Abstract

Soil moisture has a fundamental influence on the processes and functions of tundra ecosystems. Yet, the local dynamics of soil moisture are often ignored, due to the lack of fine resolution, spatially extensive data. In this study, we modelled soil moisture with two mechanistic models, SpaFHy (a catchment-scale hydrological model) and JSBACH (a global land surface model), and examined the results in comparison with extensive growing-season field measurements over a mountain tundra area in northwestern Finland. Our results show that soil moisture varies considerably in the study area and this variation creates a mosaic of moisture conditions, ranging from dry ridges (growing season average 12 VWC%, Volumetric Water Content) to water-logged mires (65 VWC%). The models, particularly SpaFHy, simulated temporal soil moisture dynamics reasonably well in parts of the landscape, but both underestimated the range of variation spatially and temporally. Soil properties and topography were important drivers of spatial variation in soil moisture dynamics. By testing the applicability of two mechanistic models to predict fine-scale spatial and temporal variability in soil moisture, this study paves the way towards understanding the functioning of tundra ecosystems under climate change.