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. The Glomma river is the largest in Norway with a catchment area of 154 450 km2. People living near the shores of this river are frequently exposed to destructive floods that impair local cities and communities. Unfortunately, design flood predictions are hampered by uncertainty since the standard flood records are much shorter than the requested return period and also the climate is expected to change in the coming decades. Here we combine systematic- historical and paleo-information in an effort to improve flood frequency analysis and better understand potential linkages to both climate and non-climatic forcing. Specifically, we (i) compile historical flood data from the existing literature, (ii) produce high resolution X-ray fluorescence (XRF), Magnetic Susceptibility (MS) and Computed Tomography (CT) scanning data from a sediment core covering the last 10 300 years, and (iii) integrate these data sets in order to better estimate design floods and assess non-stationarities. Based on observations from Lake Flyginnsjoen, receiving sediments from Glomma only when it reaches a certain threshold, we can estimate flood frequency in a moving window of 50 years across millennia revealing that past flood frequency is non-stationary on different time scales. We observe that periods with increased flood activity (4000–2000 years ago and Stor-Ofsen ) flood being the largest on record for the last 10 300 years at this site. Using the identified non-stationarities in the paleoflood record allowed us to estimate non-stationary design floods. In particular, we found that the design flood was 23 % higher during the 18th century than today and that long-term trends in flood variability are intrinsically linked to the availability of snow in late spring linking climate change to adjustments in flood frequency.

New flood frequency estimates for the largest river in Norway based on the combination of short and long time series