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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #392091
Research Project: Linkages Between Crop Production Management and Sustainability in the Central Mississippi River Basin

Location: Cropping Systems and Water Quality Research

Title: Precipitation influence on the soil vulnerability index classification

Author
item THOMPSON, ALLEN - University Of Missouri
item Baffaut, Claire
item PHUNG, QUANG - University Of Missouri

Submitted to: Soil and Water Conservation Society International Annual Conference
Publication Type: Abstract Only
Publication Acceptance Date: 2/16/2022
Publication Date: 7/31/2022
Citation: Thompson, A., Baffaut, C., Phung, Q. 2022. Precipitation influence on the soil vulnerability index classification [abstract]. 77th Soil and Water Conservation Society International Annual Conference, July 31-August 3, 2022, Denver, Colorado. p. 124.

Interpretive Summary:

Technical Abstract: The Soil Vulnerability Index (SVI) developed by NRCS uses available inputs from the SSURGO database to classify agricultural land into four levels of vulnerability to sediment and nutrient losses: low, moderate, moderately high, and high. Soil properties considered in the classification include hydrologic soil group, soil erodibility, slope, organic or mineral soil, drainage class, and soil parent material. Improvements in assigning vulnerability classification by including rainfall amount and intensity have been suggested, including the R-factor of the Universal Soil Loss Equation which is used to describe the combined effects of rainfall amount and intensity on sheet and rill erosion. The objective of this research was to evaluate rainfall characteristics on the runoff and sediment yield component of SVI, with the goal to improve SVI vulnerability classification. The study simulated sediment yields using calibrated models developed with the Soil and Water Assessment Tool (SWAT) or the Agricultural Non-Point Source Pollution Model (AnnAGNPS). These models represented four Conservation Effects Assessment Project (CEAP) watersheds having a range of physiographic and hydrologic characteristics. Sediment yields were simulated using precipitation data from 1985 to 2014 from 14 different CEAP watersheds having a range in precipitation characteristics. Classification based on simulated sediment yields were evaluated across a range of landscape slopes. Results indicate that classification can shift to more or less vulnerability due to differing precipitation characteristics of rainfall intensity and R-factor, and this shift is more pronounced for steeper slopes. Possible modifications in the SVI classification rule-set to account for these differences will be discussed.