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Journal of Hydrology 404 (2011) 50–66
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Journal of Hydrology
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Hydrological signatures of flood trends on German rivers: Flood frequencies,flood heights and specific stages
Helge Bormann a,⇑, Nicholas Pinter b,1, Simon Elfert c,2
a University of Oldenburg, Department of Biology and Environmental Sciences, Uhlhornsweg 84, 26121 Oldenburg, Germanyb Southern Illinois University, Carbondale, Department of Geology, Mailcode 4324, Carbondale, IL 62901, USAc University of Bremen, Department of Geosciences, Klagenfurter Straße, 28359 Bremen, Germany
a r t i c l e i n f o
Article history:Received 15 September 2010Received in revised form 21 March 2011Accepted 8 April 2011Available online 16 April 2011This manuscript was handled byA. Bardossy, Editor-in-Chief, with theassistance of Efrat Morin, Associate Editor
Keywords:Flood magnificationGerman riverTrend analysis on stage and dischargeSpecific gauge analysisEnvironmental changeRiver engineering
0022-1694/$ - see front matter � 2011 Elsevier B.V. Adoi:10.1016/j.jhydrol.2011.04.019
⇑ Corresponding author. Now at University of SEngineering, Siegen, Germany. Tel.: +49 441 7984459
E-mail addresses: [email protected] (H. Bormann), [email protected] (N. Pinter)(S. Elfert).
1 Tel.: +1 618 453 7375; fax: +1 618 453 7393.2 Tel.: +49 421 21865288; fax: +49 421 21865309.
s u m m a r y
Climate change, land-use change and in-stream river engineering affect trends in river discharges andriver stages, and distinguishing such overlapping contributions is a major challenge in hydrologictime-series analysis. In this study, a systematic investigation of river stages and discharges was carriedout for 78 stream gauges of rivers in Germany. We analysed the available times series for trends in floodstages, flood discharges, flood frequency and in stage-discharge relationships over time. With respect toannual maximum discharges and flood frequencies, no significant trends could be identified consistentlythroughout the study area. Significant discharge trends were identified at a number of stations, however,and tended to be catchment-specific. In contrast, trends in flood stages tended to be gauge-dependent, asstages over time are influenced by changes in local rating curves and thus by local and reach-scale chan-nel modifications. Specific gauge analysis is a suitable tool for analysing such changes. No significanttrends in specific stages over time were identified at most of the investigated gauges, generally parallel-ing the trend-based stage results at the same sites. Nevertheless, we could identify several river gaugeswith significant decreasing specific-gauge trends (e.g., Danube at Ingolstadt, Elbe at Magdeburg, Weser atIntschede) and others with significant increasing trends (e.g., Elbe at Dresden, Ems at Greven, Fulda atGrebenau, Leine at Herrenhausen). The identified trends were small compared with trends identifiedon heavily engineered rivers in the US driven by local changes in the channel (e.g., incision or wing dikegroyne construction) or changes on the floodplain (e.g., dike displacement or changing land use in theflood plain). The trends in discharges and stages documented here have contributed to past changes inflood frequency and intensity on German rivers.
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1. Introduction
Recent research has focused on assessing the impacts of diverseenvironmental and anthropogenic changes upon rivers. Both cli-mate change (e.g., Petrow and Merz, 2009) and basin land use(change) are key factors controlling the hydrological behaviour ofcatchments and their discharge dynamics (Hörmann et al., 2005).Additionally, flood stages can be affected by changes in thestage-discharge relationship and therefore be influenced by localin-stream river modifications such as engineering measures (Pinteret al., 2006a,b). Pinter et al. (2006a) identified site-specific trends
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iegen, Department of Civil; fax: +49 441 7983769..de, helge.bormann@uni-sie-, [email protected]
along the Rhine and Mississippi rivers and compared the contrast-ing river histories and management strategies to explain differ-ences between the two river systems.
Following several severe floods in Germany during the past twodecades (e.g., Rhine 1993 and 1995; Odra 1997; Elbe 2002 and2006; Danube 1999, 2002 and 2006), mass media as well as scien-tists have debated the relative contributions of climate and/oranthropogenic processes to those floods. Mudelsee et al. (2003,2004) did not see any clear increase in flood occurrence rates forthe Elbe and Odra rivers. Instead, based on long-term time series,they found decreasing winter flood occurrence, while summerfloods showed no trends. Petrow and Merz (2009) analysed trendsin flood peaks for German rivers between 1951 and 2002, fromwhich they identified significant changes in flood behaviour inwestern, southern and central Germany (mostly increasing floodindicators). In northeast Germany, in contrast, they did not identifyflood-related changes. As Radziejewski and Kundzewicz (2004)noted, however, failure to identify statistically significant trendsin hydrological time series is different from proving that no trends
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 51
are present. Trends may indeed be present but may not meet thethreshold for significance depending on the magnitude ofthe trends, the interannual variability in the data, the length ofthe time series, as well as the choice of start- and end-datesof the time series.
Other studies have analysed trends in flood indicators in differ-ent parts of the world. For example, Douglas et al. (2000), Burnand Hag Elnur (2002) and Adamowski and Bocci (2001) foundfew and only heterogeneous (some increasing and some decreas-ing) trends in maximum annual floods in North America (US andCanada). This previous result contrasts with the findings of someother researchers in the US (e.g., Groisman et al., 2001; Ya et al.,2004). In the UK, Robson et al. (1998) did not find any significanttrends for annual time series, whereas in western Australia,Franks (2002) identified a marked increase in floods after 1945.In summary, flood-related trends might be detectable in some re-gions of the world, but they are often non-uniform, and trends atmany stations are not statistically significant (Kundzewicz et al.,2005; Svensson et al., 2005).
All these studies investigated flood discharge (e.g., time series ofannual maxima or peak-over-threshold flows), but few studieshave rigorously analysed the related flood stages. Stage, orwater-surface elevation, is traditionally viewed as a secondary fac-tor, dependent largely upon discharge and therefore typically notthe focus of independent time-series analysis. The public, however,perceives flood events most urgently in terms of flood stage andnot (only) in terms of discharge. Different factors affect local ratingcurves and therefore stages over time, so that stage time series canprovide discharge-independent information. For the Rhine River,Pinter et al. (2006b) found changes due to channel incision andto river engineering over the past �100 years; these changes onthe Rhine were small compared to much larger alteration ofstage-discharge relationships on navigable rivers in the US (Pinteret al., 2006a, 2008, 2010).
In this study, long time series of stage and discharge data from78 river gauges in Germany are analysed for trends in flood fre-quency, peak discharge, peak stage and stage-discharge relation-ship. According to Blöschl and Montanari (2010), simultaneouslyanalysing many catchments in a large region should help to reduceselection bias with respect to flood trends. These analyses involvedanalysis of flood stages in addition to discharges and investigatedriver engineering effects by quantifying changes in the rating curveusing specific-gauge analysis. We looked for both local changesand broader regional patterns in order to try to explore the causalmechanisms driving the identified changes.
2. Material and methods
2.1. Data
For this study, daily river flows and stages from 78 German rivergauges (Table 1 and Fig. 1) were obtained from the Global RunoffData Centre (GRDC, Koblenz; discharges) and from the Bundesan-stalt für Gewässerkunde (Koblenz; stages). For all gauges, time ser-ies of either stage or discharge or both variables have a minimumlength of about 50 years. Before performing the analysis, all datasets were checked for completeness, outliers, and consistency ingauge datum and location. Changes in gauge datum were correctedin order to guarantee homogeneity and inter-comparability in thestage records. Based on information from Bundesamt für Gewäs-serkunde hydrologic yearbooks and specific-gauge analysis (seebelow), discontinuities were detected and corrected. Afterwards,annual maximum values were extracted from the pre-checkedtime series. Finally, we tested the homogeneity of the time seriesapplying Pettit’s test (Pettit, 1979) and the standard normal homo-geneity test (SNHT; Alexandersson, 1986).
2.2. Statistical tools for data analysis
Three different reconnaissance tools, following the statisticaltests used in Pinter et al. (2006a), were applied in order to testfor trends in the available time series. Comparing and contrastingthe results of the different tests can suggest or exclude some causalmechanisms driving observed trends. For example, while statisti-cally significant trends in peak discharges may suggest climaticand/or land-use change, changes in flood stages (in the absenceof significant trends in discharge) suggest in-stream river engi-neering that have altered the local rating curve at that location.
2.2.1. Trends in flood frequencyTrends in flood frequency over time were investigated using
chi2 test on two-way contingency tables of designated flood versusnon-flood years (Pinter et al., 2006a). For each gauge station, thedaily time series was screened for the top 1% flood stages. Any yearcontaining at least one value within the top 1% stages was countedas a flood year, and any year without one such value was desig-nated as a non-flood year. The 1% threshold has no physical mean-ing but distinguishes well between years with relatively highstages vs. those without. For each station, the full period of recordwas then divided in equally in half, and the number of flood yearscompared in the first versus the second halves of the total record ateach gauge. Finally, the significance of the difference in the numberof flood and non-flood years was assessed by applying the chi2 test(Table 2; P 6 5%).
