Abstract
Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere1. These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe2. Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe3, because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results—arising from the most complete database of European flooding so far—suggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century4,5, suggesting that climate-driven changes are already happening and supporting calls for the consideration of climate change in flood risk management.
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Data availability
The flood discharge data from the data holders/sources listed in Extended Data Table 1 that were used in this paper are available at https://github.com/tuwhydro/europe_floods. The precipitation and temperature data from the E-OBS dataset are available at www.ecad.eu/download/ensembles/ensembles.php. The CPC soil moisture data can be downloaded from www.esrl.noaa.gov/psd.
Code availability
The code used for the trend estimation and the extreme value analysis can be downloaded from https://github.com/tuwhydro/europe_floods.
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Acknowledgements
This work was supported by the ERC Advanced Grant ‘FloodChange’ project (number 291152), the Horizon 2020 ETN ‘System Risk’ project (number 676027), the DFG ‘SPATE’ project (FOR 2416), the FWF ‘SPATE’ project (I 3174) and a Russian Foundation for Basic Research (RFBR) project (number 17-05-41030 rgo_a). The data analysis was performed in R using the supporting packages automap, boot, lattice, maptools, ncdf4, plyr, raster, RColorBrewer, rgdal and rworldmap. The authors acknowledge the involvement in the data screening process of C. Álvaro Díaz, I. Borzì, E. Diamantini, K. Jeneiová, M. Kupfersberger, S. Mallucci and S. Persiano during their stays at the Vienna University of Technology. We thank L. Gaál and D. Rosbjerg for contacting Finnish and Danish data holders, respectively; B. Renard (France), W. Rigott (South Tyrol, Italy), G. Lindström (Sweden) and P. Burlando (Switzerland) for assistance in preparing and/or providing data or metadata from their respective regions. We acknowledge all flood data providers listed in Extended Data Table 1.
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Contributions
G.B. and J. Hall designed the study and wrote the first draft of the paper. G.B. initiated the study. J. Hall collated the database with the help of most of the co-authors and conducted the analyses. A.V. conducted the MCMC analysis. G.B., J. Hall, A.V., R.A.P.P., J.P. and B.M. interpreted the results in the context of underlying geophysical mechanisms. J.P. compiled the catchment boundaries. D.L. contributed to the statistical analysis. M. Boháč, I.Č., A.K., S.K., O.L., M.M.-G., R.M., P.M., I.R., J.L.S., J.S. and N.Ž. interpreted the results in central Europe. G.T.A., A.B., O.B., M. Borga, A.C., G.B.C., P.C., D.G., A.M., L.M., M.Š., E.V. and K.Z. interpreted the results in southern Europe. B.A., J.J.K. and D.W. interpreted the results in northern Europe. J. Hannaford, S.H., T.R.K., N.M., C.M. and E.S. interpreted the results in western Europe. N.F., L.G., A.G., M.K., M.O. and V.O. interpreted the results in eastern Europe. All authors contributed to framing and revising the paper.
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Extended data figures and tables
Extended Data Fig. 1 Map of European study area.
a, Elevation (in metres above sea level), main rivers and lakes. b, Locations of the hydrometric stations analysed. Open and full circles indicate stations with more than 30 years (n = 3,738) and more than 40 years (n = 2,835) of flood discharge data, respectively.
Extended Data Fig. 2 Observed trends of river flood discharges in Europe (1960–2010).
a, Points show local trends (n = 2,370), with larger points indicating statistically significant trends (significance level α = 0.1). Background pattern represents regional trends. Blue indicates increasing flood discharges and red denotes decreasing flood discharges. Rectangles indicate hotspot areas as in Fig. 2, Extended Data Fig. 3, Extended Data Table 2c. b, Uncertainties of the trends in terms of standard deviation. Points show local uncertainties. The background pattern represents regional uncertainties at the scale of a block size of 200 × 200 km2. Units of both panels are per cent of mean per decade.
Extended Data Fig. 3 Flood trends as in Fig. 1 and Extended Data Fig. 2, but using fewer stations.
a, Only stations with significant trends are used (n = 664). b, Only stations with distances larger than 50 km from each other are used (n = 745).
Extended Data Fig. 4 Long-term temporal evolution of timing of floods and their drivers for seven hotspots in Europe.
a, Northern United Kingdom; b, western France; c, southern Germany and western Czechia; d, northern Iberia; e, central Balkans; f, southern Finland; g, western Russia. Shown are the timing of observed floods (green), the seven-day maximum precipitation (purple), the snowmelt index (orange) and the maximum monthly soil moisture (blue). Lines show the median timing and shaded bands indicate the variability of timing within the year (±0.5 circular standard deviations). All data were subjected to a circular ten-year moving-average filter. Vertical axes show month of the year (June to May).
Extended Data Fig. 5 Seven-day maximum precipitation (1960–2010).
a, Long-term mean (in millimetres per day). b, Trends in precipitation (per cent of mean per decade), for which larger points indicate statistically significant trends (α = 0.1). Blue indicates increasing precipitation and red denotes decreasing precipitation.
Extended Data Figure 6 Spring (January to April) mean air temperatures (1960–2010).
a, Long-term mean (in degrees Celsius); b, trends in temperatures (in degrees Celsius per decade), with larger points indicating statistically significant trends (α = 0.1). Red indicates increasing temperature and blue represents decreasing temperature. JFMA, January to April.
Extended Data Fig. 7 Annual maximum monthly soil moisture (1960–2010).
a, Long-term mean (in millimetres). b, Trends in maximum soil moisture (per cent of mean per decade), for which larger points indicate statistically significant trends (α = 0.1). Blue indicates increasing soil moisture and red denotes decreasing soil moisture.
Extended Data Fig. 8 Estimated return period in 2010 for the 1960 100-year flood discharge.
Points show local return periods (n = 2,370), with larger points indicating agreement of the 5th and the 95th percentiles of the uncertainty distribution in the sign of change. The background pattern represents regional return periods. Blue indicates lower return periods, representing increasing flood discharges, and red indicates higher return periods, representing decreasing flood discharges. This figure provides a continental overview and does not replace national-scale and local studies, for which more detailed information may be available.
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Blöschl, G., Hall, J., Viglione, A. et al. Changing climate both increases and decreases European river floods. Nature 573, 108–111 (2019). https://doi.org/10.1038/s41586-019-1495-6
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DOI: https://doi.org/10.1038/s41586-019-1495-6
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