Articles | Volume 25, issue 10
https://doi.org/10.5194/hess-25-5535-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5535-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characteristics and process controls of statistical flood moments in Europe – a data-based analysis
David Lun
CORRESPONDING AUTHOR
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
Alberto Viglione
Department of Environment, Land and Infrastructure Engineering,
Politecnico di Torino, Turin, Italy
Miriam Bertola
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
Jürgen Komma
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
Juraj Parajka
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
Peter Valent
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
Department of Land and Water Resources Management, Faculty of Civil
Engineering, Slovak University of Technology, Bratislava, Slovakia
Günter Blöschl
Institute of Hydraulic Engineering and Water Resources Management,
Vienna University of Technology, Vienna, Austria
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Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
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Lovrenc Pavlin, Borbála Széles, Peter Strauss, Alfred Paul Blaschke, and Günter Blöschl
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We compared the dynamics of streamflow, groundwater and soil moisture to investigate how different parts of an agricultural catchment in Lower Austria are connected. Groundwater is best connected around the stream and worse uphill, where groundwater is deeper. Soil moisture connectivity increases with increasing catchment wetness but is not influenced by spatial position in the catchment. Groundwater is more connected to the stream on the seasonal scale compared to the event scale.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
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We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Miriam Bertola, Alberto Viglione, Sergiy Vorogushyn, David Lun, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1347–1364, https://doi.org/10.5194/hess-25-1347-2021, https://doi.org/10.5194/hess-25-1347-2021, 2021
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We estimate the contribution of extreme precipitation, antecedent soil moisture and snowmelt to changes in small and large floods across Europe.
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Mattia Neri, Juraj Parajka, and Elena Toth
Hydrol. Earth Syst. Sci., 24, 5149–5171, https://doi.org/10.5194/hess-24-5149-2020, https://doi.org/10.5194/hess-24-5149-2020, 2020
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One of the most informative ways to gain information on ungauged river sections is through the implementation of a rainfall-runoff model, exploiting the information collected in gauged catchments in the study area. This study analyses how the performances of different model regionalisation approaches are influenced by the informative content of the available regional data set, in order to identify the methods that are more suitable for the data availability in the region.
Cited articles
Amponsah, W., Ayral, P.-A., Boudevillain, B., Bouvier, C., Braud, I., Brunet, P., Delrieu, G., Didon-Lescot, J.-F., Gaume, E., Lebouc, L., Marchi, L., Marra, F., Morin, E., Nord, G., Payrastre, O., Zoccatelli, D., and Borga, M.: Integrated high-resolution dataset of high-intensity European and Mediterranean flash floods, Earth Syst. Sci. Data, 10, 1783–1794, https://doi.org/10.5194/essd-10-1783-2018, 2018.
Azen, R. and Budescu, D. V.: The dominance analysis approach for comparing
predictors in multiple regression, Psychol. Meth., 8, 129, https://doi.org/10.1037/1082-989x.8.2.129, 2003.
Bayliss, A. C. and Jones, R. C.: Peaks-over-Threshold Flood Database: Summary
Statistics and Seasonality Institute of Hydrology, Wallingford, UK, 1993.
Bednorz, E.: Snow cover in eastern Europe in relation to temperature,
precipitation and circulation, Int. J. Climatol., 24, 591–601, 2004.
Berghuijs, W. R., Woods, R. A., Hutton, C. J., and Sivapalan, M.: Dominant
flood generating mechanisms across the United States, Geophys. Res. Lett., 43, 4382–4390, 2016.
Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J., and Kirchner, J.
W.: The relative importance of different flood-generating mechanisms across
Europe, Water Resour. Res., 55, 4582–4593, 2019.
Bertola, M., Viglione, A., Lun, D., Hall, J., and Blöschl, G.: Flood trends in Europe: are changes in small and big floods different?, Hydrol. Earth Syst. Sci., 24, 1805–1822, https://doi.org/10.5194/hess-24-1805-2020, 2020.