2.2.2. Trends in flood heightsTrends in maximum annual flood stages and discharges were
determined by ordinary least-square linear regression (OLS; Pinteret al., 2006a). At each river gauge, a linear regression was fit to theavailable time-series data. For each time series, a null hypothesiswas tested that the linear fit had a slope that was indistinguishablefrom zero (i.e., no change over time). These null hypotheses wereassessed using rejection thresholds of both P < 0.10 and P < 0.05.
Since OLS method requires normality which often is not guaran-teed for extreme events, the non-parametric Mann–Kendall test(Kendall, 1975) was performed to further test trend significance.In addition, the non-parametric Sen’s estimator (Sen, 1968) wasapplied to detect linear trends.
2.2.3. Specific gauge analysisUnlike the two approaches above, specific gauge analysis (e.g.,
Jemberie et al., 2008) tests for changes in stage-discharge relation-ship over time. By identifying stages associated with (contingentupon) different specific discharges and then holding those dis-charges constant through time, changes in the related stages arefiltered. In this study, specific-gauge analysis was performed forall gauge stations and all years for which both stage and dischargedata were available. Data were separated by year in order to deter-mine annual stage-discharge (rating) relationships. For each year,stage was regressed against discharge using the best fitting model(in most cases, 2nd-order polynomial or semi-log polynomialregressions). Those years were excluded from the analysis forwhich no model provided a goodness of fit (coefficient of determi-nation: r2) of at least 0.95. The equation of each model was tabu-lated along with minimum and maximum measured dischargesof the respective year. Finally, several discharge values were se-lected and associated specific stages were calculated for all yearsof the gauge-specific record based on the annual regression models.No stage-discharge regression relationship was extrapolatedbeyond the observed maxima and minima of any given year.
Table 1Time periods for which records of daily stage and discharge are available for gauges on German rivers.
River Gauge Period: discharge Period: stage River Gauge Period: discharge Period: stage
Aller Celle 1890–2005 1971–2005 Main Schweinfurt 1844–2005 1970–2005Marklendorf 1940–2005 1937–2005 Steinbach 1964–2005 1970–2005Rethem 1940–2005 1942–2005 Trunstadt 1975–2005 1970–2005
Diemel Helminghausen 1940–2005 1974–2005 Würzburg 1823–2005 1823–2005Danube Achleiten 1900–2005 1980–2005 Mosel Cochem 1900–2006 1823–2005
Hofkirchen 1900–2004 1974–2004 Perl 1974–2006 1965–2006Ingolstadt 1924–2005 1963–2005 Trier 1930–2006 1966–2006Oberndorf 1975–2005 1976–2005 Nahe Grolsheim 1935–2004 1993–2004Pfelling 1960–2004 1976–2004 Neckar Lauffen 1948–2004 1970–2004Schwabelweiss 1930–2004 1974–2004 Plochingen 1918–2004 1971–2004
Eder Affoldern 1940–2005 1980–2005 Rockenau 1984–2003 1982–2003Schmittlotheim 1930–2005 1970–2005 Odra Eisenhüttenstadt 1940–2004 1940–2004
Elbe Aken 1935–2005 1925–2005 Hohensaaten-Finow 1958–2004 1958–2004Barby 1899–2003 1899–2003 Rhine Andernach 1930–2002 1819–2005Dresden 1852–2005 1852–2005 Düsseldorf 1930–2001 1872–2001Magdeburg 1930–2004 1930–2004 Kaub 1930–2002 1856–2002Neu-Darchau 1874–2005 1970–2005 Cologne 1816–2000 1816–2000Tangermünde 1965–2005 1960–2005 Mainz 1930–2002 1930–2002Torgau 1935–2004 1935–2004 Maxau 1921–2001 1889–2001Wittenberg 1950–2003 1925–2003 Rees 1930–2001 1814–2001Wittenberge 1899–2005 1895–2005 Speyer 1950–2001 1948–2001
Ems Dalum 1964–2003 1964–2003 Worms 1820–2002 1890–2002Greven 1940–2003 1971–2003 Saale Calbe-Grizehne 1931–2005 1990–2005Rheine 1930–2004 1971–2004 Spree Große Tränke 1992–2000 1994–2000Versen 1941–2005 1915–2005 Spremberg 1960–1989 1970–1989
Fulda Grebenau 1950–2005 1950–2005 Treene Treia 1931–2004 1945–2004Guntershausen 1920–2005 1920–2005 Unstrut Laucha 1945–1989 1970–1989Rotenburg 1920–2005 1920–2005 Werra Allendorf 1941–2005 1971–2005
Havel Ketzin 1936–2005 1990–2005 Heldra 1950–2005 1971–2005Rathenow 1951–2005 1899–2005 Letzer Heller 1940–2005 1988–2005
Inn Wasserburg 1826–2005 1970–2005 Weser Bodenwerder 1839–2005 1839–2005Kinzig Schwaibach 1921–2000 1889–1979 Dörverden 1953–2005 1971–2005Kocher Neuenstadt 1929–1981 1929–1979 Hannoversch-Münden 1831–2005 1830–2005Lahn Leun 1935–2004 1969–2004 Intschede 1857–2005 1856–2005Leine Herrenhausen 1940–2005 1915–2005 Karlshafen 1940–2005 1878–2005
Schwarmstedt 1940–2005 1940–2005 Liebenau 1953–2005 1971–2005Main Frankfurt 1963–2005 1976–2005 Porta 1935–2005 1936–2005
Kemmern 1958–2006 1963–2006 Vlotho 1820–2005 1820–2005Kleinheubach 1958–2005 1950–2005 Wahmbeck 1940–2005 1941–2005
52 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
3. Historical changes in German river catchments
In order to relate hypothesized trends in flooding to environ-mental or anthropogenic changes, a general review of historicchanges in climate, land use and river regulation is required.
3.1. Observed climate change
Schönwiese (1999) identified a homogenous positive trend of0.5–1.0 �C in German temperatures through the 20th century. Thistemperature trend was confirmed by Gerstengarbe and Werner(2008) and Bormann (2010), analysing climate data from the Ger-man Weather Service (DWD, Offenbach, www.dwd.de). In contrast,changes in precipitation have been observed to vary regionally andseasonally (Schönwiese, 1999; Pfister et al., 2004; Gerstengarbeand Werner, 2008; Trömel and Schönwiese, 2008; Bormann,2010). Schönwiese (1999) identified an increase in winter precipi-tation of 10–30% in Germany between 1961 and 1990, while sum-mer rainfall mainly decreased. Trömel and Schönwiese (2008)found no significant trends for the Elbe catchment in winter forthe period from year 1901 to 2000, although an increase in winterprecipitation was found for the upper Rhine and Danube catch-ments (15–30%). Increases in winter precipitation for the Weserand Ems catchments were estimated at 5–20%. For summer peri-ods, Trömel and Schönwiese (2008) identified a decrease in precip-itation for the Elbe catchment of 5–20%, while for all other regions,
precipitation trends depended on the estimation technique (gener-alised decomposition versus ordinary trends) rather than on the re-gion. For the Rhine catchment, Pinter et al. (2006b) identifiedincreases in extreme precipitation events through the 20th cen-tury. Bardossy and Caspary (1990) and Caspary (1995) assumedthat changes in atmospheric circulation patterns across Europehave been responsible for changes in flood-generating precipita-tion in Germany.
3.2. Observed land-use change
In Germany, large changes in land use have occurred since1945. Data from the Federal Statistical Office indicate that, be-tween 1951 and 1989, agricultural area in Germany decreasedfrom 57.8% to 53.7%, while forested areas remained almost con-stant. During the same time, impervious areas increased sharplyfrom 7.4% to 12.3%. This trend has continued since 1989 (DESTATIS,2010), although data following German reunification makes inter-comparison difficult. From year 1992 to 2008, in the reunified Ger-many, impervious areas further increased from 11.2% to 13.1%,forest areas increased from 29.3% to 30.1%, and agricultural areadecreased from 54.7% to 52.5% (DESTATIS, 2010).
As a consequence of increasing impervious surfaces, runoffgeneration can be expected to increase and infiltration andgroundwater recharge decrease. Van der Ploeg et al. (2001) foundthat land consolidation and intense agriculture contributed to a
Fig. 1. Location of the investigated river gauges and river catchments within Germany.
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 53
magnification of flood events across the Elbe catchment. Althoughmodelling by Bronstert et al. (2004) suggested that effects ofland-use change on generation of large floods are small at regionalscales, empirical data and analyses continue to suggest land-useimpacts on flood generation (see also Niehoff et al., 2002).
