Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ected ff 1,3 , and B. Merz 2,3 8126 8125 ected, but also other countries such as Austria, , B. Mühr ff 1,3 , F. Elmer 2,3 ected most in the catchment was the with its trib- ff , M. Kunz 1,3 This discussion paper is/has beenSciences under (HESS). review Please for refer the to journal the Hydrology corresponding and final Earth paper System in HESS if available. Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, CEDIM – Center for Disaster Management and Risk Reduction Technology, Potsdam, most, in particular the dischargesexceptional in flood the level Hasel and (BfG, Schmalkalde 2013). tributaries As were a on an consequence of major dike breaches at the Switzerland, , Poland,all Hungary, rivers Slovakia, in Croatia and showedthe . high water Almost levels: downstream the ofwater between Halle, levels. Coswig Severe and and flooding Lenzen, occurred the especiallywell along as the along in Danube the Elbe and tributaries experienced Elbeexceptional rivers, new flood and as Saale. record magnitudes In the were,tributaries. and The however, Rhine area observed catchments a onlyutaries locally Eyach and in Starzel. some In smaller the Weser catchment the Werra catchment was a 1 Introduction In June 2013, wide partssouthern of and Central eastern Europe Germany were were hit a by largescale flooding. Particularly events in Germany, notably the high1954. impact Our summer analysis floods from showstional August that scale 2002 – and the caused July combination by a– of pronounced and extreme precipitation strong, anomaly initial but in not wetnessceptional the extraordinary month flood at of event event. the precipitation May This 2013 were na- providesmoisture the for new key high insights drivers return to period for the floods thismethodological on importance ex- developments a provide of large-scale. The a antecedent data consistent soil of base framework future compiled and for floods. the the rapid evaluation The summer flood 2013at sets least a 1952. newextreme In value record statistics this for as paper well large-scalesification as we floods aggregated of analyze severity in the indices. the Germany For recent the key since flood long-term hydro-meteorological we clas- factors draw comparisons using to a set of past large-scale flood Abstract Hydrol. Earth Syst. Sci. Discuss.,www.hydrol-earth-syst-sci-discuss.net/11/8125/2014/ 11, 8125–8166, 2014 doi:10.5194/hessd-11-8125-2014 © Author(s) 2014. CC Attribution 3.0 License. What made the June 2013Germany flood an in exceptional event? A hydro-meteorological evaluation K. Schröter 1 Section Hydrology, Potsdam, Germany 2 Karlsruhe, Germany 3 Karlsruhe, Germany Received: 23 June 2014 – Accepted: 30Correspondence June to: 2014 K. – Schröter Published: ([email protected]) 15 July 2014 Published by Copernicus Publications on behalf of the European Geosciences Union. 5 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | cial estimates of economic loss ffi 8128 8127 The paper is organized as follows. Section 2 describes the data and methods used For this purpose we analyze key hydro-meteorological factors including circulation The subsequent phase of this FDA activity focused on the research question: what The June 2013 flood was an extreme event both with regard to magnitude and spatial Estimates on overall losses caused by the flooding in Central Europe are in the range For the analysis ofing the major meteorological flood and events hydrological in conditions Germany prior and to the and relation dur- to the climatological context, a precipitation, initial river flowisons conditions with and flood the peak extremeSect. discharges. 4 summer Detailed we floods discuss compar- of the key August findings 2002 and provide and recommendations July for future 1954 work.2 are drawn. In Data and methods 2.1 Data base of large-scale floods flood with the event of Uhlemann et al. (2010). to conduct the hydro-meteorological analysis ofscale the flood June events. 2013 Section flood 3 and describesJune the the past meteorological flood large- situation 2013 associated with and the presents the results from the analysis of antecedent and event patterns, initial soil moisture,precipitation and initial flood streamflow peak conditions dischargeshydro-meteorological and factors in using evaluate the methods the of recurrence river extremeclassification intervals value network, statistics. of of For event these a the long-term Juneimpact 2013 summer flood flood we eventsfloods. in draw For this Germany comparisons purpose, specifically to we the use otherscale updated August large-scale flood information 2002 about high events and thedeliberately occurrence over July limited of 1954 the 74 to large- the last national borders 60 of years Germany to (Uhlemann be et able to al., compare the 2010). 2013 The analysis is notion that the influencethan of high-return catchment wetness periods is andevent greater that precipitation for the low-return and magnitude period1987). only of events a secondly flood to is the related catchment primarily wetness to (e.g. the Ettrick et al., moisture and heavy precipitation on a large-scale. This hypothesis is contrary to the June 2013 flood was exceptional due to the superposition of extreme initial soil done by compiling scatteredsitu information sensors available and from remoteas sensing diverse data, by sources the including applying internet, in- CEDIM’sfirst media own report and rapid focused social on sensors assessmentparisons as the tools. to well meteorological major Two floods and reports fromon hydrological were the impact conditions past issued: and including (CEDIM, management the 2013a), com- issues while (CEDIM, the 2013b). second one focused made the Juneof flood view? 2013 This an question exceptional is event analyzed from in a this hydro-meteorological paper. point We check the hypothesis that the The Forensic Disaster Analysisment (FDA) Task and Force Risk of Reduction theJune Technology Center (CEDIM) flood for 2013 closely Disaster including monitored Manage- thereal the impacts time. evolution on of In people, this the transportationof way and CEDIM major economy made event in science-based drivers near facts and available for for the disaster identification mitigation. The first phase of this activity was EUR 10 billion occurred in Germanyfor alone. Germany Current amount o toEUR 2 EUR billion 6.6 billion of (Deutscher insuredtotal Bundestag, losses loss 2013) of (GDV, 2013). with EUR 14.1extreme additional billion These summer flood (normalized numbers in August values are 2002 bythe (Kron, about 2004; most 2013) Thieken expensive 60 in et % natural al., Germany hazard 2005) of experienced which caused remains the in by Germany the so far. extent and its impact on society and economy (Blöschl et al., 2013; Merz et al., 2014). at Groß Rosenburg andstrong at impacts the on Elbe society near insystems, see terms Fischbeck Fig. of large A1 direct areas in damage were the and Appendix inundated interruption for with of geographic transportation locations. of EUR 11.4 billion (Munich Re, 2013) to EUR 13.5 billion (Swiss Re, 2013), whereof Danube in Fischerdorf near Deggendorf, at the confluence of the Saale and Elbe rivers 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect is of minor impor- ff 1 km. The interpolation routine ected by flooding. × ff 8130 8129 and provide continuous records since at least 1950. The 2 ects at least 10 % of the river network considered in Germany. Ap- ff Based on the procedure proposed by Uhlemann et al. (2010), the point observations Additionally, weather charts and radiosounding data are used to describe the char- Strahler order of thea river gauge stretch is decreases representative until by the two Strahler orders. order In of downstream the direction, river changes by one order or discharges were available foreastern 121 parts gauges of mainly Germany which covering have the been mostly central, a southernof and discharge peaks attion in the a 162 particular gauges riverscheme stretch are uses and regionalized the its location to associated1957) of catchment represent area. which the the The gauges accounts flood regionalization and forassumed situa- the the as hierarchical representative branching Strahler for complexity order a of (Strahler, upstream the river reach river until network. the A next gauge gauge and/or is the We use time series of dailywater mean discharges and from shipment 162 gauging administration stations (WSV),(BfG) operated by the or the by German hydrometric Federal services Institutearea of of larger the Hydrology federal than states.same 500 These km selection gauges of have gauges a hasof drainage been large-scale used flood by events Uhlemann in et Germany. For al. the (2010) June to flood compile 2013 the raw data set of daily mean 1990; Petrow et al.,patterns 2009). labelled In “low central 2013, Europepersisted the (TM)” together general and on situation “trough 16 was centralpast days Europe flood dominated events from (TRM)”, by considered which mid-May in the till thisexplain two the study, beginning this extraordinary persistency of situation is June. in not 2013. Compared significant and to cannot the 2.3 Hydrological data sets tance in the present study. acteristics of the atmospheretablished on relations the between large-scale days weather withclassification patterns, maximum for of rainfall. example Hess according Various and to authors Brezowsky the es- (1969), and floods (e.g. Bárdossy and Caspary, flood events are mainly driven by advective precipitation, this e tion, where a very highunderestimate density the of actual stations spatial is variability required, of it precipitation. can be However, since expected large-scale that REGNIE tation are morewe important used than the the 24 hthe small-scale precipitation period temporal sums 1960 variability. to of ForWeather 2009 REGNIE Service this and (regionalized April–June reason, (Deutscher precipitation 2013 totals) Wetterdienst,climatological compiled for stations DWD). and to These provided an data byconsiders equidistant the several are grid German geographical interpolated factors of such from guishing 1km as between altitude, background exposition, monthly orRauthe climatological slope et by fields al., distin- and 2013 daily for anomalies further (see details). In cases of convective or orographic precipita- sources, their spatial andTable 1. temporal resolution, and methods applied2.2 is presented in Meteorological data sets For the triggering of large-scale floods the amount and spatial variability of precipi- and significant flood peaks atfor other gauges the within time a defined shiftet time between window al. hydraulically that (2010), accounts coherent large-scaleflooding peak floods which flows. are According a characterized to byplying a Uhlemann this spatial criterion, extent 74 ofeach large-scale mean flood floods we annual derive are consistent identifiedculation samples in for patterns, hydro-meteorological the initial factors period soil includingand cir- 1960–2009. moisture, peak For event discharges. precipitation, A initial compilation streamflow of conditions hydro-meteorological factors and related data considered a set oftent large-scale way by floods Uhlemann whichfurther et had updated al. been to (2010) first includeidentified for floods determined from the daily until in period mean 2009 a discharge fromover within consis- records threshold 1952 this at (POT) to study. 162 criterion: These 2002 gauges one flood in and gauge Germany events reporting has using are discharges been a above peak a 10 year flood consistent data base of precipitation and discharge data was compiled. For this, we 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) i 30 Q = erent ff m ects di ff represents the day i ) and y , x 8132 8131 er largely for the flood events investigated; thus ff ), (1) i − m )( y erent days. Therefore, we do not consider a fixed event start , ff x ( i R i 0.9 ) is the 24 h total at a specific grid point ( 1 y = 30 i X , x = ( i ) R y , x erent hydro-meteorological factors instantaneously (e.g. initial river flow) forward We determine flood triggering 3 day precipitation totals within a centered 21 day time ff partial series which arescale derived flood using events the in event the start period 1960–2009. dates identified for the 74 large- by the sum of dailydays) of precipitation rainfall weighted occurrence with before respect the to reference the day: time span (here: API( where prior to the 3tecedent day precipitation maximum. are This clearly procedure separated. ensures For that the event statistical precipitation analysis and of API an- we use ples of the antecedentreflecting precipitation wetness index and (API) initialAPI and is flow initial used conditions as streamflow a prior conditions proxyprecipitation. and for ( We moisture at stored quantify the in API astart onset catchment over dates in of a the at the period 30 each day before flood. the grid period The event point prior for to each the event meteorological of event the large-scale flood set. API is given For the statistical evaluation of eventtotals precipitation, are annual maximum determined 3 over daystatistics precipitation the return entire period periods fromdently are 1960 for determined each to grid for 2009. point. Using the extreme event-triggering value R3d2.4.3 totals indepen- Antecedent precipitation The meteorological event starts (first day of maximum R3d) are used to generate sam- We have performed this analysis forand maximum found precipitation total that of these 3we totals to further 7 do days consider not duration only di the former ones. 2.4.2 Event precipitation precipitation fields, these days will be more or less correlated for adjoined grid points. Uhlemann et al.,event 2010). start The for first a day given grid of point. the Depending R3d on period the defines space-time characteristics the of meteorological the data set. Considering R3d totalssample, avoids local which scale may convective precipitation trigger to2003). flash enter the floods but not large-scale floods (Merzwindow and that spans Blöschl, from 10in days the ahead large-scale to flood 10 eventthe set. days The after time dimension the of lag event the startDuckstein which chosen dates et time links included al., window 1993) considers flood and triggering the travel precipitation times with of flood discharge waves along response the (e.g. river-course (e.g. one grid point to another or from one sub-catchment2.4.1 to another, respectively. Definition of event start dates To identify the start dateuse of the a maximum large-scale 3 flood day from precipitation a totals meteorological (R3d) perspective, at we each grid point of the REGNIE parison of flood events,quired. a The clear start event definition ofdi including an its event onset determines and(event the duration precipitation, point is peak in re- discharges) timeindex and API backward for as in which a time wethe proxy (antecedent evaluate for precipitation precipitation the initial fields soil across moisturecatchment Germany, conditions). areas flood Due at triggering to di date temporal precipitation for dynamics a the of whole of Germany, but one that may vary in space and time, that is, from The total length of the river network considered amounts2.4 to 13 400 km. Methods For the statistical analysis of the hydro-meteorological factors and the consistent com- a confluence enters the river which has the same Strahler order or one order smaller. 5 5 20 15 10 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | n λ 162 = n mean of for which = L : k the sum of the k for the areal mean i Q , (3) ) associated with a certain gauge n l 5year RP n . n  l n n l i P Q = MHQ , (2) n  8134 8133 λ ≥ ) and the mean annual flood (MHQ: exceeds the 5 year return period: i n , (4) p Q  j Q , 5year RP i i X Q ≥ MHQ 5year RP n j p  , k i

