Spatial extrapolation of soil characteristics using whole-soil particle size distributions.

Soils support ecosystem functions such as plant growth and water quality because of certain physical, chemical, and biological properties. These properties have been studied at different spatial scales, including point scales to satisfy basic research needs, and regional scales to satisfy monitoring needs. Recently, soil property data for the entire USA have become available in the State Soil Geographic Data Base (STATSGO), which is appropriate for regional-scale research. We analyzed and created models of STATSGO data in this study to serve as a research tool, for example, for linking the soil to regional water quality monitoring data in our companion paper. Map units in STATSGO define geographic land areas by soil characteristics (SCs) of similar soil series. We selected 27 SCs that influenced water properties (in varying degrees), aggregated the layer and component SCs to map unit SCs, and used SCs to calculate relationships among map units. The relationships were defined by equations of conditional mean for the qth SC (SCq), while using the remaining 26 SCs as predictors. The relative standard errors for 22 of the 27 SCs were less than 10%, and less than 22% for the remaining five. We conclude that spatial extrapolation of SCs is feasible and the procedures are a first step toward extrapolating information across a region using SC-water property relationships. Although our procedure is for regional scale monitoring, it is also applicable to finer spatial scales commensurate with available soil data.