Historical (1984-2014) Landsat-based ET maps were generated for Palo Verde Irrigation District (PVID) and eight other sub-basins in parts of Middle and Lower Central Valley, California. A total of 3,396 Landsat images were processed using the Operational Simplified Surface Energy balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study areas over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively strong association between SSEBop ET and validation datasets. Historical trend analysis of seven agro-hydrologic variables were done using the Seasonal Mann-Kendall test.

The associated geotiff rasters represents the total actual evapotranspiration (ETa) from June through September for the years 2004, 2006, 2008-2010, and 2013-2016 for the entire Klamath Basin in southern Oregon. The ETa was created using Landsat imagery and the Operational Simplified Surface Energy Balance (SSEBop) model to estimate actual ET and the Python scripts to complete that process is also provided. Additionally, the June-September average (mean) ETa for the "base years" of 2004, 2006, 2008-2010 and ETa Anomaly (deviation from the base years average mean) for each year between 2013-2016 is provided. Text files of SSEBop daily actual ET along with actual ET from Ameriflux eddy co-variance flux tower sites is also provided including an R code to generate comparison charts.

The associated geotiff rasters represents the total actual evapotranspiration (ETa) from June through September for the years 2004, 2006, 2008-2010, and 2013-2016 for the entire Klamath Basin in southern Oregon. The ETa was created using Landsat imagery and the Operational Simplified Surface Energy Balance (SSEBop) model to estimate actual ET and the Python scripts to complete that process is also provided. Additionally, the June-September average (mean) ETa for the "base years" of 2004, 2006, 2008-2010 and ETa Anomaly (deviation from the base years average mean) for each year between 2013-2016 is provided. Text files of SSEBop daily actual ET along with actual ET from Ameriflux eddy co-variance flux tower sites is also provided including an R code to generate comparison charts.

CONUS-wide actual ET (ETa) from Landsat thermal imagery-using the Operational Simplified Surface Energy Balance (SSEBop) model (version 4) in the Google Earth Engine (GEE) cloud computing platform. Over 150,000 Landsat satellite images were used to produce 10 years of annual ETa (2010-2019).

CONUS-wide actual ET (ETa) from Landsat thermal imagery-using the Operational Simplified Surface Energy Balance (SSEBop) model (version 4) in the Google Earth Engine (GEE) cloud computing platform. Over 150,000 Landsat satellite images were used to produce 10 years of annual ETa (2010-2019).

Understanding how different crops use water over time is essential for planning and managing water allocation, water rights, and agricultural production. The main objective of this paper is to characterize the spatiotemporal dynamics of crop water use in the Central Valley of California using Landsat-based annual actual evapotranspiration (ETa) from 2008-2018 derived from the Operational Simplified Surface Energy Balance (SSEBop) model. Crop water use for ten crops are characterized at multiple scales. The Mann-Kendall trend analysis revealed a significant increase in area cultivated with almonds and their water use, with an annual rate of change of 16,327 hectares in area and 13,488 ha-m in water use. Conversely, alfalfa showed a significant decline with 12,429 ha in area and 13,901 ha-m in water use per year during the same period. A pixel-based Mann-Kendall trend analysis showed the changing crop type and water use at the level of individual fields for all of Kern County in the Central Valley. This study demonstrates the useful application of historical Landsat ET to produce relevant water management information. Similar studies can be conducted at regional and global scales to understand and quantify the relationships between land cover change and its impact on water use.

Understanding how different crops use water over time is essential for planning and managing water allocation, water rights, and agricultural production. The main objective of this paper is to characterize the spatiotemporal dynamics of crop water use in the Central Valley of California using Landsat-based annual actual evapotranspiration (ETa) from 2008-2018 derived from the Operational Simplified Surface Energy Balance (SSEBop) model. Crop water use for ten crops are characterized at multiple scales. The Mann-Kendall trend analysis revealed a significant increase in area cultivated with almonds and their water use, with an annual rate of change of 16,327 hectares in area and 13,488 ha-m in water use. Conversely, alfalfa showed a significant decline with 12,429 ha in area and 13,901 ha-m in water use per year during the same period. A pixel-based Mann-Kendall trend analysis showed the changing crop type and water use at the level of individual fields for all of Kern County in the Central Valley. This study demonstrates the useful application of historical Landsat ET to produce relevant water management information. Similar studies can be conducted at regional and global scales to understand and quantify the relationships between land cover change and its impact on water use.

,The Southern Great Plains 1997 (SGP97) Hydrology Experiment originated from an interdisciplinary investigation, "Soil Moisture Mapping at Satellite Temporal and Spatial Scales" (PI: Thomas J. Jackson, USDA Agricultural Research Service, Beltsville, MD) selected under the NASA Research Announcement 95-MTPE-03. The core of the 1997 experiment involves the deployment of the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) for daily mapping of surface soil moisture. The region selected for investigation is the best instrumented site for surface soil moisture, hydrology and meteorology in the world. This includes the USDA/ARS Little Washita Watershed, the USDA/ARS facility at El Reno, Oklahoma, the ARM/CART central facility, as well as the Oklahoma Mesonet. The temporal coverage for this dataset is as follows: Begin datetime: 1995-10-01 00:00:00, End datetime: 2001-03-31 23:59:59. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Soil Water Retention Data Set is one of the various sub-surface data sets developed for the ARM/GCIP (Global Energy and Water Cycle Experiment (GEWEX) Continental-scale International Project) 1996 Near-Surface Observation (NESOB-96) Data Set. This data set contains a table for each of the ARM SWATS (Soil Water and Temperature System) sites at the SGP site containing the observed soil water retention data as obtained from laboratory tests using pressure plates and hanging columns. The soil characterizations were perfomed by Oklahoma State University.,

,The Southern Great Plains 1997 (SGP97) Hydrology Experiment originated from an interdisciplinary investigation, "Soil Moisture Mapping at Satellite Temporal and Spatial Scales" (PI: Thomas J. Jackson, USDA Agricultural Research Service, Beltsville, MD) selected under the NASA Research Announcement 95-MTPE-03. The region selected for investigation is the best instrumented site for surface soil moisture, hydrology and meteorology in the world. This includes the USDA/ARS Little Washita Watershed, the USDA/ARS facility at El Reno, Oklahoma, the ARM/CART central facility, as well as the Oklahoma Mesonet. The High Plains Climate Network (HPCN) dataset is one of various datasets provided for the Southern Great Plains 1997 (SGP97) project. This dataset contains HPCN data from 15 stations in the SGP97 domain. This dataset covers the complete SGP97 time period (18 June 1997 through 18 July 1997) and for the SGP97 domain. The SGP97 domain is approximately 97W to 99W longitude and 34.5N to 37N latitude. The HPCN dataset contains different parameters depending upon the reporting station. Each station provides Station Name, State, and Identification Number preceding that station's data within the dataset. Each parameter column has a self explanatory title indicating the data available for that station and parameter units.,

Remote sensing-based evapotranspiration (ET) can be derived using various methods, from soil moisture accounting to vegetation-index based approaches to simple and complex surface energy balance techniques. Due to the complexity of fully representing and parameterizing ET sub-processes, different models tend to diverge in their estimations. However, most models appear to provide reasonable estimations that can meet user requirements for seasonal water use estimation and drought monitoring. One such model is the Operational Simplified Surface Energy Balance (SSEBop). This study presents a formulation of the SSEBop model using the psychrometric principle for vapor pressure/relative humidity measurements where the “dry-bulb” and “wet-bulb” equivalent readings can be obtained from satellite-based land surface temperature estimates.