Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 5 ects and ff Sciences erent Euro- ff , U. Ehret erent climatic 4 Discussions ff ratios (less than Earth System Hydrology and ff , E. Gaume 3 , L. Marchi 2 ect, these analyses have shown that the ff 10740 10739 , D. Zoccatelli response to response. The flood response can be reasonably well 2 ff ff ¨ asserentwicklung, Bereich Hydrologie KIT Karlsruhe, Germany , M. Borga 1 ´ e, IFSTTAR, GER, 44341 Bouguenais, France 5 ¨ ur Wasser und Gew This discussion paper is/has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS if available. Institut f Natural Hazards Division, Geological SurveyDepartment of of Spain Land (IGME), and Madrid, Agroforest Spain CNR Environment, IRPI, University Padova, of Italy Padova, Legnaro, Italy LUNAM Universit tria and Slovakia)forcing. tend to Consistent occur with in the the seasonality e summer months, revealing di 1 Introduction Analyses of inventories of flashassociated floods space-time in scales Europe in have thepean outlined distribution seasonality regions of e (Gaume these et eventsflash al., across 2009; floods di Marchi in et thethe al., Mediterranean autumn 2010). region months, (Italy, According whereas France to and events these in Catalonia) analyses, the mostly inland occur Continental in region (Romania, Aus- motion had a noticeable impact on20 %) flood peak characterized magnitude. the Small runo reproduced runo with the distributed hydrological model,vations using and high model resolution parameters rainfall obser- calibratedarea at impacted a by the river storm. section which includes most of the from radar observationscharge and estimates a from rain athe gauge detailed post-event hydrometeorological network, survey, provides and together the hydrologicalstorm with opportunity mechanisms and indirect to associated the study peak with ensuingestimates dis- of this flood. peak extreme discharges Radar-derived areconstruct used rainfall, hydrographs along at streamgauge with multiple a data locations. distributedand The and hydrologic influence motion model indirect of to on storm re- structure, thements evolution modeled of catchment flood rainfall” hydrograph (Zoccatelli is et al., examined 2011). by It using is the shown that “spatial downbasin mo- storm The 2 June 2008 flood-producingmany storm is on examined as the a Starzelupper prototype river tail basin for of organized in the convective South-Westflash systems Ger- precipitation flood that frequency dominate peaks distribution the in and this are likely region. responsible for The the availability of high-resolution rainfall estimates Abstract Hydrol. Earth Syst. Sci. Discuss.,www.hydrol-earth-syst-sci-discuss.net/8/10739/2011/ 8, 10739–10780, 2011 doi:10.5194/hessd-8-10739-2011 © Author(s) 2011. CC Attribution 3.0 License. Extreme runo short-duration convective rainfall in South-West Germany V. Ruiz-Villanueva Received: 22 November 2011 – Accepted: 22Correspondence November to: 2011 V. – Ruiz-Villanueva Published: ([email protected]) 7 DecemberPublished 2011 by Copernicus Publications on behalf of the European Geosciences Union. 5 and E. Zehe 1 2 3 4 5 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). 2 ¨ oschl, 2006). sub-basin of the Neckar river 2 10742 10741 ratios. Finally, hydrologic modeling analyses are generation under flash flood conditions (Braud et ff ff These observations are used together with high-resolution rainfall observations de- A detailed post-flood survey was carried out in the period 10–14 November 2008 by In this paper, we examine the hydrometeorology and hydrology of an extreme flood The recognition of the poor observability of flash floods has stimulated in the last rived from radar andreconstruct rain the event gauge over observationsrainfall various estimates and sub-basins and a and indirect estimates distributed tovations of check hydrologic and peak the simulations model discharges. consistency from Indirect to the between floodscale hydrological peak water model obser- are balance examined andused to the to assess runo the examine the flood dependencepattern of of flood rainfall response and inZoccatelli storm the et motion. Starzel al. River For (2011) on this based the on purpose, spatial the we Spatial use Moments the of method Catchment devised Rainfall. by discharges from flood marks (Lumbrosotime and evolution Gaume, of 2011) the and floodflood documentation by and of means the of local informationdetailed authorities. collected pattern from of eyewitnesses Overall, flash-flood of response the this along has the stream made network. it possible to depict a spatially- rainfall rates over the Starzeland River claimed catchment the for lives a ofon period three of people. volume approximately Estimates scan 1 of hby reflectivity the 30 min related the observations rainfall German event from are Weathercharacterise two based Service the C-band (DWD) structure weather (Fig.input and radars 1). to motion operated a The of distributed hydrological rainfall the model estimates for flash flood are flood-producing simulation. used storman to international and team as of an experts. The field work included indirect estimation of peak and flood. Asareas, analyses an of “end Starzelextreme member” response floods provide in in insights the small-medium intoJune flood size the 2008 response processes catchments flood in that in spectrum the produce South-Westernwas Starzel at Germany. produced river small basin, by The similar drainage an to 2 organized other extreme system floods of in thunderstorms. the region, The storm produced large system in South-Western Germany, Fig. 1), through analyses of the 2 June 2008 storm in the Starzel catchment at Rangendingen (a 120 km Delrieu et al., 2005)Gaume and et al., at 2009). theexplicitly Statistical regional, incorporate regional data multi-event from procedures scale post-flood have surveysquantiles (Costa been to (Gaume developed and improve which et the Jarrett, estimation may al., of 2008; data 2010). extreme generated Ongoing research by focuses thistween on various observational understanding hypotheses how methodology of the mayal., runo 2010; be Bonnifait used et to al.,2008; 2009), discriminate Versini et to be- al., test 2010) flash and flood to forecasting identify models patterns (Norbiato of et predictability al., (Bl decade the development offlood a surveys, focused use monitoringelling of methodology, (Costa which weather and involves radar Jarrett, post- observationet 2008; al., re-analyses Borga 2011). and et The al., hydrologicalcharacterisation implementation 2008; of mod- of flash Gaume this floods, and observation both Borga, strategy at 2008; has the led Brauer individual to event an scale improved (Hicks et al., 2005; distributions for short durationat small rainfall and drainage areas areprominently represented in likely in this responsible flood frequency region foreven analyses (Parajka the for those most et with flood stream al., relatively gauging peaks events stations, long 2010). whose records. However, observation Flash theymeteorological floods and are networks are monitoring (Carpenter not spatially-limited, et is locally al.,Brauer 2007; challenging rare et Borga al., given et 2011). al., the 2008; Smith available et hydro- al., 2011; pared to thoseregime occurring is in generally the more intenseareas, Mediterranean flash in region. floods the occurring Mediterranean in the Region Evencific belt than from though role in Southern in the Germany the to the Continental flashOrganised Romania regional play flood convective a flood spe- systems hydrology dominate at the small upper drainage tail areas of (less the than precipitation 100 km frequency spatial extent and duration of the events is smaller for the Continental events com- 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 1 − s 3 . In order 1 − s 3 C) and maximum in July ◦ production is influenced by ff 0.5 − . A total of 498 yr of peak flow obser- 2 , near the Starzel basin) on 20 May 1906, ), with a central value of 150 m 2 2 10744 10743 km 1 − (s ¨ abische Alb in the South. Also, the rim of the plateau 3 for this catchment). A second catastrophic flood is re- ¨ abische Alb rim. The analysis of regional extreme floods 1 − ected by the flash flood of 2 June 2008, covers an area of s ff C, with minimum in January ( ◦ 3 ). The event consisted of three individual flood events that oc- 2 100-yr floods (more than 70 % are larger than 10-yr floods) (Fig. 3). ); the event claimed the lives of 40 people. According to the avail- > . 