Q X 

≥ n k n     p i Q ) is a key figure to characterize the magnitude of a flood at a spe-

Q j p , k } is the integrated outcome of hydrological and hydraulic processes i MHQ Q X j p  , that exceed the 5 year return values. For each event 5year RP the peak discharge i Q 100 j × X k × , n i    λ n λ j is either R3d or API and 5 year RP denotes the values for a 5 year return pe-  , { i X n X represented by the total number of REGNIE grid points in Germany. n 1 X Γ X Γ = = = i Further, we introduce an initial load severity index representing the spatially weighted The streamflow situation at the beginning of the flood event provides information on k k k Q X S gauges. For each gauge aevent partial start series dates is in createdflood the by events. evaluating corresponding sub-catchment identified for the 74 large-scale sum of the initial hydraulic load level in the river network for each event annual maximum discharges from the period 1950 to 2009) for each of the S To further evaluate theand importance to rank of their the spatialprecipitation extent hydro-meteorological and and factors wetness magnitude for severity R3d the indices and past as flood API aggregated event measures: set we introduce 2.4.4 Precipitation and wetness indices L annual maximum series (AMS) of dailyWe mean evaluate discharges the from spatial the periodevent flood 1950 severity. extent For to this and 2009. purpose magnitude weduring using calculate event an the length aggregated of measure the of river network and the total length of the river network: 2.4.6 Peak discharge Peak discharge ( cific location. upstream of that locationsources and management provides issues important instatistical information evaluation particular of for the flood numerous observed estimation water flood peaks and re- at flood each of design. the For 162 gauges the we use the where 5 year RP denotescorrespond the to discharge the for ratio a of 5 the year river return stretch period length and ( the weights sition of the subsequent flood waveand may may increase aggravate inundations. the For load the onditions, statistical flood analysis we protection of schemes normalize the initial the streamflowdischarge con- discharge on values the by event calculating start the ratio date of ( the daily mean resulting “areal mean” dates per sub-catchmenthydrological are analyses. used as the event start date for the the initial hydraulic load of themay considerably river strain cross the section. discharge An capacity already of increased a discharge river level section, and thus the superpo- ratios of R3d andsize API to the 5 years return period are2.4.5 normalized with the Initial mean hydraulic area load To transfer the meteorological eventcell, start to the dates, discharge possibly time varying seriesand given from at hence grid gauge to locations, cell average we the to needsub-basins. event to grid start spatially We integrate dates use for the individual sub-catchments grid of points within the hydrological 162 river gauges as spatial units. The where riod. In this formulation, values ofgrid R3d and points API, respectively, are considered at REGNIE 5 5 20 15 10 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (7) are n λ is the mode is a location β ζ ) for the various hydro- n -direction, T low that moved slowly with x as weights: ff n , observed for the June 2013, λ p Q we fit a generalized extreme value low (CEDIM, 2013a). On the north- p ff Q . (5) MHQ and / 8136 8135 i 5year RP n Q p Q ecting the extension in ≥ ff ecting the extension in x-direction and ) ff k n /γ p 1 , (6) Q −

