Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect ff ) for 2 7552 7551 cult to estimate as climate projections were not in phase ffi ect, there is a growing potential for intense precipitation that may cause floods ff 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. of climate change. Generally,in a warmer e atmosphere can hold more water vapor and, when adapting to climatethe change. paper, Uncertainties both related for toassessments observed the in data study hydrology. and are for discussed the in complex model chain of climate1 impact Introduction Numerous severe floods havegrowing been concern reported that globally flooding in will recent become years more and there frequent is and a extreme as an e by on average 1 % per(–2 decade, % mainly per due decade) to lower causedcontrary, peaks autumn by from flows higher snow may melt temperatures increase inThis by and the indicates 3 shorter spring % a per snow shift decade in season.rain flood due On generated generating to floods. the processes more This in intensive should the rainfall. be future, considered with in more reference influence data of for design variables century. The resultsoscillate show between that decades, theA but changes small there of tendency is forand daily no high 10-year annual significant flows flood high trend to frequencywas decrease flows for was found by in the to noted, 0.3–0.4 be but past % Sweden related the not per 100 to years. strongest statistically decade snow climate significant. in melt driverdecades, Temperature magnitude in for but Sweden. these river Also were high-flows, di with in as observations. these the However, in are future the long mainly there term, will the daily be annual oscillations high-flows may between decrease There is an on-goingthe discussion past whether and floods whether are theywe will more merged increase frequent observed in nowadays a time-seriesthe than future from in past climate. 69 To century explore sites this with across for Sweden the high-resolution country dynamic (450 scenario 000 km modeling of the up-coming Abstract Hydrol. Earth Syst. Sci. Discuss.,www.hydrol-earth-syst-sci-discuss.net/11/7551/2014/ 11, 7551–7584, 2014 doi:10.5194/hessd-11-7551-2014 © Author(s) 2014. CC Attribution 3.0 License. Climate impact on floods –high-flows changes in of Sweden for thefuture past (1911–2100) and B. Arheimer and G. Lindström Swedish Meteorological and Hydrological Institute, 601 76 Norrköping,Received: Sweden 3 June 2014 – Accepted: 20Correspondence June to: 2014 B. – Arheimer Published: ([email protected]) 4 July 2014 Published by Copernicus Publications on behalf of the European Geosciences Union. 5 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 7554 7553 culties and uncertainties involved, much scientific ffi What changes in daily annualthe high-flows last have century, we experienced andyears? in which Sweden future during changes can we expect for the next hundred future? Which climate drivers can be attributed to suchHow changes? will flood regime and dominating flood-generation processes change in the orts during the last decade have been put on compensating for these two major In this study, we therefore used 69 unregulated rivers with gauged time-series Hall et al. (2013) argue that future work should aim to draw upon, extend, and Most of the published works relate changes in climate to mean annual flow, Changes of the river flood regime are traditionally analyzed either through statistical 1. 2. 3. ff climate model projections of 100 yearswas (2000–2100). used An to overlapping check the period agreement ofThe between 50 observed following years and scientific modelled questions trends are in high being flows. addressed in this paper: series of more than(Yue et 50–60 al., years 2012, are Chen recommended and Grasby, to 2009). account forfor natural 100 years variability (1911–2010)magnitude. The to modeling of examinemodelling the future recorded chain: was changes performed “emissionbias according in to scenario–global the correction–hydrological flood typical climatehydrological-model model–flood impact frequency system S-HYPE model–regional frequency and for Sweden downscaling– with analysis”, observed climatology, and using for two the national combine the strengthThe of present both study is thepast in with flow line dynamic with record scenario this modeling analysisshould of idea the be and to future. based merge Moreover, the climate analysis on changenatural scenario of good detection conditions long quality (e.g. approach. Lindström time-series data and of from Bergström, the 2004; observation Hannah networks et al., of 2010) rivers and time- with near- and their changes (e.g. Parajka et al., 2009; Petrow and Merz, 2009). e problems to find methods(see for full more review in robust Hall trend et al., analysis 2013). and scenario-modelwhile results impact studiesexamined. on One high waythe flows to analysis are of understandprecipitation, rare seasonality. the convective Some precipitation, and change and of specificflood snowmelt of the occurrence events within drivers main the are flood year are highly may driving generating therefore seasonal. give usually processes clues The processes