Using GIS to Map the Distribution of Peoria Loess on the Green Bay Lobe Glacial Surface in South-Central Wisconsin Carlene Polk & Peter Jacobs (mentor), Geography and Geology. • Loess is windblown dust that was transported from distant barren land-surfaces. • Peoria Loess is the term applied to a recognizable deposit of dust that covers much of the mid-continent, from Colorado to Ohio and down the Mississippi Riv • Loess is a paleoenvironmental indicator and an important sediment in which soils have formed because the physical and mineralogical properties of loess im • The Green Bay Lobe (GBL) is the name applied to the glacial lobe that affected south central Wisconsin. • Loess has long been recognized on the GBL surface, but the chronology, source, and distribution are not well understood. Glacial Boundary Sand Dunes Loess >100cm Loess >50cm and <100cm Loess <50cm Thick loess in south central Nebraska. Peoria Loess is above dark band. Note person for scale. Analyzing The Map • Regional thinning pattern is to the E and SE of the Central WI Sand Plain. 90 cm Source: U.S. Geological Survey Typical thin loess mantle in south central Wisconsin. Peoria Loess mantles stony glacial sediment below. Producing The Map • Maps were created from digital soil survey data (SSURGO) for each county. • Soil series descriptions were evaluated for occurrence and thickness of a loess mantle. • Sharp boundaries with sandy soils and dunes in Columbia and counties to NW indicates sand mobilized dust and provided a local source of dust. • Loess thickness in Jefferson Co. appears to have been under recorded by soil surveyors (see poster of Degen). • Thick loess on the Rock Prairie and outwash fans in front of Lake MI Lobe indicates there surfaces stabilized because new drainage routes for glacial melt water must have established quickly. • Soil series were grouped into three classes of loess thickness: <50 cm, 50100 cm, and >100 cm. • Each thickness layer for a county was exported and joined to the regional map to interpret source and distribution. • The GIS tools that were utilized for this map were; layering, categorizing, extract, overlay, projections and transformations, exporting, clipping, querying, and union. We wish to acknowledge support for this research from the Provost’s Summer Research Scholars program, the UWW Undergraduate Research Program, and Dr. Tom Jeffery for GIS help.