Blöschl, G. and Sivapalan M.: Process controls on regional flood frequency: Coefficient of variation and basin scale, Water Resour. Res., 33, 2967–2980, 1997.
Blöschl, G., Sivapalan, M., Wagener, T., Savenije, H., and Viglione, A. (Eds.).: Runoff prediction in ungauged basins: synthesis across processes,
places and scales, Cambridge University Press, Cambridge, 2013.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A., Merz, B.,
Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M., Canjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fi-ala, K., Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J., Ledvinka, O., Macdonald, N., MavrovaGuirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živkovic, N.: Changing climate shifts timing of European floods, Science, 357, 588–590, https://doi.org/10.1126/science.aan2506, 2017.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A. P., Merz, B., Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M., Canjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fi-ala, K., Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J., Ledvinka, O., Macdonald, N., MavrovaGuirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živkovic, N.: Changing climate both increases and decreases European river floods, Nature, 573, 108–111, https://doi.org/10.1038/s41586-019-1495-6, 2019.
Bobee, B. and Robiataille, R.: Correction of bias in the estimation of the
coefficient of skewness, Water Resour. Res., 11, 851–854, 1975.
Boorman, D. B., Hollis, J. M., and Lilly, A.: Hydrology of soil types: a
hydrologically-based classification of the soils of United Kingdom, Institute of Hydrology, Wallingford, UK, 1995.
Brath, A., Montanari, A., and Moretti, G.: Assessing the effect on flood
frequency of land use change via hydrological simulation (with uncertainty),
J. Hydrol., 324, 141–153, 2006.
Burn, D. H.: Catchment similarity for regional flood frequency analysis
using seasonality measures, J. Hydrol., 202, 212–230, 1997.
Carney, M. C.: Bias Correction to GEV Shape Parameters Used to Predict
Precipitation Extremes, J. Hydrol. Eng., 21, 04016035, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001416, 2016.
Chaoimh, Ú. N.: European snow cover and its influence on spring and
summer temperatures, Geogr. J., 164, 41–54, 1998.
Copernicus: Copernicus Land Monitoring Service, available at: https://land.copernicus.eu/, last access: 6 October 2021.
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J., and Jones, P. D.: An ensemble version of the E-OBS temperature and precipitation data sets, J. Geophys. Res.-Atmos., 123, 9391–9409, (data available at: https://www.ecad.eu/download/ensembles/download.php, last access: 6 October 2021), 2018.
Cressie, N. A.: Statistics for spatial data, John Wiley and Sons. Inc., New
York, 1993.
Danielson, J. J. and Gesch, D. B.: Global multi-resolution terrain elevation data 2010 (GMTED2010), US Department of the Interior, US Geological Survey [data set], https://doi.org/10.3133/ofr20111073, 2011.
Desai, S. and Ouarda, T. B. M. J.: Regional hydrological frequency analysis at ungauged sites with random forest regression, J. Hydrol., 594, 125861,
https://doi.org/10.1016/j.jhydrol.2020.125861, 2021.
Didovets, I., Lobanova, A., Bronstert, A., Snizhko, S., Maule, C. F., and
Krysanova, V.: Assessment of climate change impacts on water resources in
three representative Ukrainian catchments using eco-hydrological modelling,
Water, 9, 204, https://doi.org/10.3390/w9030204, 2017.
England Jr., J. F., Cohn, T. A., Faber, B. A., Stedinger, J. R., Thomas Jr., W. O., Veilleux, A. G., Kiang, J. E., and Mason Jr., R. R.: Guidelines for
determining flood flow frequency, in: Bulletin 17C (ver. 1.1, May 2019), book 4, chap. B5, US Geological Survey Techniques and Methods, US Geological Survey, Reston, VA, p. 148, https://doi.org/10.3133/tm4B5, 2019.
ESDAC: https://esdac.jrc.ec.europa.eu, last access: 6 October 2021.