3.3. History of river regulation in Germany
German rivers and their catchments have been progressively af-fected by increasing human influence over many centuries. In thelast 200 years, human population in central Europe has increased
Table 2Two-way contingency table used to test for changes in flood frequency at each studygauge.
Time period Flood-year Non-flood year
First half of the time series n1,1 n1,2
Second half of the time series n2,1 n2,2
54 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
dramatically, e.g. from 10 to 50 million inhabitants in the Rhine ba-sin. This population growth was coupled with large increases intechnology and intensity of land utilization. German rivers haveseen increasing use for transportation of goods and passengers,driving progressive channelization of the rivers. Many of the Ger-man rivers are also now used for power supply. Over the same timeperiods, flood protection measures also were installed and en-larged to protect humans, floodplain infrastructure and agricul-tural activity (Buck et al., 1993).
3.3.1. Pre-industrial eraAlready in Roman times, river engineering works were con-
structed on European rivers, including in Germany. During the Ro-man era, rivers were used for transportation, and settlements andagricultural land already were locally protected by dikes (Bucket al., 1993). In the Middle Ages, deforestation, climate variationand population growth drove increasing magnitudes of interven-tion on the landscape as well as in the rivers themselves. Riverdiversions were carried out, and weirs and water mills were in-stalled for generation of hydropower. On the lower Rhine, forexample, dike boards constructed permanent flood protectionworks of progressively greater extent and strength (Buck et al.,1993). Although the floodplains were increasingly used for settle-ment and economic purposes, the fluvial dynamics of most riverswere modified only locally (Busch et al., 1989), with long-term re-gional changes reflecting primarily climatic rather than humancontrols (e.g., Schenk, 2001). Along the Weser River, fishermenand millers built dams as early as the 5th century. Later, whenthe Weser began to be used for navigation, maintenance workalong the banks and in the channel bed led to erosion. Along theOdra River (Oderbruch), dikes were built on the floodplain as earlyas 1746–1753 for protection of agricultural land, and the Odra Riv-er was partly redirected into a new channel bed (Wulle, 1935).
3.3.2. 19th centuryIn the beginning of the 19th century, the upper Rhine was mod-
ified from a multi-thread, braided system to a single, stable chan-nel under the direction of engineer Johann Gottfried Tulla. At thattime, 280 km of the Rhine River were regulated, and dikes wereconstructed to improve flood protection (Buck et al., 1993). Regu-lation and subsequent weir construction resulted in intensivebed degradation (incision). Other parts of the Rhine River systemalso were channelized and protected. Meanders were cut off, andthe narrowest parts of the rivers were widened (e.g., Binger Loch).In addition to the Rhine, other river systems and tributaries to theRhine also were regulated and channelized in the 19th century. Onthe Main River, flow was regulated between 1846 and 1875, fol-lowed by the construction of five weirs by 1885 (Steinhauser,1962). By 1900, the channelization of the Main River was extendedin order to deepen the river bed from 2 to 2.5 m. Along the LahnRiver, 20 of the 30 locks present today were constructed by 1859(Schönefeld, 1986). On the Mosel River, river regulation was per-formed between 1839 and 1870 by stabilisation of the river banks,building groynes and removing islands within the river (Buck et al.,1993). An organised regulation of the Weser River started around1800, involving construction of groynes, longitudinal dikes and
controls on the river bed, and the river channel became narrowerand deeper within a few decades (Busch et al., 1989). Along theElbe River, systematic channelization was initiated in 1815 (Faistand Trabant, 1996), and by 1858 almost 4000 groynes and over100 km of longitudinal dikes were built. In the second half of the19th century, further channelization of the Elbe served to maintainminimum navigation depths during average to low-flow condi-tions. The Odra River was channelized at the end of the 19th cen-tury: twelve barrages were installed, polders were constructed,and meanders were cut off (Grünewald and Schümberg, 2000;Wulle, 1935).
3.3.3. 20th centuryRiver regulation activities in the 19th century were not com-
pletely successful, so that continued regulation work was requiredduring the 20th century. The construction of groynes was contin-ued to deepen navigation channels. After 1950, a number of weirswere constructed on the Rhine River to generate water power andenable passage by larger ships (Buck et al., 1993). 20th century reg-ulation of other German rivers was continued in a similar way. Onthe Lahn and Main Rivers, locks and weirs were renewed and newpower plants constructed (Schönefeld, 1986; Steinhauser, 1962).Between 1924 and 1963, weirs, locks and water power plants wereconstructed at 27 sites along the Main River to establish a naviga-tion channel that connected the North Sea to the Black Sea (Bucket al., 1993). In order to improve river regulation for large ships,the channelization of the Lower Main was changed in 1929, andfive earlier weirs were replaced by three new ones (Pfaue, 1930).Along the Mosel River, the construction of weirs and locks startedlater compared to the other tributaries of the Rhine. The first locknear Koblenz was competed in 1951, and weirs and locks werebuilt at 12 sites within the German part of the Mosel River by1964. Along the Saar River, which is the main tributary of the Mo-sel, river regulation was performed even later. Between 1975 and1988, weirs, locks and power plants were built at seven sites inthe German part of the Saar. Where the Emscher River dischargesinto the Rhine, large areas of land subsidence caused by coal min-ing occurred during the beginning of the 20th century. Due to thissubsidence, the river course close to the mouth was displacedtwice (1910 and 1949 Ramshorn (1949)).
Channelization of the Weser River was extended during the20th century to meet demands for larger barge capacities (Buschet al., 1989). In 1987, regulation of the middle Weser aimed toapproximately double minimum navigation depths to 2.5 m (Buschet al., 1989). Today, seven dams and locks regulate the flow of themiddle Weser between Bremen and Minden. Along the Elbe River,further channelization was examined in the early 20th centurywith the goal of improving navigation conditions during low flowsby installing ground sills. By the end of the 20th century, 6903groynes and longitudinal dikes were in place along 327 km of theElbe (Faist and Trabant, 1996). River regulation work along theOdra River in the 20th century first focused on closing gaps inthe dike line after the flood of 1903; later, dikes were raised andpolders were constructed (Grünewald and Schümberg, 2000).
In summary, German rivers have been influenced by humansover several millennia and channelized intensively over the past�two centuries to improve the navigability of the rivers and pro-vide increasing levels of flood protection. Other motivations for riv-er modification have included energy production as well asdrainage of floodplains in order to use them for agricultural pur-poses and for protection against epidemics diseases. In additionto regulation of low, mean and high discharges, river regulationshave been linked to degradation of the ecological value of flood-plains and rivers (Busch et al., 1989).
Table 3Results of the flood frequency analysis, showing those gauges documenting signif-icant changes in flood frequency (n1,1/n2,1; n1,2/n2,2). Other gauges not noted belowshowed no significant trends in flood frequency.
River Gauge stations with increasingflood frequency
Gauge stations with decreasingflood frequency
Aller Rethem (3/13; 29/19) –Danube – Ingolstadt (18/10; 4/11)Fulda Rotenburga (10/36; 33/7) –Main Kleinheubach (6/14; 18/10) Würzburg (63/48; 29/43)Rhine Maxau (17/26; 24/14) –
Speyer (11/19; 15/7)Saale Calbe-Grizehneb (2/6; 6/2) –Treene – Treiaa (21/0; 9/30)Unstrut Lauchab (0/4; 10/6) –Weser – Bodenwerder (60/43; 24/40)
Hann. Münden (71/41; 17/46)Intschede (43/17; 32/57)Vlotho (60/39; 33/54)
a Change in gauge datum possible.b Short time series.
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 55
4. Results
4.1. Homogeneity of time series
According to the homogeneity tests, most of the time seriesof discharge (56 out of 78 gauges in total) and stage (47 out of78) were found to be homogenous, while 17 discharge and 18stage time series were inhomogeneous. For 5 discharge and 13stage data sets, the two homogeneity tests suggested contrastingresults.
The homogeneity tests revealed higher percentages of inhomo-geneity for those gauges with significant trends in discharge orstage: 9 homogenous versus 16 inhomogenous discharge time ser-ies, and 5 homogenous versus 17 inhomogenous stage time series(Table 4). In particular, all Weser River gauges which showed sig-nificant trends were detected to be inhomogenous. However,although arriving at the same conclusion, the different tests inmost cases disagreed in the time step of the detected inhomogene-ities, indicating that possible inhomogeneities could not be de-tected unambiguously by both methods. Such ambiguities maybe prevalent for time series with both a long-term trend and largeinterannual variability. Thus, despite the indication that some timeseries might be influenced by abrupt changes, we decided not toexclude those time series from the analysis. Here we test for trendsover the duration of record without claiming whether these aregradual or sudden changes within the duration of record.
