Direct Penman–Monteith parameterization for estimating stomatal conductance and modeling sap flow

Abstract

The novel approach for direct parameterization of the Penman–Monteith equation was developed to compute diurnal courses of stand canopy conductance from sap flow. The Penman–Monteith equation of evaporation is often combined with sap flow measurements to describe canopy transpiration and stomatal conductance. The traditional approach involves a two-step calculation. In the first step, stomatal conductance is computed using an inverted form of Penman–Monteith equation. The second step correlates these values with environmental factors. In this work, we present an improved approach for direct parameterization of the Penman–Monteith equation developed to compute diurnal courses of stand canopy conductance (g c) from sap flow. The main advantages of this proposed approach versus using the classical approach are: (1) the calculation process is faster and involves fewer steps, (2) parameterization provides realistic values of canopy conductance, including conditions of low atmospheric vapor pressure deficit (D), whereas the traditional approach tends to yield unrealistic values for low D and (3) the new calculation method does not require enveloping curves to describe dependence of g c on D and thus avoids subjective data selection but it still allows to visualize separable responses of g c to environmental drivers (i.e., global radiation and vapor pressure deficit). The proposed approach was tested to calculate g c and to model the sap flow of a high mountain Pinus canariensis forest. The new calculation method permitted us to describe the stand canopy conductance and stand sap flow in sub-hour resolution for both day and night conditions. Direct parameterization of the Penman–Monteith approach as implemented in this study proved sufficiently sensitive for detecting diurnal variation in g c and for predicting sap flow from environmental variables under various atmospheric evapotranspirative demands and differing levels of soil water availability.