s u m m a r yCold region hydrological systems exhibit complex interactions with both climate and the cryosphere. Improving knowledge on that complexity is essential to determine drivers of extreme events and to predict changes under altered climate conditions. This is particularly true for cold region flooding where independent shifts in both precipitation and temperature can have significant influence on high flows. This study explores changes in the magnitude and the timing of streamflow in 18 Swedish Sub-Arctic catchments over their full record periods available and a common period . The MannKendall trend test was used to estimate changes in several hydrological signatures (e.g. annual maximum daily flow, mean summer flow, snowmelt onset). Further, trends in the flood frequency were determined by fitting an extreme value type I (Gumbel) distribution to test selected flood percentiles for stationarity using a generalized least squares regression approach.Results highlight shifts from snowmelt-dominated to rainfall-dominated flow regimes with all significant trends (at the 5% significance level) pointing toward (1) lower magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest widespread permafrost thawing and are supported by increasing trends in annual minimum daily flows. Trends in selected flood percentiles showed an increase in extreme events over the full periods of record (significant for only four catchments), while trends were variable over the common period of data among the catchments. An uncertainty analysis emphasizes that the observed trends are highly sensitive to the period of record considered. As such, no clear overall regional hydrological response pattern could be determined suggesting that catchment response to regionally consistent changes in climatic drivers is strongly influenced by their physical characteristics.

Fluvial flood events have substantial impacts on humans, both socially and economically, as well as on ecosystems (e.g., hydroecology and pollutant transport). Concurrent with climate change, the seasonality of flooding in cold environments is expected to shift from a snowmelt-dominated to a rainfall-dominated flow regime. This would have profound impacts on water management strategies, that is, flood risk mitigation, drinking water supply, and hydro power. In addition, cold climate hydrological systems exhibit complex interactions with catchment properties and largescale climate fluctuations making the manifestation of changes difficult to detect and predict.Understanding a possible change in flood seasonality and defining related key drivers therefore is essential to mitigate risk and to keep management strategies viable under a changing climate.This study explores changes in flood seasonality across near-natural catchments in Scandinavia using circular statistics and trend tests. Results indicate strong seasonality in flooding for snowmelt-dominated catchments with a single peak occurring in spring and early summer (March through June), whereas flood peaks are more equally distributed throughout the year for catchments located close to the Atlantic coast and in the south of the study area. Flood seasonality has changed over the past century seen as decreasing trends in summer maximum daily flows and increasing winter and spring maximum daily flows with 5-35% of the catchments showing significant changes at the 5% significance level. Seasonal mean daily flows corroborate those findings with higher percentages (5-60%) of the catchments showing statistically significant changes. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt-dominated to rainfall-dominated with consistent changes towards earlier timing of the flood peak (significant for 25% of the catchments). Regionally consistent patterns suggest a first-order climate control as well as a local second-order catchment control, which causes inter-seasonal variability in the streamflow response.