Validation and parametrization of the soil moisture index for stomatal conductance modelling and flux-based ozone risk assessment of Mediterranean plant species

Artikel i vetenskaplig tidskrift, 2024

The Mediterranean region chronically experiences high levels of tropospheric ozone (O3) that can affect the health of vegetation. However, limiting plant growing conditions, such as low soil moisture, may restrict the stomatal phytotoxic ozone dose (POD) absorbed by vegetation, modulating O3 detrimental effects. Atmospheric chemistry transport models that estimate POD for O3 risk assessment of effects on vegetation species, such as the European Monitoring and Evaluation Programme (EMEP), have adopted the soil moisture index (SMI) to consider the influence of soil moisture on POD. The objectives of this study were the parametrization and validation of the SMI effect on stomatal conductance (gs) for improving the POD estimation and O3 risk assessment for different vegetation species under water-limiting growing conditions, using field data collected in Italy and Spain and a literature review. The modelled SMI from EMEP proved to be a good indicator of soil moisture dynamics across sites and years, although it showed a general tendency to overestimate soil moisture availability for plants, particularly in the driest seasons. New parametrizations derived for modelling SMI effects on gs under Mediterranean conditions proposed in this study stress the importance of using species-specific parameters for species showing contrasting water-saving strategies in contrast of the current approach of using a simple relation between SMI and gs for all the species. Furthermore, gs modelling parametrizations based on soil water potential (SWP) were found to be more suitable than SMI for local scale estimation of POD under water-limiting conditions. Further consideration of rooting depth and distribution will be required in the future to determine the soil depth at which the soil moisture should be measured in POD modelling, since these features represent one of the most important uncertainties affecting the estimation of POD that could not be addressed with the present database.