Skip to main content
ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Plant Physiology and Genetics Research » Research » Publications at this Location » Publication #357997

Research Project: Enhancing Abiotic Stress Tolerance of Cotton, Oilseeds, and Other Industrial and Biofuel Crops Using High Throughput Phenotyping and Other Genetic Approaches

Location: Plant Physiology and Genetics Research

Title: Remote sensing of evapotranspiration over the central Arizona irrigation and drainage district, U.S.A.

Author
item French, Andrew
item Hunsaker, Douglas - Doug
item BOUNOUA, LAHOUARI - Nasa Goddard Institute For Space Studies
item KARNIELI, ARNON - Ben Gurion University Of Negev
item LUCKETT, WILLIAM - US Department Of Agriculture (USDA)
item STRAND, BOB - Lemnatec

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/15/2018
Publication Date: 11/26/2018
Citation: French, A.N., Hunsaker, D.J., Bounoua, L., Karnieli, A., Luckett, W., Strand, B. 2018. Remote sensing of evapotranspiration over the central Arizona irrigation and drainage district, U.S.A. Agronomy Journal. 8(12):278.

Interpretive Summary: Accurate estimates of evapotranspiration (ET) are important for effective and efficient crop water management. Commonly used techniques to estimate ET are based on generalized guidelines for each crop, and so have uncertain accuracy. Remote sensing from space of land surface vegetation and temperature offers opportunities to improve knowledge of ET because the observations, and the models using them, are no longer generalized but specific. Research in an irrigation district in South Central Arizona was undertaken to assess ET uncertainties from three different remote sensing models relative to guidelines. The study collected image data from Landsat 5, 7, MODIS, and ASTER and estimated ET over wheat, cotton, and alfalfa. Modeling outcomes showed that uncertainty of remote sensing ET estimates were within 18% of each other. These results will help Arizona farmers, irrigation advisers, and water district managers quantify and forecast crop water needs.

Technical Abstract: A remote sensing-based evapotranspiration (ET) study was conducted over the Central Arizona Irrigation and Drainage District (CAIDD), an Arizona agricultural region. ET was assessed means for 137 wheat plots, 183 cotton plots, and 225 alfalfa plots. The remote sensing ET models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. The models produced similar daily ET for wheat, with 6-8 mm/d mid-season. For cotton and alfalfa daily ET showed greater differences, where TSEB produced largest daily ET, METRIC the least, and VISW in the midrange. Modeled cotton ET at mid-season ranged from 9.5 mm/d (TSEB), to 8 mm/d (VISW), and 6 mm/d (METRIC). For alfalfa ET, values at peak cover ranged from 8 mm/d (TSEB), 6 mm/d (VISW), and 5 mm/d (METRIC). Model bias ranged -10% to +18%. Relative to potential ET, FAO-56 ET, and USDA-SW gravimetric-ET, model variability ranged from negligible to 35% of annual crop water use. Model averaging was found a useful way to consider and reconcile all ET estimates.