 )     ζ β − δ α − x k n ( x p normalized by a 5 year flood using γ − Q 5year RP n p p  + is a shape parameter. Q Q 1 γ  × exp − n − λ  (    is the scale parameter a is the scale parameter a n exp exp δ α X = = = ) ) MHQ samples. For the statistical analysis of p x x Nearly all central European flooding events are caused by a complex combination / i ( ( k Q Europe. Moisture sources by continental(Grams evapotranspiration were et even al., more 2014). important vection of moist and warm airfinally over long led distances. The to intense the andJune widespread severe rain 2013. flooding that Responsible in for the Centralits heavy Europe center rainfall from occurred was France end a (29 cut-o May) of(1 over June; May/beginning northern Fig. of Italy 2b). (30 Inshort-wave May; the Fig. troughs latter that 2a) region, travelled to three around eastern the consecutiveeastern Europe cut-o surface flank lows of were triggered the by air upper masses low were and advected near from the the secondary Mediterranean surface and lows, Black warm Sea and region moist into Central and over the Northare Atlantic prevented Ocean; from due enteringand to central humid this Europe air blocking from situation massesand the Atlantic eventually were curved west. air repeatedly into On masses Germany forced the and from Austria. other southeastern side, Europe warm and northward interaction of upper-level pressure systems, associated surface lows and the ad- and “trough central Europethe (TRM)” 500-hPa persisted over geopotential moreclearly height than show two averaged the weeks. for area Chartsthe 16–31 way of with to May low southern France, 2013 geopotential Germany,trough northern values (Fig. results Italy stretching and in 1, Poland. from a This leftto the quasi-stationary deviation the panel) of British long-term geopotential mean Isles valuesative (1979–1995; all anomaly of Fig. values 1, 15 is gpdm right centered andtrough panel). over France, above The is Switzerland area compared flanked and with northwestern by maximum Italy. high The neg- pressure ridges that are located over northeastern Europe 3.1 Meteorological conditions The second halfcentral of Europe. the Two large-scale month weather of patterns May labelled 2013 “low central was Europe exceptionally (TM)” wet across most of 3 Results defined as explained above.peak The discharges flood severity index represents a weighted sum of S where 5 year RP denotes the values for a 5 year return period and the weights where parameter and Q distribution to the AMS ofvalue daily distribution mean has discharges. a The function CDF of of the generalized extreme F 2.4.7 Extreme value statistics To calculate exceedance probabilitiesmeteorological and factors, return i.e. periods R3d,August API, 2002 ( and July 1954distribution floods, we (Embrechts applied et the classical al.,of generalized precipitation 1997). extreme value is Most the appropriateGumbel Fisher–Tippett distribution, and type with widely a I cumulative used extreme distribution value in function distribution, (CDF) the of also case knownF as where that determines the location of the maximum. This distribution is also suitable to the 5 5 25 20 10 15 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erence was even two days. This ff 8138 8137 erences and similarities of the three flood events ff 346 mm was observed at the DWD weather station of Aschau-Stein (31 May to = Even if the flood-related rainfall in 2013 was mainly driven by meso-scale processes The interaction between the pronounced trough and a shallow high pressure system far outside the interquartile range of all heavy precipitation events between 1971 and 200 and 310 %. Thisexplained by substantial the local-scale characteristics increase of thecondensation in air precipitation level mass can on (LCL) the be was large-scale.levels plausibly First very around of 930 low hPa, all, i.e. the on near lifting of the the surface, Munich, first as Stuttgart, three observed at days Meiningen,amount the of in and radiosounding humidity, which stations June Kümmersbruck. decreases with Low almostbe exponentially pressure LCL with converted elevation, ensures into basically that can rain.the a specific Furthermore, water large precipitable vapor content water wasStuttgart, pw large for with as example, values measured the of a up vertical pw to value integral 25 of mm. of 25.9 The mm sounding (1 in June, 12:00 UTC), which is the rain totalsMountains substantially. (near Highest Dresden), the rain mountains sumseast of of Black occurred Forest Stuttgart, and respectively), over Swabian theAlps. the Jura Alpine (west Overall, Foothills crests and the (south rain of of enhancement Munich)ratio the over and between the the Ore low-mountain areal Bavarian ranges rainfall estimated over from the the mountains and adjacent low-lands was between (German part) the maximapecially occurred near Dresden one and dayconsecutive Passau, later. shift the Over of the temporal the main di the very precipitation flow eastern fields direction in parts, of west-to-eastpeaks. es- the direction, Danube, i.e. caused following an additional amplification of thesuch high-water as uplift relatedsuggests to the that troughs additional and orographically-induced advection lifting of moist over air the masses, mountains the R3d increased map This station also recorded1 the June maximum 06:00 UTC 24 h untilmany 2 rain other June sum stations 06:00 in of UTC). the 170.5 OnOverall, mm federal the that states on R3d day, of peak maxima 1 , were rainfall , June registered1 and was almost (from Baden-Württemberg. recorded June homogeneously at (Julian between day 30 May 152, and Fig. 5, left panel). At the upper reaches of Danube and Elbe 3 June, 06:00 UTC), which is situated in the Bavarian Alps at an elevation of 680 m a.s.l. southern and easternR3d Germany (Fig. 4, left panel). The highest rain maximum with considered, we analyzed both maximumcipitation 3 and day precipitation precipitation totals incases, (R3d) the the as quantities month event pre- are beforegridded calculated the precipitation independently data flooding (see at in Sect. each 2.2). terms grid of point API.Event of precipitation In the both REGNIE Maximum 3 day totals (R3d) in 2013 show high values in excess of 60 mm over characteristics are almost1954, the respectively. same Especially for forhigh the the up other Elbe to two 17 catchmentthe floods days large in prior totals considered, May 28 the 2002 days 2013,of event ahead and May, rain start, of mean the totals precipitation and 2002 in higher were flooding Germanyriod compared is was 1881–2012. neglected). 178 to To % For better the of the explain the other whole di long-term month events average (if for the pe- caused embedded convection inheavy the rainfall that mainly lasted stratiform over several clouds days. resulted in3.2 widespread Precipitation Highest precipitation totals wereflood observed event between start, three and asaged four shown over days the by ahead upper the of Elbe time the (Fig. series 3a) and of Danube cumulated (Fig. areal 3b) precipitation catchments. Note aver- that these further to the westtions. created The quite northerly strongrainfall. flow horizontal Largest rain wind was amounts speeds predominant were from foundchains, in upstream northerly e.g. of particular the the direc- west-east-oriented on Alps, mountain ing Ore the downstream of Mountains, days the and with troughs Swabian in maximum combination Jura. with Substantial moist large-scale and unstable lift- air masses that 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erences ff of the Elbe. In 1954, most ff (850 hPa) this led to a substantial 1 − 8140 8139 er largely from those prevailing during the floods ff The most important rainfall characteristics that were decisive for the 2013 flood can These meteorological conditions di To relate the June 2013 precipitation event to the climatological context, we quantify index API. This proxyin is Fig. 5 based minus on 3 the days) starting and date computed of independently R3d at (day each of grid the point of year REGNIE. shown covering more than half ofserved Bavaria precipitation (Fig. directly 6, prior right theextreme onset panel). event of Thus, that the considering occurred flooding, only 1954 within the was the certainly ob- last the 60 most years. 3.3 Initial catchment state 3.3.1 Antecedent precipitation In the next step, we assess initial soil moisture by means of the antecedent precipitation parts of Bavaria experienced 3right day panel). accumulated This rainfalls was in evenAlps excess the of as case 150 well for mm as the (Fig.300 lowlands over 4, mm in the or the western even north parts more.day of (Fig. of These Bavaria. 