on such not the flood is as producing drivers synoptic will influence all statisticalchosen trend for analysis and the makeobserved study; them climatology very (2) (Murphy et sensitive global al., tomodel 2007) climate the chain and period models in uncertainties hydrological arise (GCMs)al., impact in 2014). do each assessments As step not (Bosshard a of response et correspond the to al., to the 2013; di the Donnelly et approaches using observed dataal., (e.g. 2010; Lindström Schmocker-Fackel and andmodeling Alexandersson, Naef, using 2004; 2010), the Stahl scenario or et al., approach 2012; through Bergström (e.g. process-based et Dankerschallenges, numerical al., and as discussed 2012). Feyen, by 2008; Bothwith Hall Arheimer these climate et methods et impact al. assessments include (2013). islong-term potentials To that: sum-up, cycles, and (1) the which observed many fundamental may time-seriesof be problems may hydrological induced include processes by natural (Markonis climatic and oscillations Koutsoyiannis, or 2013; persistent Montanari, memory 2012). This (e.g. observed increase in precipitation intensity)(e.g. already Kundzewicz have et an al., impact 2007, on 2008; riverin Bates floods et floods al., 2008). is However, detectionwhen associated of exploring changes trends with in methodological both past problems and future and high large flows. uncertainties arise (Huntington, 2006). Some scientists have argued that the observed changes in climate 5 5 10 15 20 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . 2 erent ff ects of the ff erent general circulation models ff and produces daily values of hydrological 2 7556 7555 et al., 2000). GCM results from both models were ć enovi ć For climate model results, two grids based on di The S-HYPE model was forced with daily precipitation and temperature, using both for thelength, calibration using period the and forcing an grid independent based validation on period observations. of Moreover, the simulated same trends 4 km and bias corrected,reference using data the from Distribution-Based the Scaling gridgridded (Yang based et values on al., were observations 2010) transformed for with the to the S-HYPE each period model. subbasin 1981–2010. for Finally, the period 1961–21002.3 to force Quality check and analysis The model skillwithout to predict regulation daily for annual the high S-HYPE flows version was tested 2010. in Model 157 deviation gauging was sites calculated ones with the largest futureprojection temperature is increase in in Scandinaviaemission the scenario whereas small-to-medium A1B the (Naki Echam range.first Both down-scaled dynamically projections to 50 simulate kmThereafter, with e the daily RCA3 surface model (Samuelsson temperatures et al., and 2011). precipitation were further down-scaled to and direction, and slopes (Johansson,were 2002). transformed For to this study eachmodel. on subbasin floods, for gridded values the period 1961–2010 to(GCMs) force were the S-HYPE used;ECHAM5r3 (Roeckner et HadCM3Q0 al., 2006). Thesignals (Johns projections concerning were et the chosen to future representprojections al., temperature di change. studies 2003; Within by the Collins ensemble Kjellström of et 16 et climate al. al., (2011), 2006) the Hadley and projection is among the 2010. national grids of 4 kmThe based grid based on on observations observationssome and is 800 climate produced meteorological daily model by stations results, optimal considering respectively. interpolation variables of such data as from altitude, wind speed changes in flood magnitude and frequency was made using the S-HYPE version from improved and released in newin versions every 400 second year. sites Observations are for available model evaluation of daily water discharge. The present study on Water discharge and hydrometeorologicalextracted time-series from of a national the multi-basin pastmodel model system and system covers for more the Sweden, than future 450 calledvariables 000 was “S-HYPE”. km in The 37 000 catchmentsbased from and 1961 semi-distributed and HYdrological onwards. Predictions It for(Lindström the et is al., Environment based 2010). (HYPE) on The code S-HYPE theLindström, application processed- (Strömqvist 2013) et covers al., 2012; the ArheimerThe Swedish and landmass first including national transboundary model-system river was basins. launched in 2008, but S-HYPE is continuously but also represent the Swedishrecords catchments and of no, the or very marinethe little, basins. national up-stream 69 regulation water gauges in archive with to the long catchment, represent were the chosen four from regions2.2 (Fig. 1). Model approach of the past and the future of the country. Swedenthe is south bordered by and mountains east,which to meaning start the that west in the andNorth country the a Atlantic is long west drained Sea. coastline and byelectricity to Most run a consumption of eastwards originates large the from number toin hydropower. rivers of flood the To change, are search rivers results Baltic from for regulated analyses general Seaaggregated of as to tendencies long-term and four records some regions and southwest in scenario 50 Sweden % modelling(2004). to (Fig. was