Soil-Moisture Variability at Big Meadows, Shenandoah National Park, Virginia: Impacts on the Water Balance

Lawrence, Justin Earl, Department of Environmental Sciences, University of Virginia
Hornberger, George, University of Virginia
Mills, Aaron, Department of Environmental Sciences, University of Virginia
D’Odorico, Paolo, Department of Environmental Sciences, University of Virginia

Variability in soil-moisture is controlled by temporal variability in atmospheric conditions and spatial variability in land-surface conditions. In past studies, observations of soil-moisture have revealed a variety of patterns. In some studies, variance increased with decreasing mean moisture content, while in other studies variance decreased with decreasing mean moisture content. These seemingly conflicting observations lead to several open questions: (1) How do spatial patterns of soil-moisture evolve over different time scales? (2) How do topography, soil, and vegetation control the evolution of soilmoisture? (3) How can available data be used with knowledge of hydrologic processes to model the evolution of soil-moisture in small catchments? (4) How does soil-moisture variability impact other parts of the water balance? and (5) How might climate change affect present-day soil-moisture distributions? Soil-moisture patterns were analyzed at Big Meadows, an upland wetland in Shenandoah National Park, Virginia and a different trend from that reported in past studies was found: maximum variance occurred at midmoisture contents instead of low or high moisture contents. An adapted soil-moisture dynamics model, driven by hourly inputs of temperature and precipitation, was used to reproduce observed spatial patterns of soil-moisture. The deep drainage component of the soil-moisture dynamics model was related to ground-water levels and stream discharge, and gave reasonable results. The results of this study provide insight into the controls of soil-moisture variability, may generally apply to sites in temperature climate zones, and can be used to forecast effects of climate change on soil-moisture patterns.

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MS (Master of Science)
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