A s part of development of a regional source water protection plan, in 2015–2016, the New Mexico Bureau of Geology and Mineral Resources performed a technical review of existing hydrogeology studies in Curry and Roosevelt counties in east-central New Mexico. Additionally, groundwater quality was tested in several wells, and groundwater levels were examined to provide up-to-date information on the availability of groundwater in the region. This report describes the results of the hydrogeologic review and findings from the groundwater study.

The AQUASTAT portal enables users to access the core database of country statistics, focused on water resources, water uses and agricultural water management. Along with it, other water information in the form of complementary databases, such as the irrigated crop calendars and the sub-national irrigation areas databases, the detailed database on dams and reservoirs and the water-and agriculture-related institutions database are available. The glossary is also an important component of AQUASTAT, offering multilingual definitions of 500+ water-related terms and key indicators, including detailed reference sources and links to related terms.

This dataset was created under a sub grant agreement with the NM Department of Homeland Security and Emergency Management (DHSEM) by the Earth Data Analysis Center (EDAC) at the University of New Mexico. It was created by combining multiple data sources including USGS NHD, existing linework from the NM Office of the State Engineer, Aerial image and DEM digitizing, and contributions from local irrigation districts. Project began early 2017 and ended October 2019.

https://www.reacchpna.org/sites/default/files/AR3_1.2.pdf Pixel classification: Classification, Stable, Dynamic, Unstable Urban, 1, 101, 202 Rangeland, 3, 103, 203 Forest, 4, 104, 204 Water, 5, 105, 205 Wetlands, 6, 106, 206 Barren, 7, 107, 207 Wilderness, 9, 109, 209 Annual, 11, 111, 211 Transition, 12, 112, 212 Grain-fallow, 13, 113, 213 Irrigated, 14, 114, 214 Orchard, 15, 115, 215 Agriculture, 50, 150, 250 Water and Other, 51, 151, 251

This dataset consists of agronomic calendars for each growing season (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. A crop calendar for each season lists by date the pertinent agronomic and maintenance operations (e.g., planting, thinning, fertilization, pesticide application, lysimeter maintenance, harvest). For each year there is a crop calendar for the two east lysimeters (NE and SE) and another calendar for the two west lysimeters (NW and SW). 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: Resource Title: 1989 Bushland, TX, east maize agronomic calendar. File Name: 1989_East_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 1990 Bushland, TX, east maize agronomic calendar. File Name: 1990_East_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 1994 Bushland, TX, east maize agronomic calendar. File Name: 1994_East_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 1994 Bushland, TX, west maize agronomic calendar. File Name: 1994_West_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2013 Bushland, TX, east maize agronomic calendar. File Name: 2013_East_Maize-Calendar.xlsx. Resource Description: This agronomic calendar lists agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2013 Bushland, TX, west maize agronomic calendar. File Name: 2013_West_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2018 Bushland, TX, west maize agronomic calendar. File Name: 2018_West_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2018 Bushland, TX, east maize agronomic calendar. File Name: 2018_East_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2016 Bushland, TX, west maize agronomic calendar. File Name: 2016_West_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units. Resource Title: 2016 Bushland, TX, east maize agronomic calendar. File Name: 2016_East_Maize_Calendar.xlsx. Resource Description: This agronomic calendar lists by date the agronomic operations on the Bushland, TX, large weighing lysimeters and surrounding fields, including tillage, planting, fertilization, pesticide application, furrow diking, irrigations, etc., and also sensor installation, sensor reading that might disturb lysimeter operation (neutron probe readings), maintenance operations such as emptying drainage tanks, adjusting lysimeter scale counterweights, electronic and electrical maintenance, etc. Amounts and kinds of fertilizer and pesticide applications are given with proper chemical names and SI units.

This database contains climatic, hydrologic, water quality and biological information for the Lake Beysehir catchment, Turkey. The dataset includes meteorological data (precipitation, air temperature, wind speed, solar radiation, relative humidity), discharges for the main inflows and lake outflow, lake water level, water chemistry data for inflows and lake. In addition, lake biological data (phytoplankton, zooplankton, fish and macrophyte) is avaiable. Data was compiled during the METU-DPT-TEAB project, EU-FP7 REFRESH project and EU-FP7 MARS project . More information on this dataset can be found in the Freshwater Metadatabase - MARS_09 (http://www.freshwatermetadata.eu/metadb/bf_mdb_view.php?entryID=MARS_09).

