This paper addresses the identification and evaluation of extreme flood events in the transitional area between western and central Europe in the period 1951–2013. Floods are evaluated in terms of three variants on an extremity index that combines discharge values with the spatial extent of flooding. The indices differ in the threshold of the considered maximum discharges; the flood extent is expressed by a length of affected river network. This study demonstrates that using the index with a higher flood discharge limit changes the floods' rankings significantly. It also highlights the high severity events.
In general, we detected an increase in the proportion of warm half-year floods when using a higher discharge limit. Nevertheless, cold half-year floods still predominate in the lists because they generally affect large areas. This study demonstrates the increasing representation of warm half-year floods from the northwest to the southeast.
Hydrological events, especially floods, are serious natural hazards in western and central Europe (Kundzewicz et al., 2005; Munich Re, 2015). Several extreme floods occurred in western and central Europe, e.g., in August 2002, January 2003, March/April 2006, and June 2013. The last was one of the largest in some river basins over the last 2 centuries (Blöschl et al., 2013).
In addition to river floods, flash floods affect this part of Europe, although these are mostly local events that usually produce less damage (Barredo, 2007). Therefore, we are interested in extensive floods affecting several river basins. Uhlemann et al. (2010) call these floods trans-basin. They are usually triggered by persistent heavy rainfall and/or snowmelt. Differences in the causes of river floods can be detected between the western and central parts of Europe. Western Europe experiences flooding primarily during the cold half of the year due to zonal westerly circulation systems (Caspary, 1995; Jacobeit et al., 2003). Towards the east, warm half-year floods become more frequent. This is largely due to cyclones moving along the Vb pathway described by van Bebber (1891). These cyclones move from the Adriatic in a northeasterly direction (e.g., Nissen et al., 2014), and the “overturning” moisture flux brings warm and moist air into the central part of Europe (Müller and Kašpar, 2010). However, it is not possible to delineate the borders of western and central Europe precisely with respect to differences in their flood events because of a broad transitional zone where both types of flooding occur.
An extremity index is useful for comparing individual flood events and determining their overall extremity. Various indicators and indices are used for the assessment of extreme events (including floods) and in their quantitative comparison. Different approaches are applied because the definition of event extremity is not uniform (Beniston et al., 2007), so various sets of extreme floods have been compiled in individual papers. The assessment of extreme floods is based on the quantification of human and material losses (severity), high discharge values (intensity), peak discharge return periods (rarity), or a combination of these indicators. The ranking of the largest floods can differ depending on which aspect of extremity was evaluated.
An assessment based on flood severity may be a simple way to evaluate a flood's extremity. Barredo (2007) identified major flood events in the European Union between 1950 and 2005 to create a catalog and map of the events. He utilized two simple selection criteria: damage amounting to at least 0.005 % of EU GDP and a number of casualties higher than 70.
Other authors prefer evaluations based on the intensity or rarity of flooding because these aspects better reflect causal natural processes. Some authors classified floods into extremity classes based on the observed water levels (Brázdil et al., 1999; Mudelsee et al., 2003), which is most suitable for long-term pre-instrumental flood records. Water level values for individual flood events are at our disposal due to high water marks, chronicle records or other documents. This type of flood extremity evaluation was applied to the long-term flood records of the Basel gauge station on the Rhine River (Brázdil et al., 1999) and in the Elbe and Oder River basins (Mudelsee et al., 2003).
Additionally, Rodda (2005) used maximum discharges to express flood extremity in the Czech Republic. He considered the ratio of the maximum mean daily discharge to the median annual flood. This was completed for each station and flood event to study the spatial correlations among flood intensities in various basins.
Rarity can be used to compare extreme floods at different
locations, when extremity is defined not by absolute thresholds
(e.g., discharge values), but by relative ones (e.g.,
Comprehensive indicators of flood extremity typically combine
some aspect of extremity or consider other factors, such as the
areal extent or duration of events. When creating these
indicators, researchers attempt to add information about flooding
from all locations where it was observed. The Francou index
Müller et al. (2015) designed a more complicated extremity index using return periods of peak discharges. They present 50 maximum floods in the Czech Republic for the period 1961–2010, which are identified based on the so-called flood extremity index (FEI) (Müller et al., 2015). In addition to the peak discharge return periods, the size of the relevant basin is considered for each location. The authors also suggested extremity indices other than the FEI that are applicable to precipitation events: the weather extremity index (Müller and Kašpar, 2014) and the weather abnormality index. Comparison of these indices with the FEI may aid in examining the relationship between precipitation and flood extremity (Müller et al., 2015).