2 1 − . Overall, this shows the relevance of floods triggered by organized km 1 1 − − s 3 , i.e. from 1.0 to 1.5 m (s 1 3 ), with areas ranging from 29 to 331 km − . The elevation ranges from 419 to 954 m a.s.l., (average 644 m) and the mean ects caused by the Schw 2 s 2 ff C). The Starzel river catchment is part of the Neckar river system (Fig. 1). As 3 ¨ ◦ abische Alb. In the catchments along this edge, runo The three highest recorded flood events at each of the 15 gauges are character- Estimates of the 2 June 2008 flood peak at Rangendingen range between 125 and According to long term data (1961–1990) recorded in Hechingen, average annual The catchment consists mainly of Jurassic sedimentary rocks, predominantly lime- with 135 m on 4–7 June 1895at Balingen in (128 a km curred catchment on close 4, 5 to and200 the 7 mm June Starzel 1895 rainfall. each river: causedthe In by the intense catchment the thunderstorms Eyach to totaling days saturation. river around beforei.e. basin 2.7 The the m reported flood, peak substantialable discharge regional rainfall at flood occurred, frequency Balingen analyses, is bringing (which this 350 flood is m peak around exceeded 1000 210 yrported m return for period the Echaz catchment (133 km fore representative inthree this highest region recorded withoccurred floods during respect at this gauge to season (theand Rangendingen, occurrence other 21 in two season. June largest operation 2007). floodswhich since occurred From In information 1991, on an is 11 fact, historical all reported August perspective, 2002 the (albeit the not largest in flood the in form the of region for a systematic record) occurred range from 2-yr to These data provide a representativemation sample about of the extreme climatology floods of in(8.4 extreme the km) precipitation region. rainfall is amounts The provided for infor- infrom various the raingauge durations form statistics of (5 min–72 gridded from h) the and KOSTRA return project periods (DWD, 1997). derived ized according topredominantly the in month the of period flood May–August. occurrence. The Almost Starzel 75 event % of of June the 2008 floods is occur there- gauge measurements provided by theered local in water the authorities. analysis The were(120 catchments selected km consid- to be similarvations in is size to included the in StarzelThe the at recurrence overall Rangendingen period regional of sample, the with three a highest mean recorded record flood length events of for 33 yr. each catchment recorded floods and 2-yr and 100-yr peak discharge statistics derived from stream- is based on data from 15 stream gauges, namely peak discharge of the three highest Schw karst e is a typical spotformation and for for the orographic rainfall triggering900–1000 enhancement. mm of a Annual convective rainfall along uplift, the which rim facilitates lies at thunderstorm 175 m to provide a context forcatchments the along Starzel flash the flood, Schw we examined the flood hydrology of the precipitation is 836 mm,nual with temperature is maxima 8.3 in(17.3 summer (fromshown June by to the August); relief map mean in Fig. an- 1b, it is situated at the edge of a Karst plateau named stone, marls and claystone.erns, is Karst locally topography observed includingstone on fissures, outcrops. the sinkholes Three very and mainforest, eastern cav- land agriculture portions use and classes of can urban themost be areas. catchment, of found basin where in Coniferous, slopes. lime- themeadows. mixed catchment Agricultural Three and (Fig. major areas deciduous 2): urban mostly forestsinhabitants), areas consist Hechingen cover are (19.386 of present inhabitants) arable and in land, Rangendingen the (5.400 orchards valley inhabitants). floor: and Jungingen (1.416 The catchment of thethe Starzel area most river severely closed120 a km at Rangendingen (Fig.slope 1), is 12 which %. includes 2 The study area and its flood regime 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1 − the ff ¨ urttemberg, with ¨ urkheim and Feldberg erent case study; a summary is ff 10746 10745 ¨ urkheim and Feldberg (Fig. 1), about 60 and 90 km o ective radar calibration correction factor, assuming a drop size distri- ff The Starzel river flows through the towns of Jungingen, Hechingen and Rangendin- bution model and theknown. subsequent At reflectivity-rain each rate-attenuation time relationships step, to the be radar observations from either T described in detail byprovided Bouilloud below. et al. Due (2010)weather to for radar, the specific a attention di extremely was highmeans paid of rain to the the rates, Mountain correction and of ReferenceBy Technique the the applying (MRT, signal hereinafter) the characteristics attenuation MRT, (Delrieu maximum of by et path8 the al., integrated and attenuation 2000). 14 (PIA, hereinafter) dB between over were a measured 50-km for path. path-averagedtimation rain By rates of considering between an the 10 e PIA and constraint 15 mm equation, h the MRT allowed es- time resolution of 5 min,imuth) and were spatial made resolution of availableapplication 250 by of m an DWD in integrated for rangefollowing set by radar errors: of 1.0 rainfall procedures, degree (i) estimation. in aimingof partial az- at reflectivity beam This detecting (VPR), occlusion; (iv) enabled and radar correcting (ii) the hardware the signal miscalibration. The attenuation; correction (iii) procedures vertical are profile 4.1 Rainfall data and spatial distribution Radar and rain gauge2008 observations storm. were The used rainfallC-band to observation radar derive resources located rainfall include at fields twostudy volume-scanning T for watershed, Doppler the respectivley. 2tension: June The only region 4 impacted hourly(Fig. rain by 1). gauges the could Data storm be from used has to the a check original limited the volume radar-based ex- scan estimates data (which include 18 elevations, with gen, which were floodedpeople died with as damage a consequence to of roads, the flood buildings in and Jungingen and infrastructures; in three 4 Hechingen. Rainfall estimation and analyses to the town of Jungingen. Hechingen equal to 85.1 mm,of to 108.2 be mm. contrasted with However,two more a days, than climatological as a 1961–1990 half consequence mean theMay–2 of monthly June the 2008. system rain of The was MCSs flood concentratedboth which was the in characterized not morphological the associated the characteristics period with of last 28 landsliding theand catchment the or short (with debris relatively character flow, short of due the hillslopes) pore to rain water event pressure which likely required prevented for thelandslides slope formation instability. were of Only documented the a high on few the shallow catchment slope area failures most and impacted by the storm close extreme rain intensities in partsRangendingen of was the struck Neckar by basin.characterised the The by Starzel flood. strong catchment closedat spatial The at storm the gradients was and start verydays. motion. of localised The the month in The of event space soil May were and 2008 moisture relatively was conditions not wet, particularly given wet, with the a precipitation rain depth in measured the in previous The rainstorm that triggered theof flash mesoscale flood precipitation of systems the (called Starzel Hilal)2008 River which covering was most occurred part of from Western of 28 Germany. a Mayformed The to sequence Hilal 2 along organised June system a of stationary thunderstorms air air in mass the southwest boundary fromand separating dry was warm, air focused in moist on the Mid-West Mediterranean from northeast. Germany the The (city Starzel first of system area. Dortmund),Luxembourg, occurred about Rhineland-Palatinate, A on 800 and km 28 second North North-West May system Rhine-Westphalia.June, occurred torrential On on storms the 29–30 led evening to May, of flash causing 2 flooding flooding and inundation in in Baden-W spring/summer season. 