4.2. Trends in flood frequencies
Trends in flood frequency over time were assessed using chi2
tests on two-way contingency tables comparing the occurrenceof floods in the first half versus the second half of record at eachgauge location. Using this approach, statistically significant differ-ences in flood frequency were detected for 14 out of the 78 gaugesin the study (Table 3). From those 14 gauges, the same number ofgauges (seven) showed increasing as showed decreasing flood fre-quencies. Unlike some studies that have analysed hydrologic re-cords from multiple sites for a common time interval (e.g.,Petrow and Merz, 2009), the study here examined sites with vary-ing lengths of record. Average time-series duration of those sta-tions showing higher flood frequency in the second half of therecord was 52 years. Those stations were consistent with the re-sults of Petrow and Merz (2009), who saw increased flood hazardin Germany in particular in terms of flood frequency. In contrast,the gauges showing lower flood frequency in the second half ofthe record had an average time-series length of 136 years, i.e.much longer than for the stations suggesting increased floodfrequencies.
In order to assess the impact of differing time-series durations,truncated time series dating uniformly from 1950 were analysedusing the same two-way chi2 test. In contrast to the results usingthe full time series, these uniform post-1950 records show no dif-ferences (first half of record versus second half) significant at theP95% level. Four of the five gauges (Weser River at Bodernwerder,Hann. Münden, Vlotho and Main River at Würzburg) show morefloods in the 2nd half of their records (suggest increasing trends),but the differences are not significant. One gauge (Weser River atIntschede) had equal occurrence of flood and non-flood years inthe two periods, and none of these stations indicated a decreasein flood frequency using the truncated datasets.
4.3. Discharge trend analyses
In these analyses, we tested for statistically significant trends inmaximum annual discharges at each of the study gauges. Applying
the OLS method, 19 of 79 gauges showed significant trends in an-nual maximum discharge at a 6 0.05, and another 8 (27 of 79 total)at the more liberal confidence level of a 6 0.10 (Table 4). Of those27 gauges with significant trends, 21 of those trends were positive(increasing discharge), while 6 were negative (decreasing flood dis-charges). The Mann–Kendall test identified 14 gauges showingtrends in annual maximum discharge at a 6 0.05 and another 10gauges at a 6 0.10 (Table 4). 17 of those 24 gauges showed increas-ing trends, while seven were negative. Mann Kendall test and OLSmethod thus gave comparable results.
These results are in agreement with other studies (e.g., Kundze-wicz et al., 2005; Svensson et al., 2005), suggesting that increasesor decreases in flood flows are quite heterogeneous across Ger-many and elsewhere in central Europe, with no clear regional pat-tern evident at the present time. Based on 1951–2002 data, Petrowand Merz (2009) found increasing flood discharges for similar per-centages of river gauges in southern, western and central Germany.The results here confirm the positive trends in many of the sameareas, for example on the Rhine and Main Rivers (Table 4), butthe discharge time series from the Danube River and its tributariesshowed no significant trends. For the Weser River, we identifieddecreasing rather than increasing trends. Regionally, we concurwith Petrow and Merz (2009) that the identified trends are catch-ment-specific.
On the Elbe River, non-uniform trends were found, similar tothe results of Petrow and Merz (2009) and Mudelsee et al.(2003). Increasing discharge trends were identified at two gauges(Tangermünde and Wittenberg), but flood discharges decreasedover the duration of record at Dresden. Three other gauges showednon-significant increases in flood discharge, while another threeriver gauges showed no change at all. On the Elbe tributaries, sig-nificant increases in discharge were seen only on the Saale River, inagreement with Petrow and Merz (2009). In contrast, no significanttrends were detected for the Havel River (no change) and the SpreeRiver (non-significant negative trend).
On the Ems River, results were similar to those for the Wesergauges. Annual maximum flows decreased (non-significantly atthose gauges with more than 60 years data (e.g., Versen)), whileflows increased non-significantly at those gauges where data col-lection started after the 1960s. At the Greven gauge, which had33 years of record, discharges increased even significantly.
Most gauges on the Danube River showed slightly increasingflood discharges over the duration of record, trends that were notstatistically significant. Therefore, the results here are not in agree-ment with those of Petrow and Merz (2009) nor those of Caspary
Table 4Results of trend analysis of maximum annual stages (flood heights; cm/a) and discharges (m3/s/a), calculated from ordinary least squares regression (OLS) and from Sen’sestimator (Sen). Trend significance was estimated by Mann–Kendall test (MK). Gauges not mentioned below did not show any significant trend.
River Gauge Trend in discharge Trend in flood stage
OLS Sen MK OLS Sen MK
Aller Celleb +1.07 *,d +2.5**,d +2.39 *,d
Rethem +0.69**,d +0.57 **,d
Danube Oberndorf +12.8*,b
Ingolstadt �2.1**,d �2.52 **,d
Pfelling +4.2**,b +3.57 *,b
Eder Schmittlohheim +3.05**,c +3.15 **,c +1.74**,d +1.86 **,d
Elbe Dresden �3.9**,c �2.8 **,c �0.64**,c �0.65 **,c
Tangermünde +18.1**,b +17.6 **,b +2.27**,b +1.74 **,b
Wittenberg +11.96**,b +11.1 *,b +0.97*,b
Ems Greven +3.44**,c +3.56 **,c +4.38**,d +2.74 **,d
Rheine +2.87*,c +3.13 *,c
Fulda Rotenburg +2.28**,c +2.08 **,c
Inn Wasserburg �7.96 **,b
Lahn Leun +5.36**,c +5.83 **,c +2.0**,c +1.43 **,c
Leine Herrenhausen +0.64 *,b
Main Kemmern +3.44**,c +3.6 **,c
Kleinheubach +7.96**,d +7.54 **,d +2.18*,b
Schweinfurt +11.46**,c +12.2 **,c +4.48**,c +5.0 **,c
Steinbach +8.41**,c +8.68 **,c +3.61**,c +3.51 **,c
Trunstadt +9.29*,b +9.29 *,b +4.53*,d +4.19 **,d
Würzburg �1.28**,c �1.02 **,c �1.01**,c �0.95 **,c
Neckar Lauffen +2.29*,d +2.1 *,d
Rhine Andernach +13.4**,b
Düsseldorf +13.4**,b
Kaub +13.4**,c +11.9 *,c
Mainz +11.78*,d +11.1 *,d +0.88*,c
Maxau +6.75**,b +6.27 *,b +1.56**,c +1.45 **,c
Rees +20.81*,b
Speyer +10.88*,c
Worms +6.76**,c +7.26 **,c
Treene Treia �2.93**,c,a �2.72a **,c
Unstrut Laucha +2.31*,d +2.57 *,d +4.12 *,d
Weser Bodenwerder �2.13**,c �1.54 **,c �0.47**,c �0.45 *,c
Dörverden +7.78*,c +7.36 *,c +3.64*,c +3.31 *,c
Hann. Münden �1.19**,c �1.21 **,c �0.76**,c �0.8 **,c
Intschede �5.01**,c �3.08 **,c �1.0**,c �0.87 **,c
Liebenau +8.63*,c +10.3 *,c +3.2*,c +2.64 *,c
Vlotho �2.83**,c �2.39 **,c �0.63**,c �0.74 **,c
* Significant at a 6 0.10.** Significant at a 6 0.05.
a Probably caused by unrecorded datum shift.b Both tests on homogeneity were positive.c Both tests on homogeneity were negative.d Both tests on homogeneity were inconsistent.
56 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
and Bardossy (1995) for the Danube. The only significant increasehere was observed for the gauge at Oberndorf (Table 4). At mostgauges on the Danube, the available discharge time series weretoo short for significant trends to emerge from the interannualvariability.
On the Rhine, all 9 gauges analysed here showed positivetrends in annual maximum discharge. Applying the OLS method,five gauges show increasing trends significant at the P95% level(e.g., Maxau and Worms, Fig. 2), three more (eight total) at theP90% level, and one gauge showed a non-significant upwardtrend. The Mann–Kendall test identified only four gauges showingsignificant trends. These discharge trends are in accordance withthe findings of Petrow and Merz (2009), Pinter et al. (2006a) andPfister et al. (2004). Gauges on the German Rhine tributaries, theMosel and Neckar Rivers, revealed a heterogeneous pattern. Ofthe Rhine tributaries, only the gauges on the Main and Lahnshowed significant increases in annual maximum discharge.Interestingly, the trends identified for the Main differ along theriver. While all gauges with time-series length of 30–50 yearsshowed increasing flood discharges, the Würzburg gauge(180 years of record) showed a strong negative trend (Fig. 2).Such a result highlights the importance of time-series lengthand homogeneity for such comparisons.
