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Articles

Comparing SSURGO Data with Geospatial Field Measurements to Estimate Soil Texture and Infiltration Rate Classes in Glaciated Soils

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Pages 1309-1318 | Received 08 Sep 2016, Accepted 02 Feb 2017, Published online: 27 Jul 2017
 

ABSTRACT

The infiltration rate (IR) of water is a key soil property related to hydrological processes, soil health, and ecosystem services. However, detailed measurements of IR in the field and/or laboratory are labor-intensive and expensive to perform. Soil judging in the field provides a rapid and inexpensive method to estimate IR classes based on soil texture, soil organic carbon/matter, and soil structure. The objectives of this study were to classify and compare soil texture and IR for the A horizon across the 147 ha Cornell University Willsboro Research Farm using the Soil Survey Geographic (SSURGO) database and field-based measurements. Soil texture was the dominating factor to explain the general trend of Entisols > Inceptisols > Alfisols with regard to IR in the A horizon. In general, the variability in soil texture observed in field measurements was consistent with the variability reported in the SSURGO database, although the SSURGO representative values for soil texture did not completely match measured mean values for all soil map units. With the exception of one soil map unit, estimates of IR classes utilizing soil judging in the field criteria also were consistent when using either SSURGO or field-based data. Estimating infiltration rate classes for ecosystem services frameworks using geospatial analysis of field and/or SSURGO data can be enhanced with emerging technologies (e.g., sensors) and/or easily measured conventional soil properties.

Funding

This material is based upon work supported by NIFA/USDA, under projects: SC-1700452, and SC-1700462. Clemson University provided funding for this study through Technical Contribution number 6426 of the Clemson University Experiment Station.

Additional information

Funding

This material is based upon work supported by NIFA/USDA, under projects: SC-1700452, and SC-1700462. Clemson University provided funding for this study through Technical Contribution number 6426 of the Clemson University Experiment Station.

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