3 The flash flood of 2 June 2008 systems of short, convective events for the study region, mainly occurring during late 5 5 20 25 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | culties arising with the ffi cient (equal to 0.90), showing the quality of ffi ects, which were particularly severe for this ff 10748 10747 ects were quantified using a numerical model of radar beam propagation ff The analysis of the mean areal rainfall depth over the basin at Ragendingen provides The spatial distribution of the event-cumulated rainfall depth over the catchment is The distribution of exceedance areas, i.e. the areas over which various rain thresh- Measuring rainfall for storms that produce extreme localised floods is fraught by large Radar-rainfall estimates obtained in this way were evaluated by comparing them with Even though the radar estimates and raingauge measurement compare well, the relative to a distancedrainage metric path imposed from by a the generic flow point distance, within i.e. the the basin distance to along the the outlet of the basin drainage responding to 1000-yr recurrence interval100-yr, indicates but that below the a rainfallfield-estimated 1000-yr was discharge. well event. beyond This a corresponds4.2 also to the Space-time return rainfall period variabilityThe and of spatial storm the and motion temporal rainfall characteristicsmoments are of examined catchment here rainfall by (Zoccatelli usingmethod et the and al., spatial of 2011). its As assumptionsthe a is detailed method reported description is in of given Zoccatelli the et here. al. With (2010), only these an statistics, outline rainfall of spatial variability is examined ing to highest intensities.(DWD, 2006) A shows that statistical thecurrence analysis interval. observed based However, short-term the on recurrence rainfall interval theis corresponds of more KOSTRA the to extreme. entire methodology a event The (85,6 100-yr 100-yr mmto in rainfall re- 63.6 10 of mm, h) 9 which h corresponds duration to according 67.6 to mm DWD for (2006) 10 amounts h. Examination of the quantiles cor- radar estimates or onvalue the of accuracy 240 mm of inworld the 55 record min rain accumulation is measures of an 305 by extreme mm1947. rainfall in the depth, 42 The local min which rain observer. recorded can observationsbeen in be The Holt, by used compared Montana, in Mr. to on Heizelmann this the 22in could work June rainfall but not estimation are be for reported validated extreme convective as and events. an have indication not ofa the value potential of 85.6mm uncertainties for the entire storm event, and of 55.5 mm for the 90 min correspond- by a weather amateur residentgauge is in located Jungingen on (Mr. a Heizelmann).reasonably fence accurate Mr. 1.5 m measurement Heizelmann’s high rain of inamount rainfall. his exceeded garden According 240 mm and to is in hishighest appropriately 55 observations, min. radar located the for estimates, This a rain rain which amount points is to significantly uncertainty higher than either the on the adjustment of the Information concerning the amount and the timing of the strong rainfall was collected uncertainties. The 2 June 2008 flood provides a useful illustration of this uncertainty. event. reported in Fig. 5,central which and lower shows portions that of thetributaries. the largest catchment, rainfall with amounts very large are values localised over on the right-hand the olds were exceeded, is reportedamounts, in exceeding Fig. 100 mm, 6, impacted which just shows around that 30 the % most of important the rainfall catchment. 2010). uncertainties in reproducingneed fine to features of beadjustment the acknowledged. for highly This the variable is signal precipitation mainly attenuation pattern e related to the di lation from the instantaneousthe surface final rainfall rainfall rate accumulations estimation. werethe scaled To adjusted account with radar a for estimated bias the and factor, bias, the computed raingauge by values comparing at therain event gauge aggregation scale. observations (whichaggregation scales were (Fig. 4). considered The as comparisonError was (equal reference carried to out values) 0.48) in terms at andthese of Correlation the Mean estimates Coe Absolute hourly even with respect to results reported in other studies (Zanon et al., rain-rate threshold (hail cap) parameterscreening was also e imposed. Besides signalin attenuation, the atmosphere and thetivity terrain was model modelled of with the thevolume. region. normalized The apparent The final VPR step vertical of estimated structure the over of processing the reflec- chain whole consisted radar of generating rainfall accumu- were used depending on the computed attenuation. Due to the presence of hail, a 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (2) (1) less with is the 2 1 ) is the routing ∆ δ A close to ff 2 x,y δ ( and d 1 , ∆ t are greater than ) respectively, are 2 t ( ∆ represents the ratio erence between the 2 (e.g. a storm event), influences the shape ff δ 1 s 2 T δ ∆ ) and (which means that rainfall is t is to increase the flood peak ( 1 1 2 ∆ δ close to 1. A value of ∆ 1 δ ) in the basin and time x,y 1 are greater than zero and take the value of ∆ , respectively. 2 ] 2 10750 10749 ) ∆ , indicated with t ∆ t ( ] T dA 2 ) is defined as: ] and ective storm velocity as it is filtered by the drainage dA T,w travel time. The first and second order scaled spatial s [ ) are obtained as the ratio between the instantaneous 2 ff ] t 1 t V ave var[ ff ( d ∆ ave − w d ) dA ) cov ) t ( 1 x,y 1 ( x,y g δ dA ( ) d − d [ − ) R R A A propagation celerities can be neglected, the flow distance may ] x,y 1 1 ect of decreasing the value of ) ( − − x,y ff | | ff t ( d (which means that rainfall is concentrated towards the headwater) ( ) [] denotes the temporal covariance operator and var[ ] denotes the A A | | d t 1 [ is the mean value of the flow distance over the basin and w ) ) ∆ ] dA dA t ) ) x,y,t ( ( T less than one indicates that rainfall has a unimodal concentration along ave r 1 x,y,t ective averaging of spatial rainfall excess across locations with equal R A ( d 2 ff ) is the rainfall rate at position ( r 1 x,y,t x,y,t δ R − ( ( A | var[ r r T,δ 1 A [ R R A A | − | t 1 1 A − − | | | is time, cov x,y,t A A ( | | cov r T 1 = = g ) ) t t represents the ratio of the rainfall-weighted variance of the flow distances and the ( ( = Equation (2) shows that the storm velocity is defined as the di Based on the formulation of the spatial moment relationships in Eq. (1), it is possible Equation (1) can also be extended to describe the spatial rainfallZoccatelli organization et cor- al. (2011) showed that it is possible to relate the values of A spatial rainfall distribution either concentrated close to the position of mean flow In a similar way, a spatially uniform rainfall distribution results in values of Accordingly with these definitions, the first scaled moment 2 1 2 s δ δ V slope terms of two linearterm regressions is