New flood frequency estimates for the largest river in Norway based on a novel combination of streamflow-, historical- and paleo-data

The Glomma river is the largest in Norway and repeated destructive floods continue to represent a major climate hazard. Area planning and dam safety assessment in Norway, including the large catchment that feeds Glomma, are based on estimates of design flood sizes from 200 to 1000 years return periods despite the fact that most streamflow time series are ≤50 years. Consequently, design flood estimates are subject to sample uncertainty. Other data than streamflow measurements such as historical data and lake sediment cores can be employed not only to increase knowledge about floods, but also to reduce uncertainty in design flood estimates. By merging different data sources, it is possible to reduce the uncertainty associated with flood frequency analysis. The primary objective of this study is to combine systematic- historical and paleo-information in a methodological effort to improve flood frequency analysis.

We approach this ambition by (i) compiling historical flood data from the existing literature, (ii) presenting  high resolution XRF, MS and CT scanning data from a sediment core covering the last 10 000 years, and (iii) combining flood data from systematic streamflow measurements, historical sources and lacustrine sediment cores for estimating design floods and assessing non-stationarities in flood frequency.

Based on the lake sediments from Lake Flyginsjøen, which faithfully records flood events in Glomma, we can estimate flood frequency in a moving window of 50 years. Whenever the discharge is sufficient the floodwater crosses a local threshold and suspended sediments are deposited in the lake, providing information about how flood frequency has changed over the last 10 00 years. 

The lake sediment data shows that past flood frequency is non-stationarity on different time scales. Periods with increased flood activity corresponds broadly to similar timeseries from eastern Norway and also in the Alps on centennial time scales. The flood frequency shows significant non-stationarities within periods with increased flood activity as was the case for the 18th century. The lake data indicates that the major historical flood in 1789 is the largest on record for the last 10 000 years at this site.

The results show that estimation of flood quantiles can benefit from the inclusion of historical and paleodata. The paleodata were in particular useful for evaluating how the flood information in historical data represent flood frequency on longer time scales. Using the frequency of floods obtained from the paleo-flood record resulted in minor changes in design flood estimates.   

This study has shown that the potential advantage of including paleoflood data and we suggest that paleodata has a high potential for detecting links between climate and flood frequency. The data presented here can be used alone, or in combination with paleoflood data from other locations in Norway and Europe, to assess and better understand the potential links between changes in climate and the corresponding changes in flood frequency.