The 1) of the defined river the by basins Lindström Swedish and in Alexandersson these regions have similarities in climate and morphology 2.1 Landscape characterization and observed high-flowsSweden of is the situated past in NorthernAbout 65 Europe % and is covered has by a forest, surface but there area are of significant about agricultural 450 areas 000 km in the south 2 Data and Methods 5 5 25 20 10 15 20 25 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.05) was estimated = P erent time-slots. Simple linear ff 7558 7557 erent trend test used for Swedish flood data ff C) were used as the variability is less and it is not area ◦ 30 % deviation from the mean of the reference period (Fig. 2). ± erence in results from di ff erence in trends between regions was found and therefore only results for entire Model results are presented after Gauss filtering, with a standard deviation To attribute climate drivers to changes, time-series of temperature and precipitation To distinguish major long-term changes in the flood generating mechanisms, To explore the spatial variability of climate change, the high resolution results from To quantify temporal changes of annual high flows in the past and future, recorded ff as 60 %. Spring floods normally correspond to the annual high flow (cf. the two middle 3.1 Observed annual maximum of dailyDuring high the flows during last the hundreds past flow years, is the normally observed within anomaliesDuring in the 1980’s annual to maximum 2010except of the from daily variability the in extended flood event in frequencya 1995 has 10-year when flood. been most This less of was pronounced, thewhere linked 69 to previous sites maximum the experienced discharge outstanding at records spring least were flood, exceeded especially at in some the sites north, by as much The four regions of Swedenwhole, were respectively, analyzed using separately the and 69 lumped catchmentsdi for or the the country S-HYPE as model. a Sweden However, no are clear presented below. periods in the long time-series.climate The trend trend more of clearly thesingle without Gauss years curves the from will noise a reflectthat from climate the specific single possible year model years. as should the Ina not climate addition, forecast models be for results gives considered specific a of years. to projection for be long-term representative mode, and for not 3 Results the country, are mostlyrain-driven driven in by snow Sweden. melt, Analyzingshift while each in autumn/winter group hydrological peaks regime separately are and will dominant primarily thus processes give causing the a highcorresponding hint to flows. about a moving a average of 10 years, to distinguish flood rich and flood poor peaks, which appears in March–June along the climate gradient from south to north of separating peaks appearing in March–June and July–February, respectively. Spring were extracted from the S-HYPE modelingand for each 1961–2100). subbasin Also and dataset theseannual (1961–2010, anomalies data compared were to averaged thesite. for long-term Relative average regions, changes for based were thetemperature considered on reference absolute period for site values in average specific ( each and extremedependent. precipitation, but for seasonal changes in magnitude and frequency of high flows were analyzed by with the averageanomalies in value each site. Then ofregion, these respectively, anomalies the so were that averaged reference for ayear. the relative Frequency country period change analysis and was was each received (1961–1990) based for10-years on each flood to how domain for many and each of get each year all in sites the each that region. were relative exceeding the (Lindström and Bergström,based 2004). on the Statistical formula significance by Yevjevich (1972; ( p. 239). the S-HYPE modelling was plottedof as 2035–2065 maps and end for of twoeach century: time-windows climate mean (mid-century: of projection. mean 2071–2100), showing estimated change for values for the 69 gauges and modeled data from the 37 000 subbasins were divided were overlapping for theto period check 1961–2010 agreement69 and between river this simulations. gauges Observed 50-year wereregression period and extracted was modelled was and thus results used comparedno used from as for large the di trend di test, as previous studies have shown that there is were compared between the various simulations. Observed and modeled time-series 5 5 20 15 10 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect was missing in the model ff erent forcing data, no significant erences and sometimes conflicting ff ff 7560 7559 erences in spatial patterns when forcing S-HYPE with ff erent parts of Sweden. The model results based on the Echam erent parts in Sweden. The increase is faster in the Hadley model ff ff ected the central-southern parts of Sweden. ff According to both projections, the mean temperature will increase with between 3 The predicted change in average river flow varies between 30 % increase and The slope in the modelled time-series using observed climate was generally larger When comparing S-HYPE simulations using di For the past hundreds years of this study, no obvious trends in magnitude of high the country. The decrease isthe most other pronounced hand, at shows the increased mid-century river (Fig. flow 4). in Hadley, all on of northern Sweden and a decrease and 5 degrees for di compared to Echam,extended although areas Echam by eventually the100–400 shows end mm of high per this year temperature depending century.a on for The faster location average and more in more precipitation Sweden. significant The will Hadley increase increase projection in by shows precipitation. 