For the Weser River, the results here differ from those obtainedby Petrow and menz (2009). At most Weser gauges analysed here,negative trends in flood discharge were found, among them statis-tically significant decreasing trends for four of those gauges (e.g.,Intschede, Fig. 2). The reason for these decreasing trends is thatseveral large floods occurred on the Weser prior to 1950. At twogauges (Dörverden and Liebenau), collection of discharge datastarted in the 1970s, and increasing trends in annual maximumflows were detected at these sites (e.g., Dörverden, Fig. 2). At theother Weser gauges, data collection started between 1840 and1940. The Weser tributaries show non-uniform trends which arepredominantly non-significant (except the increasing annual max-imum discharge trend on the Eder River at Schmittlotheim).
The results obtained by this study show that the identified dis-charge trends vary broadly by catchment, and occasionally withinindividual catchments. This confirms Blöschl and Montanari’s(2010) conclusion that simultaneous analysis of many catchmentsis required to avoid potential bias associated with selective choiceof study area. While the increase in flood discharges is in agreementwith increasing winter precipitation for the Rhine catchment, it isnot for stations in the Danube catchment (except the Oberndorfgauge). For other large river catchments (Elbe, Weser, Main), trendsvary within the catchment despite homogenous trend signals in
Weser: Intschede
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]Weser: Dörverden
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³s]
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[m³s
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Elbe: Tangermünde
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[m³s
]
Fig. 2. Sample trends in annual maximum discharge (HQ) for Intschede and Dörverden (Weser River), Maxau and Worms (Rhine), Würzburg and Schweinfurt (Main) andDresden and Tangermünde (Elbe).
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 57
precipitation. These results also show that trends strongly dependon the length of the available time series. For example, as mentionedabove, all gauges on the Weser River with long time series(>150 years) exhibit negative trends in annual maximum discharge,while gauges with time periods of about 60 years show no trends,and gauges with time series shorter than 40 years show increasingtrends (e.g., Dörverden, Liebenau). At the end of the 19th century,some gauges exhibit a marked decrease in variability of flood dis-charges (e.g., Intschede, Fig. 2). Such changes should be furtherinvestigated in detail to identify possible causal Mechanisms.
In addition to the discussion on data reliability (see Petrow andMerz, 2009), the question should be emphasized how significant
are recent trends in flood discharges in comparison to trends inhistoric time series. Finally, many of the gauges here show trendswhich, by visual inspection, appear to be remarkable, but whichin fact are not statistically significant. This reiterates the findingsof Radziejewski and Kundzewicz (2004) that there may be incipi-ent trends at some sites which cannot (yet) be detectedstatistically.
4.4. Stage trend analyses
In these analyses, we tested for statistically significanttrends in maximum annual stages at each of the study gauges.
Weser: Intschede
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[cm
]Weser: Dörverden
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[cm
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Rhine: Maxau
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[cm
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W [c
m]
Main: Würzburg
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[cm
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Elbe: Dresden
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[cm
]
Elbe: Tangermünde
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[cm
]
Fig. 3. Sample trends in annual maximum stages (HW) for Intschede and Dörverden (Weser River), Maxau and Worms (Rhine), Würzburg and Schweinfurt (Main) andDresden and Tangermünde (Elbe).
58 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
Comparable to the results for discharges, we found trends inannual maximum stages that were significant at a 6 0.05 at20 of the 79 study gauges (OLS; Mann–Kendall: 18). Anothereight gauge stations (28 of 79 in total) had trends that weresignificant at a 6 0.1 (OLS; Mann–Kendall: another nine gaugestations; Table 4). As with the discharge trend analysis, thepattern of significant trends in peak stages is not consistentacross all of Germany; rather these results suggest that changesin flood stages are primarily localized to individual sites and/orriver reaches.
On the Elbe River, the pattern of stage trends was heteroge-neous at the different stations analysed, similar to the resultsfor flood discharges. Peak flood stages decreased over time at
Dresden but increased at Tangermünde and Wittenberg (the lat-ter not for the Mann–Kendall test). None of the other gauges onthe Elbe, nor gauges on its tributaries: the Havel, Spree, Saaleand Unstrut, showed any significant trends in flood stages.
On the Ems River, flood stages increased significantly at two offour available gauges (at Greven and Rheine), while no significanttrends were identified at the two remaining gauges (at Dalumand Versen).
Most gauges on the Danube River showed no significant trendsin flood stages. Significant changes were found only at Ingolstadt(decreasing trend) and at Pfelling (increasing trend). The resultsfor the Danube stages therefore match with the corresponding dis-charge trends.
Donau: Ingolstadt
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[m³s
]Donau: Ingolstadt
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[cm
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Fulda: Rotenburg
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[m³s
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Fulda: Rotenburg
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m]
Fig. 4. Comparison of trends in maximum annual dischages (HQ) and maximum annual stages (HW) for two gauges with opposite trends: Ingolstadt (Donau) and Rotenburg(Fulda) gauges.
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 59
On the Rhine, two gauges showed statistically significant in-creases in flood stages: Maxau and Mainz (the latter not for theMann–Kendall test). The other Rhine gauges showed a heteroge-neous pattern of non-significant behaviour, as did gauges on theGerman Rhine tributaries. While increasing trends in flood stageswere identified for individual gauges on the Neckar (at Lauffen)and the Lahn (at Leun) Rivers, no significant trends were foundon the Mosel and Nahe Rivers. On the Main River, in contrast, allgauges showed significant changes in flood stages. Most of theMain gauges show significant increases in peak stages over thedurations of gauge record, with the exception of Würzburg, whichshowed a significant negative trend in stages. Similar to the resultsfor flood discharges, the direction of stage trends is closely relatedto the length of the time-series analysed: positive trends for shorttime series (30–50 years), but negative trends for longer time ser-ies (Würzburg: 180 years).
For the Weser River, flood stages decreased for the majority(four) of the gauges (at Bodenwerder, Hann. Münden, Intschede,Vlotho), but increasing stage trends were found at two Wesergauges (Dörverden, Liebenau). As previously, duration and timingof each gauge’s record strongly influenced the directions of theoverall trends; negative trends were identified for those gaugeswhere data collection started in the 19th century, while positivetrends were found for those gauges where data collection startedafter 1970. At those gauges where data collection started betweenin 1936 (Porta) and 1940 (Karlshafen), no significant trends inflood stages were detected.
Testing for trends over time in peak stages showed that theidentified trends vary among the catchments, as did the patternof significant discharge trends. For the majority of the studygauges, trends in flood stage parallel trends in discharge (19gauge stations for OLS, 18 according to Mann–Kendall; Table 4),suggesting that trends in stage in Germany are predominantlydriven by the so-called upstream mechanisms (Pinter et al.,2006a), meaning changes in hydrological catchment behavioursuch as climate and/or land use. But these results also show thatthe trends strongly depend on the length of the available time
series (e.g., Weser River). However, for several gauge stations,trends in stage and discharge diverge (e.g., Worms at the Rhine(Figs. 2 and 3); Rotenburg on the Fulda River; and Ingolstadt onthe Danube River, Fig. 4), indicating that in-stream processes lo-cally can drive net change in flood behaviour on German rivers.For those gauge locations, local channel or floodplain engineeringlikely drive the divergent behaviour of peak flows versus peakstages over time.
In summary, correlation between direction of trends is high fordischarge and stage, emphasizing the dominance of catchmentchanges (land use, climate). For several rivers, regionally homoge-nous trends were observed (Table 4). For example, increasing floodstages were observed for the Aller, Ems, Main Rivers and for partsof the Rhine River. In contrast, negative trends were observed forthe Weser River for those gauges with long time series (>100 years).Trends in annual maximum stages generally parallel dischargetrends at most stations, but some gauges show different patternsof stage change over time from discharge trends. For most of thelarge rivers investigated in this study, the catchment-specific vari-ability in trends in flood stages is much higher than the variabilityin trends in flood discharges. The causes of such stage changes cansometimes be clarified using specific gauge analysis.
4.5. Specific gauge analysis
The analyses of annual maximum stages and discharges re-vealed parallel trends for the two parameters at many stationsbut also divergent trends in stage and discharge at several others.In order to help identify causal mechanisms, and in particular toelucidate mechanisms driving divergent stage and dischargetrends, specific gauge analysis was performed. Specific gauge anal-ysis tests for trends or changes in the form of the rating curve (i.e.,stage-discharge relationship) at measurement stations, which iso-lates reach-scale in-channel processes from basin-scale shifts inprecipitation and runoff. The Rhine River was not included in theseanalyses as such work was already completed by Pinter et al.(2006b).
60 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
The results of specific gauge analysis for stations on the Ger-man rivers show that, for the majority of the gauges investi-gated, specific stages (stages for constant and pre-specifieddischarge conditions) were relatively invariant over time. These
Table 5Types of engineering structures emplaced up- and downstream of the study gaugesearth.google.com/).