Carlsbad Irrigation District links and information

Dropping Ogallala aquifer levels and changing commodity prices and energy costs make irrigation management an important but uncertain issue to west Texas cotton producers. For example, is deficit or full irrigation more profitable under the current lint price and pumping cost conditions? Also, what is the best way to divide production into dryland and irrigated acreage with limited well capacity? To help producers answer these questions this web application estimates the effects of irrigation on the profitability of center pivot cotton production on the Southern High Plains. It's main purpose is to show the impact of irrigation on yield and the related effects on both profits per acre and profits over a center pivot area with combined dryland and irrigated production.

Groundwater quality and quantity monitoring sites in the Elephant Butte Irrigation District.

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 growing season (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 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.

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 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 site presents results of IWMI's first attempt to map global irrigated and rainfed croplands for the nominal year of 2000 using satellite images. The products include 10 km irrigated and rainfed cropland and a LULC map for the globe, 500 meter irrigated area map for South Asia, and 30 meter irrigated area maps for Syr Darya River Basin in Central Asia and Krishna River Basin in India. The maps contain various levels of information including irrigation water sources (surface, groundwater), cropping intensity (single, double, continuous) and dominant crop types.

This site presents results of IWMI's first attempt to map global irrigated and rainfed croplands for the nominal year of 2000 using satellite images. The products include 10 km irrigated and rainfed cropland and a LULC map for the globe, 500 meter irrigated area map for South Asia, and 30 meter irrigated area maps for Syr Darya River Basin in Central Asia and Krishna River Basin in India. The maps contain various levels of information including irrigation water sources (surface, groundwater), cropping intensity (single, double, continuous) and dominant crop types.

GMIA shows the amount of area equipped for irrigation around the year 2005 in percentage of the total area on a raster with a spatial resolution of 5 arc-minutes (about 10 km at the equator). Additional map layers show the percentage of the area equipped for irrigation that was actually used for irrigation and the percentages of the area equipped for irrigation that was irrigated with groundwater, surface water or non-conventional sources of water. The data layer on area equipped for irrigation was developed by combining sub-national irrigation statistics with geospatial information on the position and extent of irrigation schemes to compute the irrigation density (fraction of 5 arc-minute cells equipped for irrigation). The information for the additional layers on area actually irrigated or on the water source for irrigation was derived from statistical survey data (e.g. census reports) only, therefore the accuracy at pixel level is limited. GIS users can import the map as either ASCII grids or as shape files.

The Water Data Portal (WDP), following ""one-stop shop"" approach, provides access to a large amount of data related to water and agriculture. WDP contains meteorological, hydrological, socio-economic, spatial data layer, satellite images as well as hydrological model setups. The data in the WDP, both spatial & non-spatial, are supported by the standardized metadata and are available for download by user including academia, scientists, researchers and decision makers. However, access is provided in compliance with copyrights, intellectual property rights and data agreements with our partners. Data products include Global Environmental Flow Information System, Global Drought Patterns, Global Irrigated Area Mapping, Flow Management Classes, and regional data on Irrigated Area (Asia and Africa), Glacier and Snow (Asia), Flood Risk Mapping (East Asia) (South East Asia), Flood Risk Mapping (Nigeria), Water Resources Management (Eastern Ganges), Climate Change vulnerability (Nepal), Water Quality Mapping (Sri Lanka), Kabul River Basin Geodatabase, Tana River Basin Information System. The Portal also links to the IWMI Irrigation Benchmarking Service, providing data on irrigation system performance (service delivery, financial, agricultural, environmental, gender) based on voluntary submissions from irrigation schemes across the world.

Note: Updates to this data product are discontinued. This data product summarizes the farm-structural characteristics for irrigated farms in each of the 50 States, the 17 Western States (aggregated) and the Nation as a whole, based on USDA's 2013 Farm and Ranch Irrigation Survey (FRIS). (See the Documentation for data sources and methods.) The tables are grouped into three sections of sets of tables. Section I covers all irrigated farms; sets of tables are grouped into 18 broad categories, ranging from total irrigation values to higher efficiency irrigation, to irrigated farms receiving technical/financial assistance designed to encourage onfarm water and energy conservation. Sets of tables in Section II cover all irrigated horticulture farms, and tables in Section III cover irrigated horticulture under protection (HUP) farms. All tables identify specific irrigation characteristics for four farm-size classes, by State and region. The list of tables in each set is found in the first tab of each Excel workbook. A previous release of this data product—which summarized the farm-structural characteristics for irrigated farms in the 17 Western States based on USDA's 2008 and 1998 Farm and Ranch Irrigation Surveys—is available in a zipped archive file.

Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn. Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields. The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019. Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform.

Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn. Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields. The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019. Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform. The mobile version of the app can be downloaded at https://irrigatorpro.org

Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn. Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields. The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019. Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform. The mobile version of the app can be downloaded at https://irrigatorpro.org

Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn. Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields. The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019. Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform. The mobile version of the app can be downloaded at https://irrigatorpro.org

NVND Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Sidney, Montana Management practices, such as irrigation, tillage, cropping system, and N fertilization, may influence soil greenhouse gas (GHG) emissions. We quantified the effects of irrigation, tillage, crop rotation, and N fertilization on soil CO2, N2O, and CH4 emissions from March to November, 2008 to 2011 in a Lihen sandy loam in western North Dakota. Treatments were two irrigation practices (irrigated and non-irrigated) and five cropping systems (conventional-tilled malt barley [Hordeum vulgaris L.] with N fertilizer [CTBFN], conventional-tilled malt barley with no N fertilizer [CTBON], no-tilled malt barley-pea [Pisum sativum L.] with N fertilizer [NTB-PN], no-tilled malt barley with N fertilizer [NTBFN], and no-tilled malt barley with no N fertilizer [NTBON]). The GHG fluxes varied with date of sampling while peaking immediately after precipitation, irrigation, and/or N fertilization events during increased soil temperature. Both CO2 and N2O fluxes were greater in CTBFN under the irrigated condition but CH4 uptake was greater in NTB-PN under the non-irrigated condition than in other treatments. While tillage and N fertilization increased CO2 and N2O fluxes by 8 to 30%, N fertilization and monocropping reduced CH4 uptake by 39 to 40%. The NTB-PN, regardless of irrigation, might mitigate GHG emissions by reducing CO2 and N2O emissions and increasing CH4 uptake relative to other treatments. To account for global warming potential for such a practice, information on productions associated with CO2 emissions along with N2O and CH4 fluxes are needed.

Nitrogen Source Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Fort Collins, Colorado Nitrogen fertilization is essential for optimizing crop yields; however, it increases N2O emissions. The study objective was to compare N2O emissions resulting from application of commercially available enhanced-effi ciency N fertilizers with emissions from conventional dry granular urea in irrigated cropping systems. These emissions were monitored from several irrigated cropping systems receiving N fertilizer rates ranging from 0-246 kg/ha from years 2007-2008 with intermediate rates of 157 kg/ha applied to the barley crop in corn-barley rotation and 56 kg/ha applied to the dry bens in the corn-dry bean rotation. Cropping systems included conventional-till continuous corn (CT-CC), no-till continuous corn (NT-CC), no-till corn–dry bean (NT-CDb), and no-till corn–barley (NT-CB). Nitrous oxide fluxes were measured during ten growing seasons using static, vented chambers and a gas chromatograph analyzer. This work shows that the use of no-till and enhanced-effi ciency N fertilizers can potentially reduce N2O emissions from irrigated systems.

A range of data for the Orange-Senqu basin, including narrative and numerical data covering rainfall, evaporation, radiation, soil type, groundwater recharge, yield, groundwater quality, dam infrastructure, surface water flows, surface water quality, flood, irrigation, urban water supply. The database can be searched by category or keywork, and will produce particular studies, with coverage of particular regions or the whole basin. Where data is available, it will be linked within the study pages, and provided either in pdf, xls, or GIS-compatable formats.

Organic Amendment Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network and Nutrient Use and Outcome Network in Fort Collins, Colorado Dairy manure is commonly used in place of inorganic N fertilizers but the impacts on trace gas flux, yields and soil N are not well understood in the semiarid western US. CO2, N2O, and CH4 were monitored using surface chamnbers from 5 N treatments to determine their effect on greenhouse gas emissions from a tilled clay loam soil under irrigated, continuous corn production for a 3 yr. time period. Treatments included (i) partially composed dairy manure (DM) (412 kg N ha -1), (ii) DM + AgrotainPlus (DM + AP), (iii) enhanced efficiency N fertilizer (SuperU, or SUPRU) (179 kg N ha-1), (iv) Urea (179 kg N ha-1), and (v) check. These results highlight the importance of best-managemnet practices such as immediate irrigation after N application and use of urease and nitrification inhibitors to minimize N losses.

