Assessment of Landsat-Based Evapotranspiration Using Weighing Lysimeters in the Texas High Plains

• Published in: Agronomy (Basel) Vol. 10; no. 11; p. 1688
• Main Authors: Hashem, Ahmed A., Engel, Bernard A., Bralts, Vincent F., Marek, Gary W., Moorhead, Jerry E., Radwan, Sherif A., Gowda, Prasanna H.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-11-2020
• Subjects: Accuracy; Agricultural production; Algorithms; Aquifers; Arid lands; Arid zones; BEARS; bushland; climate; Cotton; Crops; Energy; Evapotranspiration; groundwater management; High plains; Interpolation; Irrigated farming; Irrigation; Irrigation water; irrigation water management; Landsat; Landsat satellites; Leaf area; Lysimeters; Methods; Regional planning; Remote sensing; Scheduling; Spatial discrimination; Spatial resolution; Spectroradiometers; Surface roughness; Surface temperature; Water management; Water resources; Water shortages; Water use; Weighing; United States > US; Texas
• ISSN: 2073-4395; 2073-4395
• DOI: 10.3390/agronomy10111688

Evapotranspiration (ET) is one of the largest data gaps in water management due to the limited availability of measured evapotranspiration data, and because ET spatial variability is difficult to characterize at various scales. Satellite-based ET estimation has been shown to have great potential for water resource planning and for estimating agricultural water use at field, watershed, and regional scales. Satellites with low spatial resolution, such as NASA’s MODIS (Moderate Resolution Imaging Spectroradiometer), and those with higher spatial resolution, such as Landsat (Land Satellite), can potentially be used for irrigation water management purposes and other agricultural applications. The objective of this study is to assess satellite based-ET estimation accuracy using measured ET from large weighing lysimeters. Daily, seven-day running average, monthly, and seasonal satellite-based ET data were compared with corresponding lysimeter ET data. This study was performed at the USDA-ARS Conservation and Production Research Laboratory (CPRL) in Bushland, Texas, USA. The daily time series Landsat ET estimates were characterized as poor for irrigated fields, with a Nash Sutcliff efficiency (NSE) of 0.37, and good for monthly ET, with an NSE of 0.57. For the dryland managed fields, the daily and monthly ET estimates were unacceptable with an NSE of −1.38 and −0.19, respectively. There are various reasons for these results, including uncertainties with remotely sensed data due to errors in aerodynamic resistance surface roughness length estimation, surface temperature deviations between irrigated and dryland conditions, poor leaf area estimation in the METRIC model under dryland conditions, extended gap periods between satellite data, and using the linear interpolation method to extrapolate daily ET values between two consecutive scenes (images).