Land-surface evapotranspiration derived from a first-principles primary production model

Abstract

We propose an application of eco-evolutionary optimality theory in the context of monitoring and modelling physical land-surface processes. Evapotranspiration (ET) links the water and carbon cycles in the atmosphere, hydrosphere, and biosphere. We develop an ET modelling framework based on the hypothesis that canopy conductance acclimates to plant growth conditions so that the total costs of maintaining carboxylation and transpiration capacities are minimized. This is combined with the principle of co-ordination between the light- and Rubisco-limited rates of photosynthesis to predict gross primary production (GPP). Transpiration (T) is predicted from GPP via canopy conductance. No plant type- or biome-specific parameters are required. ET is estimated from T by calibrating a site-specific (but time-invariant) ratio of modelled average T to observed average ET. Predicted seasonal cycles of GPP were well supported by (weekly) GPP data at 20 widely distributed eddy-covariance flux sites (228 site-years), with correlation coefficients (r) = 0.81 and root-mean-square error (RMSE) = 18.7 gC/week and Nash-Sutcliffe efficiency coefficient (NSE) = 0.61. Seasonal cycles of ET were also well supported, with r = 0.85, RMSE = 5.5 mm week-1 and NSE = 0.66. Estimated T/ET ratios (0.52-0.92) showed significant positive relationships to radiation, precipitation and green vegetation cover and negative relationships to temperature and modelled T (r = 0.84). Although there are still uncertainties to be improved in the current framework, particularly in estimating T/ET, we see the application of eco-evolutionary principles as a promising direction for water resources research. HighlightsO_LIBuilding an evapotranspiration estimation framework based on a priori primary productivity model (the P model). C_LIO_LIAssessing the contribution of environmental indicators to the ratio of transpiration to evapotranspiration. C_LIO_LIProving the reliability of this approach to estimate evapotranspiration. C_LI