Impacts of Pixel Scale and Phenology on the Satellite-Based Evaporative Stress Index (Invited Presentation)

The Evaporative Stress Index (ESI) quantifies temporal anomalies in a normalized evapotranspiration (ET) metric describing the ratio of actual-to-reference ET (fRET) as derived from satellite remote sensing data using a surface energy balance approach. Using high temporal resolution thermal infrared (TIR) inputs from geostationary satellites (at 3-10 km resolution), the ESI has demonstrated capacity to capture rapidly developing crop stress and impacts on regional yield variability in water-limited crop growing regions. However, ESI performance appears to be degraded in some regions where the vegetation cycle is compressed and intensively managed. Our hypothesis is that this localized degradation is related to 1) interannual shifts in crop phenology, and 2) strong sub-pixel landcover heterogeneity in at the geostationary pixel scale. The former will add noise to the anomaly computations, while the latter may dilute response in strong drought years. This hypothesis was tested by generating maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from moderate resolution satellite platforms with good temporal coverage and Landsat, which provides field-scale spatial detail. At this scale, pure pixels associated with specific crops can be isolated, and annual fRET curves can be aligned based on crop emergence date rather than calendar date. In comparison with standard ESI at 4 km resolution, results at 30 m show significant improvement in yield-ESI correlations for corn crops over a mixed rainfed/irrigated agricultural landscape in Nebraska. These ET modeling approaches will be used in the upcoming ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission to more broadly investigate variability in drought response and resilience across different agricultural landscapes.