Assessing maize crop water stress using an aerodynamic temperature approach - Costa Filho, Edson, author; Chavez, Jose L., author (Colorado State University. Libraries, 2019)
This study evaluates two methods for determining maize crop water stress index (CWSI) using a surface energy balance coupled with an aerodynamic temperature approach. Data were collected on an irrigated maize field, at a research farm located near Greeley, Colorado, USA, in 2018. The irrigation treatment was subsurface drip. Weather data were measured on-site at 3.3 m above ground level. Remote sensed red (RED) and Near infrared (NIR) surface reflectance data were obtained on-site through radiometry measurements done twice a week. Nadir surface temperature was measured using infrared thermometers kept at 1 m above canopy height. Aerodynamic temperature models developed by Chavez et al. (2005) and Costa-Filho (2019) were used to independently estimate CWSI based on the surface energy balance approach. Independent CWSI from measured surface heat fluxes were used as reference for model performance assessment. Results indicated that estimated CWSI based on Costa-Filho (2019) model had mean bias error (MBE) of -0.01 and root mean square error (RMSE) of 0.08, while model from Chavez et al. (2005) resulted on MBE of -0.24 and RMSE of 0.27. Both models underestimated CWSI values due to negative values of MBE, but Costa-Filho (2019) model improved CWSI estimation by reducing the magnitude of RMSE in 30 % when compared to CWSI estimated using Chavez et al. (2005) aerodynamic model. Therefore, research results indicate that there is evidence that the CWSI approach based on Costa-Filho (2019) model for aerodynamic temperature seems to improve estimation of maize CWSI for semi-arid conditions.
The purpose of the study is to assess improvements on irrigation water management by evaluating the applicability of aerodynamic temperature methods for sensible heat flux to estimate crop water stress index. Analysis were performed for maize under water stress conditions. Data were collected at a research farm located in Greeley, CO in 2018. Areas of investigation: Irrigation water management, surface energy balance concepts, remote sensing.
Keywords: crop water stress index; sensible heat flux; surface energy balance; remote sensing; irrigation water management