Gauge station (river) Levees Wing dikes
Ingolstadt (Danube) Yes NoneHofkirchen (Danube) Yes NoneDresden (Elbe) Yes NoneTorgau (Elbe) Yes YesFulda (Grebenau) None NoneKemmern (Main) Yes NoneWürzburg (Main) Yes NoneVlotho (Weser) Yes YesIntschede (Weser) Yes Yes
Fig. 5. Specific stages for the Danube River at Ingolstadt (above) and Hofkirchen (bottIngolstadt gauge, specific stages remained almost constant at Hofkirchen. On the right,
results were consistent with the discharge and stage trend re-sults at most stations, which suggested forcing predominantlyby upstream mechanisms which would not alter stage-discharge(rating) relationships at specific locations. Compared to changes
, based on reconnaissance assessment of Google Earth satellite imagery. (http://
Meander cutoffs Bridges Locks and dams
Yes Yes YesYes Yes NoneYes Yes NoneYes Yes NoneNone Yes YesNone Yes YesYes Yes YesYes Yes NoneYes Yes Yes
om). While specific stages decreased for both low flows and for high flows at thesatellite image shows station vicinity.
Fig. 6. Specific stages for the Elbe River at Dresden (above) and Torgau (bottom). While specific stages decreased for both low flows and for high flows at the Torgau gauge,specific stages for high flows increased at the Dresden gauge. On the right, satellite image shows station vicinity.
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 61
in specific stages found in the US (shifts up to 6–7 m at somelocations; Pinter and Heine, 2005; Pinter et al., 2006a; Jemberieet al., 2008) changes found on the German rivers are quite small.However, at several of the investigated stream gauges, largerchanges in the stage-discharge relationship were observed. Be-low, we present examples where distinguishable and noteworthychanges in specific stages were identified. These gauge stationsand the related in-stream engineering measures are introducedin Table 5.
Specific gauge analysis for the Danube River showed specificstages that changed little over the period of record at the followingstations: Achleiten, Hofkirchen (Fig. 5), Oberndorf and Pfelling. Atthe Ingolstadt gauge, specific stages for both low and high flowsdecreased by almost 1 m during the past 50 years (Fig. 5). Exami-nation of satellite imagery revealed that the reach of the Danubein the vicinity of the Hofkirchen gauge station (Fig. 5) is ruraland engineering structures here are relatively sparse (Table 5). Incontrast, at the Ingolstadt gauge, the Danube River passes through
the city, and river engineering structures in this reach (e.g., levees,bridges, locks and dams; see Table 5) are quite extensive.
Similar to the Danube, specific stages remained constantthrough the past several decades at most gauges on the Elbe River(e.g., at Aken, Magdeburg, Neu-Darchau, and Wittenberge). At sev-eral of these stations, specific stages for low flows decreasedslightly (e.g., Barby, Torgau, Tangermünde, and Dresden), suggest-ing moderate incision of the channel. Incision of the Elbe channelbed (e.g., Fig. 6) has been previously noted and has been associatedwith the construction of wing dikes (groynes) since the early 19thcentury (Helms et al., 2002), dredging to facilitate river navigation,and later installation of ground sills (Faist and Trabant, 1996). Forflood flows, the trends over time in specific stages are different atdifferent stations on the Elbe. While specific stages for flood flowsincreased at Dresden (despite decreasing stages at low flows), spe-cific stages for flood flows decreased at Torgau (Fig. 6). Althoughdetailed records were not available at the national level, we as-sume that development and the increasing extent and height of
Fig. 7. Specific stages for the Fulda River at Grebenau. While specific stages for high flows increased, specific stages decreased for low flows at this gauge. On the right, thesatellite image shows station vicinity.
62 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
flood protection in urban areas (e.g., in the city of Dresden) havereduced floodplain storage and conveyance capacity, while thefloodway has been less constricted or obstructed in rural areas(e.g., Torgau, Fig. 6).
The Grebenau gauge on the Fulda River shows a pattern in spe-cific stages similar to the Dresden gauge on the Elbe. While specificstages for low flows decreased, specific stages for flood flows in-creased over the past 50 years (Fig. 7). This is the same patternof specific-stage response associated with large-scale groyne con-struction on US rivers (e.g., Pinter et al., 2008, 2010). We interpretthe same response on the Fulda River – channel-bed incision due toconstriction of the channel by groynes, combined with decreasedcapacity to convey large (flood) flows due to decreased flow veloc-ities and reduced cross-sectional area in response to constructionof dikes, bridges, and other channel and floodplain structures(Table 5).
For the Main River, specific gauge analysis revealed no long-term trends in specific stages for the gauges at Frankfurt, Truns-tadt, Steinbach and Schweinfurt. But distinguishable trends wereobserved at Kemmern and Würzburg (Fig. 8). While specific stagesfor low flows decreased over time at the Würzburg gauge, theyincreased at Kemmern. And while specific stages for high flows re-main constant at the Kemmern gauge (after a likely but unidenti-fied change in gauge datum in 1969; Fig. 8), specific stages forhigh flows decreased slightly at Würzburg. Another reason for ob-served specific-stage changes for low-flow conditions probably isthe impact of the Main channelization during the second half ofthe 19th century and the associated construction of weirs andlocks (Steinhauser, 1962; Buck et al., 1993; Table 5). Activities inthe channel such as sand and gravel mining (Kemmern) and urbandevelopment (Würzburg) also may have influenced the observedchanges in specific stages over time.
In its recent history, the Weser River has been extensively engi-neered. As noted previously, wing dikes (grognes), levees andground sills were built on the Weser since 1800, with the resultthat the river channel has become narrower and deeper (Buschet al., 1989). This is reflected in the specific gauge plots spanningthe 19th century (at Bodenwerder, Hann. Münden, Intschede(Fig. 9), and Vlotho). In contrast, those gauges where data collec-tion started only during the mid-20th century (Porta, Liebenau,Karlshafen, Dörverden, and Wahmbeck) do not show significant
changes in specific stages for low-flow conditions. In addition tothe change for low flows, specific stages for flood discharges chan-ged as well at several Weser gauges. For example at Intschede(Fig. 9), flood stages decreased by about 70 cm during the past50 years. No large flood has occurred on the Weser since 1950. Thisis due to advanced flood prevention management based on severalbarrages, constructed between 1914 (Eder), 1924 (Diemel) and1979 (Twiste).
At most gauges studied on the German rivers, specific stageschanged little through the most recent decades, confirming theconclusion that trends in flood discharges in Germany have beendriven mainly by upstream changes. However, there are severalgauging stations where specific stages for high and/or low flowschanged up to 1 m over the period of available gauge record. Suchchanges can be interpreted as change in flow conveyance and ap-pear to result from engineering activities within the rivers andtheir floodplains (e.g., construction of dikes, bridges, and dams,meander cutoffs, channel constriction by wing dikes [groynes]).In order to confirm the mechanisms driving the identified changesin rating curves, additional analyses such as detailed hydraulicmodelling on the local scale would be necessary.
5. Discussion
This study confirmed that – in agreement with previous find-ings (e.g., Petrow and Merz, 2009) – there is no uniform patternin hydrological time series across all German rivers. We examinedboth discharge and stage time series and found, for example, pre-dominantly decreasing trends for the Weser catchment, while an-nual maximum flows in the Rhine and the Main catchmentsincreased significantly. However, for 42 (OLS; Mann–Kendall: 45)out of 78 stations no statistically significant trends were identified(Table 6).
A strong dependency of trends upon time-series lengths wasfound. Within the same river system, long time series systemati-cally resulted in different trends compared to short time series(e.g., for the Weser and Main gauges). This is the main reasonwhy different results were obtained in this study compared to Pet-row and Merz (2009), who based their analyses on time series offixed range, from 1951 to 2002, which is much shorter than the
Fig. 8. Specific stages for the Main River at Kemmern (above) and Würzburg (bottom). While specific stages for high flows remained constant at Kemmern, specific stages forlow flows increased sharply. In contrast, specific stages at Würzburg decreased for both high and low flows. On the right, satellite image shows station vicinity.
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 63
longest records examined here. While Petrow and Merz (2009)thus guaranteed a better comparability of results for a large num-ber of gauging stations, they neglected the question of significanceof recent flood events in comparison to the longer historical record.Unfortunately, only a few gauging stations have historical recordsstarting from middle of the 19th century (see Table 1). Hence astudy limited only to sites with such long discharge and stage timeseries would be limited to a very few rivers and few stations. Bothlong-term and shorter-term studies complement each other interms of assessing recent trends in flooding for a dense networkof gage stations on one hand versus a sparser record of historic var-iability in flooding on the other. Studies such as performed byMudelsee et al. (2006) for the Werra catchment or Schmocker-Fac-kel and Naef (2010) for Switzerland demonstrated that historicalflooding events for those rivers exceeded recent extremes, indicat-ing that historic variability in flooding envelopes today’s (climate-and land-use-related) trends in flooding.