5, Near the extreme right the Ore totals panel) mountains, correspond recorded to R3d within statistical reached a return values time periods of of shift more of than only 200 years one flood triggering precipitation occurred witheastern a parts shift of of 2 Germanyspectively (Fig. days that 5, between middle correspond the panel). southern toin Note and the the that occurrence the Danube of regions R3d and with(see maxima larger Elbe are Fig. temporal not catchments, 4). di associated re- with Applicationof high of amounts more extreme of than precipitation value statistics 200mated for to years the R3d for lowlands totals north thein yield of that maxima. the return region Return Ore also periods Mountains contributed periods (Fig. to 6, around the middle large 100 panel). increase years Precipitation in are runo esti- Zinnwald-Georgenfeld, Ulbrich et al., 2003). Thea R3d larger totals (Fig. area 4, at middlerain panel) the totals show eastern were parts onlySwabian with observed Jura. values at This in the distribution excessa southern is of so-called mainly border 300 Vb caused mm. of weather by However, Bavaria situation higher northerly as (Ulbrich flow et well in al., as 2003). conjunction over Comparable with the to the 2013 event, reaching values of 312 mm in 24 h (7 to 8 August 2002 at the station of spectively. The most striking feature in 2002 was the extreme precipitation over the Danube and Elbe catchments, (ii)was substantial decisive for rainfall the increase onset overtion of the the with mountains flooding; a that and slight (iii)Germany. temporal almost shift simultaneous areal of precipita- two days between the western andin eastern 2002 parts and of (Germany 1954. only, Areal up 3 day to2002 the rain and inflow totals 68.8 mm from averagedmean in Saale) over areal 1954. were the rain Over 49.3 was upper mm the 75.7 compared Elbe mm upper compared to catchment Danube to 75.9 catchment mm 62.5 (Germany and in 111.2 only), mm the in 2002 and 1954, re- tioned station of Aschau-Stein. Thus,high, one but can conclude not thatflood. extraordinary, the which, rainfall was alone unusually cannot explain thebe dimension summarized of as: the (i) 2013 high – but not extraordinary – 3 day totals over parts of the statistical return periods basedFig. on 6 REGNIE (left data for panel),200 the the years. period return Higher from return periods 1960increases periods are to due are to displayed 2009. the neglected only In short as inof observation statistical period the the of uncertainty Ore range 50 substantially Mountains, years. between Overreturn the 5 the Swabian periods southwestern and Jura parts are and in thepoints a show very peak range southern values between in border excess 5 of of 100 and Bavaria, or 20 the even 200 years. years, Only for example a the aforemen- limited number of grid horizontal wind speeds betweenincrease 20 of and the incoming 75 km water h vaporupper flux limit (Fwv). of This quantity the canKunz, conversion 2011). be of Thus, considered the as moisture high an into Fwvexplain values precipitation the observed substantial (Smith during orographic the and rainfall first Barstad, enhancement days in over 2004; June the plausibly mountains. 2000 at the same station according to the study of Kunz (2011). Together with high 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | cients. ffi coe ff MHQ samples at each / i Q 8142 8141 ected. Note that, for many gauges in the Weser and lower Rhine catchments ff erence to the 2013 event. From the statistical extreme value analysis applied to the In comparison, for the August 2002 and July 1954 floods the initial hydraulic load of Regarding the initial moisture conditions, it is found that API was significantly lower ff river. gauge we obtain anation estimate for for the the June returnFig. 2013, period 10 August of show 2002 the that for and specificmany, the July initial in June 1954 river 2013 particular flow floods. flood at the situ- TheWipper, initial the results Saale, flow upper presented ratios Weiße observed Main in incatchment) Elster, (Rhine exhibit central Mulde return catchment), Ger- periods (Elbe Werra in (Weser theeven catchment) above range catchment), 100 of and 10 years. Naab to 50 and years, in Vils some river (Danube stretches in this range. Theregions lower of coincidence increased API of forthat regions the the of increased July initial increase 1954 hydraulic flood initialferent load (compare mechanisms hydraulic particularly Fig. than along load 7 the high with and Rhine amountssnow-melt was Fig. of in induced 9) the antecedent by suggests alpine precipitation, dif- headwaters presumably of due the to Rhine river and probably also of the Danube Appendix for geographic locations. the river network wassically clearly the lower Danube with and fewincrease its exceptions of tributaries (Fig. , initial 9). , riverhigh In API discharge August and values. (ca. 2002, Similarly, at ba- 0.5 showedits the a southern of beginning noticeable tributaries MHQ). of an These the increaseble. Also July of catchments the 1954 river showed middle discharges flood and also about for upper 0.4 the parts to of Danube 0.8 the and Rhine of show MHQ increased is initial visi- hydraulic loads prominent in this regardthe were western the part Saale of the RiverRhine, Elbe and upper catchment its Main, with tributaries Danube, analso initial with Wipper flow tributaries a and ratio Naab above and 0.8 in no of Isar MHQ. and discharge The the data Werra have River were been available for the June 2013 flood, see Fig. A1 in the panel). This mostly applies to the central and south-eastern parts of Germany. Most in 2013. In general,in the Fig. pattern 9 of (left increased panel) initial resembles hydraulic the load spatial in distribution the of rivers high shown API values (Fig. 7, left but in general notFig. in 4 the and regions Fig. where 7).di the Apart event from precipitation areal was precipitation as highest described (compare above,3.3.2 this is the Initial major hydraulic load As a consequence ofMay, reflected the by large the amounts extendedriver of areas network rainfall of was accumulated high already during clearly API, increased also the at the month the initial of beginning hydraulic of load the in event the precipitation maxima of API correspond wellevents. with Especially those over of R3d, the thisobserved, Ore is API Mountains not was and the below case north 50 mmat for of in the most both two it, of other cases, where the yieldingment highest grid return in rainfall periods points 1954. was below (Fig. Both 20 8). in years The 2002 same and 1954, applies the to initial the soil API moisture in was the comparatively Danube high, catch- and rivers inespecially those the at Weser the catchment. endwith of The decreasing May temporal high (recall distance the rain toof increasing totals R3d), storage weighting resulted capacities in of in and rain the thus very totals very wet month in favorable catchments of API conditions and for May, filling highprior runo to the floodsof in API 1954 and up 2002, toto respectively orographic 150 (Fig. mm precipitation 7). can induced In be by both northerly observed cases, flow only high directions. values over Whereas parts in of 2013 the the Bavarian Alps related of Germany, especially –Danube (Fig. and 7, left most panel). Atcatchment, importantly a the large – number return of periods over grid are points,excess the especially between of in 100 catchments the the and latter upper of Elbe 200 (Fig.between years, Elbe 8, Hannover at left and and some panel). Magdeburg points Note, was even however, related that in to the moderate maximum flooding that at occurred the , Oker API reached high values between 100 mm and in excess of 150 mm over large parts 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ected by ff ected simultane- ff describing the spatial flood extent L 8144 8143 ect of increased initial hydraulic load was stronger ff ected even though the magnitude of the peak discharges ff erences of the June flood 2013 in comparison to August 2002 and ff The major di The August 2002 and July 1954 floods show peak discharges in the order of For the August 2002 and July 1954 events comparable extremes are only observed The initial hydraulic load of the river network (13 400 km) was clearly increased in 74 past large-scale floodeach events hydro-meteorological with factor. This regard allows to for the the spatial identification extent of and singularities magnitude in of flood along the Danube downstreamments of were . Also considerably the a Rhinewas and not Weser as catch- extreme as in the Elbe and3.5 Danube catchments. Index based classification We evaluate the importance of theferent individual flood hydro-meteorological factors events within using the the dif- severitywetness-, indices introduced initial in hydraulic Sect. 2.3. load- The and precipitation-, flood severity indices enable us to compare the July 1954 are that theously Elbe, by the extraordinary Mulde flooding andprecedented which the flood by Saale levels superposition particularly Rivers of weretributaries in flood a of the the waves middle Danube resulted part showed in flood of un- responses the and Elbe. jointly