005‐Adjoint for the definition of variables in the Layer Property Flow package. Parameters are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the parameterAuthorsM. D'Oria, M. N. FienenApproaches to highly parameterized inversion: Pilot-point theory, guidelines, and research directions
Pilot points have been used in geophysics and hydrogeology for at least 30 years as a means to bridge the gap between estimating a parameter value in every cell of a model and subdividing models into a small number of homogeneous zones. Pilot points serve as surrogate parameters at which values are estimated in the inverse-modeling process, and their values are interpolated onto the modeling domaiAuthorsJohn E. Doherty, Michael N. Fienen, Randall J. HuntInverse modeling with RZWQM2 to predict water quality
This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the WalnuAuthorsBernard T. Nolan, Robert W. Malone, Liwang Ma, Christopher T. Green, Michael N. Fienen, Dan B. JaynesSimulation of groundwater flow and effects of groundwater irrigation on stream base flow in the Elkhorn and Loup River basins, Nebraska, 1895-2055: Phase Two
Regional groundwater-flow simulations for a 30,000-square-mile area of the High Plains aquifer, referred to collectively as the Elkhorn-Loup Model, were developed to predict the effects of groundwater irrigation on stream base flow in the Elkhorn and Loup River Basins, Nebraska. Simulations described the stream-aquifer system from predevelopment through 2005 [including predevelopment (pre-1895), eAuthorsJennifer S. Stanton, Steven M. Peterson, Michael N. FienenUsing prediction uncertainty analysis to design hydrologic monitoring networks: Example applications from the Great Lakes water availability pilot project
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 preAuthorsMichael N. Fienen, John E. Doherty, Randall J. Hunt, Howard W. Reeves - Science
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