To analyze the spatial and temporal distribution of floods in Germany, Uhlemann et al. (2010) developed a comprehensive method for the identification and evaluation of major flooding affecting several river basins. They used a time series of mean daily discharges and searched for simultaneously occurring significant discharge peaks comprising individual flood events. Their index accounts for the spatial extent of flooding (expressed by the length of the affected rivers) and discharge peak values exceeding the 2-year return value. The authors present 80 major flood events in Germany from 1952 to 2002.
Subsequently, Schröter et al. (2015) adopted the approach of Uhlemann et al. (2010) and compared several major floods in Germany. Their modified index compiled only those maximum discharges that exceeded the 5-year return value; the discharges were normalized by the respective 5-year return values and weighted by the portion of the affected river length. The final index equals the sum of these values from affected stations. Thus, the indices by Uhlemann et al. (2010) and Schröter et al. (2015) differ only in the threshold of the discharge values entered into the index calculation (2- and 5-year return values, respectively). However, Schröter et al. (2015) presented only the June 2013 flood extremity in comparison with two other major floods in August 2002 and July 1954. Because other major flood events were not presented for comparison, it is not possible to precisely identify the influence of this methodological change on their results.
The main aim of this paper is to present lists of extreme flood events from the period 1951–2013 and describe their spatial and temporal distribution. The flood events are selected on the basis of extremity indices with different thresholds of the considered maximum discharges. The discussion of the role of discharge thresholds in the floods' rankings is a part of the paper. The presented indices are based primarily upon the approach of Uhlemann et al. (2010). Each of the indices combine the flood discharge magnitude with the spatial extent of flooding.
The area of interest might be called “Midwestern” Europe and is basically a transitional area between western and central Europe. It has natural boundaries: the Alps to the south, the Carpathian Mountains and Lesser Poland Upland to the east and the coasts of the North and Baltic seas to the northwest and the north. The area is defined by six main river basins: Rhine, Elbe, Oder, Weser, Ems, and Danube up to Bratislava. As mentioned above, this area is interesting because of a noticeable shift in the seasonality of floods in a west-to-east direction. Due to its heterogeneity and vastness, the area is also convenient for index design assessment when evaluating the extremity of floods affecting several river basins.
Gauge stations in the area of interest. Strahler stream order is distinguished by color.
We used mean daily discharge values at selected stations (for each
day during the period 1951–2013) as a basis when searching for
floods that occurred simultaneously within the study area. Only
data from stations enclosing at least 2500
As a result, 93 gauging stations from seven countries (the Czech
Republic, Slovakia, Poland, Austria, Switzerland, Germany and the
Netherlands) were selected to analyze the time series of mean daily
discharges between 1951 and 2013. The study area is approximately
579 000
The methodology is primarily based upon the approach of Uhlemann et al. (2010). Here, we briefly describe the used methods and we focus mainly on the differences arising from the larger size of the study area.
The first step in this study is the selection of flood peaks at
individual stations. The local maxima within the time series of
mean daily discharges (
For each gauging station, most sets of local maxima are due to
minor flow fluctuations. To select real flood peak discharges, the
local maxima are compared with the 2-year return periods of mean
daily discharges at a station (
A flood event is defined here as a group of time-related
Therefore, we introduce an additional rule for dividing flood
peaks that were identified as time-related but are in fact
associated with different atmospheric causes. If more
Over 150 flood events are identified in the period
1951–2013. Each event can be described by its extent expressed as
a length of affected river network:
Both the spatial extent of floods and the aspect of the discharge magnitudes must be incorporated into an extremity index for evaluating extreme flood events. To demonstrate the role of the threshold of the considered maximum discharges, we defined three index variants with differences in discharge limits and applied them to the identified flood events.
