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

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 nonpoint source pollution loads with limited data. One such tool, the Soil Vulnerability Index (SVI), is tested here in 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 45% and 68% 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 nonpoint source pollution, which can then be combined with field-based knowledge and/or imagery to provide valuable insight for placement of conservation practices.