Further, contributed nearly to all the record periods of 100 yearsand occurred the at Isar, Rott the andof Weiße Inn 50 Elster years in and were the observed Mulde DanubeSalzach at in catchment. as the well Flood the Danube as downstream peaks Elbe the Regensburg, withand catchment the upper a Naab, Isar right Inn return rivers. panels), and However, period as the canextended river be August stretches seen 2002 with from high Fig. and 11amounts magnitude July to (middle flood 1954: 19 % peaks the in are index Augustin clearly 2002, the 27 less % Appendix in for July geographic 1954 locations. and 45 % in June 2013, see Fig. A1 high amounts of antecedent precipitation and substantial initial hydraulic load. 100 years at thegen Elbe and Mindel between and Dresdendownstream of and of 50 Wittenberg Wittenberg, years to in at Wittenberge the parts (see Freiberger Fig. of and 11, the Zwickauer left Mulde Mulde, panel). and In Re- July the 1954 Elbe return this applies to the Saale, Werra and Main catchments. However, these regions show as a consequence of dikefected breaches. by It flooding is did remarkable not that receive exceptional large amounts parts of of rain catchments (see af- Fig. 4). In particular, as the Inn and Salzach100 years. rivers In experienced addition, peak the discharges Isar,return Naab with periods. and return Further periods rivers in showed above well flood the peaks as Rhine above the 50 catchment, year Werra50 the year river Neckar in return and the period. partsCoswig Weser New of and catchment record Lenzen the (along experienced water Main a peakand total levels as discharges length at were of above the registered 250 km), Danube at atand in the the Elbe Passau. Saale rivers, Elbe Severe downstream as of flooding between Halle, well occurred as especially along along the the Elbe Danube tributaries Mulde and Saale, in most cases ments showed flooding, namely theticularly Weser, Rhine, the Elbe and Elbe Danubeextraordinary and catchments. high Par- Danube flood levels. rivers Ina the and return Elbe period many catchment of flood of 100 peak yearsberge, their discharges along the the exceeded tributaries Mulde, whole and Elbe were stretch thethe between Weiße a Dresden Danube Elster and catchment, and Witten- the Ilm section rivers of tributaries the of Danube the downstream Saale of River. Regensburg In as well in June 2013 thanflow in ratios August occurred 2002 onlytributaries. and in July particular 1954. However, river extraordinary stretches, high namely initial 3.4 the Saale river Peak and flood discharges its In June 2013, 45discharges % above a of 5 year the flood. total As can river be network seen in considered Fig. 11 in (left Germany panel), all showed major peak catch- for few river stretchesInn in and the Salzach rivers Danube in catchment 2002 including and the the upper Regen,June Iller, upper 2013 Lech given and Isar, the Isar Ilz, comparison rivers to60 in other years. large-scale 1954. Hence, summer the flood events aggravating from e the last 5 5 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ff er ff erent hydro- ff 8146 8145 13.2) suggest that additional factors and characteristics = RMS E The results illustrate that the sequence of prevalent circulation patterns in the month The span specifies the percentage of data points thatThe are inclined considered orientation of for the estimating response surface indicates that both precipitation and Figure 12 shows a scatterplot of the precipitation and wetness indices of the 74 past Among these events, the June 2013 flood is characterized by the highest wetness, for the exceptional hydrologicalment severity the of increased the initial June hydraulic 2013 load flood. in In the the river Saale network catch- has been an additional combination with high amounts oftinuously precipitable sustained water by in the the strongpersistent atmosphere. influx flow This of of was high air con- water from vaporonset the resulting of north from the to a flood, north strong unprecedented and east.large amounts Second, areas of during of “antecedent” the Germany. precipitation weeks As occurredamply before the over overlapping, the areas these of extremely high wetresponse antecedent initial and to conditions event event strongly precipitation precipitation. intensified were Hence, theand particularly wet runo initial the catchments interplay within of a event large precipitation areal superposition turns out as the key driver significantly from situations associatedand with thus other cannot past explain largeGermany. For alone scale this flood, the floods diverse in extraordinary hydro-meteorological factors Germany acteristics. outcomes showed First, exceptional of char- the development the of June eventorographic precipitation flood and rainfall in 2013 enhancement particular was in the driven substantial by a very low lifting condensation level in This study provides newthat insight caused to the the characteristicsciated June of return flood hydro-meteorological periods. factors 2013 Thevalues and data-based which approach presents consider further a bothmeteorological comprises the statistical factors aggregated spatial evaluation and index extent of allowsflood and events. the for magnitudes the asso- of the comparison di to past andof May future put large-scale an importantobserved. boundary condition However, for with the regard extraordinary precipitation to anomaly persistence, the circulation patterns did not di melt or seasonal variations in base flow play a role in this4 regard. Conclusions overlaps of either factors as well as other hydrological processes, for instance snow the response value at a certain location. wetness are equally relevant factors tomodel, explain resulting flood flood severity severity. According index totionate values this with above around precipitation 40 andthe increases response wetness surface, approximately severity. visible propor- However, for both precipitationvalues index below the values 60, below concave and 30 the shape and moderateability wetness of performance of index of flood the severity LOWESS ( modelinfluence to this explain relationship. vari- The spatial variability and the corresponding degree of areal indices as flood drivers anda the locally-weighted scatter flood plot severity smooth indexcally (LOWESS) as model weighted a (Cleveland, linear 1979). dependent least-squares For variable regression, thisof we the lo- 50 apply tri-cube % weight are function used. and a span June 2013 by a factorevent. of These proportions three emphasize and the isitation prominent nearly role and two of increased times extreme as antecedent initialformation precip- high of hydraulic as the load for record in the flood August in the 2002 June river 2013. networklarge-scale as floods key in factors Germany. forthe The wetness the June index, 2013 whereas the floodthe July is precipitation 1954 the index. flood To most is explore extreme by the far in relationship the terms between most precipitation of extreme and in wetness terms of June 2013, August 2002 and July 1954 events are listedinitial in hydraulic Table load 2. and floodthe severity August indices 2002 which flood are and moreJuly with than regard 1954 twice to flood. the wetness In values more of than contrast, five the times precipitation the index value of of the July 1954 exceeds the value of terms of extreme situations associated with individual events. The index values for the 5 5 25 15 20 10 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ce of ffi , 2013. er support for the hypothesis that the ff ce of Environment, Health and Consumer 10.5194/hessd-10-9533-2013 ffi ecting large parts of Bavaria. In contrast to ce of Environment, Measurements and Envi- ff ffi 8148 8147 ). They emphasized the increased probability ce of environment, water management and factory 2 ffi ce of Environment, Agriculture and Geology (SMUL), ffi erent hydro-meteorological factors than to unusual magni- ff , 1990. ce for water management, coast protection and nature protection ffi The study was undertaken and financed under the framework of CEDIM ce of Flood Protection and Water Management (LHW), Thüringen State ffi 10.1007/BF00866871 ce of Environment and Geology (TLUG),ce Hessian for Agency Nature, for Environment and the Consumer Environment Protection and North Rhine-Westphalia (LANUV The interplay of various hydro-meteorological factors has been studied primarily for In comparison, the August 2002 flood was triggered by extremely intense precipita- in the Upper Danube basin,Earth and Syst. comparisons Sci. Discuss., with 10, the 9533–9573, 2002, doi: 1954 and 1899 floods, Hydrol. atmospheric circulation patternsdoi: from 1881 to 1989, Theor. Appl.Gewässerkunde, Climatol., Deutscher 42, Wetterdienst, Koblenz, 155–167, 2013. ffi ffi such extreme scenarios could provideard, new spatial insight risk to as patterns well of as large cumulated scale flood flood losses. haz- corresponding transition of related weather