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Predicting Wetland Plant Composition Based on Soil Moisture Regime Using a Quasi-
3D Variably-Saturated Groundwater Flow Model
**Eric G. Booth, University of Wisconsin – Madison, Limnology and Marine Science, Madison,
WI, egbooth@wisc.edu
Steven P. Loheide II, University of Wisconsin – Madison, Department of Civil and
Environmental Engineering, Madison, WI, loheide@wisc.edu
The ability to predict vegetation composition based on environmental variables can be
powerful for assessing the impacts of land-use change, climate change, or land management
activities on an ecosystem. In wetland ecosystems, the soil water regime is the primary
environmental variable controlling the distribution of vegetation. Previous studies have used
observed and simulated depth-to-water-table as a proxy of the soil water regime to predict
vegetation composition. However, depth-to-water-table may not be an effective indicator of
the soil water regime at some sites due to several factors including strong vertical hydraulic
gradients and deep water table. In these cases, soil moisture may be more effective for
developing regime metrics as predictors of plant composition.
We have developed a methodology that links a quasi-3D, variably-saturated, groundwater
flow model with a statistical vegetation model to predict the probability of presence of several
dominant plant species across a recently-restored floodplain wetland near Barneveld, WI. The
hydrologic model was created using a general-purpose, finite-element software (COMSOL)
and consists of a 2-D confined saturated groundwater flow model linked with a 1-D variablysaturated
groundwater flow model. The statistical vegetation model then uses several
simulated soil moisture regime metrics (e.g., mean growing season soil moisture at 25 cm
depth) as predictors in a non-parametric regression model using the software HyperNiche 2.
This modeling framework produces predictive maps of vegetation distribution and provides
the ability to assess potential climate and land-use change scenarios.
** Graduate student presentation
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