Assessment of the Soil Vulnerability Index and comparison with AnnAGNPS in two Lower Mississippi River Basin watersheds

Authors: Witthaus, Lindsey; LOHANI, SAPANA - University Of Nevada; Bingner, Ronald - Ron; Locke, Martin; Baffaut, Claire; THOMPSON, ALLEN - University Of Missouri

Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/8/2019
Publication Date: 1/15/2020
Citation: Yasarer, L.M., Lohani, S., Bingner, R.L., Locke, M.A., Baffaut, C., Thompson, A.L. 2019. Assessment of the Soil Vulnerability Index and comparison with AnnAGNPS in two Lower Mississippi River Basin watersheds. Journal of Soil and Water Conservation. 75(1):53-61. https://doi.org/10.2489/jswc.75.1.53.
DOI: https://doi.org/10.2489/jswc.75.1.53

Interpretive Summary: Agricultural producers and conservation practitioners require quick tools and indices to determine vulnerable agricultural land that would be best served by conservation investments. Geographic information systems (GIS) technology and widespread availability of spatial data has made GIS-based tools ideal for identifying areas that potentially contribute high loads of non-point source pollution. However, these tools need to be tested for accuracy in a variety of agricultural systems. The Soil Vulnerability Index (SVI) is a GIS-based tool that uses limited data to estimate runoff and leaching vulnerability. The SVI was tested in Beasley Lake and Goodwin Creek watersheds and results were compared with long-term land use histories, aerial imagery, and results from a watershed model, the Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model. The SVI tool correctly identified vulnerable areas that matched with land that had been removed from production and land that was visibly degraded in aerial images. The SVI categories and corresponding AnnAGNPS-predicted sediment yield also had moderate agreement, with 41% and 60% of watershed area in agreement in Beasley Lake and Goodwin Creek watersheds, respectively. In general, the tool is a quick way to assess spatial areas potentially contributing to non-point source pollution, which can then be combined with field-based knowledge and/or imagery to provide valuable insight for conservation practice placement.

Technical Abstract: There is an increasing need to quickly and accurately identify areas where agricultural conservation practices can provide the greatest reduction in nutrient and sediment runoff. Geographic information systems (GIS)-based tools and indices are promising for identifying critical areas that are significant contributors of non-point source pollution loads with limited data. One such tool is tested here, the Soil Vulnerability Index (SVI), in the Beasley Lake and Goodwin Creek watersheds in Mississippi. The SVI runoff component results are compared against aerial images and long-term land use histories in the watershed to determine if a higher SVI score is related to visibly degraded land or land removed from cultivation. SVI results are also compared to sediment-yield estimates generated with the Annualized Agricultural Non-Point Source pollution model (AnnAGNPS) to determine the degree of agreement. The SVI Runoff score demonstrated agreement with imagery and land-use histories in both watersheds. The SVI categories and corresponding AnnAGNPS-predicted sediment yield also had moderate agreement, with 42% and 61% of watershed area in agreement in Beasley Lake and Goodwin Creek watersheds, respectively. In general, the tool is a quick way to assess spatial areas potentially contributing to non-point source pollution, which can then be combined with field-based knowledge and/or imagery to provide valuable insight for conservation practice placement.