Generally, the index is derived from
Finally, we select 30 major floods according to each of the three
extremity index variants. As the total study period covers
63
Relationship between the proportion of the affected river length
(
The floods are sorted based on whether they occurred in the colder
or warmer half of the year; the decisive day for classification
is the mean point of the event. The mean day is found using the
method of directional statistics, which was originally designed for
the analysis of flood seasonality (Black and Werritty,
1997). However, it is applicable to the determination of the mean day
of the flood event. The method transforms the day of
The identified floods have various natures, from 1- or 2-day
flood events caused mainly by localized convective precipitation
to long-lasting and extensive cold half-year floods. Although the
cold half-year events hit mostly larger areas than warm half-year
floods, the flood of June 2013 was the largest one with respect to
the affected river network. Flows higher than a 2-year return
period occurred at about 13 700
List of 30 major floods according to the
As we mainly focus on extensive floods affecting more river basins
at the same time, three lists of 30 major floods are created
according to values of the index variants (Table 1). The events
are listed with respect to the
The 30 largest flood events in the study area from 1951 to 2013
according to
The occurrence of discharges equal to or greater than 2-, 5- and
10-year flood at individual stations during each of the 30 maximum floods
according to the
Figure 2 depicts differences among the extremity index variants in
terms of their dependence on the proportion of the affected river
length
Figure 3 indicates large spatial differences among the flood
events. It is clear that the warm half-year floods relate more to
the Oder, Danube and Elbe River basins. The Rhine River basin is less
represented and, in the Weser and Ems River basins, the warm
half-year floods rarely occur. A more comprehensive insight into
this issue is provided in Fig. 4. The occurrence of flood
discharges in the basins is demonstrated on 30 maximum floods
according to
Seasonal distribution of 30 maximum floods according to
Interannual variability of 30 major floods according to
Spatial distribution of 30 maximum floods according to
Floods of the cold half-year are generally better represented
among the major flood events. The seasonal distribution is quite
similar for
Major floods do not occur regularly over time. Some clusters of
flood events are apparent in Fig. 6, which presents the
distribution of major floods between 1951 and 2013. The July flood
of 1954 is the first recorded flood in the period
examined. A significant accumulation of flooding is apparent in
the 1980s and from 1993 to 2006. By contrast, a long period
without major floods occurred at the beginning of the 1960s. The
first 15
Generally, there are more major floods in the second half of the
period, which applies to both index variants. It seems that the
number of events increases mainly from the 1980s, as is their extremity.
However, the extremity according to
Regarding the spatial distribution of floods, Fig. 3 demonstrates that floods during the warm half-year relate more to the Oder, Danube and Elbe River basins. Warm half-year floods are less frequent in the Rhine River basin, and they occur very rarely in the Weser and Ems River basins, where cold half-year floods dominate. This is confirmed by Fig. 7, which depicts the frequency of 30 major floods in both half-years within individual gauge stations.
In general, the number of cold half-year floods decreases towards the southeast, whereas the number of warm half-year floods increases in the same direction. Regardless of the variant of the extremity index, there are regions affected by extreme floods only in one part of the year. This is true for the Weser, Ems, and the lower part of the Rhine River basin including the Main (cold half-year) and most of the Alpine rivers (warm half-year). By contrast, other regions are prone to extreme floods in both the cold and warm halves of the year: the Oder, Elbe and Danube River basins, apart from the Alpine tributaries. However, a low number of identified floods does not exclude their occurrence at individual stations. It means that floods in a given location are not part of large-scale cold or warm half-year floods, which were evaluated in this study.