30 % decrease for di projection shows higher flow in the northern mountains and a decrease for the rest of Sweden. The resultsclimate for projections (Hadley the and Echam) since referencescaled precipitation against and period temperature the have (1981–2010) same been 4change, km are however, grid, there similar are which in is for many basedresults cases the on between large the observations. di two climate For future models, in climate particular for local conditions. time slices, the S-HYPEslope model as forced observed with gauges.are Again, observed significant. it climate should show be the noted same that sign none4.1 of of these trend Future slopes climate projections of Sweden Figure 4 showsthe the large two di future projections of annual precipitation and average temperature across than in observed trends.sensitivity This indicates to that changes the inincluded S-HYPE in model forcing the may data overestimate S-HYPE or the may model also that (e.g. be changes there an in areAlexandersson artifact land-use, (2004) compensating from vegetation, and bias abstractions). processes Hellström in It and not precipitation Lindström (2008). data In as 4 discussed out by of Lindström the and 5 examined opposite sign of slope compared to Hadley as well as to observed climate. trends wereperiod found of in 50 yearsoverlapping observed (Table period 1). and or reference Some period, whichno modelled small was deviation only significant high 20 could years trends shorter.projection, be flows Accordingly, for found which for shorter between shows thereference the periods significant full period. were full trends Climate foundclimate overlapping during projections either, fluctuations, the which except are was independentwas for not the also period found the case necessarily for with the and Hadley longer in the time-period the projections of phase 50 used years, with when in the this observed Echam projection study. show This validation period resulted incould a be related median to underestimation somethe missing of lakes model –3.5 in overestimated %. this high model The flows version,set-up. as major and the for outliers dampening those e catchments falling. 1970 appears as1920s the were turning actually higher point than and in the recent decades. summer and autumn floods4 in the Model performance and comparison ofThe trends in median simulations absolute errormodel was (version on 2010) 15 in(Fig. % 157 3). for sites daily For results annual calibration both high there for flows calibration was of and the a validation S-HYPE median periods underestimation of –0.7 %, while the year 2000 which a flows can be seenfrequency in the can observed be time-series noted.have for increased Sweden. In substantially A a over slight shorter the decrease last in perspective, 30 flood however, years, autumn but floods before that seem the to tendency was panels of Fig. 2), with a few exceptions. One such exception is the autumn flood of the 5 5 25 20 10 15 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erence in river flow is mainly ff erences when assessing future climate ff 7562 7561 ect of precipitation and evapotranspiration in the hydrological model. ff erence between the results of the climate projections means that the ff Autumn floods show a trend in the opposite direction, with some 20 % higher The annual maximum of daily flow does not show any trend for the past 50 years The results confirm that there are large di The future changes in mean high flow as well as the magnitude of the 10-year flood for climate projections, the Hadleyfuture. projection The show the results largest indicate increase an in on-going trend shift for the in flow regime, which can be referred to of the century vs. the 1970s. magnitudes by the end ofare the in century. However, it general shouldSweden only be where noted about autumn that floods half autumnregime are floods as usually is higher. high not Thiscountry, detected as is also which when the why are only spring this dominatedincrease looking change floods, in in at by except flow autumn the maximum from peaks annual spring southern shows values peak a for due very the to significant whole snow trend melt. for the The last observed 50 years, while The most significant result of changesannual in floods maximum for Sweden of wasshows found daily a when significant comparing flows decrease in during magnitudeautumn of the floods. spring For floods spring spring and a and floods,but significant the the autumn increase trend trend of when separately. for using climate Figure observed projections 6 forcing reduces data the is spring weak, flood by some 20 % by the end but a decreasing trend insnow-melt the as future. This the can behigher