104B Base Grants – Mapping the Spatial and Temporal Distribution or Cover Crops

Despite substantial investment in on-farm conservation, water quality impairment remains a persistent and complex problem. One promising development has been the increase in cover crop adoption nationally and within Indiana. However, we know very little about whether cover crop adoption is occurring where it will be most effective to improve water quality. Existing data on cover crop adoption are primarily available at the county level, which does not provide spatially relevant information to inform environmental outcomes at watershed scales. Remote sensing can help to address this gap by providing large-scale, longitudinal data on where cover crops are located. To date, remote sensing has been used infrequently to assess watershed-scale implementation of conservation practices, focusing instead on improving vegetation indices. While cover crop adoption continues to increase, adoption research has shown that farmers face a range of barriers that may lead to variable use or discontinued adoption. This variability means that watershed-scale analysis is needed to understand the large-scale and long-term effects that cover crops have had on water quality and what this portends for future adoption trends. Our proposed research combines remote sensing, hydrological modeling, and spatial and temporal statistical analysis to examine statewide trends on the extent and location of cover crops and their effect on water quality outcomes from 2000-2019. The proposed research would generate pixel-level raster data with a range of normalized difference vegetation index values to capture cover crop locations. Hot spot and monotonic trend statistical analysis would be used to identify where cover crops are clustered geographically and the continuity of cover crops over time. Vegetation index values would inform Agro-IBIS modeling of the agro-ecosystem to show the effect of cover crops on water quality along stream networks across Indiana.