This paper addresses the evaluation of major flood events in the
transitional area between western and
central Europe in the period
1951–2013. Major floods are defined according to the value of
a flood extremity index. We created three variants of the index
with differences in terms of discharge thresholds. We were
motivated by Uhlemann et al. (2010) and Schröter et al. (2015),
who used similar flood extremity indices, with only a difference in
the threshold of the discharge values entered into the
calculation. Uhlemann et al. (2010) used a 2-year flow threshold, while
Schröter et al. (2015) chose a higher limit of a 5-year
flow, thus making these studies incomparable. In this paper, we
introduce the differences that arise in the resulting lists of
major floods when we use indices with different discharge
thresholds. We selected the value of
Generally, the lists of major floods are quite similar to the list of German trans-basin floods presented by Uhlemann et al. (2010) because Germany covers more than half of the area studied in this work. The duration of “identical” floods is slightly different, as is their ranking. This is mainly due to the different size of the area of interest. Schröter et al. (2015) used an index similar to Uhlemann et al. (2010), but the authors only offered a comparison of the extremity of three summer flood events: the floods of 1954, 2002 and 2013. The flood event of 2013 is reported as the largest, followed by the flood of 1954. In this paper, the flood of August 2002 is always more extreme than the flood of 1954, regardless of the index variant used, because of the differences in the extent of the area of interest. Nevertheless, the flood of June 2013 remains on top of the lists.
We can also compare our results with those of Barredo (2007), who
provided a set of 21 large European river floods compiled according
to the amount of damage caused. Six of these floods affected our
area of interest; all are included in the set of major floods
according to
Regarding the seasonal distribution of major flood events, the predominance of cold half-year floods is apparent in both lists. Uhlemann et al. (2010) showed the same result. By contrast, floods during the warm half of the year dominate the list of the 30 major floods in the Czech Republic by Müller et al. (2015). This may be due to the fact that the occurrence of warm half-year floods is increasing from the northwest to the southeast in the studied area.
The temporal distribution of major flood events during the period
between 1951 and 2013 is rather uneven. There are certain clusters
in terms of the occurrence of major floods. Some periods of reduced
or increased frequencies of major flooding are identical to the
results of other papers (Uhlemann et al., 2010; Müller et al.,
2015). For example, we found these identical trends: a higher
frequency of major floods in the 1980s and a decline in the number
of identified floods in the 1990s. The 5-year period between
2006 and 2010 is different, however, because it is a period with
a higher frequency of major flooding in Müller
et al. (2015). The increase in major flooding in the second half of
the period is again consistent with the findings of Uhlemann
et al. (2010). However, it remains unclear whether this is a trend
or just a part of a cycle. In recent years, there has been a discussion
about increasing flood risk due to ongoing climate change and
anthropogenic modifications of the landscape and especially
floodplains. On a local level, the runoff is influenced by the
changes in land use, riverbeds or the surface drainage, which often
lead to runoff acceleration and steeper flood waves (Langhammer and
Vilímek, 2008). By contrast, the construction of water reservoirs can
reduce a flood. The Slapy Dam at the Vltava River
was only partially filled before the flood of July 1954. Unaffected
discharge of 2920
The temporal characteristics of major flood events are also connected with the opposite extreme. The historical records show that an extreme flood was followed by a great drought in same cases (Brázdil et al., 2005). Lloyd-Hughes and Saunders (2002) conclude that the greater pan-European droughts occurred in the early 1950s and the 1990s; lesser drought incidence is apparent in the 1980s. For the analysis, they used the Palmer drought severity index and standardized precipitation indices calculated at different timescales.
At a shorter timescale, the wetness conditions are crucial for flood initiation; antecedent soil moisture can highly influence the flood extremity. The June 2013 flood was the case when great precipitation amounts coincided with high antecedent soil moisture and produced an exceptional flood (Blöschl et al., 2013). The effect of antecedent wetness conditions depends on the season and a type or an extremity of flood. High antecedent soil moisture relates in particular to cold half-year floods, while the signal varies in warm half-year cases (Nied et al., 2013).
Further research on the topic of extreme floods will examine the related meteorological conditions. A comprehensive evaluation of antecedent wetness conditions, causal atmospheric circulation, the consequent precipitation and the flow response is needed. A comparison of major floods with precipitation and circulation extremes would be useful for a better understanding of the causes of extensive floods, which affect several river basins.
Mean daily discharge data were mainly provided by the
Global Runoff Data Centre (GRDC, 2017). Some data are accessible via the
Austrian server eHYD (2016) at
The authors declare that they have no conflict of interest.
This work was supported by the Czech Science Foundation (grant number 17-23773S). Acknowledgements also belong to the Global Runoff Data Centre and the Czech Hydrometeorological Institute for providing runoff data. Edited by: Vazken Andréassian Reviewed by: two anonymous referees