Fan, Y. and Van Den Dool, H.: Climate Prediction Center global monthly soil moisture data set at 0.5 resolution for 1948 to present, J. Geophys. Res.-Atmos., 109, D10102, https://doi.org/10.1029/2003JD004345, 2004.
Farquharson, F. A. K., Meigh, J. R., and Sutcliffe, J. V.: Regional flood
frequency analysis in arid and semi-arid areas, J. Hydrol., 138, 487–501, https://doi.org/10.1016/0022-1694(92)90132-F, 1992.
Fatichi, S., Ivanov, V. Y., and Caporali, E.: Investigating interannual
variability of precipitation at the global scale: Is there a connection with
seasonality?, J. Climate, 25, 5512–5523, 2012.
Fischer, S., Schumann, A., and Schulte, M.: Characterisation of seasonal flood types according to timescales in mixed probability distributions, J. Hydrol., 539, 38–56, 2016.
Gaál, L., Szolgay, J., Kohnová, S., Parajka, J., Merz, R., Viglione,
A., and Blöschl, G.: Flood timescales: Understanding the interplay of
climate and catchment processes through comparative hydrology, Water Resour. Res., 48, W04511, https://doi.org/10.1029/2011WR011509, 2012.
Gaál, L., Szolgay, J., Kohnová, S., Hlavčová, K., Parajka,
J., Viglione, A., Merz, R., and Blöschl, G.: Dependence between flood peaks and volumes: a case study on climate and hydrological controls, Hydrolog. Sci. J., 60, 968–984, 2015.
Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A.,
Blaškovicová, L., Blöschl, G., Borga, M., Dumitrescu, A.,
Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnova, S., Koutroulis, A.,
Marchi, L., Matreata, S., Medina, V., Preciso, E., Sempere-Torres, D.,
Stancalie, G., Szolgay, J., Tsanis, I., Velasco, D., and Viglione, A.: A
compilation of data on European flash floods, J. Hydrol., 367, 70–78, 2009.
Gibbons, J. D. and Chakraborti, S.: Nonparametric Statistical Inference, CRC Press, Boca Raton, 650 pp., 2010.
Gioia, A., Iacobellis, V., Manfreda, S., and Fiorentino, M.: Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distribution, Hydrol. Earth Syst. Sci., 16, 937–951, https://doi.org/10.5194/hess-16-937-2012, 2012.
Giorgi, F., Bi, X., and Pal, J. S.: Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day
climate (1961–1990), Clim. Dynam., 22, 733–756, 2004.
Griffis, V. W. and Stedinger, J. R.: Log-Pearson Type 3 distribution and its application in flood frequency analysis. III: Sample skew and weighted skew estimators, J. Hydrol. Eng., 14, 121–130, 2009.
Grillakis, M. G., Koutroulis, A. G., Komma, J., Tsanis, I. K., Wagner, W., and Blöschl, G.: Initial soil moisture effects on flash flood generation – A comparison between basins of contrasting hydro-climatic conditions, J.
Hydrol., 541, 206–217, 2016.
Hall, J., Arheimer, B., Aronica, G. T., Bilibashi, A., Bohác, M.,
Bonacci, O., Borga, M., Burlando, P., Castellarin, A., Chirico, G. B., Claps, P., Fiala, K., Gaál, L., Gorbachova, L., Gül, A., Hannaford, J., Kiss, A., Kjeldsen, T., Kohnová, S., Koskela, J. J., Macdonald, N., Mavrova-Guirguinova, M., Ledvinka, O., Mediero, L., Merz, B., Merz, R., Molnar, P., Montanari, A., Osuch, M., Parajka, J., Perdigão, R. A. P., Radevski, I., Renard, B., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Blöschl, G.: A European Flood Database: facilitating comprehensive flood research beyond administrative boundaries, P. Int. Ass. Hydrol. Sci., 370, 89–95, 2015.
Hayashi, F.: Econometrics, Princeton University Press, Princeton, 2000.
