On the relation between antecedent basin conditions and runoff coefficient for European floods

Journal Article (2023)
Author(s)

Christian Massari (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche)

Victor Pellet (Observatoire de Paris, ESTELLUS)

Yves Tramblay (Institut de Recherche pour le Développement)

Wade T. Crow (USDA-ARS Hydrology and Remote Sensing Laboratory)

G. J. Gründemann (TU Delft - Water Resources)

Tristian Hascoetf (Kobe University)

Daniele Penna (University of Florence, Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche)

Sara Modanesi (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche)

Luca Brocca (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche)

More Authors (External organisation)

Research Group
Water Resources
Copyright
© 2023 Christian Massari, Victor Pellet, Yves Tramblay, Wade T. Crow, Gaby J. Gründemann, Tristian Hascoetf, Daniele Penna, Sara Modanesi, Luca Brocca, More Authors
DOI related publication
https://doi.org/10.1016/j.jhydrol.2023.130012
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Christian Massari, Victor Pellet, Yves Tramblay, Wade T. Crow, Gaby J. Gründemann, Tristian Hascoetf, Daniele Penna, Sara Modanesi, Luca Brocca, More Authors
Research Group
Water Resources
Volume number
625
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Abstract

The event runoff coefficient (i.e. the ratio between event runoff and precipitation that originated the runoff) is a key factor for understanding basin response to precipitation events. Runoff coefficient depends on precipitation intensity and duration but also on specific basin geohydrology attributes (including soil type, geology, land cover, topography) and last but not least, antecedent (or pre-storm) conditions (i.e., the amount of water stored in the different hydrological compartments, like the river, groundwater, soil and snowpack). The relation between runoff coefficient and basin pre-storm conditions is critical for flood forecasting, yet, the understanding of where, when and how much basin pre-storm conditions control runoff coefficients is still an open question. Here, we tested the control of basin pre-storm conditions on runoff coefficient for 60620 flood events across 284 basins in Europe. To do so, we derived basin pre-storm conditions from different proxies, namely: antecedent precipitation; surface and root zone soil moisture from hydrological models, reanalyses and land surface models also ingesting satellite observations; pre-storm river discharge, and pre-storm total water storage anomalies. We evaluated the coupling strength between runoff coefficient and pre-storm conditions proxies in relation to five classes of European basins, defined based on land use and soil type (as indexed by the Soil Conservation Service curve number CN), topography, hydrology and long-term climate and tested their ability to explain stormflow volume variability. We found that precipitation explains relatively well the stormflow volumes for both small and large events but not very well the peak discharge, especially for large floods. The runoff coefficient of events shows different distributions for the five different classes and correlates well with deep soil storages (such as root-zone soil moisture and pre-storm total water storage anomalies), pre-storm river discharge, and pre-storm snow water equivalent. Overall, these correlations depend on the class. Poor correlations are found against antecedent precipitation index despite its wide use in the hydrological community. Seasonal and interannual climate variability exert a key role on the coupling strength between runoff coefficient and pre-storm conditions by inducing sharp changes in the correlation with season and climate. These results increase our understanding of the coupling between pre-storm conditions and runoff coefficients. This will aid flood forecasting, hydrological and land surface model calibration, and data assimilation. Furthermore, these findings can help us to better interpret future flood projections in Europe based on expected changes in long and short-term climatic drivers.