Significant trends in flood stages generally paralleled changes inflood discharges (at 19 at 19 stations using OLS;18 stations usingMann -Kendall), suggesting that trends in stage on German riversare predominantly caused by upstream changes such as climatechange and/or changes in runoff-response in the catchment suchas from land-use and land-cover shifts. Statistically significantdecreasing trends in both discharge and stage were identified atsix stations (a 6 0.05). Four of these six stations were on the WeserRiver. A likely mechanism driving these decreases may be the con-struction of upstream dams, which would simultaneously reduceextreme flood peaks and promote channel incision downstream,causing data inhomogeneities as described above. In-stream engi-neering measures on the Weser River may also have contributed tothe observed decreases in flood stages due to incision of the Weser(see specific gauge results).
Statistically significant increases in discharge and stage wereidentified at 13 (OLS; Mann–Kendall: 12) gauge stations
Fig. 9. Specific stages for the Weser River at Vlotho (above) and Intschede (bottom). While specific stages for high flows remained constant at Vlotho, specific stages for lowflows decreased sharply. In contrast, specific stages at Intschede decreased for both high and low flows. On the right, satellite image shows station vicinity.
64 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
(a 6 0.10; seven stations for a 6 0.05), including gauges on theEder, Elbe, Ems, Lahn, Main, Rhine and Weser Rivers (7 of 26 riversanalysed; for the Rhine River, see Pinter et al., 2006b). These resultsare in agreement with documented changes in regional climate,including increases in flood-generating circulation patterns andprecipitation events in central Europe (Caspary, 1995; Casparyand Bardossy, 1995; Pfister et al., 2004) as well as previous re-search showing increased runoff yields associated with urbanisa-tion and intensified agriculture (Bormann et al., 1999; van derPloeg and Schweigert, 2001; Pinter et al., 2006b).
For about 20% of the investigated gauges, we also identified sig-nificant changes in flood frequency. In general, these significanttrends were catchment-specific, although variations exist alongindividual rivers as well. Table 6 summarises the identified trendsfor flood stages, flood discharges and frequencies. For all stationsexcept one (Calbe-Grizehne on the Saale River, where only ashort time series was available), trends in flood frequency were
accompanied by (and presumably driven by) significant trends instage or discharge.
The differing trends (increasing vs. decreasing) for stage anddischarge time series of varying durations raises the questions:(1) to what extent does time-series length have a significant im-pact on trends (in particular if the trends are supposed to be re-lated to climate change as suggested by Petrow and Merz(2009)), and (2) how significant are current trends in flood fre-quency in comparison to trends based on long time series that in-clude data from the 19th and early 20th century (before climatechange may have accelerated). As noted above, Mudelsee et al.(2006) assembled a 500-year flood inventory for the Werra River.They found that winter flood occurrence (which is dominant inthat catchment) has increased since the middle of the 20th centurybut peaked around 1760 and 1860. Those floods that occurredin the second half of the 19th century are included within thelong-term data sets here, for example for the Weser River. Similar
Table 6Summary of stations showing significant trends in stage, discharge (OLS method/Mann–Kendall test) and/or flood frequency. Total number of stations with long-termdata on both stage and discharge = 78.
Numberofstations
Number ofstations:upwardtrend
Number ofstations:downwardtrend
No trend in either stage ordischarge
42/45 0/0 0/0
Trends in discharge but notstage
8/6 8/5 0/1
Trends in stage but not indischarge
9/9 7/7 2/2
Trends in both stage anddischarge
19/18 13/12 6/6
Trends in flood frequency 14 7 7
H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66 65
results were found by Schmocker-Fackel and Naef (2010) for SwissRivers with respect to flood frequency. Therefore, negative trendsin flood frequency are plausible for long-term data sets, whilerecent time series show increasing trends for the past few decadesof flooding. Mount (1995) showed how even a single extreme floodevent can dramatically shift probability distributions of hydrologictime series of short duration.
Effects of river engineering were explored using specific gaugeanalysis, focusing mainly on those stations showing significanttrends in flood stage but not in discharge (9 stations) or vice versa(8 stations [OLS] resp. 6 stations [Mann–Kendall]; Table 6). Whiletrends in specific stages were small for most of the investigatedgauge stations, the effects of urbanisation (e.g., construction ofbridges, reduction of floodplains) and in-stream activities (e.g.,construction of wing dikes [groynes], ground sills, locks and dams)could be demonstrated for several stations. These shifts documentchanges in flow conveyance and, as a result, in rating curves,resulting in increases or decreases in specific stages at differentflow levels. However, compared to large changes in specific stageson some US rivers (Pinter et al., 2008, 2010; Jemberie et al., 2008),the trends identified in this study are small in magnitude.
6. Conclusion
This study presents a systematic investigation of flood-relatedtrends in German rivers. Based on analyses of trends in flood fre-quency, flood height, and annual maximum discharges and basedon specific gauge analysis, some findings of previous studies wereconfirmed and others supplemented. Most stations analysed on theGerman rivers did not show statistically significant trends in any ofthe metrics analysed here. Similar to previous studies, we confirmsignificant trends at about 30% of the gauges, with most of thosesignificant trends reflecting increases in flood-related metrics overtime. However, we have shown that the directions and magnitudesof such trends strongly depend upon the time-series length andupon the consideration (or not) of historical observations.
A few stations exhibit ‘‘upstream’’ forcing mechanisms such asclimate and land-use change and the effects of upstream reser-voirs. But in agreement with previous studies, we have shown thatdespite data uncertainties, most decadal-scale climate-change im-pacts on flooding (Petrow and Merz, 2009) are small compared tohistoric peaks in flood occurrence (Mudelsee et al., 2006). Thisshould be emphasized in the recent discussion on the effect of cli-mate change on flooding. We have also shown that in-stream engi-neering activities can influence flood stages, but on the Germanrivers these effects are smaller and more localized than on heavilyengineered rivers, for example in the US. Such changes are super-
imposed upon climate-related or other upstream-driven changes,possibly resulting in an aggravation or a compensation of upstreameffects. This should be a focus on continued research, especially onlocal scale. For the planning of local flood protection measures(taking into account possible future changes as well), these influ-encing factors need to be considered in order assist an optimisedorganisation of flood protection measures and river and floodplainmanagement strategies.
Acknowledgements
Funding for this research was provided by the Alexander vonHumboldt Foundation. We also thank the Global Runoff Data Cen-tre (GRDC) and the Bundesanstalt für Gewässerkunde (Koblenz) forproviding data for this study.
References
Adamowski, K., Bocci, C., 2001. Geostatistical regional trend detection in river flowdata. Hydrol. Process. 15, 3331–3341.
Alexandersson, H.A., 1986. A homogeneity test applied to precipitation data. J.Climatol. 6, 661–675.
Bardossy, A., Caspary, H.J., 1990. Detection of climate change in Europe by analysingEuropean atmospheric circulation patterns from 1881 to 1989. Theor. Appl.Climatol. 42, 155–167.
Blöschl, G., Montanari, A., 2010. Climate change impacts – throwing the dice?Hydrol. Process. 24, 374–381. doi:10.1002/hyp. 7574 (Invited commentary).
Bormann, H., 2010. Changing runoff regimes of German rivers due to climatechange. Erdkunde 64 (3), 257–279.
Bormann, H., Diekkrüger, B., Hauschild, M., 1999. Impact of landscape managementon the hydrological behaviour of small agricultural catchments. Phys. Chem.Earth (B) 24 (4), 291–296.
Bronstert, A. Bardossy, A., Bismuth, C., Buiteveld, H., Busch, N., Disse, M., Engel, H.,Fritsch, U. Hundecha, Y., Lammersen, R., Niehoff, D., Ritter, N., 2004.Quantifizierung des Einflusses der Landoberfläche und derAusbaumaßnahmen am Gewässer auf die Hochwasserbedingungen imRheingebiet. KHR-Report II-18.
Buck, W., Ferkel, K., Gerhard, H., Kalweit, H., Malde, J. van, Nippes, K.-R., Ploeger, B.,Schmitz, W., 1993. Der Rhein unter Einwirkung des Menschen – Ausbau,Schifffahrt, Wasserwirtschaft. KHR-Report I-11, 252 p.
Burn, D.H., Hag Elnur, M.A., 2002. Detection of hydrologic trends and variability. J.Hydrol. 255, 107–122.
Busch, D., Schirmer, M., Schuchardt, B., Ullrich, P., 1989. Historical changes of theRiver Weser. In: Petts, G.E. (Ed.), Historical Change of Large Alluvial Rivers:Western Europe. John Wiley & Sons Ltd., pp. 297–321.
