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Erik A Smith

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St. Louis River estuary (Minnesota-Wisconsin) EFDC hydrodynamic model for discharge and temperature simulations: 2016–17
The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers Engineer Research and Development Center and the U.S. Environmental Protection Agency, developed a predictive, mechanistic, three-dimensional hydrodynamic model for the St. Louis River Estuary (SLRE), Minnesota. This model was developed with Environmental Fluid Dynamics Code (EFDC), a grid-based, surface-water modeling package for simulating three-dimensional circulation, mass transport, sediments, and biogeochemical processes. The new model predicts discharge, water-surface elevations, flow velocity, and water temperature. The model was calibrated using data collected from April 2016 through November 2016 and validated with...
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DRAINMOD, a field-scale, process-based, distributed model (Skaggs, 1980; https://www.bae.ncsu.edu/agricultural-water-management/DRAINMOD/), was used to simulate subsurface drainage flow and field water-surface elevations. DRAINMOD simulations are often used to optimize drainage patterns for agricultural fields with subsurface drainage. For this study, the model results were also used to simulate deep seepage rates. Deep seepage is the amount of water that moves past the agricultural drains. These deep seepage rates were then used as a surrogate for potential groundwater recharge rates. A total of nine different scenarios were run, each sceanrio corresponding to a different location on one of three different field...
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A histrogram-based boosted regression tree (HBRT) method was used to predict the depth to the surficial aquifer water table (in feet) throughout the State of Wisconsin. This method used a combination of discrete groundwater levels from the U.S. Geological Survey National Water Information System, continuous groundwater levels from the National Groundwater Monitoring Network, the State of Wisconsin well-construction database, and NHDPlus version 2.1-derived points. The predicted water table depth utilized the HBRT model available through Scikit-learn in Python version 3.10.10. The HBRT model can predict the surficial water table depth for any latitude and longitude for Wisconsin. A total of 48 predictor variables...
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A water table fluctuation model simulated potential recharge rates from 2016 to 2018 for two agricultural sites in southeastern Minnesota. The model calculated potential recharge rates through the analysis of groundwater rises. A total of 42 piezometers were analyzed for this study using the water table fluctuation model. This methodology of calculating potential recharge rates was used as an independent method from two other methods: a soil-water-balance model (https://doi.org/10.5066/P90N4AWG), and DRAINMOD (https://doi.org/10.5066/P987N30U).
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The U.S. Geological Survey (USGS), in cooperation with the St. Croix River Research Station – Science Museum of Minnesota, updated a previously developed CE-QUAL-W2 hydrodynamic and water-quality model of Madison Lake, Minnesota (Smith and others, 2017). The previous version partitioned phytoplankton into four general algal communities or groups: (1) Bacillariophyta (diatoms) and Chrysophyta (chrysophytes); (2) Chlorophyta (green algae); (3) Cyanophyta (cyanobacteria); and, (4) Haptophyta and Cryptophyta (flagellates). For the updated model, the Cyanophyta group (originally referred to as blue-green algae) has been divided into two groups: a nitrogen-fixing Cyanophyta group, generally representative of Anabaena,...
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