Effects of spatial and temporal variability in vegetation, soil moisture, and depth of thaw on modeled evaporation estimates in Arctic coastal plain ecosytems

Evapotranspiration (ET) is a key link between the surface energy, carbon and water balances of Arctic tundra ecosystems. Because of the sensitivity of Arctic ecosystems to future change, understanding the links between changes in the surface energy, carbon and water balances are important for predicting the impacts of climate change on the global water, energy and carbon cycles. Given that the ET process is acutely non-linear, using time and space averaged inputs in evaporation models may potentially lead to significant errors. It was hypothesized that heterogeneity associated with permafrost dynamics, soil moisture, and vegetation (vascular/non-vascular) would lead to large uncertainties in model estimates of ET. Therefore, this study investigated the significance of this heterogeneity on modeled ET estimates Arctic Coastal Plain ecosystems. The significance of these effects was investigated using a combination of field based soil moisture measurements and a modified version of the BIOME BGC model. Results indicated that there was substantial variability in soil moisture over small areas which was controlled by a combination of micro- and macro-topography. Modeling results indicated that the BIOME BGC model did not provide good estimates of ET. Therefore, the model was adapted to Arctic coastal plain environments by including: (1) a water storage and vertical drainage/infiltration routine that accounts for permafrost and non-vascular vegetation (mosses), (2) a new representation of energy available at the surface that incorporates standing dead vegetation and ground heat flux, (3) a two step background evaporation routine that simulates both moss and open water evaporation. The modifications resulted in a new model, Arctic BIOME BGC that significantly reduced the random and systematic errors in estimated ET when compared to eddy flux tower measurements. However, the modifications made in Arctic BIOME BGC added complexity and a number of new parameters. The relative importance of these new adaptations and their associated parameters was investigated using a sensitivity analysis. Results from the sensitivity analysis indicated that the model was highly sensitive to the majority of the new parameters indicating that the new process representations added in Arctic BIOME BGC were important for modeling ET in Arctic coastal plain ecosystems.