While forest evapotranspiration (ET) dynamics in the Amazon have been studied both as point estimates using flux towers, as well as spatially coarse surfaces using satellite data, higher resolution (e.g., 30 m resolution) ET estimates are necessary to address finer spatial variability associated with forest biophysical characteristics and their changes by natural and human impacts. The objective of this study is to evaluate the potential of the Landsat-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model to estimate high-resolution (30 m) forest ET by comparing to flux tower ET (FT ET) data collected over seasonally dry tropical forests in Rondônia, the southwestern region of the Amazon. Analyses were conducted at daily, monthly and seasonal scales for the dry seasons (June–September for Rondônia) of 2000–2002. Overall daily ET comparison between FT ET and METRIC ET across the study site showed r² = 0.67 with RMSE = 0.81 mm. For seasonal ET comparison, METRIC-derived ET estimates showed an agreement with FT ET measurements during the dry season of r² >0.70 and %MAE <15%. We also discuss some challenges and potential applications of METRIC for Amazonian forests.

Although seasonal and temporal variations in evapotranspiration (ET) in Amazonia have been studied based upon flux-tower data and coarse resolution satellite-based models, ET dynamics over human-impacted landscapes are highly uncertain in this region. In this study, we estimate ET rates from critical land cover types over highly fragmented landscapes in the southern Amazon and characterize the ET dynamics during the dry season using the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC, a Landsat-based ET model, that generates spatially continuous ET estimates at a 30 m spatial resolution widely used for agricultural applications, was adapted to the southern Amazon by using the NDVI indexed reference ET fraction (ET_rF) approach. Compared to flux tower-based ET rates, this approach showed an improved performance on the forest ET estimation over the standard METRIC approach, with R² = 0.73 from R² = 0.70 and RMSE reduced from 0.77 mm/day to 0.35 mm/day. We used this approach integrated into the METRIC procedure to estimate ET rates from primary, regenerated, and degraded forests and pasture in Acre, Rondônia, and Mato Grosso, all located in the southern Amazon, during the dry season in 2009. The lowest ET rates occurred in Mato Grosso, the driest region. Acre and Rondônia, both located in the southwestern Amazon, had similar ET rates for all land cover types. Dry season ET rates between primary forest and regenerated forest were similar (p > 0.05) in all sites, ranging between 2.5 and 3.4 mm/day for both forest cover types in the three sites. ET rates from degraded forest in Mato Grosso were significantly lower (p < 0.05) compared to the other forest cover types, with a value of 2.03 mm/day on average. Pasture showed the lowest ET rates during the dry season at all study sites, with the dry season average ET varying from 1.7 mm/day in Mato Grosso to 2.8 mm/day in Acre.

Agricultural subsurface drainage changes the field hydrology and potentially the amount of water available to the crop by altering the flow path and the rate and timing of water removal. Evapotranspiration (ET) is normally among the largest components of the field water budget, and the changes in ET from the introduction of subsurface drainage are likely to have a greater influence on the overall water yield (surface runoff plus subsurface drainage) from subsurface drained (TD) fields compared to fields without subsurface drainage (UD). To test this hypothesis, we examined the impact of subsurface drainage on ET at two sites located in the Upper Midwest (North Dakota-Site 1 and South Dakota-Site 2) using the Landsat imagery-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. Site 1 was planted with corn (Zea mays L.) and soybean (Glycine max L.) during the 2009 and 2010 growing seasons, respectively. Site 2 was planted with corn for the 2013 growing season. During the corn growing seasons (2009 and 2013), differences between the total ET from TD and UD fields were less than 5 mm. For the soybean year (2010), ET from the UD field was 10% (53 mm) greater than that from the TD field. During the peak ET period from June to September for all study years, ET differences from TD and UD fields were within 15 mm ( 0.05) and showed no consistent relationship.

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%.