with estimated time (Zoccatelli based et on al., the 2011). space-time The regression first between slope weighted scaled first catchment scale storm velocity ( where variance. The rainfall weigths mean areal rainfall rate andstorm the mean event. value of the basin-averaged rainfall rate over the one. In general the(Zoccatelli e et al., 2011). to derive an expressionproperties for the of e the catchment. Zoccatelli et al. (2011) have shown that the resulting with respect to the samethan-one hydrograph value of obtained by aresults spatially in uniform a storm. delay A ofof greater- the the mean flood hydrograph hydrograph. time.one The The when values value the of of rainfall fieldrainfall is field which spatially is uniform. spatially Lesscases concentrated when than anywhere the one in rainfall values the field corresponds basin.at has to the In a a headwaters the bimodal and less spatial at frequent distribution, the with outlet concentration of the both catchment, the values of responding to the cumulated rainfallobtaining over the a statistics certain termed time period the shape of the hydrograph.concentrated A towards the less-than-one outlet) value results of in an anticipation of the mean hydrograph time the flow distances.rainfall A distributions. value greater than one indicates indicate cases of multimodal computed as follows: δ product of the mean areal rainfall rate and the variancedistance of or the flow spatially distances. than uniform one results indicates that in rainfallgreater values is than distributed of one towards indicates the that basin rainfall outlet, is distributed whereas towards a the value 1. headwaters. A value of imposes an e routing time, in spite ofand the variations inherent in runo spatial variability.be When used hydrodynamic a dispersion s amoments surrogate of for catchment runo rainfall at time where flow distance, basin area. between the mean rainfallrainfall weighted rate flow distance and and the the mean product value of of the mean the areal flow distance. The second scaled moment network. The use of the flow distance is motivated by the observation that runo 5 5 25 15 20 10 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | depends at 15 min s 1 V − http://www.hydrate.tesaf. according to the current rat- 1 − s 3 will be equal to zero. Note that the in the first part of the second storm. s V , lasted between 16:00 to 17:15 CET; ) shows that during the first storm the 1 t 1 − ( − 2 δ ) is constant and the value of t ( . 1 w 10752 10751 ) and − t s ( 3 1 δ ) is constant), the two slope terms will be equal in t ( 1 δ on more than 75 % of the catchment. 1 − ¨ urttenberg hydrological services (M. Moser, local Water Authority, per- ), funded by the EU Commission, Sixth Framework Programme (Borga et al., A post-flood survey campaign (denoted IPEC, Intensive Post-Event Campaign, here- Examination of the time series of Results from the analysis with the spatial moments of catchment rainfall are reported et al., 2009). The location of the cross sections is reported in Fig. 2. The discharge organised in the frameunipd.it of the European2011), Project with HYDRATE ( the collaborationtween of the local date authorities. ofrecognisable. Even the Also, though the flood 6 stream andmany bed months sectors that morphology passed of of (which be- the is thegives typical confidence channel field of in network) survey, a using was the bedrock thethree not river post-flood HWM cross-sections in geometry severely were were modified for still surveyed peakwere by assessed flood clearly during the using computation. the the flood. Thirty- slope-conveyance field method This (Gaume campaign and and Borga, 2008; peak Marchi discharges inafter) was organised in theexamine period the 10–14 spatially November 2008work distributed with included flood the surveying main response of objectivesectional high properties to geometry water to at marks multiple the (HWM), sitesestimate water storm. along indirectly surface the the slope river The flood and network. peaks cross- field These by data were means used of to hydraulic equations. The IPEC was recorded stage value (corresponding toing around curve) 80 was m considered toAn underestimate indirect high peak discharge, flood especiallyriver the estimate, flood sections based peak. on upstream analysis theby of the streamgauge flood Baden-W station traces was insonal carried communication, non-overflooded 2008). out The just indirect peakof after flood peak estimate the flow provided between an flood 120 assessment and 155 m The Starzel river catchment isbut equipped the with recorded a maximum streamgauge stage stationdirect during at current the Rangendingen, meter event exceeds measurements byfloodplain are far upstream available. the the stages section The for were streamgauge which inundated and during parts the flood, of so the that the maximum 5 The post event survey and indirect peak discharge estimation troid, with a peakyand spatial the distribution. rainfall centroid Around shiftsond 17:15–17:30 suddenly storm CET to is rain the less headwaters ratesthe localised, of decrease basin with the to catchment. a positions centroid close Thestorm to moving sec- motion, the regularly with outlet. from a This velocity theThis originates around far velocity a 0.5–0.6 m periphery is downbasin s around catchment of 30 scale %it of is that far estimated from for beingmay the optimal have stream for added flow peak velocity, to flow showing generation the that that (Ogden severity expected et of purely al., the based 1995). on storm, However, the this giving spatial rise distribution to of a rain stronger depth flood and intensities. peak than the second storm was muchtime more intervals) intense and (peak occurred rainrates between rate exceeded 18:00 around 20 and 50 mm mm h 19:30. h During the second stormprecipitation rain was mainly concentrated around the catchment geomorphological cen- tance coordinate. In theareal opposite rainfall case, if and there novalue is and motion only opposite ( temporal in variation sign,sign which of of means the the that mean the velocity ismotion. positive (negative) for the case of upstream (downstream) storm in Fig. 7. Thefirst, temporal with distribution 15-min of peak mean rain areal rate around rainfall 25 shows mm two h main storms. The and time. Conceptually, thisthe means rainfall that centroid storm coordinateinto motion and account may in in produce the the changes meantemporally estimation both areal uniform of in rainfall mean the values. areal catchmentonly rainfall, scale Both on storm the are evolution velocity. taken in For time the of case the of position of the rainfall centroid along the flow dis- moments and time, and the second term is based on the regression between weights 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 | for catch- ects. 1 ff − ), located in the area 2 ) for Sections 12 and 37 and 2 km ected by a range of uncertainties, ff 1 − (s 3 for catchments 25 and 26. 1 − 10754 10753 in the study region). 