Estimation of Evapotranspiration from Fields with and without Cover Crops Using Remote Sensing and in situ Methods

Abstract: Estimation of actual evapotranspiration (ET_a) based on remotely sensed imagery is very valuable in agricultural regions where ET_a rates can vary greatly from field to field. This research utilizes the image processing model METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) to estimate late season, post-harvest ET_a rates from fields with a cover crop planted after a cash crop (in this case, a rye/radish/pea mixture planted after spring wheat). Remotely sensed ET_oF (unit-less fraction of grass-based reference ET, ET_o) maps were generated using Erdas Imagine software for a 260 km² area in northeastern South Dakota, USA. Meteorological information was obtained from a Bowen-Ratio Energy Balance System (BREBS) located within the image. Nine image dates were used for the growing season, from May through October. Five of those nine were captured during the cover crop season. METRIC was found to successfully differentiate between fields with and without cover crops. In a blind comparison, METRIC compared favorably with the estimated ET_a rates found using the BREBS (ET_λE), with a difference in total estimated ET_a for the cover crop season of 7%.