Radiometric surface temperature calibration effects on satellite based evapotranspiration estimation

Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer, leading to steady decline in water table levels. Therefore, efficient water management is essential for sustaining agricultural production in the THP. Accurate evapotranspiration (...

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Bibliographic Details
Published in:International journal of remote sensing 2009-01, Vol.30 (9), p.2337-2354
Main Authors: Chávez, J. L., Gowda, P. H., Howell, T. A., Copeland, K. S.
Format: Article
Language:English
Subjects:
Applied geophysics
Calibration
Earth sciences
Earth, ocean, space
Evapotranspiration
Exact sciences and technology
Hydrology. Hydrogeology
Internal geophysics
Mapping
Mathematical models
Remote sensing
Satellites
Surface temperature
Water resources
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Summary:Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer, leading to steady decline in water table levels. Therefore, efficient water management is essential for sustaining agricultural production in the THP. Accurate evapotranspiration (ET) maps provide critical information on actual spatio-temporal crop water use. METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration) is a remote sensing based energy balance method that uses radiometric surface temperature (T s ) for mapping ET. However, T s calibration effects on satellite based ET estimation are less known. Further, METRIC has never been applied for the advective conditions of the semi-arid THP. In this study, METRIC was applied and predicted ET was compared with measured values from five monolithic weighing lysimeters at the USDA-ARS Conservation and Production Research Laboratory in Bushland, Texas, USA. Three different levels of calibration were applied on a Landsat 5 Thematic Mapper's thermal image acquired on 23 July 2006 to derive T s . Application of METRIC on a MODTRAN calibrated image improved the accuracy of distributed ET prediction. In addition, ET estimates were further improved when a THP-specific model was used for estimating leaf area index. Results indicated that METRIC performed well with ET mean bias error±root mean square error of 0.4±0.7 mm d −1 .
ISSN:0143-1161
1366-5901
DOI:10.1080/01431160802549393