2 ). In particular, the sections 12, 26 and 37 (all cor- 2 ). However, field-estimated flood peak from catchment 2 in the reaches upstream Rangendingen, with a value in 1 − s 3 ) for Section 26. These are extreme values for the study area. 2 analysis km ff 1 − (s 3 for a basin area of 120 km 1 − s 3 cients, in the use of the post-flood geometry and its survey, in the assumptions ffi ected by the most intense rainfalls, are characterised by very high values of spe- ect on the flood wave of the Starzel river. The peak discharge indirect estimates The pattern of the relations between precipitation and unit peak discharge is very Small catchments induce a large scatter in the relationship presented in Fig. 8. For The chronology of the start of overflooding and of the peak stage was also investi- Uncertainty ranges reported in Table 1 account for the uncertainty in the selection Despite the mentioned sources of uncertainties, the values reported in Table 1 ap- Indirect peak discharge estimates are potentially a ff ff and 127.3 mm, respectively) and intensities,very they are similar very size close (around to each 2 km other and have similar for cumulated stormbe precipitation ascribed and to 1-h the maximum closefall, rainfall correlation which between intensity. becomes total This poor event can rainfall whencatchments and 30-min 10, 1-h rainfall 12, maximum is rain- 25 considered and1-h (Fig. 26 rain 9a, have b). depths. very For similar However, instance, maxments event-cumulated rain 10 30-min depths and rain and 12, depths max and are close less to than 130 mm 90 h mminstance, h catchments 25 and 26 are characterised by very similar rain depths (127.2 responding to catchmenta areas in thecific range discharge. of These 1.1 valuesaround are to 12 around m 2.1 5.8 km m 6.1 Relationships between field-derived peak flowsThe and relationship rain properties between theand the distribution properties of of the thethree rainfall field-observed basin-averaged forcing rainfall is unit characteristics reported peak aremulated in reported discharges Fig. rainfall, 8. and the analysed: For each maximumsurprisingly, the surveyed hourly event the basin, cu- rainfall highest and valuescatchments the of (area less maximum unit than 30-min peak 10 rainfall. km discharge are Not observed in the smallest 20:30 the river stageinformation reduces provided to by the the rainfall embankment sequence. level”. Overall this agrees with the 6 Rainfall-runo the peak at around 18:45, maintaining the level for around 20 min. Between 20:00 and from bankfull to peak, with around 1.2–1.5 of water in the streets. The river reached Sect. 3 which appears relativelyuncertainty. higher than The downstream sections inundatione even of accounting the for townin of Hechingen Ragendingen may corresponds have160 to m had a an return attenuating time around 100 yrgated based (which on the is witnesses’ interviewsflood. estimated and movies at In recorded Jungingen, by eye-witnesses theis of sequence the given of here in the local events solar was time, reconstructed i.e. as CET): follows “Around (timing 18:15, river level in Jungingen rose reported in future works. pear to be consistent withheadwaters each-other. to The Jungingen. peak Downstream discharge Jungingenare increases the steadily field-observed around from peak 120–170 the discharges m which may be induced bycoe errors in HWM assessmentconcerning the and energy in line the slope, choice and of by roughness possibly undetected backwaterof e the Manning roughnessof parameter a and in 95 % theindirect uncertainty energy peak slope discharge range. estimation, estimation. inuncertainty However, This a the involved complete leads form in quantitative to the treatment underestimate of survey the is the not actual a uncertainty central in objective of this paper and will be the Reichenbach, as wellof as the the original contributiondistance of cross each parts section other of along data, their theinformation, concerning tributaries. is same reported river 17 A in reach, sections Table selection thus 1. which providing relatively are independent at reasonable estimates help mapping the flood responses along the Starzel River, its main tributary 5 5 20 25 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (3) (4) ] is the is equal T [ h v (x,y) is higher than τ and response when 2 1 ff − erence between the ff . This is not a surprising 2 rate is computed from the are two invariant hillslope ff c v ), the three soil hydraulic pa- to the channel network follow- c is computed as v and x,y is equal to 3 m s h c and (x,y) v v . The runo τ h v x,y ) is computed by the model at any location t ( Q 10756 10755 culty to correctly estimate the watershed area ) is the length of the subsequent drainage path ffi x,y ( ) to the outlet of the basin specified by the region and c and location d t x,y dxdy ) ] ) , 1997). The routing time c x,y v modelling ) is found equal to 2.43 ha, ( x,y s c ( ff rate at time d A using the Green-Ampt infiltration model with moisture redistribution τ ff ), two kinematic parameters ( − + s ) A )is the distance from the generic point . The value of channel celerity agrees well with field based observations ] indicates the area draining to the specified outlet location, h , a relatively good relationship is found between specific unit peak flow erences includes the di 1 x,y r(x,y,t) 2 v 2 x,y,t ( ff − [ h x,y [L ( q d s h A is the runo d A = ZZ . ) 2 = ) t The model requires estimation of seven calibration parameters: the channelization The hydrological model is described in detail in Zanon et al. (2010) and only an When examination of the values reported in Fig. 8 is limited to catchments larger x,y ( ( Ogden and Saghafian tion support area ( to 0.05 m s Q rameters used by thelinear Green-Ampt reservoir. method The andtime model the step was and time implemented using constantand a over soil of 90 the properties. m the Starzel The grid most conceptual size catchmenttivity sensitive cell model and at parameters for flow 15-min (saturated the velocity hydraulic parameters) description conduc- in were of Rangendingen calibrated landscape and based morphology on oncharge the the peak raising information flood time concerning estimated and theby peak chronology using flow the of methodology time) the followed collected by flood Zanon in (dis- et Rangendingen al. and (2010). in Accordingly, the Jungingen channeliza- τ and channel flood celerities, respectively.reservoir The for model base includes also flow aby modeling the linear (Borga infiltrated conceptual et rate computed al., based 2007). on the The Green-Ampt reservoir method. support input area is ( provided where routing time from the location ( q(x,y,t) rainfall rate ( where ing the steepest descentthrough path, streams down to the watershed outlet. (i) analysis of the accuracyapplying in model simulating the calibration spatially at distributedexamination the of runo outlet the hydrologic sections consistency in ofassessment the Rangendingen of field-derived and peak the Jungingen; discharges; impact and (ii) ofat (iii) Rangendingen. the rainfall variability on the simulated flood hydrographs outline is provided here. Thealong discharge the river network as follows: 30 min, according to the analyses carried out in6.2 the study. Rainfall-runo Hydrologic response to the June 2008hydrologic storm is model. examined by Three using a main spatially distributed objectives are pursued with this modelling application: study and for the size of1 km the Starzel basin, but is rather rough for basin sizethan as 10 small km as and the rain event-accumulation andwhen 1 30 h min maximum. maximum rain However, theinfluence is on considered, linear catchment showing pattern response that is for this basins lost result, rain larger property since than bears the 10 limited km time of concentration of watersheds exceeding 10 km velocity is very similartwo (Table estimates 1), is which infor means the such that surveyed the di HWM main andfor di section these geometry. small catchments. Possibleelevation explanations model The of watershed 90 m area grid was size, estimated which based is on adequate a for digital the main objectives of this 26 is almost three times that reported for catchment 25. Even the field-estimated flow 5 5 25 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ratio. ciency ff ffi e e depth is just ff on the areas ff 1 − . The success in 2 culties in reproducing the ffi response to the extreme rain, ff ect the findings about the runo ratio, with initial losses accounting for ff ff culties in delineating the actual extension of ffi 10758 10757 ratio is very low. In