The Pecos Valley Artesian Conservancy District (PVACD) website for water level reports, graphs and more.

Quick Stats is the National Agricultural Statistics Service's (NASS) online, self-service tool to access complete results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

REAP Study for Resilient Economic Agricultural Practices in West Lafayette, Indiana Corn stover is an important livestock feed and will probably be a major source of renewable bioenergy, especially in the U.S. Corn Belt. Overly aggressive removal of stover, however, could lead to greater soil erosion and hurt producer yields in the long-run. Good residue management practices could help prevent erosion of valuable topsoil by wind and water while still providing a revenue source for producers, either as livestock feed or for use in renewable bioenergy. Plant residues also contribute to soil structure, nutrient cycling, and help sustain the soil microbiota. Good residue management could also help control the loss of greenhouse gases from agricultural soils that could add to already increasing levels of atmospheric greenhouse gases contributing to global climate change. Cumulative GHG emissions varied widely across locations, by management, and from year-to-year. Despite this high variability, maximum stover removal averaged across all sites, years, and management resulted in lower total emissions of CO2 (-12 ± 11%) and N2O (-13 ± 28%) compared to no stover removal. Decreases in total CO2 and N2O emissions in stover removal treatments were attributed to decreased availability of stover-derived C and N inputs into soils, as well as possible microclimatic differences. Soils at all sites were CH4 neutral or small CH4 sinks. Exceptions to these trends occurred for all GHGs, highlighting the importance of site-specific management and environmental conditions on GHG fluxes in agricultural soils.

[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: Resource Title: 1989 Bushland, TX, standard 15-minute weather data. File Name: 1989_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: The weather data are presented as 15-minute mean values of solar irradiance, air temperature, relative humidity, wind speed, and barometric pressure; and as 15-minute totals of precipitation (rain and snow). Daily total precipitation as determined by mass balance at each of the four large, precision weighing lysimeters is given in a separate tab along with the mean daily value of precipitation. Data dictionaries are in separate tabs with names corresponding to those of tabs containing data. A separate tab contains a visualization tool for missing data. Another tab contains a visualization tool for the weather data in five-day increments of the 15-minute data. An Introduction tab explains the other tabs, lists the authors, explains data time conventions, explains symbols, lists the sensors, and datalogging systems used, and gives geographic coordinates of sensing locations. Resource Title: 1990 Bushland, TX, standard 15-minute weather data. File Name: 1990_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1990. Resource Title: 1994 Bushland, TX, standard 15-minute weather data. File Name: 1994_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1994. Resource Title: 2013 Bushland, TX, standard 15-minute weather data. File Name: 2013_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2013. Resource Title: 2016 Bushland, TX, standard 15-minute weather data. File Name: 2016_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2016. Resource Title: 2018 Bushland, TX, standard 15-minute weather data. File Name: 2018_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 2018. Resource Title: 1996 Bushland, TX, standard 15-minute weather data. File Name: 1996_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1996. Resource Title: 1997 Bushland, TX, standard 15-minute weather data. File Name: 1997_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1997. Resource Title: 1998 Bushland, TX, standard 15-minute weather data. File Name: 1998_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1998. Resource Title: 1999 Bushland, TX, standard 15-minute weather data. File Name: 1999_15-min_weather_SWMRU_CPRL.xlsx. Resource Description: As above for 1999.

