Factsheet – Mapping the Spatial and Temporal Distribution of Cover Crops to Model Water Quality Outcomes
A research project funded by the Indiana Water Resources Research Center through the U.S. Geological Survey’s 104B annual base grants (section 104 of the Water Resources Research Act of 1984, as amended).
Start Date: 2020-03-01
End Date: 2021-12-31
Total Federal Funds: $14,966
Total Non-Federal Funds: $69,389
More than 40% of Indiana rivers and lakes are impaired, while Indiana also contributes substantially to harmful algal blooms in Lake Erie and the Gulf of Mexico “dead zone.” Indiana’s 56,000 farms earned over $10 billion in cash receipts in 2017, contributing substantially to the state’s economy. At the same time, agriculture remains the leading source of water quality impairment. Cover crops represent a potentially critical win-win effort to reduce nutrient and soil losses from farming while also increasing the farm resiliency through healthier soils. Both private and public sectors in Indiana recognize this crucial challenge and have catalyzed efforts to restore state waters. The Indiana Conservation Partnership, comprised of federal and state agencies, has been active in coordinating and leading efforts to increase cover crop adoption across the state, such as through the Conservation Cropping Systems Initiative. Cover crop adoption has increased from 200,000 to 1 million acres statewide over the past decade, making Indiana a national leader. Despite these positive developments, we know very little about whether cover crop adoption is occurring where it will be most effective to improve water quality. This research combined remote sensing, hydrological modeling, and spatial and temporal statistical analysis to identify past trends that can inform outreach efforts and complement existing research to model the environmental effects of on-farm conservation practices.
Research Objectives
To understand the current and potential impact of cover crops on water quality, this research combined remote sensing, agro-ecosystem modeling, and spatial and longitudinal statistical analysis to provide a detailed picture of their extent and location across Indiana.
1. Remote Sensing—use of in-hand transect data of cover crops for five Indiana counties to create a set of more than 100 cover crop polygons to be incorporated into remote sensing computations to train and validate Normalized Difference Vegetation Index (NDVI) values to classify bare soils and living vegetation.
2. Agro-ecosystem Modeling—results from the remote sensing computations were incorporated into an agro-IBIS hydrological model to generate water quality outcomes over the past 20 years.
3. Spatial and longitudinal statistical analysis—spatial statistical analysis of cover crops was conducted to identify if they are co-located with hot spots of nutrient losses predicted by the model.
Counties in Indiana with cover crop/tillage survey data, overlain on winter Normalized Difference Vegetation Index from MODIS. Colors indicate the percentage of GPS points with fall cover crops in 2015 (out of all GPS points) per county.
Researcher Profile
Major Conclusions & Significance
This project resulted in the development of two modeling approaches to be integrated to show patterns in cover crop adoption at different spatial and temporal resolutions.
- The first modeling approach focused on remote sensing of cover crops, in which a new model using random-forest classification was developed with high accuracy for cover crops, conservation tillage, and conventional tillage land covers for several counties in Indiana. Following this, we attempted to replicate these findings for the entire state of Indiana but were unable to achieve generalizability in predicting these land covers for all counties. Some counties continued to achieve high accuracy, while others did not.
- The second modeling approach forecasted water quality outcomes resulting from cover crop presence at large scales using Agro-IBIS modeling to simulate potential ecosystem benefits of cover crops, such as nitrate loss reduction, carbon sequestration, etc. Our model results indicated that cover crops reduced nitrate leaching and increased total soil carbon in space and time, but also forecasted minimal changes to surface runoff or evapotranspiration.
What Does This Mean For Indiana?