Helsel, D. R., Hirsch, R. M., Ryberg, K. R., Archfield, S. A., and Gilroy, E. J.: Statistical methods in water resources, in: Supersedes USGS Techniques of
Water-Resources Investigations, book 4, chapter A3, version 1.1, US Geological Survey Techniques and Methods, US Geological Survey, p. 458, https://doi.org/10.3133/tm4a3, 2020.
Hofstätter, M., Lexer, A., Homan, M., and Blöschl, G.: Large-scale
heavy precipitation over central Europe and the role of atmospheric cyclone
track types, Int. J. Climatol., 38, e497–e517, https://doi.org/10.1002/joc.5386, 2018.
Hosking, J. R. M. and Wallis, J. R.: Regional frequency analysis: an approach based on L-moments, Cambridge University Press, Cambridge, 2005.
Iacobellis, V., Claps, P., and Fiorentino, M.: Climatic control on the
variability of flood distribution, Hydrol. Earth Syst. Sci., 6, 229–238,
https://doi.org/10.5194/hess-6-229-2002, 2002.
Kemter, M., Merz, B., Marwan, N., Vorogushyn, S., and Blöschl, G.: Joint trends in flood magnitudes and spatial extents across Europe, Geophys. Res. Lett., 47, e2020GL087464, https://doi.org/10.1029/2020GL087464, 2020.
Kendall, M. and Stuart, A.: The advanced theory of statistics, Griffin, London, 1969.
Laaha, G. and Blöschl, G.: A comparison of low flow regionalisation methods – catchment grouping, J. Hydrol., 323, 193–214, 2006.
Lilly, A., Boorman, D. B., and Hollis, J. M.: The development of a hydrological classification of UK soils and the inherent scale changes, in: Soil and Water Quality at Different Scales, Springer, Dordrecht, 299–302, 1998.
Marchi, L., Borga, M., Preciso, E., and Gaume, E.: Characterisation of selected extreme flash floods in Europe and implications for flood risk
management, J. Hydrol., 394, 118–133, https://doi.org/10.1016/j.jhydrol.2010.07.017, 2010.
Maréchal, D. and Holman, I. P.: Development and application of a soil
classification-based conceptual catchment-scale hydrological model, J. Hydrol., 312, 277–293, 2005.
Merz, R. and Blöschl, G.: A process typology of regional floods, Water
Resour. Res., 39, 1340, https://doi.org/10.1029/2002WR001952, 2003.
Merz, R. and Blöschl, G.: Process controls on the statistical flood moments – a data based analysis, Hydrol. Process., 23, 675–696, 2009.
Merz, R., Blöschl, G., and Parajka, J.: Spatio-temporal variability of
event runoff coefficients, J. Hydrol., 331, 591–604, 2006.
Miller, J. D. and Brewer, T.: Refining flood estimation in urbanized catchments using landscape metrics, Landscape Urban Plan., 175, 34–49, 2018.
Mimikou, M. and Gordios, J.: Predicting the mean annual flood and flood
quantiles for ungauged catchments in Greece, Hydrolog. Sci. J., 34, 169–184, 1989.
National Weather Service: Climate News, available at: https://www.cpc.ncep.noaa.gov/, last access: 6 October 2021.
Nováaky, B.: Climatic effects on the runoff conditions in Hungary, Earth
Surf. Proc. Land., 16, 593–599, 1991.
Ohmura, A.: Physical basis for the temperature-based melt-index method, J. Appl. Meteorol., 40, 753–761, 2001.
Pallard, B., Castellarin, A., and Montanari, A.: A look at the links between
drainage density and flood statistics, Hydrol. Earth Syst. Sci., 13, 1019–1029, https://doi.org/10.5194/hess-13-1019-2009, 2009.
Panagos, P., Van Liedekerke, M., Jones, A., and Montanarella, L.: European Soil Data Centre: Response to European policy support and public data
requirements, Land Use Policy, 29, 329–338, https://doi.org/10.1016/j.landusepol.2011.07.003, 2012.
