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Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves
Authors:Masahiro Tasumi  Richard G Allen  Ricardo Trezza  James L Wright
Affiliation:1Post-Doctoral Researcher, Univ. of Idaho Research and Extension Center, 3793 N. 3600 E., Kimberly, ID 83341. E-mail: tasumi@kimberly.uidaho.edu
2Professor, Water Resources Engineering, Univ. of Idaho Research and Extension Center, 3793 N. 3600 E., Kimberly, ID 83341. E-mail: rallen@kimberly.uidaho.edu
3Associate Professor, Univ. of the Andes, Merida, Venezuela.
4Soil Scientist, USDA-ARS Northwest Irrigation and Soils Research Laboratory, 3793 N. 3600 E., Kimberly, ID 83341.
Abstract:Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.
Keywords:Evapotranspiration  Satellites  Remote sensing  Irrigation scheduling  Water resources management  Crops  
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