,A spreadsheet was designed for weighing lysimeter raw relative water storage data analysis and reduction to values of evapotranspiration, dew and frost accumulation, precipitation, irrigation, and drainage tank emptying. Algorithms in the spreadsheet automatically identify precipitation, and dew and frost accumulations in the 5-minute data, and places flags appropriately (“P” or “DW”) in a column that is referenced by formulae that separately calculate values for these. Noise can, however, cause false identification of precipitation or frost and dew accumulations, so another column is made available in which the user can enter flags to either nullify (“NO”) false automatic identification, or conversely, identify precipitation or dew and frost accumulations (“P” or “DW”) not automatically identified. This column also serves for entry of flags identifying irrigation, drainage tank emptying, counterweight adjustments, etc. Algorithms in other columns act upon these flags to correct the original raw relative storage values so that the adjusted relative storage reflects only evapotranspiration, while simultaneously computing 5-min values for precipitation, irrigation, dew and frost accumulation, and drainage tank emptying.,

,This dataset contains water balance data for each year when winter wheat was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Winter wheat was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field in the 1989-1990, 1991-1992, and 1992-1993 seasons. Irrigation was by linear move sprinkler system. Full irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Deficit irrigations were less than full - see crop calendars and irrigation data in these files for details. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <0.3% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on winter wheat ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield.,,

,This dataset contains water balance data for each year when alfalfa was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Alfalfa was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field in 1996 through 1999. Irrigation was by linear move sprinkler system. Irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <0.3% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), reference "tall crop" ET, crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on alfalfa ET, crop coefficients, crop water productivity reference "tall crop" ET, alternative methods of estimating reference ET from weather data. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield.,,

,This dataset contains water balance data for each year when soybean [Glycine max (L.) Merr.] was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Soybean [Glycine max (L.) Merr.] was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field in 1995, 2003, 2004 and 2010. Soybean was grown on four large, precision weighing lysimeters and their surrounding 4.4-ha fields in 2019. Irrigation in 1995, 2003, 2004, and 2010 was by linear move sprinkler system. Irrigation in 2019 was by subsurface drip irrigation (SDI) system on the northeast (NE) and southeast (SE) weighing lysimeters an fields, while irrigation was by linear move sprinkler system on the northwest (NW) and southwest (SW) lysimeters and fields. Full irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Deficit irrigations were less than full - see crop calendars and irrigation data in these files for details. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <0.3% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on crop ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield.,See the README for descriptions of each data file.,,

,This dataset contains water balance data for each year when sunflower was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Sunflower was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field in 2009 and 2011. Irrigation was by linear move sprinkler system. Full irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Deficit irrigations were less than full - see crop calendars and irrigation data in these files for details. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <0.3% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on sunflower ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield.,,

,This dataset contains water balance data for each growing season (year) when maize (Zea mays, L., also known as corn in the United States) was grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Maize was grown for grain on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field. Irrigation was by linear move sprinkler system in 1989, 1990, and 1994. In 2013, 2016, and 2018, maize was grown on four lysimeters; two lysimeters and their respective fields were irrigated using subsurface drip irrigation (SDI), and two lysimeters and their respective fields were irrigated by a linear move sprinkler system. Irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <1% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on maize ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used by the Agricultural Model Intercomparison and Improvement Project (AgMIP), by OPENET, and by many others for testing, and calibrating models of ET that use satellite and/or weather data.,Resources in this dataset:,,

,[NOTE - 2022-09-07: this dataset is superseded by an updated version https://doi.org/10.15482/USDA.ADC/1526433 ],This dataset consists of weather data for each year when maize was grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Maize was grown for grain on four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The four square fields are themselves arranged in a larger square with the fields in four adjacent quadrants of the larger square. Fields and lysimeters within each field are thus designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW). Irrigation was by linear move sprinkler system in 1989, 1990, and 1994. In 2013, 2016, and 2018, two lysimeters and their respective fields (NE and SE) were irrigated using subsurface drip irrigation (SDI), and two lysimeters and their respective fields (NW and SW) were irrigated by a linear move sprinkler system. Irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. The weather data include solar irradiance, barometric pressure, air temperature and relative humidity, and wind speed determined using sensors placed at 2-m height over a level, grass surface mowed to not exceed 12 cm height and irrigated and fertilized to maintain reference conditions as promulgated by ASCE (2005) and FAO (1996). Irrigation was by surface flood in 1989 through 1994, and by subsurface drip irrigation after 1994. Sensors were replicated and intercompared between replicates and with data from nearby weather stations, which were sometimes used for gap filling. Quality control and assurance methods are described by Evett et al. (2018). These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on maize ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used by the Agricultural Model Intercomparison and Improvement Project (AgMIP), by OPENET, and by many others for testing, and calibrating models of ET that use satellite and/or weather data.,Resources in this dataset:,,

Actual evapotranspiration (ETa) rates from the Operational Simplified Surface Energy Balance (SSEBop) method, before and after bias corrections (Sepúlveda, 2021), are presented for basins located wholly or partially within the Northwest Florida Water Management District (NWFWMD) and parts of Alabama and Georgia. The SSEBop annual rates are provided at about a one square-kilometer scale from 2000 to 2017. Annual ETa rates calculated from the application of the water-balance method (wbETa) to 5 basins in the NWFWMD and annual land-use ETa (luETa) rates calculated from monthly average crop coefficient ratios are also provided in this data set. A GIS shapefile provides land-use type and annual ETa rate for each year of record. Data are tabulated in spreadsheets for each basin and are referred to by the name between parenthesis: Lower Ochlockonee basin (Lower_Ochlockonee), Apalachicola – Chipola River basin (Apalachicola_Chipola), Lower Choctawhatchee River basin (Lower_Choctawhatchee), Yellow River basin (Yellow), and Escambia – Perdido River basin (Escambia_Perdido). Inflows and outflows from various sources in the water-balance equation used to calculate annual average wbETa rates for each basin are presented in this dataset.

Actual evapotranspiration (ETa) rates from the Operational Simplified Surface Energy Balance (SSEBop) method, before and after bias corrections (Sepúlveda, 2021), are presented for basins located wholly or partially within the Northwest Florida Water Management District (NWFWMD) and parts of Alabama and Georgia. The SSEBop annual rates are provided at about a one square-kilometer scale from 2000 to 2017. Annual ETa rates calculated from the application of the water-balance method (wbETa) to 5 basins in the NWFWMD and annual land-use ETa (luETa) rates calculated from monthly average crop coefficient ratios are also provided in this data set. A GIS shapefile provides land-use type and annual ETa rate for each year of record. Data are tabulated in spreadsheets for each basin and are referred to by the name between parenthesis: Lower Ochlockonee basin (Lower_Ochlockonee), Apalachicola – Chipola River basin (Apalachicola_Chipola), Lower Choctawhatchee River basin (Lower_Choctawhatchee), Yellow River basin (Yellow), and Escambia – Perdido River basin (Escambia_Perdido). Inflows and outflows from various sources in the water-balance equation used to calculate annual average wbETa rates for each basin are presented in this dataset.