Parajka, J. and Blöschl, G.: MODIS-based snow cover products, validation, and hydrologic applications, in: Multiscale Hydrologic Remote Sensing: Perspectives and Applications, edited by: Chang, N.-B. and Hong, Y., CRC Press, 2012.
Paretti, N. V., Kennedy, J. R., Turney, L. A., and Veilleux, A. G.: Methods
for estimating magnitude and frequency of floods in Arizona, developed with
unregulated and rural peak-flow data through water year 2010, No. 2014-5211, US Geological Survey, 2014.
Parrett, C., Veilleux, A., Stedinger, J. R., Barth, N. A., Knifong, D. L.,
and Ferris, J. C.: Regional skew for California, and flood frequency for
selected sites in the Sacramento-San Joaquin River Basin, based on data
through water year 2006, US Geological Survey, 2011.
Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C., and Sanderson, B. M.: Precipitation variability increases in a warmer climate, Scient. Rep., 7, 1–9, 2017.
Penna, D., Tromp-van Meerveld, H. J., Gobbi, A., Borga, M., and Dalla Fontana, G.: The influence of soil moisture on threshold runoff generation processes in an alpine headwater catchment, Hydrol. Earth Syst. Sci., 15, 689–702, https://doi.org/10.5194/hess-15-689-2011, 2011.
Perdigão, R. A. P. and Blöschl, G.: Spatiotemporal flood sensitivity to annual precipitation: Evidence for landscape-climate coevolution, Water Resour. Res., 50, 5492–5509, https://doi.org/10.1002/2014WR015365, 2014.
Peschke, G. and Sambale, C.: Hydrometric approaches to gain a better understanding of saturation excess overland flow, IAHS Publ., 258, 13–22, 1999.
Picciafuoco, T., Morbidelli, R., Flammini, A., Saltalippi, C., Corradini,
C., Strauss, P., and Blöschl, G.: A pedotransfer function for field-scale
saturated hydraulic conductivity of a small watershed, Vadose Zone J., 18, 190018, https://doi.org/10.2136/vzj2019.02.0018, 2019.
Rahman, A., Charron, C., Ouarda, T. B. M. J., and Chebana, F.: Development of regional flood frequency analysis techniques using generalized additive models for Australia, Stoch. Environ. Res. Risk A., 32, 123–139, https://doi.org/10.1007/s00477-017-1384-1, 2018.
Ries, F., Schmidt, S., Sauter, M., and Lange, J.: Controls on runoff generation along a steep climatic gradient in the Eastern Mediterranean, J. Hydrol.: Reg. Stud., 9, 18–33, 2017.
Roekaerts, M.: The biogeographical regions map of Europe, in: Basic principles of its creation and overview of its development, European Environment Agency, Copenhagen, available at: https://www.eea.europa.eu/data-and-maps/data/biogeographical-regions-europe-3
(ast access: 6 October 2021), 2002.
Rogger, M., Pirkl, H., Viglione, A., Komma, J., Kohl, B., Kirnbauer, R., Merz, R., and Blöschl, G.: Step changes in the flood frequency curve: Process controls, Water Resour. Res., 48, W05544, https://doi.org/10.1029/2011WR011187, 2012.
Rogger, M., Viglione, A., Derx, J., and Blöschl, G.:. Quantifying effects of catchments storage thresholds on step changes in the flood frequency curve, Water Resour. Res., 49, 6946–6958, 2013.
Rogger, M., Agnoletti, M., Alaoui, A., Bathurst, J. C., Bodner, G., Borga, M., Chaplot, V., Gallart, F., Glatzel, G., Hall, J., Holden, J., Holko, L., Horn, R., Kiss, A., Kohnova, S., Leitinger, G., Lennartz, B., Parajka, J., Perdigão, R., Peth, S., Plavcová, L., Quinton, J. N., Robinson, M.,
Salinas, J. L., Santoro, A., Szolgay, J., Tron, S., van den Akker, J. J. H.,
Viglione, A., and Blöschl, G.: Land-use change impacts on floods at the
catchment scale: Challenges and opportunities for future research, Water Resour. Res., 53, 5209–5219, https://doi.org/10.1002/2017WR020723, 2017.
