Location: Soil and Water Management Research
Title: Comparison of infrared thermometry and soil water derived stress indices and crop ET in cottonAuthor
Schwartz, Robert | |
Colaizzi, Paul | |
DOMINGUEZ, ALFONSO - University Of Castilla-La Mancha(UCLM) | |
Baumhardt, Roland - Louis | |
Ulloa, Mauricio |
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 8/21/2024 Publication Date: 10/16/2024 Citation: Schwartz, R.C., Colaizzi, P.D., Dominguez, A., Baumhardt, R.L., Ulloa, M. 2024. Comparison of infrared thermometry and soil water derived stress indices and crop ET in cotton. Applied Engineering in Agriculture. 40(5):537-551. https://doi.org/10.13031/aea.16104. DOI: https://doi.org/10.13031/aea.16104 Interpretive Summary: Upland cotton is an economically important crop in the semiarid Texas High Plains that is increasingly being managed under subsurface drip irrigation (SDI). Scheduling irrigation based on water stress detected by infrared thermometers that measure the temperature of the crop canopy may improve efficient use of water under SDI. The objectives of this study were to refine a procedure to estimate relative water stress of cotton using infrared thermometers and compare this index with water stress determined using measured plant available soil water. In addition, ARS scientists at Bushland evaluated methods to calculate crop water use with measured canopy temperatures. The calculated stress index derived from infrared thermometer measurements was responsive to irrigation, rainfall events, and differing irrigation rates. The stress index derived from infrared thermometers was weakly correlated to the fraction of plant available water, but it was more responsive to irrigation events. Predictions of crop water use inferred from canopy temperature measurements agreed closely with measured water use. Employing the thermal stress index to schedule irrigation and optimize crop water use will require additional field studies. Technical Abstract: Upland cotton (Gossypium hirsutum L.) is an economically important crop in the semiarid Texas High Plains (THP) that is increasingly being managed under subsurface drip irrigation (SDI). Scheduling irrigation using a thermally based crop water stress index (CWSI) has the potential to overcome limitations of soil water-based methods and facilitate efficient use of water. The objectives of this study were to develop a CWSI calculation procedure using stability correction, determine an appropriate window for averaging CWSI during daytime hours, compare CWSI with soil water-based indicators of crop water stress, and evaluate methods for estimating crop evapotranspiration (ET) using measured canopy temperatures. Infrared thermometer measurements of canopy temperature and corresponding cotton water use derived from soil water measurements were acquired under two irrigation levels (100 and 33%) under SDI during three growing seasons. A theoretical approach was used to calculate the CWSI using the Businger-Dyer stability correction. Basing daily CWSI on short one or two-hour periods in the afternoon overestimated crop water stress. In contrast, CWSI averaged during daytime periods with 0.25-h solar radiation and air temperature exceeding 0.3 MJ m-2 and 24°C, respectively, was strongly correlated (R2=0.76) with the soil water depletion-based stress coefficient Ks with a plausible lower canopy resistance of 25 s m-1. The CWSI was weakly correlated (R2=0.48) with the fraction of plant available water and more responsive to irrigation. Using the proposed CWSI scaling at different locations for canopies with dissimilar cover fractions yielded satisfactory estimates of crop ET (RMSE=0.74 mm d-1) compared with soil water balance-calculated ET (ETswb). When summed over weekly intervals, energy balance predictions of 0.25-h crop transpiration inferred from canopy temperature measurements had an acceptable agreement with ETswb (RMSE=0.92 mm d-1). Employing the CWSI to trigger irrigation will require targeted field studies to evaluate thresholds and strategies to optimize water management. |