spite of the wet antecedent soil cult to determine. When considering these results, ff ffi ratio equal to 0.20 and 0.30, respectively. Uncertainties ff in the urbanized area in the floodplains and to 20–40 mm h 1 − Model simulated peak values were also used to examine the hydrologic consistency The hydrological model was applied to simulate peak discharges over the 17 sub- Flood water balance data are reported in Table 2 for the catchments closed at Jungin- Results from the model application are reported for the catchment at Rangendingen charges whose uncertainty range does not include the simulated peak discharges are 26, all corresponding to verysubstantially small catchments underestimate (Table 1), the where verysite simulated 25, peak high the values model specific overestimates values significantlysources the of obtained uncertainties field-derived by peak may be discharge. the consideredflood Several to IPEC. for explain For the these di smallerrors basins. in rainfall These estimation, sources asthe of well catchments as uncertainty and di errors certainly in include indirect possible peak discharge estimation. of the field-derived peak discharges. With this analysis, the field-derived peak dis- properties) which areone more should di take intodischarges. account that Analysis this ofpermits representation the closer tends results examination to of obtained weight theallows for more simulations one the for the to the unit large isolate smaller peak the basins. behavior discharges The of (Fig. examination the 12b) tributaries corresponding to sites 37, 12 and shown together with the centralfit values. between simulated The results andequal reported observed to in peak 0.91. Fig. discharges, Overall, 12a this withgood show suggests a description that a Nash-Sutcli the of good hydrological the modelat spatial provides least a distribution for reasonably of catchments the exceedingthe runo a hydrological threshold simulation area may of bewas around ascribed estimated 10 to with km the relatively good strongovercome accuracy forcing other of for sources the the of study rainfall, spatial basin which variability and (such was likely as able those to related to soil/geological an important contribution to the overall losses. catchments where IPEC post-floodprovided surveys in are Fig. available. 12a, btively. Corresponding for results the In are peak both discharges figures, and the the unit uncertainty peak discharges, ranges respec- for field-derived peak discharges are rainfall duration is an important control on runo rope (Zoccatelli et al., 2010). When considering these events, it is apparent that the simulations, show that themoisture runo conditions and ofa the small high percentage rain of rates thesignificantly and rainfall lower volume, accumulations, ranging than runo from those 0.13and reported hydro-climatic to conditions, 0.16. by with These Marchi Alpine and valuesized et Continental are by al. flash mean flood (2010) values events character- for ofin similar runo rainfall estimates catchments and model simulationsHowever, may these a values are in thesize range catchments of and those for reported events for characterized specific by small short and rain medium durations in Continental Eu- of the river bank overtoppingis (Fig. included 11). in For the boththe range catchments, post-flood of the survey. indirect simulated peak flood discharge peak estimates reported ongen the and basis at of Rangendingen. These data, obtained by using the field-validated model (Fig. 10) andin at Rangendingen Jungingen shows (Fig. large 11).basis discrepancies of with As the respect expected,cross observed to the section streamgauge the flood and data. one of hydrographsimulated derived the simulated flood This on floodplain peak is the upstreamaccounts is related the reported anticipated. section. to by the Owingsatisfactory The witnesses. overflowing agreement to chronology of with this The of the the reason,witnesses hydrograph the chronology the about of simulated flood the the at peak start flood of Jungingen agrees as the shows reported with bank a in overtopping, the the account time of of flood peak and the end 10 mm h characterized by agriculture and forestthe land Green-Ampt use, model were respectively. set TheAs to such, initial fit they conditions were the in relatively observed wet. initial discharge in Rangendingen. reported in Table 1. The value of saturated hydraulic conductivity was set equal to 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). 1 − s 3 are the 2 ∆ . The mag- 2 and 1 ∆ , sites 3 and 6 are flagged 2 ) to control scenario (145 m 1 − , and catchment scale storm velocity s 2 3 ∆ ect of catchment scale storm velocity on , 1 ff ∆ , and (iv) the catchment scale storm velocity. 2 10760 10759 ∆ ect of and ff 1 ∆ ect of rainfall space-time variability on modelled hydrograph prop- ff ) to constant pattern (127 m 1 − s 3 , the four sites 37, 12, 25 and 26 are all inconsistent, as defined above. 2 properties ing in the Starzel rivernitude basin of at the basin flooding scales inparable ranging to terms from that of observed 1 rainfall in to rates the 30 and km same unit region peak for discharge past was extreme events com- and for other The Hilal organised system of thunderstorms produced record rainfall and flood- erent levels of rainfall variability and zero storm velocity were used. More specifically, – Simulations were carried out for the basin closed at Rangendingen (Fig. 13). Ex- The rationale for developing the three rainfall scenarios is as follows. In our method- ff its motion that controlled the flood response. 7 Discussion and conclusions In this study weriver have basin examined in the South-West Germany. 2 The June major 2008 findings extreme of flash this work floods are: on the Starzel 12 %. The underestimation risestion. to 26 These % results assuming are aunderestimation consistent and spatially hydrograph uniform with amplitude rainfall the agrees). distribu- velocity discussion Overall, played of this a shows Fig. non-negligible that 7 role theIt in (sign storm was shaping of the the the flood combination peak hydrograph of flow during the this spatial event. distribution of rainfall volume over the basin and simulation isolates the combined e on flood hydrograph. amination of therainfall figure (107 m shows thatThis the clearly simulated indicates peak thatwhich storm flow play motion a increases role is in an from controllingonly essential hydrograph uniform the shape. element shape Neglecting of storm of space-time motion, the rainfall, conserving spatial rainfall pattern, leads to underestimating the peak flow by The control simulation is thepattern result simulation of is the controlled combination by factorstion of (i) factors is to (i) controlled (iii), to by whereas (iv), factors thepattern the uniform-rainfall (i) simulation simula- constant and permits (ii). isolation Comparisonflood of of hydrograph, the control whereas e simulation the with constant comparison of control simulation with uniform-rainfall organization at catchment scale graph is controlled by:of (i) basin-average rainfall the rates catchment (hyetograph); drainage (iii) structure, the (ii) two the descriptors temporal of pattern overall rainfall completely removed (in thetal uniform rainfall accumulation case) pattern orscaling (constant the (b) pattern total kept case). rainfall constantrainfall pattern remained and The with equal latter to equal an the was appropriate to originalorganization achieved rain. is factor the by preserved so Note to- in that that the becausesame the constant the with pattern overall basin-averaged the spatial case, rainfall control the values scenario. of ology, based on spatial moments, we assume that the shape of the flood hydro- erties, we carried out adi series of hydrologic simulations for