snow explained temperature. period by The lower will spring results10-years be peaks did flood. from shorter not For show and Sweden, anyfor temperature evapotranspiration river clear thus higher high-flow trend seems due than in to themainly to the be related precipitation. frequency to This a snow of is stronger melt the probably climate in reflecting this driver that country. high4.3 flows are Changes in the flood regime and the GaussHowever, filter the strong result trend inthe in temperature a precipitation signal rather is duringcentury not short the as 50 reflected a overlapping years whole in in period (Lindström the Fig. and for 5 river Alexandersson, 2004). is trend flow. not Note analysis. representative that for the 20th precipitation. Similar trends are found in the observed data, although only 50 years the temperature rise with 5the degrees precipitation by shows the a end strong of increase, the both in century annual in means both and projections. in Also maximum daily range of an ensemble ofat 16 climate the projections, higher used end atHYPE falls the of within Rossby the the Center, 25–27 especially % extremes. range(Bergström of The et the al., corresponding larger 2012). ensemble river when using flows the HBV calculated model with4.2 S- High flow in the futureFigure and 5 climate drivers shows thatand even the though observations, the similar forcing trends datasets for the are future out can of be phase detected. to Most substantial each is other compared to the reference period. change, dependent on which climatethe model that same is being emission used, scenario.the although they The full are range two using of projections uncertainty; shown however, here a are close far analysis from shows that covering they do cover the show a spatial variationmost between of 50 % the increasepart country and of the the 50 % change mountaindetected decrease is range in (Fig. and 15 %. the in 4), mountains Highest southwesternSweden. but of Sweden. levels for There Jämtland, Lower are is 10-year which estimatedon floods a is were for high large one Northern flows of spread theresults should in in most be larger results snow changes treated between for rich the carefully the areas whole on country two in while the projections Echam local indicates so smaller scale. changes results The Hadley projection a combined e The precipitation isis received calculated from in theThe the climate large HYPE models di model,uncertainty while based in the estimating on future evapotranspiration conditions temperature is from large. the climate models. mainly in the south-western part of the country. The di 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 | 0.05) and of some larger = ect of individual years and P ff 7564 7563 erent picture. For instance, when starting the ff 0.05 levels and confirm the visual inspection of Gauss curves erent magnitude and significance. The annual high flows show = ff P The merging of Gauss curves using both 100 years of observations and 100 years of Figure 7 show that there have been large climate induced long-term oscillations When using 100 years of climate-model data with future projections, significant (cf. Table 2 anddetection. Fig. Lindström and 7). Bergström For (2004) Swedish found that climate, trend 50 detection years is is very sensitive thus not enough for trend climate projections, clearly visualize theoscillations relative (Fig. changes 7). and This influence combined from waysimultaneously, to long-term analyze increases both observations the and understanding modelin results of long natural time-series. versushelps The the accelerated Gauss eye changes in filteringof distinguishing removes the observed trends the climate from e analysis oscillations. gives during Using the a shorter 1960’s (Figs. very timevery 5 scales di strong and 6) already, the but trends this in trend increased autumn disappears floods when seem using 100 years of observations cannot be used asin a Sweden reference in arereference the based period future. to on Most adapt with design thiscentury, climate it variables seems change. period, like for Unfortunately, this when period infrastructure but looking wasespecially not at must not very the for representative past thus for autumn natural floods. variability be either, recalculated using a new a small negative trendprevious of findings 0.4 % by per Wilsonpeak-flow decade et in events 10-year al. in flood (2010) longwhile frequency. for increase time-series This Scandinavia, confirms was from who foundfor Sweden, for future found Finland, changes, western a however, and were Norway decrease statistically andmagnitude. parts significant of Denmark. ( Daily of The annual Denmark, changes high-flowswhile we autumn may flows found decrease may increase byThe by 3 1 high % % per deviation per decade, versus but decade the the in trends reference are the far period from future, linear. shows that this period (1961–1990) 5.1 Changes of high flows inThe Sweden study shows that no tremendousor changes are in expected high flows from have climate been recorded change so in far, Sweden. Although not significant, there was 5 Discussion statistically significant for each trend (cf. Table 2). were