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There is growing concern that rapidly changing climate in high latitudes may generate significant geomorphological changes that could mobilise floodplain sediments and carbon; however detailed investigations into the bank erosion process regimes of high latitude rivers remain lacking. Here we employ a combination of thermal and RGB colour time‐lapse photos in concert with water level, flow characteristics, bank sediment moisture and temperature, and topographical data to analyse river bank dynamics during the open‐channel flow period (the period from the rise of the spring snowmelt flood until the autumn low flow period) for a subarctic river in northern Finland (Pulmanki River). We show how variations of bank sediment temperature and moisture affect bank erosion rates and locations, how bank collapses relate to fluvial processes, and elucidate the seasonal variations and interlinkages between the different driving processes. We find that areas with high levels of groundwater content and loose sand layers were the most prone areas for bank erosion. Groundwater seeping caused continuous erosion throughout the study period, whereas erosion by flowing river water occurred during the peak of snowmelt flood. However, erosion also occurred during the falling phase of the spring flood, mainly due to mass failures. The rising phase of the spring flood therefore did not affect the river bank as much as its peak or receding phases. This is explained because the bank is resistant to erosion due to the prevalence of still frozen and drier sediments at the beginning of the spring flood. Overall, most bank erosion and deposition occurrences were observed during the low flow period after the spring flood. This highlights that spring melt, while often delivering the highest discharges, may not be the main driver of bank erosion in sub‐arctic meandering rivers. © 2019 John Wiley & Sons, Ltd.

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This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resultant vegetation models successfully predict riparian vegetation patterns (Rho = 0.8 for total species richness, AUC = 0.97 for distribution) and highlight differences between eight functional species groups (Rho 0.46–0.84; AUC 0.79–0.93; functional group-specific effects). In our study setting, replacing the laser scanning-based and hydraulic modelling-based variables with a proxy variable elevation did not significantly weaken the models. However, using directly measured and modelled variables allows relating species patterns to e.g. stream power or the length of the flood-free period. Substituting these biologically relevant variables with proxies mask important processes and may reduce the transferability of the results into other sites. At the local scale, the amount of litter is a highly important driver of total species richness, distribution and abundance patterns (relative influences 49, 72 and 83%, respectively) and across all functional groups (13–57%; excluding lichen species richness) in the sub-arctic river valley. Moreover, soil organic matter and soil water content shape vegetation patterns (on average 16 and 7%, respectively). Fluvial disturbance is a key limiting factor only for lichen, bryophyte and dwarf shrub species in this environment (on average 37, 6 and 10%, respectively). Fluvial disturbance intensity is the most important component of disturbance for most functional groups while the length of the disturbance-free period is more relevant for lichens. We conclude that striving for as accurate quantifications of environmental drivers as possible may reveal important processes and functional group differences and help anticipate future changes in vegetation. Mobile laser scanning, high-resolution digital elevation models and hydraulic modelling offer useful methodology for improving correlative vegetation models.