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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #326296
Title: Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients

Author
item KULLBERG, EMILY - AQUA ENGINEERING INC.
item DeJonge, Kendall
item CHAVEZ, JOSE - COLORADO STATE UNIVERSITY

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/3/2016
Publication Date: 7/18/2016
Citation: Kullberg, E.G., DeJonge, K.C., Chavez, J.L. 2016. Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients. Agricultural Water Management. doi: 10.1016/j.agwat.2016.07.007.

Interpretive Summary: Standardized dual crop coefficient methods calculate both a non-stressed transpiration coefficient (Kcb) that is related to canopy cover, and a stress or transpiration reduction coefficient (Ks) that can be related to soil water deficit. This study compares several remote sensing methods to determine Kcb and Ks and resulting evapotranspiration (ET) in a deficit irrigation experiment of corn (Zea mays L.) near Greeley, Colorado. Three methods were used to calculate Kcb, and four canopy temperature based methods were used to calculate Ks. Results showed that stress coefficient methods with less data requirements such as DANS and DACT are responsive to crop water stress as demonstrated by low RMSE of ET calculations, comparable to more data intensive methods such as CWSI.

Technical Abstract: Remotely sensed data such as spectral reflectance and infrared canopy temperature can be used to quantify crop canopy cover and/or crop water stress, often through the use of vegetation indices calculated from the near-infrared and red bands, and stress indices calculated from the thermal wavelengths. Standardized dual crop coefficient methods calculate both a non-stressed transpiration coefficient (Kcb) that is related to canopy cover, and a stress or transpiration reduction coefficient (Ks) that can be related to soil water deficit or other stress factors (e.g. disease). This study compares several remote sensing methods to determine Kcb and Ks and resulting evapotranspiration (ET) in a deficit irrigation experiment of corn (Zea mays L.) near Greeley, Colorado. Three methods were used to calculate Kcb (tabular, normalized difference vegetation index - NDVI, and canopy cover). Four canopy temperature based methods were used to calculate Ks: Crop Water Stress Index – CWSI, Canopy Temperature Ratio - Tcratio, Degrees Above Non-Stressed – DANS, Degrees Above Canopy Threshold – DACT. Crop ET predicted by these methods was compared to observation and water balance based ET measurements. Thermal indices DANS and DACT were calibrated to convert to Ks. Results showed that stress coefficient methods with less data requirements such as DANS and DACT are responsive to crop water stress as demonstrated by low RMSE of ET calculations, comparable to more data intensive methods such as CWSI. Results indicate which remote sensing methods are appropriate to use given certain data availability and irrigation level, in addition to providing an estimation of the associated error in ET.