all significant at on changes in flow regime (Fig. 7). in maximum daily highto flows continue during for thefrequency the are last next-coming larger 100 years hundred inartifact and past years. of that observations The grid these than sizeFuture observed are in in long-term future oscillations expected climate projections. trends of projections, This were flood which may consistent be may between an underestimate climate local projections, extremes. but only one same direction but of di a declining trend, which isS-HYPE even using more Echam pronounced forcing whenthan shows looking 2 the % at largest reduction only per negative springpositive decade trend peaks. trends of with spring in in peaks. averagewhich the Autumn more resulted future, peaks, on in especially the 3 when % contrary, show higher using autumn the peaks Hadley per climate-model decade. data, These trends for the future For the past 100 years,detected no for significant maximum daily trends highfloods and flows vs. very (Table the small 2). reference The meanreference period mean deviation in period deviations could the for be is the 69 notFig. autumn river 2. gauges representative was In for 9 contrast %, autumnshow to a which floods. negative means the This trend that results for was the the for last also the 100 detected years, last although in trends 50 not years were significant. (Fig. detected 6), for the up-coming autumn changes. high Both flows projections showed trends in the melt in the springautumn. and more frequent floods generated4.4 from intensive Combined rainfall results in to the detect long-term changes in high flows flow generating processes; there will be less impact from floods generated by snow 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 ff cult to detect overall trends ffi erences in GCMs, downscaling ff erences between the Northern and Southern 7566 7565 ff cult to monitor and model. The observations are ffi ect the hydrological model results when using this grid for observed climate. ff erent projections showed large di ff erence between those regions for observed changes, they were considered too For estimates of floods in the future, major uncertainties are related to the following Precipitation is even more di Also in the literature, we find large discrepancies in results of climate change impact Spatial patterns can also be noisy and make it di ff components in the model chain: (1) climate model projections, (2) downscaling/bias study, underestimates precipitation incourse a the mountains byThe some validation 10–20 of %.and This high –3.5 will flows % of inmodel in S-HYPE is underestimation resulted up-dated in in withunderestimation is unregulated gauged a –5 flow median % rivers forregulated for absolute (Fig. rivers national mean error (Bergstrand statistics 3). high et of al., and flowsby When 2014). the 15 at design The underestimated the 400 variables, precipitation. underestimation gauging of the S-HYPE high stations, flow also is including a influenced by changes inProbably vegetation, the wind, monitoring snow/rainfall,precipitation technique and monitoring at (Lindström equipment. the andthat beginning Alexandersson, the of 2004). last 4 km We century precipitation also underestimated grid know for by operational experience hydrology, which we used in this sudden shifts in the time-series.analysis Nevertheless, using this observations can of be river auncertain flow. major Peak source than events of and normal error extreme conditions, high inof as flows all the are the more rating flow curve may andstation. then the In be water Sweden, out ice may jam of take isseries new the another flow are calibrated common paths, corrected range monitoring which problem for by-pass and ice-jamsbe the observed crucial and time- gauging for reconstructed estimates each ofof year. spring These uncertainty. peaks corrections in can some of the northern rivers and is a source it is well known thatal., rating curves 2011) change or over may time be (e.g.Coz over-simplistic Tomkins, 2014; et due Westerberg al., to et hydraulic 2014).stable conditions The but at recently gauging the an up-dated sites gauging rating30 site for %. curve (Le the changed When the Swedish estimated rating rivers water curves flow are by are considered some up-dated, as the rather historical flow is reconstructed to avoid in each site. Hence, each rating curve involves a number of variables to be decided and based on measurementstraditional of rating curve water based on level. an observed The relationship water between water flow level and is flow then calculated using a all very littleconclusions change regarding in the future water canmethods, discharge be and for referred hydrological to the models di Hall Baltic (e.g. et Bosshard Sea al., et 2013). region. al., Discrepancies 2013; in Donnelly et5.2 al., 2014; Methodological uncertainties Both observations from the pastobserved and time-series modelling of of river the flow future from involve the uncertainties. Swedish The archive of national monitoring are large. on frequency and intensity ofDankers floods for and the Northern Feyen European (2008)Lehner countries. For and et instance, Hirabayashi al. et (2006) al. suggested (2008) increase, indicated and Arheimer decrease, et while al. (2012) projected over was made in fourdi hydroclimate regions (Fig.small 1) to but represent as climatetwo the change. di However, results for showed climateregions very projections (Fig. 4). little of For the instance, the future, positiveprojection trend was the for mainly autumn seen flows in when using thedomain the north. were Hadley Only used spatially aggregated inlocal results for this or the regional study, whole as level, the the uncertainty projections in showed climate so model large results discrepancy was judged on to be very climate regions, for instance by Yue et al. (2012) ordue Chen and to Grasby (2009). localrelative deviation events. as In representative for thishow the country. extensive study The frequency in we analysis spatial also used shows terms 69 the sites specific high and flows considered were. the Originally, mean the analysis of to starting and ending years. These results are coherent with previous finding for other 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 | erent ff 0.70. All = er considerable in ff ected by regulation ff erent climate across the country, ff 5 % for the period 1999–2008. For all ± erent conclusions of hydrological impact of ff 7568 7567 0.81 for 200 stations una = regimes are improved compared to uncorrected climate-model data ff ects the simulation of snow variables (Dahné et al., 2013) and thereby also flood The S-HYPE model is assumed to be valid also for ungauged basins, which has ff although Sweden has gradientsthe in estimated temperature change and in precipitation climate that projections. are However, larger variables than that are sensitive to 400 sites, includingcriteria both regulated for and calibrationfocuses unregulated have on rivers, some timing average drawbacks and NSE the and can timing is one thus not underestimate issue perfect. the with magnitude for of NSEbeen the validated is high in flow that blind when calibrated it tests ones for for independent groups gauges, ofmodel similar resulting does catchments in not (Arheimer similar and show values Lindström, any as 2013). change in The in bias due to di Although, hydrological models are normallyand seriously uncertainties evaluated against are observed well data knownon and skills recognized, for they climate are changeversion rarely impact (2012) evaluated predictions especially has on an aand average process an level. NSE The average latest S-HYPE relative volume error of predictions of the future. Biasbeing correction used, is also which very mayclimate sensitive result to change the in even reference very dataset whenTherefore, di everything Donnelly else et is al.uncertainty, the kept (2014) uncertainties constant in urged the (Donnelly thatshould bias-correction methodology be et as and taken al., well the into impact account as 2013). model in climate climate change model impact5.2.3 and studies. scenario Hydrological model uncertainties in the region studied the hydrological model outputobserved increases, runo the variability(Bosshard bound et al., are 2011; narrower Teutschbeinmay and and also Seibert, introduce the inconsistency 2012). between Nevertheless,e temperature bias and correction precipitation, which highly in time (Maraun et al., 2010). When bias correction methods are applied, the fit of in mean and variabilityin of the those future, climate but it variables needs is clarification systematic whether and the will climate be model the errors same are stationary represented in any climate model. 5.2.2 Downscaling and bias correction Statistical down-scaling andsimulations bias of precipitation/temperature correctionquantiles empirically to techniques the by consistsimulations available fitting (e.g. of observations Yang simulated et and correcting al., mean applying 2010). the It and the is same therefore assumed correction that to the future observed biases climate projections shouldBergström be et the al., basis 2012),uncertainties. for but Ensemble decisions runs it and correspond isamong for to models) not impact and a certain not modeling “sensitivity to that an analysis”may (e.g. uncertainty also this (inter-comparison estimation be in will biased the by statistical actuallyinclude using sense. reduce Ensembles many similar versions the descriptions of overall some of model, the and the physics. GCM/RCMs In often addition, some processes are not well uncertain and we often found thethe opposite direction projections. of Accordingly, trends it in climate isprecipitation signals well between pattern known for that parts climateThe models of uncertainty di Europe further (e.g. increases vanRCMs (e.g. when Ulden Blöschl extreme and et events van al.,and are 2007). Oldenborgh, Hence, simulated 2013). the there by is results GCMs aonly should large and uncertainty aggregated be in the treated results calculations floods. with for It is caution the normally in recommended country that this the are ensemble part mean analyzed of from in using the many this di world. study Therefore, on changes in and interaction between these three components (e.g. Bosshard et5.2.1 al., 2013). Climate models The discrepancy between the climate model