Integrating eco-evolutionary optimality principle and land processes for evapotranspiration estimation

Abstract

Evapotranspiration (ET) plays an important role in land surface processes and global climate. ET cannot be observed directly at a large scale, and its spatial distribution is mainly obtained by ET models at present. However, the application of existing ET models is greatly hampered by a number of plant functional type (PFT)-specific empirical parameters and the difficulty in partitioning the contribution of ET from the canopy and soil. To this end, an eco-evolutionary optimality-based evapotranspiration model (EEOET) was developed in this study with some schemes used in the Noah-MP land surface model. The principle of eco-evolutionary optimality expresses the underlying acclimation/adaption of plants to diverse environments and thus greatly reduces the number of PFT-specific parameters. The Noah-MP provides schemes to partition the energy between the canopy and soil and to calculate photosynthetic and ET resistances. Owing to the above, the EEOET model, which has enhanced mechanisms and fewer PFT-specific parameters, requires inputs of daily land surface temperature, vegetation-related data (leaf area index and fractional vegetation), and soil information (soil texture and soil water content) in addition to routine meteorological data. The model output is daily ET. Global evaluation across 74 FLUXNET sites indicates that the model is capable of reasonably estimating ET for all PFTs and is also comparable to existing models that require more tunable parameters. In addition, the EEOET model is less sensitive to uncertainties in the input data than other models, making it a more robust solution for estimating ET under various conditions.