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

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.

Atmospheric circulation patterns associated with the variability of River Ammer floods: evidence from observed and proxy data

“…The synoptic-scale pattern associated with Ammer floods (Fig. 2a) is consistent with that provided by Schlemmer et al (2010) and Ionita et al (2015). Moreover, it contains elements of the synoptic-scale patterns associated with debrisflow events in the southern Swiss Alps (Toreti et al, 2013).…”

“…The Vb track is characterized by low-pressure systems moving northeastward from the Adriatic Sea into continental Europe, causing orographic rainfall and potentially severe flooding along the Alpine crest (e.g., Schlemmer et al, 2010) and in central Europe (Ionita et al, 2015). The synoptic-scale pattern associated with Ammer floods (Fig.…”

“…Therefore, the variability and predictability of flood occurrences have been addressed in many research studies (e.g., Jacobeit et al, 2003;Czymzik et al, 2010;Peña et al, 2015;Schillereff et al, 2014;Ionita et al, 2008Ionita et al, , 2015.…”

Links between central Greenland stable isotopes, blocking and extreme climate variability over Europe at decadal to multidecadal time scales

“…They identified regions where the NAO signal in δ 18 O field is stationary and argue that δ 18 O proxies from such regions are good predictors for NAO reconstructions. However, stable predictors for climate indices could be identified systematically through analysis of running correlation maps (Lohmann et al 2005;Ionita et al 2008Ionita et al , 2014. Certainly, the patterns of extreme temperature indices associated with central Greenland δ 18 O variability presented here are specific to the observational period.…”

Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe

“…Despite the predictive limitations, several studies prove skill for seasonal river flow forecasts in different parts of Europe (Wilby et al, 2004;Gámiz-Fortis et al, 2008;Ionita et al, 2012Ionita et al, , 2014. In recent years, multiple region-specific forecast methods and systems have been developed to predict hydrological variables several weeks and months in advance to anticipate water availability in Europe (Olsson et al, 2016;Svensson, 2016;Demirel et al, 2015;Gelfan et al, 2015;Fundel et al, 2013, Jörg-Hess et al, 2015.…”