This parent dataset (collection of datasets) describes the general organization of data in the datasets for each growing season (year) when maize (Zea mays, L.) was grown for grain 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). Maize was grown for grain on between two and four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The four fields were contiguous and arranged in four quadrants, which were labeled northeast (NE), southeast (SE), northwest (NW), and southwest (SW). See the resource titled "Geographic Coordinates, USDA, ARS, Bushland, Texas" for UTM geographic coordinates for field and lysimeter locations. Maize was grown on only the NE and SE fields in 1989 and 1990, and on all four fields in 1994, 2013, 2016, and 2018. Irrigation was by linear move sprinkler system in 1989, 1990, and 1994, although the system was equipped with various application technologies such as high-pressure impact sprinklers, low pressure spray applications, and low energy precision applicators (LEPA). In 2013, 2016, and 2018, 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 equipped with spray applicators. 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 from 0.10- to 2.4-m depth in the field. The number and spacing of neutron probe reading locations changed through the years (additional sites were added), which is one reason why subsidiary datasets and data dictionaries are needed. The lysimeters and fields were planted to the same plant density, row spacing, tillage depth (by hand on the lysimeters and by machine in the fields), and fertilizer and pesticide applications. 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, dew and frost accumulation, and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Each lysimeter was equipped with a suite of instruments to sense wind speed, air temperature and humidity, radiant energy (incoming and reflected, typically both shortwave and longwave), surface temperature, soil heat flux, and soil temperature, all of which are reported at 15-minute intervals. Instruments used changed from season to season, which is another reason that subsidiary datasets and data dictionaries for each season are required. Important conventions concerning the data-time correspondence, sign conventions, and terminology specific to the USDA ARS, Bushland, TX, field operations are given in the resource titled "Conventions for Bushland, TX, Weighing Lysimeter Datasets". There are six datasets in this collection. Common symbols and abbreviations used in the datasets are defined in the resource titled, "Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets". Datasets consist of Excel (xlsx) files. Each xlsx file contains an Introductory tab that explains the other tabs, lists the authors, describes conventions and symbols used and lists any instruments used. The remaining tabs in a file consist of dictionary and data tabs. There is a dictionary tab for every data tab. The name of the dictionary tab contains the name of the corresponding data tab. Tab names are unique so that if individual tabs were saved to CSV files, each CSV file in the entire collection would have a different name. The six datasets, according to their titles, are as follows: Agronomic Calendars for the Bushland, Texas Maize for Grain Datasets Growth and Yield Data for the Bushland, Texas Maize for Grain Datasets Weighing Lysimeter Data for The Bushland, Texas Maize for Grain Datasets Soil Water Content Data for The Bushland, Texas, Large Weighing Lysimeter Experiments Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Maize for Grain Datasets Standard Quality Controlled Research Weather Data – USDA-ARS, Bushland, Texas See the README for descriptions of each dataset. The land slope is <1% and topography is flat. The mean annual precipitation is ~470 mm, the 20-year pan evaporation record indicates ~2,600 mm Class A pan evaporation per year, and winds are typically from the South and Southwest. The climate is semi-arid with ~70% (350 mm) of the annual precipitation occurring from May to September, during which period the pan evaporation averages ~1520 mm. 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 described the facilities and research methods, and have focused on maize ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks for irrigation management. 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: Resource Title: Geographic Coordinates of Experimental Assets, Weighing Lysimeter Experiments, USDA, ARS, Bushland, Texas. File Name: Geographic Coordinates, USDA, ARS, Bushland, Texas.xlsx. Resource Description: The file gives the UTM latitude and longitude of important experimental assets of the Bushland, Texas, USDA, ARS, Conservation & Production Research Laboratory (CPRL). Locations include weather stations [Soil and Water Management Research Unit (SWMRU) and CPRL], large weighing lysimeters, and corners of fields within which each lysimeter was centered. There were four fields designated NE, SE, NW, and SW, and a weighing lysimeter was centered in each field. The SWMRU weather station was adjacent to and immediately east of the NE and SE lysimeter fields. Resource Title: Conventions for Bushland, TX, Weighing Lysimeter Datasets. File Name: Conventions for Bushland, TX, Weighing Lysimeter Datasets.xlsx. Resource Description: Descriptions of conventions and terminology used in the Bushland, TX, weighing lysimeter research program. Resource Title: Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets. File Name: Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets.xlsx. Resource Description: Definitions of symbols and abbreviations used in the Bushland, TX, weighing lysimeter research datasets. Resource Title: README - Bushland Texas Maize for Grain collection. File Name: README_Bushland_maize_for_grain_collection.pdf. Resource Description: Descriptions of the datasets in the Bushland Texas Maize for Grain collection.