Rosbjerg, D., Blöschl, G., Burn, D. H., Castellarin, A., Croke, B.,
DiBaldassarre, G., Iacobellis, V., Kjeldsen, T. R., Kuczera, G., Merz, R.,
Montanari, A., Morris, D., Ouarda, T. B. M. J., Ren, L., Rogger, M., Salinas, J. L., Toth, E., Viglione, A.: Prediction of floods in ungauged basins, in: Runoff Prediction in Ungauged Basins – Synthesis across Processes, Places and Scales, chap. 9, edited by: Blöschl, G., Sivapalan, M., Wagener, T., Viglione, A., and Savenije, H., Cambridge University Press, Cambridge, UK, 135–162, 2013.
Salinas, J. L., Laaha, G., Rogger, M., Parajka, J., Viglione, A., Sivapalan,
M., and Blöschl, G.: Comparative assessment of predictions in ungauged
basins – Part 2: Flood and low flow studies, Hydrol. Earth Syst. Sci., 17, 2637–2652, https://doi.org/10.5194/hess-17-2637-2013, 2013.
Salinas, J. L., Castellarin, A., Kohnová, S., and Kjeldsen, T. R.: Regional parent flood frequency distributions in Europe – Part 2: Climate and scale controls, Hydrol. Earth Syst. Sci., 18, 4391–4401, https://doi.org/10.5194/hess-18-4391-2014, 2014.
Scherrer, S., Naef, F., Faeh, A. O., and Cordery, I.: Formation of runoff at the hillslope scale during intense precipitation, Hydrol. Earth Syst. Sci., 11, 907–922, https://doi.org/10.5194/hess-11-907-2007, 2007.
Schmocker-Fackel, P., Naef, F., and Scherrer, S.: Identifying runoff processes on the plot and catchment scale, Hydrol. Earth Syst. Sci., 11, 891–906, https://doi.org/10.5194/hess-11-891-2007, 2007.
Serago, J. M. and Vogel, R. M.: Parsimonious nonstationary flood frequency
analysis, Adv. Water Resour., 112, 1–16, 2018.
Sivapalan, M.: Process complexity at hillslope scale, process simplicity at the watershed scale: is there a connection?, Hydrol. Process., 17, 1037–1041, 2003.
Sivapalan, M., Blöschl, G., Merz, R., and Gutknecht, D.: Linking flood
frequency to long-term water balance: Incorporating effects of seasonality, Water Resour. Res., 41, W06012, https://doi.org/10.1029/2004WR003439, 2005.
Smith, J. A.: Representation of basin scale in flood peak distributions, Water Resour. Res., 28, 2993–2999, 1992.
Šraj, M., Viglione, A., Parajka, J., and Blöschl, G.: The influence of non-stationarity in extreme hydrological events on flood frequency estimation, J. Hydrol. Hydromech., 64, 426–437, https://doi.org/10.1515/johh-2016-0032, 2016.
Sun, D., Yang, H., Guan, D., Yang, M., Wu, J., Yuan, F., Jin, C., Wang, A., and Zhang, Y.: The effects of land use change on soil infiltration capacity in China: A meta-analysis, Sci. Total Environ., 626, 1394–1401, 2018.
Tarasova, L., Merz, R., Kiss, A., Basso, S., Blöschl, G., Merz, B., Viglione, A., Plötner, S., Guse, B., Schumann, A., Fischer, S., Ahrens, B., Anwar, F., Bárdossy, A., Bühler, P., Haberlandt, U., Kreibich, H., Krug, A., Lun, D., Müller-Thomy, H., Pidoto, R., Primo, C., Seidel, J., Vorogushyn, S., and Wietzke, L.: Causative classification of river flood events, Wiley Interdisciplin. Rev.: Water, 6, e1353, https://doi.org/10.1002/wat2.1353, 2019.