whichthe rainfall hydrologic scenarios response with resulting fromcompared the original with rainfall the field results (controlrainfall obtained simulation) was pattern from (a) case. spatiallyconstant uniform In rainfall and all volume (b) cases applied constant at the spatial each basin-averaged time) rainfall while remained the constant spatial (i.e. rainfall pattern was (a) as inconsistent. This shows oncethe more size that of the the uncertainties catchment. increasethis Sites with study. flagged decreasing as inconsistent will be revised in a6.3 follow-up of Influence of rainfall space-time variability on modelled hydrograph To investigate the e bution and the model-based floodshould response be description. closely Sites scrutinisedcharge flagged estimation, for as or inconsistent errors in the in hydrologicalthan modelling the 10 application. km surveying For catchments phase smaller Moreover, among and the catchments in with the size larger peak than 10 dis- km screened out, as these are considered inconsistent with the rainfall space-time distri- 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 2008. ers the opportu- ff ´ e M. Bodoque for their response. These esti- ff doi:10.1002/hyp.7111 , due to various sources of uncer- 2 ¨ ez-Herrero and Jos ubingen and Freiburg as well as the local ı ´ ect these results. However, these values ff ´ es D ratio assessment reported for short-duration , 2006. ff 10762 10761 ¨ oschl, G., and Creutin, J.-D.: Flash flood forecasting, warning ¨ asidium Stuttgart, T This work was financially supported by the EU FP6 STREP Project HY- response. The orography played a minor role in shaping the spatial doi:10.1029/2005WR004319 ff ratios (less than 20 %) characterized the runo ff the model. The nature ofor the both) error remains (either elusive. observational, or on theThe Hilal modeling organized side, system of thunderstormsmotion. was characterized We by its developed rapidon here storm a modeled methodology flood to response.band assess was the important, The role rapid eventhe of though downbasin runo storm not motion dominant, motion ofdistribution in the of controlling rainfall. principal the rain magnitude of However, the response at threesponse sites characterized and by very field-observed small extreme catchment re- scales proved to be largely underestimated by The combined approach ofand hydrological modeling indirect based peak on discharge rainfall estimates observations based on field survey o mainly concentrated at scales lesstainty than which 10 include km rainfall estimation, structuralhydrological and model parameter and uncertainty potential in errors the in indirect peakEven flow though estimation. the antecedentruno soil moisture conditionsmates are were at relatively the lower wet, rangeevents of small runo observed in Central Europeestimates (Marchi and model et simulations al., may 2010).are a in Uncertainties the in range rainfall ofand those for reported events for characterized specific by smallcatelli short and et medium al., rain size 2010). durations catchments in Continental EuropeThe (Zoc- distributed flood responseple distributed can hydrological be model, using reasonablymodel high parameters well resolution calibrated at rainfall reproduced a observations with river and pacted section a by which the includes sim- most storm. ofpeaks the The area at model im- is 11 capable sites of (out consistently reproducing of the 17) flood estimated during the intensive post-flood survey. central European storms producingevent extreme provides flooding a at prototype theseupper for tail scales. organized of the convective The precipitation systemsin Hilal frequency several that other distribution dominate contexts in in the the Central study Europe. region as well as nity to compare peakhelps flow estimates to from validate independent thecertainty approaches. results bounds. This of greatly This flood analysis has reconstruction shown and that to uncertainty estimate in related flood simulation un- is – – – – 42, W03S02. 29, 2003 flash flood in the eastern Italian Alps,the J. ungauged Hydromet., extremes, 8, Hydrol. 1049–1067. Processes, 2007. 22, 3883–3885, Saulnier, G.-M.: Distributed hydrologic and hydraulic modelling with radar rainfall input: Re- and risk management: the HYDRATE project, Environ. Sci. Policy, 14, 834–844, 2011. ¨ oschl, G.: Hydrologic synthesis: Across processes, places, and scales, Water Resour. Res., Borga, M., Gaume, E., Creutin, J. D., and Marchi, L.: Surveying flash flood response: gauging Bl Borga, M., Boscolo, P., Zanon, F., and Sangati, M.: Hydrometeorological analysis of the August Bonnifait, L., Delrieu, G., Lay, M. L., Boudevillain, B., Masson, A., Belleudy, P., Gaume, E., and Padova (Italy), MAS Dendro-Avenidas projectsity and of the Castilla-La Geological Mancha, Surveysupport particularly of and Spain to collaboration. and Andr Univer- References Borga, M., Anagnostou, E. N., Bl Acknowledgements. DRATE. Contract GOCE-037024. Thethe post-flood authorities survey of was Regierungspr carriedmunicipalities out of in Jungingen collaboration andistry with Hechingen. of Science The and first Innovation, author for acknowledges the the grant Spanish for Min- a 4 months research stay at the University of 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , ´ a, L., , 2011. ¨ ur die Bun- ˇ skoviov ¨ ohen f , 2010. ¨ oschl, G.: Seasonal , 2009. enbach am Main, Eigen- ff ¨ oschl, G.: Bayesian MCMC doi:10.1016/j.jhydrol.2010.03.033 ¨ ur die Bundesrepublik Deutschland doi:10.5194/hess-15-1991-2011 ´ a, S., and Bl ¨ ohen f ˆ atelet, J., Walpersdorf, A., and Wobrock, W.: 10764 10763 doi:10.1016/j.jhydrol.2010.01.008 , 2008. doi:10.1016/j.jhydrol.2008.12.028 , 2011. , 2010. , 2010. , 2005. , 2007. ´ evennes–Vivarais Mediterranean Hydrometeorological Observa- ´ alint, G., Barbuc, M., Borga, M., Claps, P., Cheval, S., Gaume, E., , 2009. ´ a, S., B enbach am Main, Eigenverlag des Deutschen Wetterdienstes, 1997. ff ´ al, L., Viglione, A., Szolgay, J., Kohnov ´ a, K., Merz, R., Pfaundler, M., Stancalie, G., Szolgay, J., and Bl ¨ oschl, G., Borga, M., Dumitrescu, A., Daliakopoulos, I., Garcia, J., Irimescu, V., Kohnova, floods in Europedoi:10.1016/j.jhydrol.2010.07.017 and implications for flood riskfait, management, L., J. Hydrol., andSlovenia: Poganik, 394, observation N.: 118–133, strategydoi:10.1002/hyp.7542 Comprehensive and post-event lessons survey learned, of Hydrol. a Processes, flash 23, flood 3761–3770, inungauged Western basins, J. Hydrol., 362, 274–290, 2010. rainstorms, Water Resour. Res., 31, 1543–1547, 1995. Irrigation and Drainage Engineering, 123, 386–393, 1997. Hlavov doi:10.1029/2005WR004129 flood discharges, Journal of Hydrology, Available onlinedoi:10.1016/j.jhydrol.2011.08.048 1 September 2011, ISSN 0022-1694, based on rainfall thresholds and soil moisture conditions: An assessment for gauged and doi:10.1111/j.1753-318X.2008.00023.x orographic thunderstorm in the central Appalachians, Water Resour. Res., 41, W12428, desrepublik Deutschland (1951–2000) – Fortschreibungsbericht, O verlag des Deutschen Wetterdienstes, 2006. Bl S., Koutroulis, A., Marchi, L.,calie, Matreata, G., S., Szolgay, Medina, J., V., Tsanis, Preciso, I., E.,Sempere-Torres,flash D., Velasco, D., Stan- floods, and J. Viglione, A.: Hydrol., 367, A collation 70–78, of data on European posal of a methodology and illustrations, Journal of flood risk management, 1, 175–189, Saulnier, G.-M., Ducrocq, V.,C., Gaume, Neppel, L., E., Livet, Payrastre, M.,The O., Lang, Catastrophic M., Andrieu, Flash-Flood Parentdu-Ch H., Event of Ayral,First 8–9 P.