This parent dataset (collection of datasets) describes the general organization of data in the datasets for the 1995, 2003, 2004, 2010 and 2019 growing seasons (years) when soybean [Glycine max (L.) Merr.] was grown for seed grain 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). In 1995, 2003, 2004, and 2010, soybean was grown for seed grain on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field also seeded to soybean. The two fields were contiguous, arranged along a north-south axis, and were labeled northeast (NE), and southeast (SE). In 2019, soybean was grown on four large, precision weighing lysimeters, and on the 4.44 ha square fields surrounding each lysimeter, which were contiguous and labeled NE, SE, and northwest (NW), and southwest (SW). See the resource titled "Geographic Coordinates, USDA, ARS, Bushland, Texas" for UTM geographic coordinates for field and lysimeter locations. In 1995, 2003, 2004, and 2010, the fields were irrigated by a linear move sprinkler system equipped with mid elevation spray applicators (MESA). In 2019, the NW and SW fields were irrigated with the linear move sprinkler system equipped with low elevation spray applicators (LESA), while the NE and SE lysimeters and fields were irrigated by subsurface drip irrigation (SDI) with drip tape spaced at 1.52 m in the middle of every other interrow and buried at 0.30 to 0.32 m. Both full and deficit irrigations were applied to fields in 1995, 2003, and 2004. The 2010 crop was grown as a dryland crop with no irrigation other than an initial irrigation to establish the crop. In 2019, full irrigation was applied to all four lysimeters and fields. Except for 2010 and 2019, irrigations on a least one lysimeter 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 from 0.10- to 2.4-m depth in the field. The number and spacing of neutron probe reading locations changed through the years (additional sites were added), which is one reason why subsidiary datasets and data dictionaries are needed. The lysimeters and fields were planted to the same plant density, row spacing, tillage depth (by hand on the lysimeters and by machine in the fields), and fertilizer and pesticide applications. 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, dew and frost accumulation, and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Each lysimeter was equipped with a suite of instruments to sense wind speed, air temperature and humidity, radiant energy (incoming and reflected, typically both shortwave and longwave), surface temperature, soil heat flux, and soil temperature, all of which are reported at 15-minute intervals. Instruments used changed from season to season, which is another reason that subsidiary datasets and data dictionaries for each season are required. Important conventions concerning the data-time correspondence, sign conventions, and terminology specific to the USDA ARS, Bushland, TX, field operations are given in the resource titled "Conventions for Bushland, TX, Weighing Lysimeter Datasets". There are six datasets in this collection. Common symbols and abbreviations used in the datasets are defined in the resource titled, "Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets". Datasets consist of Excel (xlsx) files. Each xlsx file contains an Introductory tab that explains the other tabs, lists the authors, describes conventions and symbols used and lists any instruments used. The remaining tabs in a file consist of dictionary and data tabs. There is a dictionary tab for every data tab. The name of the dictionary tab contains the name of the corresponding data tab. Tab names are unique so that if individual tabs were saved to CSV files, each CSV file in the entire collection would have a different name. The six datasets, according to their titles, are as follows: Agronomic Calendars for the Bushland, Texas Soybean Datasets Growth and Yield Data for the Bushland, Texas Soybean Datasets Weighing Lysimeter Data for The Bushland, Texas Soybean Datasets Soil Water Content Data for The Bushland, Texas, Large Weighing Lysimeter Experiments Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Soybean Datasets Standard Quality Controlled Research Weather Data – USDA-ARS, Bushland, Texas See the README for descriptions of each dataset. The soil is a Pullman series fine, mixed, superactive, thermic Torrertic Paleustoll. Soil properties are given in the resource titled "Soil Properties for the Bushland, TX, Weighing Lysimeter Datasets". The land slope is <1% and topography is flat. The mean annual precipitation is ~470 mm, the 20-year pan evaporation record indicates ~2,600 mm Class A pan evaporation per year, and winds are typically from the South and Southwest. The climate is semi-arid with ~70% (350 mm) of the annual precipitation occurring from May to September, during which period the pan evaporation averages ~1520 mm. 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 described the facilities and research methods, and have focused on ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks for irrigation management. The data have utility for testing simulation models of crop ET, growth, and yield. Resources in this dataset: Resource Title: README - Bushland Texas Soybean collection. File Name: README_Bushland_soybean_collection.pdf. Resource Description: Descriptions of the datasets in the Bushland Texas Soybean collection.

