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Soil Survey Geographic Database (SSURGO) data are available for the entire United States, so are incorporated in many regional and national models of hydrology and environmental management. However, SSURGO does not provide an understanding of spatial variability and only includes saturat- ed hydraulic conductivity (K sat ) values estimated from particle size analysis (PSA). This study showed model sensitivity to the substitution of SSURGO data with locally described soil properties or alternate methods of measur- ing K sat . Incorporation of these different soil data sets significantly changed the results of hydrologic modeling as a consequence of the amount of space available to store soil water and how this soil water is moved downslope. Locally described soil profiles indicated a difference in K sat when measured in the field vs. being estimated from PSA. This, in turn, caused a differ - ence in which soil layers were incorporated in the hydrologic simulations using TOPMODEL, ultimately affecting how soil water storage was simu- lated. Simulations of free-flowing soil water, the amount of water traveling through pores too large to retain water against gravity, were compared with field observations of water in wells at five slope positions along a cat- ena. Comparison of the simulated data with the observed data showed that the ability to model the range of conditions observed in the field varied as a function of three soil data sets (SSURGO and local field descriptions using PSA-derived K sat or field-measured K sat ) and that comparison of absolute values of soil water storage are not valid if different characterizations of soil properties are used. Abbreviations: AET, actual evapotranspiration; CCHP, compact constant-head permeameter; DEM, digital elevation model; FC, field capacity; PSA, particle size analysis; PSAf, particle size analysis derived from field data; SD, saturation deficit; SSURGO, Soil Survey Geographic Database; TWI, topographic wetness index.

Three major challenges are present when studying anthropogenic impacts on soil profile properties: (i) site selection; (ii) sampling and modeling native and cultivated soil-landscape relationships; and (iii) graphically and statistically comparing native and cultivated sites to model soil profile changes. This study addressed those challenges by measuring and modeling selected soil profile properties of paired (native) forest and analogous nonnative (cultivated) loess hillslopes in central Missouri. The paired hillslopes in Saline County were mapped as Mollic Hapludalfs and the paired hillslopes in Boone County were mapped as Typic Hapludalfs. Horizonation and depth distribution of Hapludalf soil properties provide markers when measuring land use impacts on soil profile properties. Summit pedons on the four sites verified the mapping and classification. Transect data revealed soil profile variation by slope position and by site. Regression analysis identified relationships at the p < 0.007 level between depth to clay maximum (adjusted R2 = 0.74), thickness of the A horizon (adjusted R2= 0.32), thickness of the subsurface horizon (adjusted R2 = 0.69), depth to the top of the B horizon (adjusted R2 = 0.69), clay content of the surface horizon (R2 = 0.76), organic C content of the surface horizon (adjusted R2 = 0.56), and depth to =7.5 g kg-1 organic C (adjusted R2 = 0.59) and slope position and site characteristics. A different response surface for each site for each soil characteristic supported the hypothesis that vegetative history and land use significantly affected the distribution of these soil properties.

Soils are a product of the environment in which they form. The integrated effects of climate, organisms, initial parent material, and topography produce processes that, over time , differentiate soils that are characteristic of those combined environmental influences. Soil-forming processes include additions, most notably organic matter, and losses, such as dissolved ions that are leached from the soil to groundwater . Soils are also shaped by the processes of translocation, such as clay particles being moved to the subsoil by percolating water and transformation, as in the soil structural units created by shrink–swell activity. The imprint of the soil-forming factors and processes is reflected in the soils that occur on landscapes. The goal of soil survey is to model and record this imprint. The geographic pattern of soils is mapped by differentiating parts of the landscape that have experienced different combinations of soil-forming factors. Delineation with similar soils are grouped as a map unit for description and interpretation. The scale at which soils are identified and delineated depends on the intended land use. In the USA, soils are identified using the USDA Soil Taxonomy and soil survey information is available in hard copy reports and online.