conditions. The hydrological evaluation of scenarios requires an in depth analysis of synoptic meteorological situations and the tudes of the factorsinfluence themselves. of Our catchment results wetness is o floods. also Hence, considerable using for high-return theof period magnitudes knowledge large-scale of gained the about variousfloods from the hydro-meteorological the factors characteristics past associated 60 and withnarios. years, large the we In can scale range this advance the regard,be derivation the of analysed data plausible extreme base concerning sce- compiledmeteorological the for factors possibilities large as scale of for floodsJune coinciding instance 2013 in extremes and the Germany event of combination precipitation may as of individual in initial hydro- July 1954. wetness Of observed course, in the development of such of Nied et al.in (2013) the who Elbe investigated catchmentof the (ca. occurrence role 150 000 of of km large-scale antecedentnote, floods soil also related moisture Klemes to for (1993)unusual floods large-scale reasoned combinations high that of di soil high moisture. hydrological extremes On are that more due to tion which was relatively localized inerably the high Ore values Mountains. Initial in wetness somewith showed parts consid- event precipitation. of The Germany floodingceptional but in amounts these July of areas 1954 event did was precipitation forthe not a appraisal the coincide of main largely Blöschl part et al. causedflood (2013), by in initial ex- Germany. wetness was a minor factor for the July 1954 small-scale catchments, (e.g. Perry and Niemann, 2007). One exception is the study west to east, i.e.flood following waves the from streamflow the tributaries. direction, Third,marks amplified the a the spatial new extent superposition record of of for highrecord the large magnitude water flood scale levels peaks floods along in extensive Germany river since sections at in least Germany. 1952 and set new aggravating factor. In the Danube, the movement of the event precipitation field from Blöschl, G., Nester, T., Komma, J., Parajka, J., and Perdigão, R. A. P.: The June 2013 flood Bárdossy, A. and Caspary, H. J.: Detection of climate change in Europe by analyzing European BfG: Länderübergreifende Analyse des Juni Hochwassers 2013, Bundesanstalt für References O NRW), Lower Saxony O (NLWKN), Water and Shipping ManagementInstitute of for the Hydrology Fed. (BfG) Rep. who (WSV), provided prepared discharge by data. the Federal The service charges for thishave open been access covered publication by aHelmholtz Research Association. Centre of the Protection (LUGV), SaxonySaxony-Anhalt State O O O Geology (HLUG), Rhineland Palatinate O inspectorate (LUWG), Saarland Ministry for Environment and Consumer Protection (MUV), Environment (LfU), Baden-Württembergronmental Protection O (LUBW), Brandenburg O – Center forthe Disaster German Weather Management Service and (DWD) Risk for Reduction providing REGNIE Technology. We data, gratefully Bavarian State thank O Acknowledgements. 5 5 30 25 20 10 15 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 2014. , 2013. , 2004. , 2007. erent approach, in: Ex- ff , last access: 2 July 2013. 10.1051/lhb/2014001 , 2011. 10.1127/0941-2948/2013/0436 http://www.cedim.de/download/FDA_Juni_ http://www.cedim.de/download/FDA_Juni_ , 2013. , 1957. http://www.swissre.com/media/news_releases/ , 1979. 10.1016/j.jhydrol.2006.10.014 8149 8150 , last access: 18 December 2013. , 2009. , 2014. , 1993. , 1987. , Cnter for Disaster Management and Risk Reduction Tech- , Center for Disaster Management and Risk Reduction Tech- 10.1175/2010JHM1231.1 , 2005. , 2003. enbach am Main, 1969. 10.2307/2286407 ff 10.5194/hess-17-1401-2013 10.1029/TR038i006p00913 10.1175/1520-0469(2004)061<1377:ALTOOP>2.0.CO;2 10.5194/nhess-9-1409-2009 10.5194/nhessd-2-427-2014 10.1029/2005WR004177 10.1029/2002WR001952 10.1029/WR023i003p00481 10.1016/0022-1694(93)90202-K treme Hydrological Events: Precipitation,167–176, Floods 1993. and Droughts, vol. 213, IAHS, Yokohama, 458, doi: Deutscher Wetterdienst, O cost insurers worldwide USDRe 44 – billion, Leading Global Preliminary Reinsurer,nr_20131218_sigma_natcat_2013.html catastrophe available estimates at: for 2013, Swiss tors: new insights fromdoi: the August 2002 flood in Germany, Water Resour. Res., 41, 1–16, verursacht-180-000-versicherte-schaeden-in-hoehe-von-fast-2 the Central European floods in June 2013, Nat. Hazards Earth Syst. Sci. Discuss., 2, 427– 38, 913–920, doi: analysis of large-scale soil moisture patterns17, in 1401–1414, the doi: Elbe River basin, Hydrol. Earth Syst. Sci., using EOFs, J. Hydrol., 334, 388–404, doi: 1377–1391, doi: drometeorol., 12, 27–44, doi: flood in June 2013 in Germany, Houille Blanche, 1, 5–10,doi: doi: frequency and persistence of1423, circulation doi: patterns, Nat. Hazards Earth Syst.precipitation Sci., climatology 9, – Part 1409– I:data Generation set and (HYRAS), validation of Meteorol. a Z., high-resolution 22, gridded 235–256, daily doi: sichertehttp://www.presseportal.de/pm/39279/2505807/erste-schadenbilanz-hochwasser-2013- Schäden in Höhe von fast 2 Milliarden Euro, available at: sicherungswirtschaft?, DCM, Meckenheim, Würzburg, 47–63, 2004. catchment conditionsdoi: on seasonal flood risk, Water Resour. 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Un., Nied, M., Hundecha, Y., and Merz, B.: Flood-initiating catchment conditions: a spatio-temporal Perry, M. A. and Niemann, J. D.: Analysis and estimation of soil moisture at the catchment scale Munich Re: Natural Catastrophes 2013 Analyses, Assessments, Positions, Munich, 2013. Smith, R. B. and Barstad, I.: A linear theory of orographic precipitation, J. Atmos. Sci., 61, Petrow, T., Zimmer, J., and Merz, B.: Changes in the flood hazard in Germany through changing Kunz, M.: Characteristics of large-scale orographic precipitation inMerz, a linear B., perspective, Elmer, J. F., Hy- Kunz, M., Mühr, B., Schröter, K., and Uhlemann-Elmer, S.: The extreme Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., and Gratzki, A.: A Central European Kron, W.: Zunehmende Überschwemmungsschäden: eine Gefahr fürMerz, R. and Blöschl, G.: die A process typology of Ver- regional floods, Water Resour. Res., 39, 1340, GDV: Erste Schadenbilanz: Hochwasser 2013 verursacht 180.000 ver- Ettrick, T. M., Mawdlsey, J. A., and Metcalfe, A. V.: The influence of antecedent Embrechts, P., Klüppelberg, C., and Mikosch, T.: Modelling Extremal Events – for Insurance Duckstein, L., Bárdossy, A., and Bogárdi, I.: Linkage between the occurrence of daily atmo- Deutscher Bundestag: Bericht zur Flutkatastrophe 2013: Katastrophenhilfe, Entschädigung, CEDIM: June 2013 Flood in Central Europe – Focus Germany Report 2Cleveland, W. – S.: Robust Update locally 2: weighted regression Pre- and smoothing scatterplots, J. Am. Stat. CEDIM: June 2013 Flood in Central Europe – Focus Germany Report 1 – Update 2: Pre- 5 5 30 25 30 25 10 20 15 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 10.5194/hess-14-1277- Analysis/classification large scale flood events statistics based on annual series Precipitation index for all past flood events treme value statisticsconditional based on past on flood events Wetness partial index for series all past flood events conditional on past flood events Initial hydraulic loadevents index for all pastmum series flood Flood severity index for all past flood events daily mean extreme value statistics based on annual maxi- event- based resolution Dailyevent- based maximum 3 dayDaily totals R3d. extreme value event- API quantificationbased 30 days aheaddaily of mean R3d; ex- extreme value statistics based on partial series event- based 8152 8151 2 2 , 2003. 1 km Point information; 162 gauges and related sub-basins Point information; 162 gauges and related sub-basins Europe1 km Daily Relative frequency of persistency prior to past 1 1 and hy- and hy- 3 3 1 /WSV /WSV 2 2 REGNIE DWD Discharge gauges BfG Discharge gauges BfG drometric services of federal states drometric services of federal states 10.1256/wea.61.03A Antecedent precipi- tation index API Ratio of initialflow to river mean annual flood Data sources, resolution and analysis methods for hydro-meteorological parameters. , 2010. between 1952–2002, Hydrol. Earth2010 Syst. Sci., 14, 1277–1295, doi: European floods of August 2002:58, Part 371–377, 1 doi: – Rainfall periods and flood development, Weather, PrecipitationInitial catch- ment state REGNIE DWD Peak flood dis- charge Hydro-meteorological factorsCirculation patterns Data source Spatial resolution DWD Temporal German Weather Service, German Federal Institute of Hydrology, Water and Shipment Administration. Table 1. 1 2 3 Uhlemann, S., Thieken, A. H., and Merz, B.: A consistent set of trans-basinUlbrich, floods U., in Brücher, Germany T., Fink, A. H., Leckebusch, G. C., Krüger, A., and Pinto, J. G.: The central 5 26 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | nomaly nomaly site at by the a d d

