Evaluation of the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) model performance over Mediterranean maquis ecosystem

The Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) model is used to predict energy, water and carbon fluxes over a Mediterranean maquis site located in North-Western Sardinia (Italy) and the model performance is evaluated. Flux simulations are compared with Eddy Covariance field measurements collected from 2004 to 2007. The site experiences a drought season during the summer months in which the vegetation becomes water stressed. Results from the months of January, April, and July are analyzed to demonstrate the model behavior in different environmental conditions. In general, simulated and observed fluxes matched when both the thermal and moisture regime are optimal. During the July water stress period the model underestimated latent heat and carbon fluxes due to a strong stress response linked to soil properties and plant physiological characteristics. The selection of values for key parameters, e.g. maximum ideal photosynthetic capacity (RUBISCO), wilting point, soil water content, and root and leaf area ratio, is crucial to obtain close agreement between simulated and observed fluxes. The model was designed so that the most sensitive parameters are measurable quantities. Using the ACASA model to predict energy and mass fluxes between the vegetation and atmosphere appears promising in this context, and it could significantly improve our ability to estimate fluxes for use in future studies.

Research highlights
► We applied the ACASA higher order closure model over sparse canopy for the first time.
► We modeled energy and mass fluxes over Mediterranean maquis ecosystem.
► Model performances under wet and drought conditions have been evaluated.
► We validated model output with long term Eddy Covariance measurements.
► We found that soil moisture is the main factor affecting model results.