Geomorphological factors predict water quality in boreal rivers

Water quality is the outcome of numerous landscape factors in the catchment. In addition to land use, soil deposits, bedrock and topography are central in different catchment processes and thus important in predicting water quality. In this study, we explored the influence of geomorphological factors at the catchment scale on water quality in 32 boreal rivers in Finland. Water quality was studied through total phosphorus, total nitrogen, pH and water colour, whereas geomorphological factors covered variables from topography, bedrock and surficial ground material (Quaternary soil deposits). Spearman's rank correlation test was used to study the correlations between variables. The relationship between water quality and geomorphology was analysed using novel multivariate methods by fitting of geomorphological vectors and smooth surfaces onto a non‐metric multidimensional scaling (NMDS) scattergram. Hierarchical partitioning (HP) was used to assess the relative importance of geomorphological variables on water quality. Quaternary soil deposits, especially the covers of clay‐silt and till soils, were important factors in relation to phosphorus and nitrogen based on both NMDS and HP analyses. For example, clay‐silt cover explained over 40% of the variation in these nutrients according to HP. The variation in river water pH was best explained by the covers of sand and open bedrock terrain as well as by catchment topography. Geomorphological variables differed in their effect and relative significance, and thus several geomorphological attributes need to be considered when examining variation in water quality. In conclusion, these results demonstrate that geomorphological factors can be used to predict physical–chemical water quality in a cost‐efficient manner in boreal rivers. NMDS was successfully applied in water quality analyses at the catchment scale. Copyright © 2014 John Wiley & Sons, Ltd.     

Modelling spatio-temporal soil moisture dynamics in mountain tundra

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.