Predicting the June 2013 European Flooding Based on Precipitation, Soil Moisture, and Sea Level Pressure

M. Ionita Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany

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M. Dima Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany, and Faculty of Physics, University of Bucharest, Bucharest, Romania

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G. Lohmann Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany

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P. Scholz Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany

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N. Rimbu Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany, and Faculty of Physics, University of Bucharest, and Climed Norad, Bucharest, Romania

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Abstract

Over recent decades Europe has experienced heavy floods, with major consequences for thousands of people and billions of euros worth of damage. In particular, the summer of 2013 flood in central Europe showed how vulnerable modern society is to hydrological extremes and emphasized once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture, and sea level pressure. Moreover, the model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by also incorporating the amount of precipitation recorded during the days prior to the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be relevant for other rivers also, depending on their location and their climatic background.

Denotes Open Access content.

Corresponding author address: Monica Ionita, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bussestrasse 24, D-27570 Bremerhaven, Germany. E-mail: monica.ionita@awi.de

Publisher’s Note: This article was revised on 14 April 2015 to include the open access designation that was missing when originally published.

Abstract

Over recent decades Europe has experienced heavy floods, with major consequences for thousands of people and billions of euros worth of damage. In particular, the summer of 2013 flood in central Europe showed how vulnerable modern society is to hydrological extremes and emphasized once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture, and sea level pressure. Moreover, the model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by also incorporating the amount of precipitation recorded during the days prior to the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be relevant for other rivers also, depending on their location and their climatic background.

Denotes Open Access content.

Corresponding author address: Monica Ionita, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bussestrasse 24, D-27570 Bremerhaven, Germany. E-mail: monica.ionita@awi.de

Publisher’s Note: This article was revised on 14 April 2015 to include the open access designation that was missing when originally published.

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