Modeling soybean canopy resistance from micrometeorological and plant variables for estimating evapotranspiration using one-step Penman–Monteith approach

SummaryCanopy resistance (rc) is one of the most important variables in evapotranspiration, agronomy, hydrology and climate change studies that link vegetation response to changing environmental and climatic variables. This study investigates the concept of generalized nonlinear/linear modeling approach of rc from micrometeorological and plant variables for soybean [Glycine max (L.) Merr.] canopy at different climatic zones in Nebraska, USA (Clay Center, Geneva, Holdrege and North Platte). Eight models estimating rc as a function of different combination of micrometeorological and plant variables are presented. The models integrated the linear and non-linear effects of regulating variables (net radiation, Rn; relative humidity, RH; wind speed, U3; air temperature, Ta; vapor pressure deficit, VPD; leaf area index, LAI; aerodynamic resistance, ra; and solar zenith angle, Za) to predict hourly rc. The most complex rc model has all regulating variables and the simplest model has only Rn, Ta and RH. The rc models were developed at Clay Center in the growing season of 2007 and applied to other independent sites and years. The predicted rc for the growing seasons at four locations were then used to estimate actual crop evapotranspiration (ETc) as a one-step process using the Penman–Monteith model and compared to the measured data at all locations. The models were able to account for 66–93% of the variability in measured hourly ETc across locations. Models without LAI generally underperformed and underestimated due to overestimation of rc, especially during full canopy cover stage. Using vapor pressure deficit or relative humidity in the models had similar effect on estimating rc. The root squared error (RSE) between measured and estimated ETc was about 0.07 mm h−1 for most of the models at Clay Center, Geneva and Holdrege. At North Platte, RSE was above 0.10 mm h−1. The results at different sites and different growing seasons demonstrate the robustness and consistency of the models in estimating soybean rc, which is encouraging towards the general application of one-step estimation of soybean canopy ETc in practice using the Penman–Monteith model and could aid in enhancing the utilization of the approach by irrigation and water management community.