Date of Award:

5-2015

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Plants, Soils, and Climate

Committee Chair(s)

Janis L. Boettinger

Committee

Janis L. Boettinger

Committee

Joel L. Pederson

Committee

R. Douglas Ramsey

Abstract

In some parts of the western US there is limited publicly available soil information that can be used to make land management decisions on both public and private land. A goal of the USDI Bureau of Land Management (BLM) in Utah was to map an area in central Utah where such soil maps and value-added information was not available for management and restoration decisions following a wildfire. In 2007, the Milford Flat Fire had burned more than 363,000 acres, removing vegetation that was holding erosion-sensitive soils in place. Following inconsistent results from stabilization and restoration efforts, this study was funded to create soil maps for a part of the burned area west of Fillmore, UT.

Soil maps were created over an area of more than 146,000 acres using predictive statistical models that incorporated geographic information systems and statistical software. Over two field seasons soil data were collected by excavating and describing the soil more than 150 sites over the project area. The coordinates of physical locations were recorded, and soils were sampled, described, characterized, and classified to a soil series that could be used to make interpretations for management and restoration decisions. Two sets of sampling sites were collected: one to create models and maps of soils in the project area, and another set to validate the accuracy of those maps. The project area was split into two areas: one above the Lake Bonneville highstand shoreline, and one below. Points were separated out between those above and those below the shoreline. Modeling results were less accurate than desired below the shoreline, but could be useful to guide further mapping and refining of subsequent soil maps. The dominant soil order predicted was Aridisols; some had high calcium carbonate content, and some had high clay content with high sodium. The soil distribution above the shoreline was estimated since there were not enough points to model any soils with accuracy.

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