Submitted to: International Evapotranspiration Irrigation Scheduling Conference
Publication Type: Proceedings
Publication Acceptance Date: 7/12/1996
Publication Date: N/A
Citation: Interpretive Summary: As much as 100% of the water evaporated from land surfaces comes from plant leaves in the form of transpiration, which both helps them grow and keeps them cool. The evaporation of water from the soil and the plant is called evaportranspiration (ET). Equations for calculating ET have been used to schedule irrigations efficiently and estimate regional water budgets. Predicting the amount of transpiration losses in ET has not been easy. It typically is described in terms of plant resistance to water loss (canopy resistance); which is a function of environmental parameters, such as air temperature and solar radiation, and plant characteristics, such as the amount of leaf area. We examined the canopy resistance of an irrigated corn crop as a function of measured ET and then as a function of measured whole plant transpiration. We then developed a model to predict its canopy resistance based on solar radiation and amount of leaf area. Increasing and decreasing solar radiation could describe much of the hourly changes i canopy resistance, but the changing amount of illuminated leaves through the day was also an important component.
Technical Abstract: The plant resistance to vapor flux, or canopy resistance (rc), of Penman- Monteith evapotranspiration (ET) equations has frequently been modelled by stomatal resistance measurements integrated to canopy level and the 'effective' portion of leaf area index (LAIe) actively transpiring. This research evaluated rc and a plant resistance (rp) for full canopy, irrigated corn (Zea mays L.). They were calculated as a residual of an energy balance equation for vapor flux using lysimetrically measured ET for rc and whole canopy transpiration (T) from sap flow gauges for rp. We modelled rc (rcpred) as rcpred=rppred/LAIe, where rppred was rp described as a function of solar radiation (Rs) and LAIe was a constant calculated as LAIe=rp/rc. During mid-day when T fluxes dominated ET, rc and rp values were generally within 20 s/m of each other. Low light levels of early morning and late afternoon increased rp compared with rc, resulting in a greater reduction in T than in ET and a changing LAIe. The non linear model for rppred was rppred=333.9-9.5*Rs^0.5 (r**2=0.70, RMSE=50.2 s/m). Average LAIe was 1.34 (+/- 1 SD of 0.2 to 1 LAIe), or about 30% of maximum LAI. When rcpred was compared to rc, it produced the relationship of rc=20.8+0.78*rcpred (r**2=0.68, RMSE=30.2 s/m). While Rs can partially model rc, the diurnal changes in LAIe should also be considered.