Trabucco, A. and Zomer, R.: Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2, figshare [data set], https://doi.org/10.6084/m9.figshare.7504448.v3, 2018.
Troch, P. A., Lahmers, T., Meira A., Mukherjee, R., Pedersen, J. W., Roy, T., and Valdées-Pineda R.: Catchment coevolution: A useful framework for improving predictions of hydrological change?, Water Resour. Res., 51, 4903–4922, https://doi.org/10.1002/2015WR017032, 2015.
tuwhydro: europe_floods, GitHub [data set], available at: https://github.com/tuwhydro/europe_floods, last access: 6 October 2021.
Umlauf, N. and Kneib, T.: A primer on Bayesian distributional regression,
Statist. Model., 18, 219–247, 2018.
Viglione, A., Merz, R., and Blöschl, G.: On the role of the runoff coefficient in the mapping of rainfall to flood return periods, Hydrol. Earth Syst. Sci., 13, 577–593, https://doi.org/10.5194/hess-13-577-2009, 2009.
Viglione, A., Chirico, G. B., Woods, R., and Blöschl, G.: Generalised
synthesis of space–time variability in flood response: An analytical
framework, J. Hydrol., 394, 198–212, https://doi.org/10.1016/j.jhydrol.2010.05.047, 2010.
Viglione, A., Merz, R., Salinas, J. L., and Blöschl, G.: Flood frequency hydrology: 3. A Bayesian analysis, Water Resour. Res., 49, 675–692, 2013.
Vogt, J., Soille, P., De Jager, A., Rimaviciute, E., Mehl, W., Foisneau, S., Bodis, K., Dusart, J., Paracchini, M., and Haastrup, P.: A pan-European river and catchment database, European Commission [data set], https://doi.org/10.2788/35907, 2007.
Wallis, J. R., Matalas, N. C., and Slack, J. R.: Just a moment!, Water Resour. Res., 10, 211–219, 1974.
Wang, W., Li, H.-Y., Leung, L. R., Yigzaw, W., Zhao, J., Lu, H., Deng, Z.,
Demisie, Y., and Blöschl, G.: Nonlinear filtering effects of reservoirs
on flood frequency curves at the regional scale, Water Resour. Res., 53, 8277–8292, https://doi.org/10.1002/2017WR020871, 2017.
Weingartner, R., Barben, M., and Spreafico, M.: Floods in mountain areas – an overview based on examples from Switzerland, J. Hydrol., 282, 10–24, 2003.
Weisberg, S.: Applied linear regression, John Wiley & Sons, Hoboken, NJ,
352 pp., 2005.
Xoplaki, E., Gonzalez-Rouco, J. F., Luterbacher, J., and Wanner, H.: Wet
season Mediterranean precipitation variability: influence of large-scale
dynamics and trends, Clim. Dynam., 23, 63–78, 2004.
Ye, L., Gu, X., Wang, D., and Vogel, R. M.: An unbiased estimator of coefficient of variation of streamflow, J. Hydrol., 594, 125954, https://doi.org/10.1016/j.jhydrol.2021.125954, 2020.
Zaman, M. A., Rahman, A., and Haddad, K.: Regional flood frequency analysis in arid regions: A case study for Australia, J. Hydrol., 475, 74–83, 2012.
Short summary
We investigate statistical properties of observed flood series on a European scale. There are pronounced regional patterns, for instance: regions with strong Atlantic influence show less year-to-year variability in the magnitude of observed floods when compared with more arid regions of Europe. The hydrological controls on the patterns are quantified and discussed. On the European scale, climate seems to be the dominant driver for the observed patterns.
We investigate statistical properties of observed flood series on a European scale. There are...