-A., Case September Bouvier, Study 2002 for intory, the the J. Hydrometeorol., Gard C 6, Region, 34–52, France: 2005. A – KOSTRA, O approach to regional floodgauged sites, frequency J. analyses Hydrol., 394, involving 101–117, extraordinary flood events at un- X- and C-band840–850, weather 2000. radar systems operating in heavy rainfall, J. Appl. Meteorol., 39, use of distributed hydrological modelsciated for hydrological the processes, Gard J. 2002 flash Hydrol., flood 394, event: 162–181, Analysis of asso- catchment, Hydrol. Earth Syst. Sci., 15, 1991–2005, J. A.: Surveyingdoi:10.1029/2007EO060001 Flash Flood Response in Mountain Streams, EosStates Trans. Reported AGU, 88, by p. theflood 69, US science, Geological US Survey2008. Geological and Survey, implications Scientific for Investigations future Report advancement 2008–5164, of 52 pp., tion in thedoi:10.1016/j.jhydrol.2010.02.035 context of post-event analysis of flash-flood events, J. Hydrol., 394,2010. 17–27, M., and Uijlenhoet, R.: Anatomy of extraordinary rainfall and flash flood in a Dutch lowland construction of the 8-9 SeptemberAdv. 2002 Water Res., catastrophic 32, flood 1077–1089, event in 2009. the Gard region, France, Parajka, J., Kohnov Marchi, L., Borga, M., Preciso, E., and Gaume, E.: Characterisation of selectedMarchi, extreme flash L., Borga, M., Preciso, E., Sangati, M., Gaume, E., Bain, V., Delrieu, G., Bonni- Ogden, F. L., Richardson, J. R., and Julien, P. Y.:Ogden, Similarity F. in L. catchment response: and 2. Saghafian, Moving B.: Green and Ampt infiltration with redistribution, Journal of Norbiato, D., Borga, M., Degli Esposti, S., Gaume, E., and Anquetin, S.: Flash flood warning Lumbroso, D. and Gaume, E.: Reducing the uncertainty in indirect estimates of extreme flash Hicks, N. S., Smith, J. A. , Miller, A. J., and Nelson, P. A.: Catastrophic flooding from an Gaume, E. and Borga, M.: Post flood field investigations after major flash floods: pro- DWD: Deutscher Wetterdienst: KOSTRA-DWD-2000, Starkniederschlagsh Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A., Bla DWD: Deutscher Wetterdienst: Starkniederschlagsh Delrieu, G., Nicol, J., Yates, E., Kirstetter, P.-E., Creutin, J.-D., Anquetin, S., Obled, Ch., Gaume, E., Ga Delrieu, G., Andrieu, H., and Creutin, J. D.: Quantification of path-integrated attenuation for Braud, I., Roux, H., Anquetin, S., Maubourguet, M. M., Manus, C., Viallet, P.and Dartus, D.: The Costa J. E. and Jarrett, R. D.: An evaluation of selected extraordinary floods in the United Brauer, C. C., Teuling, A. J., Overeem, A., van der Velde, Y., Hazenberg, P., Warmerdam, P. M. Carpenter, T. M., Taylor, S. V., Georgakakos, K. P., Wang, J., Shamir, E., and Sperfslage, Bouilloud, L., Delrieu, G., Boudevillain, B., and Kirstetter, P. E.: Radar rainfall estima- 5 5 30 20 25 15 10 30 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) 1 − s 3 , 2011. ) (uncertainty range) (m 1 , 2010. − s ¨ 3 oschl, G.: Spatial moments of doi:10.5194/hessd-8-5811-2011 10766 10765 , 2011. , 2010. , 2010. doi:10.5194/nhess-10-805-2010 ) (central value) (central value) (m 1 − ) (m s 2 (km doi:10.1029/2010WR010190 Peak discharge estimates from the field survey. Section reference numbers are re- flooding from orographic thunderstorms in theW04514, central Appalachians, Water Resour. Res., 47, characteristics of flood regimes acrossdoi:10.1016/j.jhydrol.2010.05.015 the Alpine-Carpathian range, J. Hydrol., 394, 78–89, the design of aEarth road Syst. Sci., inundation 10, warning 805–817, system for flash flood prone areas, Nat. Hazards doi:10.1016/j.jhydrol.2010.08.020 catchment rainfall: rainfall spatialdrol. organisation, Earth basin Syst. Sci. morphology, Discuss., and 8, flood 5811–5847, response, Hy- rieu, G.:ent: Hydrological analysis the of September a 18, flash 2007 flood event across in a Western climatic Slovenia, and J. geologic Hydrol., gradi- 394, 182–197, Ref. Watershed area1 Mean3 flow velocity467 Peak10 discharge12 9.514 53.9 119.81516 47.422 85.7 Peak discharge 24 1.025 1.1 26.026 29.032 2.8 29.433 2.3 2.5 33.237 37.6 3.7 2.6 2.2 1.5 2.1 1.4 1.1 2.4 17.8 2.5 1.9 2.9 150. 9. 150. 3.3 2.3 120. 165. 3.0 2.5 3.5 2.5 6.5 3.4 23. 33. 2.6 130.–170. 45. 125.–175. 65. 6.–12. 105.–135. 90. 150.–180. 8. 25. 3.0 3.–4. 20. 20.–26. 6.–7. 28.–38. 11. 35.–55. 53.–77. 70.–110. 6.–10. 20.–30. 1.5–4. 15.–25. 8.–14. Table 1. ported in Fig. 1. Smith, J. A., Baeck, M. L., Ntelekos, A. A., Villarini, G., and Steiner, M..: Extreme rainfall and Zoccatelli, D., Borga, M., Viglione, A., Chirico, G. B., and Bl Versini, P.-A., Gaume, E., and Andrieu, H.: Application of a distributed hydrological model to Zanon, F., Borga, M., Zoccatelli, D., Marchi, L., Gaume, E., Bonnifait, L., and Del- 5 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ff ) ratio 2 /km 1 − s 3 ¨ urkheim and Feldberg ) (m 1 − s 3 (m the basin with orography and the location (b) 10768 10767 (mm) Peak discharge Unit peak discharge Runo ff Location of the Starzel basin with the two weather radars, T Water balance elements for the basin at Rangendingen and at Jungingen (analysis BasinRangendingenJungingen 120.0 Area Rain 85.6 (mm) 33.2 Runo 87.8 10.9 14.4 146.0 60.0 1.21 1.81 0.13 0.16 (crosses) and corresponding 150 km range circles; Fig. 1. (a) of the four raingauge stations and of the streamgauge. Table 2. based on the hydrological model application). Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 10770 10769 Unit peak discharges vs. catchment size for the three highest observed peak floods Land uses map of the Starzel catchment. Numbers refer to the surveyed cross sections Fig. 3. observed in 15 catchments incorresponding the to Neckar the river Starzel system flash near flood the peak Starzel. estimated in The Rangendingen uncertainty is range also reported. during the intensive post eventin campaign; bold. the 17 sections considered for the study are marked Fig. 2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 10772 10771 Scatter plot of adjusted radar rainfall estimates versus raingauges measurements for Event rainfall spatial distribution over the catchment. Fig. 5. Fig. 4. hourly accumulations. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (e) (b) , 2 δ (d) , 1 δ (c) ), 1 − precipitation intensity, (a) 20 mm h > 10774 10773 Precipitation analyses by using 15-min time series of Distribution of exceedance areas, i.e. the areas over which the event-cumulated rainfall Fig. 7. percent coverage of the catchment (for precipitation intensity catchment scale storm velocity. Fig. 6. exceeded various thresholds. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | max hourly rainfall intensity; (b) 10776 10775 event cumulated rainfall; (a) Relationship between estimated unit peak discharges and rainfall characteris- Relationship between the event-cumulated rainfall depth and the 1-h (up) and 30 min maximum rainfall intensity. The numbers refer to the basins listed in Table 1. Fig. 9. (a,30-min b) peak rainfall intensity (down) for the17 IPEC catchments. Fig. 8. (a, b,tics c) for the 17 IPEC catchments: (c) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 10778 10777 Hydrograph analysis at the Rangendingen stream gauge station: model-based hydro- Flood hydrograph simulation in Jungingen. The diamonds indicate the reported timing Fig. 11. of flooding features from eye-witnesses. Fig. 10. graph is compared withpeak estimated flow hydrograph estimates from from recorded post-event survey. stages (reconstructed) and with Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | e ff estimated versus (a) 10780 10779 model applications over the 17 selected catchments, by ff estimated versus simulated unit peak discharges. Nash Sutcli (b) Result from runo Hydrograph analysis at the Rangendingen stream gauge station: resulting model- ciency statistics are 0.92 and 0.45, respectively. ffi Fig. 13. based hydrographs by usingand constant control spatial pattern rainfall (Const. (Distributed), Pattern). spatially uniform rainfall (Uniform) simulated peak discharges; e considering uncertainty ranges in indirect peak discharge estimation: Fig. 12. (a, b)