This parent dataset (collection of datasets) describes the general organization of data in the datasets for the 2009 and 2011 growing seasons (year) when sunflower (Helianthus annuus L.) was grown for seed grain 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 for seed grain on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The two fields were contiguous, arranged along a north-south axis, and were labeled northeast (NE), and southeast (SE). See the resource titled "Geographic Coordinates, USDA, ARS, Bushland, Texas" for UTM geographic coordinates for field and lysimeter locations. The fields were irrigated by a linear move sprinkler system equipped with spray applicators. 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 from 0.10- to 2.4-m depth in the field. The number and spacing of neutron probe reading locations changed through the years (additional sites were added), which is one reason why subsidiary datasets and data dictionaries are needed. The lysimeters and fields were planted to the same plant density, row spacing, tillage depth (by hand on the lysimeters and by machine in the fields), and fertilizer and pesticide applications. 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, dew and frost accumulation, and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Each lysimeter was equipped with a suite of instruments to sense wind speed, air temperature and humidity, radiant energy (incoming and reflected, typically both shortwave and longwave), surface temperature, soil heat flux, and soil temperature, all of which are reported at 15-minute intervals. Instruments used changed from season to season, which is another reason that subsidiary datasets and data dictionaries for each season are required. Important conventions concerning the data-time correspondence, sign conventions, and terminology specific to the USDA ARS, Bushland, TX, field operations are given in the resource titled "Conventions for Bushland, TX, Weighing Lysimeter Datasets". There are six datasets in this collection. Common symbols and abbreviations used in the datasets are defined in the resource titled, "Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets". Datasets consist of Excel (xlsx) files. Each xlsx file contains an Introductory tab that explains the other tabs, lists the authors, describes conventions and symbols used and lists any instruments used. The remaining tabs in a file consist of dictionary and data tabs. There is a dictionary tab for every data tab. The name of the dictionary tab contains the name of the corresponding data tab. Tab names are unique so that if individual tabs were saved to CSV files, each CSV file in the entire collection would have a different name. The six datasets, according to their titles, are as follows: Agronomic Calendars for the Bushland, Texas Sunflower Datasets Growth and Yield Data for the Bushland, Texas Sunflower Datasets Weighing Lysimeter Data for The Bushland, Texas Sunflower Datasets Soil Water Content Data for The Bushland, Texas, Large Weighing Lysimeter Experiments Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Sunflower Datasets Standard Quality Controlled Research Weather Data – USDA-ARS, Bushland, Texas See the README for descriptions of each dataset. The land slope is <1% and topography is flat. The mean annual precipitation is ~470 mm, the 20-year pan evaporation record indicates ~2,600 mm Class A pan evaporation per year, and winds are typically from the South and Southwest. The climate is semi-arid with ~70% (350 mm) of the annual precipitation occurring from May to September, during which period the pan evaporation averages ~1520 mm. 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 described the facilities and research methods, and have focused on ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks for irrigation management. The data have utility for testing simulation models of crop ET, growth, and yield. Resources in this dataset: Resource Title: Geographic Coordinates of Experimental Assets, Weighing Lysimeter Experiments, USDA, ARS, Bushland, Texas. File Name: Geographic Coordinates, USDA, ARS, Bushland, Texas.xlsx. Resource Description: The file gives the UTM latitude and longitude of important experimental assets of the Bushland, Texas, USDA, ARS, Conservation & Production Research Laboratory (CPRL). Locations include weather stations [Soil and Water Management Research Unit (SWMRU) and CPRL], large weighing lysimeters, and corners of fields within which each lysimeter was centered. There were four fields designated NE, SE, NW, and SW, and a weighing lysimeter was centered in each field. The SWMRU weather station was adjacent to and immediately east of the NE and SE lysimeter fields. Resource Title: Conventions for Bushland, TX, Weighing Lysimeter Datasets. File Name: Conventions for Bushland, TX, Weighing Lysimeter Datasets.xlsx. Resource Description: Descriptions of conventions and terminology used in the Bushland, TX, weighing lysimeter research program. Resource Title: Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets. File Name: Symbols and Abbreviations for Bushland, TX, Weighing Lysimeter Datasets.xlsx. Resource Description: Definitions of symbols and abbreviations used in the Bushland, TX, weighing lysimeter research datasets. Resource Title: README - Bushland Texas Sunflower collection. File Name: README_Bushland_sunflower_collection.pdf. Resource Description: Descriptions of the datasets in the Bushland Texas Sunflower collection.

