Biophysically-based measurement of plant water status using canopy temperature

Methods that directly determine plant physiological responses to water availability have potential to be significantly more sensitive and accurate than indirect approaches like soil moisture measurement. Stomatal conductance is a rapid physiological response to leaf water potential. Stomatal conductance in single leaves has long been calculated using energy balance and biophysical principles. This same biophysical approach can be extended to plant communities using: 1) standard meteorological measurements, 2) accurate measurement of average canopy temperature, and 3) knowledge of canopy architecture. Here we use a two-source energy balance model designed for the calculation of stomatal conductance (gC) in row crops with random leaf spatial distribution within rows. The two-source model separates soil and canopy heat sources and accounts for the unique characteristic of vegetation clumped in rows. The distribution of plants in rows affects not only the wind and radiation penetration in the canopy but also the separation of soil and canopy heat sources. The two-source energy balance model requires measurement or estimation of the soil and canopy temperatures. Several methods can be used to derive these temperatures. This study compares two methods for determining canopy temperature for calculation of canopy stomatal conductance. The methods are compared for two crops (corn and cotton) in multiple geographic locations. By using the necessary environmental measurements, aerodynamic parameters and model modifications, gC was continuously determined for multiple locations throughout the Midwest and Southern United States. This gC value was then compared to a calculated reference gC for a well-watered crop. This ratio is an indicator of crop water status, which is called the stomatal conductance ratio (SCR). The SCR increased closer to one (one indicating no water stress) after each irrigation or significant precipitation, and steadily declined until the next irrigation event. Significant drought stress occurred in several of the fields. Daily SCR values were weighted to correspond with growth stage sensitivity to drought stress. These weighted values were highly correlated with yield (r2 values up to 0.79). SCR values for cotton were also highly correlated with yield (r2 values up to 0.96). This biophysical approach has the potential to provide a powerful tool for precision irrigation management.