Location: Soil and Water Management ResearchTitle: The Bushland, Texas, alfalfa datasets
|Evett, Steven - Steve|
|HOWELL, SR., TERRY - Retired ARS Employee|
Submitted to: Ag Data Commons
Publication Type: Database / Dataset
Publication Acceptance Date: 4/28/2022
Publication Date: 4/28/2022
Citation: Evett, S.R., Marek, G.W., Copeland, K.S., Ruthardt, B.B., Colaizzi, P.D., Howell, Sr., T.A., Brauer, D.K. 2022. The Bushland, Texas, alfalfa datasets. Ag Data Commons. https://doi.org/10.15482/USDA.ADC/1526356.
Interpretive Summary: The scarcity of water resources in the U.S. Southern High Plains is of regional, national and even international concern due to the fact that the region acts as a breadbasket for the nation and world. The majority of agricultural production in this region depends on irrigation, largely dependent on pumping from the Ogallala or High Plains Aquifer, which are yielding less water every year. Alfalfa is a crop of increasing importance in the region and is the fourth most grown crop in the USA. Scientists at the USDA ARS Conservation & Production Research Laboratory at Bushland, Texas, collected data regarding alfalfa water use over four seasons to determine the amount of water used by alfalfa in the region’s climate and the accuracy of water use models. However, these data have not been previously publicly available in a readily useable format. Thus, the scientific team has prepared these unique data sets for sharing with other scientists and the general public on the USDA National Agricultural Library online data sharing library. These data sets have already been used to improve crop growth, water use, and yield models used to forecast production nationally and to guide water planning locally and regionally. Public accessibility via the USDA National Agricultural Library will increase their use by other researchers.
Technical Abstract: Alfalfa is an important forage crop, particularly for dairy producers whose presence on the Southern High Plains has increased dramatically in recent years. And alfalfa, well-watered and fertilized, is one of two crops used as reference evapotranspiration (ET) standards for accurate estimation of crop ET. Accurate ET is important for effective irrigation scheduling to improve crop water productivity, irrigation scheme management, long term water resource planning and management, and for use in crop simulation models to improve accuracy of yield estimates. However, all crop ET estimation methods must be tested against ground truth – ET as measured by mass balance in crop fields – and improved so as to estimate ET as accurately as possible. Mass balance measurement of ET depends on solving the soil water balance in which ET is the sum of the change of water stored in the soil profile to well below the root zone, irrigation, precipitation, the sum of any runon and runoff, and any soil water flux into or out of the soil profile. Effective means of measuring the profile change in storage include the neutron probe and large weighing lysimeters. The USDA ARS weighing lysimeter team at Bushland, Texas, measured ET of alfalfa grown to reference ET standards in 1996 through 1999 using both weighing lysimeters and the neutron probe. Along with those measurements, the team measured crop growth and yield, weather, and irrigation applied. These data are presented, along with cropping calendars for each season, as machine readable files available to the public via the USDA ARS National Agriculture Library (NAL) Ag Data Commons internet site. The cropping calendars contain dates of important field operations, including dates, amounts, and kinds of fertilizers and pesticides applied, harvests and irrigations. The weather data include daily sums and averages as well as 15-minute mean data for all days of the year, and include solar irradiance, air temperature and humidity, wind speed, air pressure, and precipitation. Some seasons of the Bushland alfalfa data have already been used by several universities for projects as varied as testing and improvement of eddy covariance methods of ET estimation, remote sensing-based ET estimation, and crop model testing and improvement.