The Global Reservoir and Dam Database, Version 1, Revision 01 (v1.01) contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic km. The dams were geospatially referenced and assigned to polygons depicting reservoir outlines at high spatial resolution. Dams have multiple attributes, such as name of the dam and impounded river, primary use, nearest city, height, area and volume of reservoir, and year of construction (or commissioning). While the main focus was to include all dams associated with reservoirs that have a storage capacity of more than 0.1 cubic kilometers, many smaller dams and reservoirs were added where data were available. The data were compiled by Lehner et al. (2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network (CIESIN). For details please refer to the Technical Documentation which is provided with the data.The Global Reservoir and Dam Database, Version 1, Revision 01 (v1.01) contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic km. The dams were geospatially referenced and assigned to polygons depicting reservoir outlines at high spatial resolution. Dams have multiple attributes, such as name of the dam and impounded river, primary use, nearest city, height, area and volume of reservoir, and year of construction (or commissioning). While the main focus was to include all dams associated with reservoirs that have a storage capacity of more than 0.1 cubic kilometers, many smaller dams and reservoirs were added where data were available. The data were compiled by Lehner et al. (2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network (CIESIN). For details please refer to the Technical Documentation which is provided with the data.

A Modelling dataset containing a DSSAT cultivar file, AgMIPS platform dome code and USDA ARS LIRF drip irrigated field experiment in Greeley, Colorado average Maize biomass and yield by treatment. Irrigation treatments vary from 40% to 100% of ET. This dataset is used with the DSSAT and RZWQM2 models as part of an Agricultural Model Inter-comparison and Improvement Project (AgMIP) data node maintained at National Agricultural Library for USDA-AgMIP data. Additional data are available from https://data.agmip.org/ The complete experiment dataset in readable Excel format is USDA-ARS Colorado Maize Water Productivity Dataset 2008-2011 and can be found at http://dx.doi.org/10.15482/USDA.ADC/1254006

Recent USDA/ARS patented technologies on crop production and protection that are available for licensing are described, including summary, contact, benefits, and applications. Updated June 2018.

The 2018 Irrigation and Water Management Survey (formerly called the Farm and Ranch Irrigation Survey) is a follow-on to the 2017 Census of Agriculture by the U.S. Department of Agriculture (USDA). This survey provides the only comprehensive information on irrigation activities and water use across American farms, ranches, and horticultural operations. In responding to the survey, producers provide information on topics such as water sources and amount of water used, acres irrigated by type of system, irrigation and yield by crop, and system investments and energy costs. The full reports for the 2003, 2008, 2017, and 2018 surveys are provided in this submission. By following the link to the USDA Census of Irrigation, a specific year can be selected, in which the tables and figures of each report are provided.

The U.S. Geological Survey maintains national data bases of water-use information. The data are collected and compiled every five years for each State, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. County, state, and national water-use estimates may be downloaded from the National Water Information System Web (NWISWeb) interface, Water Data for the Nation, by selecting the Water Use button or data category pull-down. Data on NWISWeb represent the current best estimates, and may have been revised from previous publications. Data available from the USGS County Water-Use generally reflect the published report, and may have been revised in subsequent analyses. Note: State-level data from 1950-1980 and watershed data are not available on NWISWeb, but they can be downloaded USGS County Water-Use Data link.

WASUIT is a computer program which predicts the Salinity Sodicity Toxic-solute concentration of the soil-water within a simulated crop root zone resulting from the use of a particular irrigation water of given composition and at a specified leaching fraction. It can be used to evaluate the effect of a given salinity level (or solute concentration) on crop yield and of a given sodicity level on soil permeability. System Requirements: WATSUIT is written in Standard FORTRAN 77 and requires ANSI.SYS installed in your CONFIG.SYS file (i.e., DEVICE=C:\DOS\ANSI.SYS). The ANSI.SYS screen commands are used to clear your computer screen. If for some reason you do not have ANSI.SYS, the program will still run but will not your screen will not be cleared. MS-DOS 2.0 or later operating system and standard IBM 360 or 1.2 kbytes diskette drives are required.

Numerous technical reports related to water in New Mexico regions

Spatial representation of surface water points of diversion locations as interpreted from water-right documents, including (but not limited to) water-right certificates, water-right permits, water-right applications, and water-right claims.http://www.ecy.wa.gov/programs/wr/rights/water-right-home.html

Selection of 104 water security related indicators, with visualisation tools to plot up to 4 variables simultaneously. Graphs can be direct linked, and data sets can be downloaded as CSV files

WinSRFR is a hydraulic analysis tool for surface irrigation systems. The software combines simulation, evaluation, operational analysis, and design functionalities. Intended users are irrigation specialists, extension agents, researchers, consultants, students, and farmers with moderate to advanced knowledge of surface irrigation hydraulics. WinSRFR 5.1 is the fifth major release of the software. The new version offers a reprogrammed simulation engine, an application programming interface, batch simulation capabilities, and enhancements to the user interface.