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The beginning of the 20th century through the 1970s were good times for soil science in the USA, with relatively strong funding and overall growth in the profession. However, the soil science discipline in the USA hit hard times in the 1980s and 1990s. Federal funding for soil survey work began to decline as did student numbers in university programs and membership in the Soil Science Society of America (SSSA). Despite this, there were still many positive advances within soil science in the USA during these two decades. There was an increased use of geophysical instrumentation, remote sensing, geographic information systems (GIS), and global positioning systems (GPS), and research began in digital soil mapping, all of which lead to better understanding of the spatial distribution and variability of soils. Many NRCS soil products were put online, making them widely available to the general public, the use of soil knowledge was expanded into new areas such as archaeology and environmental work, and historic connections to geology were re-established. While expansion into new areas required soil science to evolve as a field, separating the discipline to an extent from its agricultural roots, it also helped reinvigorate the discipline. As we move through the early parts of the 21st century, student numbers are increasing in university soil science programs and membership in SSSA is at an all-time high. Digital soil mapping is being incorporated into the National Cooperative Soil Survey, and the impact of humans on the soil system is being fully recognized. The importance of soils is being recognized by events such as the United Nations declaration of 2015 as the “International Year of Soils”. The expansion of soils into new areas and widening recognition of the importance of soils gives the field hope for a bright future in the USA.

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.

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.

T he purpose of this article is to present some ideas and concepts that will enhance the consistency, manageability, utility, and quality of the soils interpretations within NASIS for the current updating and digitization phase of the National Cooperative Soil Survey. Following is a case for creating and linking basic soil data and interpretations to the Official Series Description within the National Soil Information System (NASIS).