ESTIMATING IRRIGATION ENHANCEMENT ACROSS THE CONUS

Irrigation applications are a common farming strategy for maximizing annual crop yields, yet farmers looking to introduce a new irrigation system do not have a reliable data source that estimates the yield increase expected when compared to dryland regimes. Irrigation use is also a notable stress on water systems, making the management of both food and water a challenge in agriculturally intensive areas. A comprehensive understanding of irrigation enhancement compared to dryland practices is needed to couple sustainable water use with increased food production. This study uses a dual end-member linear regression model to estimate yield enhancement for major row crops across the continental United States (CONUS). We constructed the model using both observed yield data and common drivers to crop production (e.g., seasonal precipitation, air temperature, soil characteristics, and geographic location). We then interpolated this county-level data to generate a spatially complete yield enhancement map. Irrigation enhancements across commodities identified general East-West trends, with little effect in the east to roughly doubling yields in the west. This data can be used to influence farmer decision making at the regional level and establish a baseline for food production and water use in agricultural systems.