Caspary, H.J., 1995. Recent winter floods in Germany caused by changes in theatmospheric circulation across Europe. Phys. Chem. Earth 20 (5–6), 459–462.
Caspary, H.J., Bardossy, A., 1995. Markieren die Winterhochwasser 1990 und 1993das Ende der Stationarität in der Hochwasserhydrologie infolge vonKlimaänderungen? Wasser Boden 47 (3), 18–24.
DESTATIS, 2010. Umweltnutzung und Wirtschaft. Tabellen zu denUmweltökonomischen Gesamtrechnungen. Ausgabe 2010. StatistischesBundesamt, Wiesbaden, Germany.
Douglas, E.M., Vogel, R.M., Kroll, C.N., 2000. Trends in floods and low flows in theUnited States: impact of spatial correlation. J. Hydrol. 240, 90–105.
Faist, H., Trabant, W., 1996. Stromregelungen und Ausbau der Elbe. Wasserwirtsch.Wassertech. 96 (7), 22–27.
Franks, S.W., 2002. Identification of a change in climate state using regional flooddata. Hydrol. Earth Syst. Sci. 6 (1), 11–16.
Gerstengarbe, F.-W., Werner, P.C., 2008. Climate development in the last century –global and regional. Int. J. Med. Microbiol. 298 (S1), 5–11.
Groisman, P.Y., Knight, R.W., Karl, T.R., 2001. Heavy precipitation and highstreamflow in the contiguous United States: trends in the twentieth century.Bull. Am. Meteorol. Soc. 82, 219–246.
Grünewald, U., Schümberg, S., 2000. Das Oderhochwasser 1997 – Ursachen, Verlauf,Schlussfolgerungen und historischer Vergleich. In: Deutsch, M, Pörtge, K.-H.,and Teltscher (Eds.): Beiträge zum Hochwasser / Hochwasserschutz inVergangenheit und Gegenwart. Erfurter Geographische Studien, vol. 9, pp.45–61.
Helms, M., Büchele, B., Merkel, U., Ihringer, J., 2002. Statistical analysis of the floodsituation and assessment of the impact of diking measures along the Elbe (Labe)river. J. Hydrol. 267, 94–114.
Hörmann, G., Horn, A., Fohrer, N., 2005. The evaluation of land-use options inmesoscale catchments – prospects and limitations of eco-hydrological models.Ecol. Model. 187, 3–14.
Jemberie, A.A., Pinter, N., Remo, J.W.F., 2008. Hydrolologic history of the Mississippiand lower Missouri rivers based upon a refined specific-gauge approach.Hydrol. Process. 22 (22), 4436–4447. doi:10.1002/hyp.7046.
Kendall, M.G., 1975. Rank Correlation Methods. Griffin, London.
66 H. Bormann et al. / Journal of Hydrology 404 (2011) 50–66
Kundzewicz, Z.W., Graczyk, D., Maurer, Th., Pinskwar, I., Radziejewski, M., Svensson,C., Szwed, M., 2005. Trend detection in river flow series: 1. Annual maximumflow. Hydrol. Sci. J. 50 (5), 797–810.
Mount, J.F., 1995. California Rivers and Streams: The Conflict between FluvialProcess and Land Use. University of California Press, Berkeley, 359 pp.
Mudelsee, M., Börngen, M., Tetzlaff, G., Grünewald, U., 2003. No upward trends inthe occurence of extreme floods in central Europe. Nature 425, 166–169.
Mudelsee, M., Börngen, M., Tetzlaff, G., Grünewald, U., 2004. Extreme floods incentral Europe over the past 500 years: role of cyclone pathway ‘‘ZugstrasseVb’’. J. Geophys. Res. 109, 1–21.
Mudelsee, M., Deutsch, M., Börngen, M., Tetzlaff, G., 2006. Trends in flood risk of theriver Werra (Germany) over the past 500 years. Hydrol. Sci. J. 51 (5),818–833.
Niehoff, D., Fritsch, U., Bronstert, A., 2002. Landuse impacts on storm-runoffgeneration: scenarios of land-use change and simulation of hydrologicalresponse in a meso-scale catchment in SW-Germany. J. Hydrol. 267, 80–93.
Petrow, T., Merz, B., 2009. Trends in flood magnitude, frequency and seasonality inGermany in the period 1951–2002. J. Hydrol. 371, 129–141.
Pettit, A.N., 1979. A non-parametric approach to the change-point detection. Appl.Stat. 28 (2), 126–135.
Pfaue, T., 1930. Die Umkanalisierung des Untermains. Die Bautechnik 8 (9),121–125.
Pfister, L., Kwadijk, J., Musy, A., Bronstert, A., Hoffmann, L., 2004. Climate change,land-use change and runoff prediction in the Rhine-Meuse basins. River Res.Appl. 20, 229–241.
Pinter, N., Heine, R.A., 2005. Hydrodynamic and morphodynamic response to riverengineering documented by fixed-discharge analysis, Lower Missouri River,USA. J. Hydrol. 302, 70–91.
Pinter, N., Ickes, B.S., Wlosinski, J.H., van der Ploeg, R.R., 2006a. Trends in floodstages: contrasting results from the Mississippi and Rhine River systems. J.Hydrol. 331 (3–4), 554–566.
Pinter, N., van der Ploeg, R.R., Schweigert, P., Hoefer, G., 2006b. Flood magnificationof the River Rhine. Hydrol. Process. 20, 147–164.
Pinter, N., Jemberie, A.A., Remo, J.W.F., Heine, R.A., Ickes, B.S., 2008. Flood trends andriver engineering on the Mississippi River system. Geophys. Res. Lett. 35,L23404. doi:10.1029/2008GL035987.
Pinter, N., Jemberie, A.A., Remo, J.W.F., Heine, R.A., Ickes, B.A., 2010. Empiricalmodeling of hydrologic response to river engineering, Mississippi and LowerMissouri Rivers. River Res. Appl. 26, 546–571.
Radziejewski, M., Kundzewicz, Z.W., 2004. Detectability of changes in hydrologicalrecords. Hydrol. Sci. J. 49 (1), 39–51.
Ramshorn, 1949. Die Verlegung des Emscherunterlaufs. Die Wasserwirtsch. 39 (12),259–265.
Robson, A.J., Jones, T.K., Reed, D.W., Bayliss, A.C., 1998. A study of national trend andvariation in UK floods. Int. J. Climatol. 18, 165–182.
Schenk, W., 2001. Auen als Siedlungs- und Wirtschaftsäume vor deningenieurtechnischen Veränderungen des 19. Jhs.; das Mittelmaingebiet alsBeispiel. Z. Geomorphol. Suppl. 124, 55–67.
Schmocker-Fackel, P., Naef, F., 2010. Changes in flood frequencies in Switzerlandsince 1500. Hydrol. Earth Syst. Sci. 14, 1581–1594.
Schönefeld, L., 1986. Zwei neue Wasserkraftwerke an der Lahn. Lahnkraftwerke-AG.Frankfurt, 63 p.
Schönwiese, C.-D., 1999. Das Klima der jüngeren Vergangenheit. Phys. Unserer Zeit30 (3), 94–101.
Sen, P.K., 1968. Estimates of the regression coefficient based on Kendall’s tau. J. Am.Stat. Assoc. 63, 1379–1389.
Steinhauser, L., 1962. Die Kraftwerkskette am Main von Aschaffenburg bis Bamberg.Elektrizitätswirtschaft 61 (21), 811–816.
Svensson, C., Kundzewicz, Z.W., Maurer, Th., 2005. Trend detection in river flowseries: 2 flood and low-flow index series. Hydrol. Sci. J. 50 (5), 811–824.
Trömel, S., Schönwiese, C.D., 2008. Robust trend estimation of observed Germanprecipitation. Theor. Appl. Climatol. 93, 107–115.
Van der Ploeg, R.R., Gieska, M., Schweigert, P., 2001. Landschaftshydrologische undHochwasser relevante Aspekte der ackerbaulichen Bodenbewirtschaftung inder deutschen Nachkriegszeit. Z. Agr. Landwirt. 79 (3), 447–465.
Van der Ploeg, R., Schweigert, P., 2001. Elbe river flood peaks and postwar agri-cultural land use in East Germany. Naturwissenschaften 88, 522–525.
Wulle, 1935. Die Verbesserung der Vorflut in der unteren Oder zwischenHohensaaten und Stettin. Zentralbl. Bauverwalt. 55 (30), 579–584.
Ya, P., Knight, R.T., Karl, T.R., Easterling, D.R., Sun, B., Lawrimore, J.H., 2004.Contemporary changes of the hydrological cycle over the contiguous UnitedStates. J. Hydrometeorol. 5, 64–85.