(left) and r Web e provide i i 3 3 g http://www.esrl. Data/imag May 201 from the 1 1 USA, 5. Credit: for 16 – 3 9 9 Colorado, 1979-19 -day mean mean -day n n 6 6 8154 8153 ) 12.7 6.0 6.1 i Q S ) 74.6 35.4 49.8 ) 16.9 30.1 55.2 p Q based o Boulder, S l height, 1 l height, R3d y / / a ) 114.1 47.3 21.1 a S API S PSD, PSD, eopotenti climatolog aa.gov/psd gg LL . IndexPrecipitation index ( Jun 2013 Aug 2002 Jul 1954 Wetness index ( Initial hydraulic load index ( Flood severity index ( ct to the : 500 hPa 500 hPa geopotential height, 16 day mean for 16–31 May 2013 (left panel) and OAR/ESR ww.esrl.no e e 1 / 1 / Severity indices for June 2013, August 2002 and July 1954 floods. w w

Figure NOAA http:// in resp Table 2. noaa.gov/psd/ Figure 1. anomaly in respect tothe the NOAA/OAR/ESRL climatology PSD, Boulder, based Colorado, on USA, 1979–1995. from Credit: their data/image Web provided site by at 1 2 3 4 5 6 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 28

. ment in tchment tchment ipitation ipitation h h a a c c

27 wetter3.de Elbe catc Danube c imum pre imum r r relative relative s of 500 . x i i a a ith analys r the uppe 3-day max the upper 00/500 hP wetter3.de o o w 0 w 00:00 UTC with analysis of (b) es) and 10 age credit: age credit: 00 UTC ipitation f ipitation ior to the to the ior n n ) and for r r c c m m a a (GFS). I e 2013(b) e (white li e (white r r n n r Saale ( r Saale mean pre mean m m he days p n grey. n grey. and for the upper Danube catchment (Germany l l t i t i e e 8156 8155 and 1 June 2013 (a) (a) cast Syste cast and 01 Ju face pressu f e e f the riv lated area is marks marks is ghlighted i o i o u u x x lobal For 0 May (a) lines), sur lines), 3 3 G G k k e inflow e inflow itation is h itation ies of cum ies of ). The x-a The ). hh rr pp ight (blac ight charts for ) from the ) from ee ss axis marks the days prior to the 3 day maximum precipitation totals. Event : Time se vent preci y up to t x ny only; b 3 3 n n E E a Weather charts for 30 May Time series of cumulated areal mean precipitation for the upper Elbe catchment in : Weather . The potential h potential phy (color 2 2

