Systematic Variability of Soil Hydraulic Conductivity Across Three Vertisol Catenas

Soil hydraulic properties, such as saturated hydraulic conductivity (Ks), have high spatial variation, but little is known about how to vary a few measurements of Ks over an area to model hydrology in a watershed with complex topography and multiple land uses. Variations in soil structure, macropores (especially in soil that shrink and swell), land use, and soil development can cause large variations in Ks within one soil type. Characterizing the impacts of soil properties that might vary systematically with land use and terrain attributes on Ks rates would provide insight on how management and human activity affect local and regional hydrology. The overall objective of this research was to develop a strategy for using published infiltration and Ks measurements by the Natural Resources Conservation Service for watershed hydrology applications in a Vertisol, and to extend this knowledge toward developing recommendations for future infiltration measurements. To achieve this goal, soil infiltration measurements were collected across three catenas of Houston Black and Heiden clays (fine, smectitic, thermic Udic Haplusterts) under three land uses (improved pasture, native prairie, and conventional tillage row crop). Measurement locations were selected to account for variation in terrain attributes. Overall, Ks values were not significantly different across different landscape positions; however, in fields under similar land uses, Ks values were found to be lower in the footslope positions and higher in the backslope positions. The pedotransfer function, ROSETTA, provided estimates of 64 percent of the overall variability in Ks while also providing accurate estimates of the mean of Ks when particle size distribution and bulk density are used as inputs in the model. Through the use of multiple regression analysis, soil antecedent water content, bulk density, clay content, and soil organic carbon along with two indicator variables for the catenas were highly correlated (r2 = 0.59) with Ks. The indicator variables explained 17 percent of the variation in Ks that could not be explained by measured soil properties. It is recommended that when NRCS measures Ks on benchmark soils, especially high clay soils, that they collect particle size distribution, bulk density, organic carbon, and antecedent water content data.