Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack a ground-based monitoring network, remote sensing allows for accurate and consistent estimates of ETa across a large spatial extent – though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an Ensemble Mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (i.e., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. Four input ETa products (i.e., Nagler-ET(EVI2), SSEBop-LS, SSEBop-MOD, MODIS-ET) were used to develop the EMET product (see metadata Processing Steps 1 and 2).
This data release consists of a series of five zipped folders, of which each include a series of months of the EMET image product for the Los Planes basin in Baja California Sur, Mexico. We use the following naming convention to recognize the respective month for each image: "YYYY_MM" (i.e., 2006_01 for January 2006). The first zipped folder (i.e., EnsembleMeanETa_EMET_Monthly_2006_2021) contains the full suite of images for all months between January 2006 and December 2021 (n = 192 bands). The remaining four zipped folders contain monthly images for four-year periods within the data release to allow for the user to more easily download images for single years. The four periods follow: (1) 2006 through 2009, (2) 2010 through 2013, (3) 2014 through 2017, and (4) 2018 through 2021 (n = 48 bands each).