Figure Germa (Germa totals. o o a a (b) 1 2 3 4 5 6

Figure hPa ge topogr only); precipitation is highlighted in grey. Figure 3. Germany up to the inflow of the river Saale Figure 2. 500 hPa geopotential height (blackative lines), topography surface (colors) pressure from (white the lines) Global and Forecast 1000/500 System hPa rel- (GFS). Image credit: 1 2 3 4 5 6 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 29

30 ne 2013 u u st 2002 and 190 um R3d um u u m m sets for J ted maxi (left), Aug 8 August, a a o o NIE data G G une, 220 t June 2013 e event rel e event J J h h ing to RE ing t where t t where d d onds to 1 y total) for for y total) n p p a a 8158 8157 4 (right). 4 (right). tion accor of the 3-d a 5 a 5 152 corres IE grid poi N precipit nd July 19 m urred (end ). The day ach REGN a a t c t c e e y maximu e year at igure 4 oc (middle) (middle) 1954 (righ aa hh 22 FF : The 3-d : The . : Day of t : Day ording to Day of the year at each REGNIE grid point where the event related maximum R3d ugust 200 The 3 day maximum precipitation according to REGNIE data sets for June 2013 (left ), and July 4 4 y y c 5 c 5 e e A A

Figure to 9 Jul total ac total (middl

Figure (left), Figure 5. total according to Fig. 4 occurred(middle (end panel), of the and 3 dayAugust, July total) and for 1954 190 June 2013 to (right (left 9 panel), July. panel). August 2002 The day 152 corresponds to 1 June, 220 to 8 Figure 4. panel), August 2002 (middle panel) and July 1954 (right panel). 1 2 3 4 5 6 1 2 3 4 5 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 32

31 3 (left), 3 (left), 1 1 isplayed isplayed id point r r d d in June 20 EGNIE g ain totals ain totals r r R R the floods r details. r details. sponding or each 54 (right). 54 (right). e f f e e 9 9 0 days for t for furth 3 3 x x cipitation cipitation and July 1 or the corr f f e e 8160 8159 ht). See te API over (middle), (middle), 0 to 2009 g ximum pr g x x 2 x 2 6 6 a tion Inde y 1954 (ri ugust 200 3-day ma a a l l d from 19 d from

A A o f o f le), and Ju nt Precipit nt f the peri periods o 013 (left), ee oo dd : Anteced Antecedent Precipitation Index API over 30 days for the floods in June 2013 (left Return periods of 3 day maximum precipitation for each REGNIE grid point derived from data 2002 (mid e 4: June 2 6: Return 6: Return 7 7 r r

Figure August

Figure derived in Figu Figure 7. panel), August 2002 (middle panel), and July 1954 (right panel). See text for further details. Figure 6. from data of the periodJune 2013 from (left 1960 panel), to August 2009 2002 for (middle the panel), corresponding and rain July totals 1954 displayed (right in panel). Fig. 4: 1 2 3 4 5 1 2 3 4 5 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

33 34 middle), middle), rence of ( r ( r lculated lculated ht). ht). a a g the occu ust 2002 n g n g r MHQ (c y 1954 (ri l o o ditional o (left), Au n n 3 malized f malized 3 le),and Jul r r d d normalized for MHQ (calculated from i Q igure 7 co June 201 : : 002 (mid F F start Qi no 2 2 8162 8161 layed in 0 to 2009 p p 6 6 ical event t), August t), August f f g g e API dis d from 19 d from h h o o e 2013 (le meteorolo n n t). t). eriods of t in the peri the in hh 09) for Ju w ratio at pp 00 oo : Return : Return 1954 (rig Return periods of the API displayed in Fig. 7 conditional on the occurrence of large- Initial flow ratio at meteorological event start ale floods ale floods S 1950-2 8 8 y y : Initial fl : Initial c c 9 9 M M

Figure large-s and Jul

Figure from A from AMS 1950–2009) for June 2013panel). (left panel), August 2002 (middle panel), and July 1954 (right Figure 9. Figure 8. scale floods inpanel), the and period July 1954 from (right 1960 panel). to 2009: June 2013 (left panel), August 2002 (middle 1 2 3 4 5 6 1 2 3 4 5 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

36 by the l states. 3 (left), re made d a a 1 1 normalized i 35 Q 09: June lized for a a e data we the feder r June 20 V) prepare V f f g o g o ces of the federal states. ffi m 1960-20 m (Qi norm t t o o any. Gau offices o Rep. (WS scharges f e . i m m period fr event star e e l l ental stat ds in Ger of the Fed od peak d m o o o o ht) loods in th eorologica g g t t f f 8164 8163 ) of flood peak discharges for June 2013 (left panel), nagement right) flo right) n nd environ (Tn) of fl ( ( a a T a a atio at me ly 1954 (ri arge scale scale arge r r l u u y (BfG) n periods uly 1954 hipping M r g r g J J rrence of l rrence dle),and J nitial flow nitial flow u u d d r Hydrolo ater and S dle), and alized retu oo dd eriods of i eriods nn WW on the occ 2002 (mi pp tt Return periods of initial flow ratio at meteorological event start ( Regionalized return periods ( Institute f 2002 (mi e by the e by 11: Regio 0: Return onditional onditional ft), Augus l l c c 1 1 e e

Figure August availab Federal

Figure MHQ) 2013 (l August 2002 (middle panel),made and July available by 1954 the (right Waterthe panel) and Federal floods Institute Shipping in for Management Germany. Hydrology Gauge of (BfG) data the and were Fed. environmental state Rep. o (WSV) prepared by Figure 11. for MHQ) conditional onJune the 2013 (left occurrence panel), of August 2002 large (middle scale panel), floods and July in 1954 the (right period panel). from 1960–2009: Figure 10. 1 2 3 4 5 1 2 3 4 5 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 37 contain between or code) t t l

lationship er does no x (grey co x (grey x e n e e n right cor verity inde verity for the r n n ) e e at the ope LOWESS he flood s ( ( h h t t ictors for for ictors ny. Note t t smooth t smooth a a d o d o 8166 8165 scatter pl s in Germ ces as pre as ces t t i i -weighted ind etness flood even yy ww data. 12: Locall 12: ation and ation large scale t t ed e

Figure precipi of past observ 1 2 3 4 5 6 Outline map of referred geographic locations. Locally-weighted scatter plot smooth (LOWESS) for the relationship between pre- Figure A1. Figure 12. cipitation and wetness indices as predictorslarge for scale the flood flood events severity in index Germany.data. (grey Note color that code) the of open past right corner does not contain observed