Can a simpler soil moisture model help assess ozone risks to forest trees?

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Abstract. DO3SE (Deposition of O3 for Stomatal Exchange) is an established model for estimating ozone (O3) deposition, stomatal flux and impacts on a variety of vegetation types across Europe. It is embedded in the EMEP (European Monitoring and Evaluation Programme) photochemical model as a policy tool linking vegetation damage risk to ozone precursor emission scenarios.

A limitation of regional flux-based risk assessments has been the approximation that soil water deficits do not limit ozone flux, because evaluated methods for modelling the deficits and their effects on stomatal conductance (gsto), and ultimately ozone flux, were unavailable. The researchers developed and evaluated a method to estimate soil moisture status and its influence on gsto for various forest tree species.

The soil moisture module uses the Penman-Monteith energy balance method to drive water cycling through the soil-plant-atmosphere system, and empirical data on the relationship between gsto and pre-dawn leaf water status to estimate biological control of transpiration. The researchers tested four methods for estimating this control, from simple methods directly relating soil water content or potential to gsto to more complex ones incorporating hydraulic resistance and plant capacitance that control water flow through plants.

They evaluated the methods against field data on soil water variables, gsto and transpiration for Norway spruce (Picea abies), Scots pine (Pinus sylvestris), birch (Betula pendula), aspen (Populus tremuloides), beech (Fagus sylvatica) and holm oak (Quercus ilex), collected at ten sites across Europe and North America. With the simple empirical methods, model estimates were consistent with observations: the timing and magnitude of soil drying were captured well across all sites, and reductions in transpiration at the onset of drought were predicted with reasonable accuracy. The more complex methods performed less well, with predicted drying cycles consistently underestimating the rate and magnitude of water lost from the soil.

A sensitivity analysis showed that performance depended strongly on local parameterisation of key model drivers, including maximum stomatal conductance, soil texture, root depth and leaf area index. The results suggest that simple methods directly linking gsto to soil water content and potential give adequate estimates of soil moisture and its influence on gsto for assessing potential ozone risks to forest trees across Europe.