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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 #367808
Research Project: Improving the Sustainability of Irrigated Farming Systems in Semi-Arid Regions

Location: Water Management and Systems Research

Title: Determining maize water stress through a remote sensing based surface energy balance approach

Author
item COSTA FILHO, EDSON - Colorado State University
item CHAVEZ, JOSE - Colorado State University
item Comas, Louise

Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/20/2020
Publication Date: 3/6/2020
Citation: Costa Filho, E., Chavez, J.L., Comas, L.H. 2020. Determining maize water stress through a remote sensing based surface energy balance approach. Irrigation Science. https://doi.org/10.1007/s00271-020-00668-1.
DOI: https://doi.org/10.1007/s00271-020-00668-1

Interpretive Summary: Determining water stress levels of vegetated surfaces is crucial for irrigation scheduling. This paper aims to evaluate a new method for determining crop water stress index (CWSI) based on the temperature difference from canopy to air. Data were collected on a deficit irrigated maize field at a research farm located in Greeley, Colorado in 2017 and 2018. Weather data were measured on-site. Crop surface reflectance data were obtained on-site through multispectral radiometer measurements, and canopy temperature was measured using infra-red thermometers. Results show that the daily soil water stress index is best represented through a non-linear rational CWSI function (i.e., a ratio of polynomial equations based on CWSI). Calculations of CWSI using the canopy to air temperature gradient were close to CWSI determined by standard procedures as well as CWSI calculated from canopy transpiration measured with plant sap flow meters, validating the CWSI model estimates under the conditions observed in the study. Thus, the new CWSI approach presented here could be used to effectively manage irrigation for maize in semi-arid regions.

Technical Abstract: Determining water stress levels of vegetated surfaces is crucial for irrigation scheduling. This paper aims to evaluate a new method for determining crop water stress index (CWSI) based on the estimation of sensible heat flux using an aerodynamic temperature gradient approach. Data were collected on a deficit irrigated maize field at a research farm located in Greeley, Colorado in 2017 and 2018. The irrigation treatment aimed to meet 40% of crop full water demand during the vegetative and reproductive growth stages using subsurface drip. Weather data were measured on-site at 3.3 m above ground level. RED and NIR surface reflectance data were obtained on-site through multispectral radiometer measurements. Nadir surface temperature data were measured using infra-red thermometers at 1 m above canopy. CWSI estimated values were used to assess daily soil water stress index (SWSI), calculated from measurements of volumetric soil water content (VWC) and management allowed depletion (MAD) of 40%. Results show that SWSI is best represented through a non-linear rational CWSI function. Modeled CWSI estimates were compared to measured surface heat fluxes, giving a mean bias error (MBE) of -0.02 and a root mean square error (RMSE) of 0.09. A MBE of 0.02 and RMSE of 0.07 were also obtained when comparing estimated CWSI with observed CWSI based on canopy transpiration measured with plant sap flow meters, validating the CWSI model estimates under the conditions observed in the study. The CWSI approach as presented could be used to effectively manage irrigation for maize in semi-arid regions.