projections show that local results are very correction techniques, and (3) hydrological model uncertainties in the region studied, 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 | as well as tools for model 7570 7569 http://vattenwebb.smhi.se/ Predictions in Ungauged Basins – Synthesis across Processes, ff This study was performed at the SMHI Hydrological Research unit, where cult to estimate as climate projections were not in phase with observations. ffi This indicates thatfuture, there with more will influence be of a rain generated shift floods. in This should flood be generating considered processes in the high-flows may decrease bypeaks from on snow melt average in the 1and % spring shorter (–2 snow per % season. per decade, On decade) thedecade due mainly contrary, due to autumn to due higher flows temperatures more may to increase intensive by rainfall. lower 3 % per in reference data for design variablesuncertainties when and adapting simultaneous changes to from climate other change.be drivers However, accounted than for. climate must also di Temperature was found to bethese the are strongest mainly climate related driver to for snow river melt high-flows in as Sweden. In the future, the daily annual the changes ofbut daily there annual is high nohigh flows significant flows in trend to Sweden during decrease byfrequency the oscillate was 0.3–0.4 past % between noted, 100 per but decades, years. decade not A statistically in small significant. magnitude tendencyAlso and for 10-year in flood the future there will be oscillations between decades, but these were – – – The present scenarios consider changes in atmospheric emissions and hydropower impact on Swedish river flow, in: Evolving Water Resources Systems: Chapter 11.20, in: Runo Places and Scales, editedSavenije, H., by: Cambridge Bloeschl, University Press, G., Cambridge, Sivapalan, UK, M., 353–359, p. Wagener, 465, T., 2013. Viglione, A., and This study of climate impact on floods in Sweden, show that: of the water resources havebe thus expected had from a climate change. larger impact on river high flow than what6 can Conclusions concentrations of climate gases. However,other there drivers may of as the well hydrological bechanges, regime or additional constructions in changes in the in the future,large river such channel impact as (Merz on land et use al., floodresults 2012). and generation of These vegetation flood (e.g. can frequency also Hall and have recently et magnitude al., in reconstructed the 2013) future. the and Arheimerregime and and add total spring Lindström uncertainties peaks (2014) impact was to foundSwedish to of the hydropower have decreased was Swedish by mainly 15 established % during hydropower on 1910–1970. a on This national human scale. The alteration the river-water their parameters are realisticseveral impact for models, a for changing instancefrom climate. Stahl eight It et global al. hydrological is models (2012)trends also over found in Europe recommended that the provided to the observations. the ensemble use best mean representation of temperature, for instance evapotranspiration, should be validated especially to test if Arheimer, B. and Lindström, G.: Electricity vs Ecosystems – understanding and predicting Arheimer, B. and Lindström, G.: Implementing the EU Water Framework Directive in Sweden, References running in parallelessential in for the theby background group. Johan material, Strömqvist Hence, and andcouncils; input analysis we Thomas of recorded from Bosshard. would flows Funding was especiallyscenarios more done was was by like persons grants achieved funded from to from by HUVA/Elforsk, thanThe and recognize Swedish the work study on the projects research the model will Hydroimpacts2.0 authors work contributeand (Formas) to society was and and the CLEO its IAHS (Swedishare working scientific EPA). available group decade for on Panta Floods.uncertainty free Rhei S-HYPE check down-loading and on results maps at changes and of observations in climate from scenario hydrology estimates. gauges Acknowledgements. much work is done in common, taking advantages from previous work and several projects 5 5 25 20 10 15 20 25 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , , ˙ e, ¯ unien i č , 2009. 10.5194/hess-15- , 2011. , 2013. , 2014. , 2010. 10.1007/s00382-002-0296-y 10.5194/hessd-10-15525-2013 , 2006. 10.1016/j.jhydrol.2008.11.031 10.1002/hyp.7794 7571 7572 10.1029/2011WR011533 10.1111/j.1600-0870.2010.00475.x 10.1007/s10584-013-0941-y , 2006. , 2008. 10.1016/j.jhydrol.2005.07.003 , 2008. , 2014. , 2007. , 2011. 10.1029/2007JD009719 10.1007/s00382-006-0121-0 10.1002/hyp.6669 10.1623/hysj.53.4.754 10.2166/nh.2013.010 ects, Potsdam, Germany, 27–30 May 2013. ff assessment based on high-resolutiondoi: climate simulations, J. 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Summary from analyzing daily high-flows in observed time-series of 100 years for the 69 gauge stations 1910–2010Hadley climateEcham climate 2000–2100 2000–2100 12 12 8 –0.4 0.4 –0.2 0.0 –0.3 –1.3 –8.5 –0.4 3.0 –7.7 0.0 –1.1 8.9 19.9 –1.1 S-HYPE with: Data sourceObservations in: 100-years period mean (%) slope mean ( %) slope mean ( %) slope mean ( %) slope Figure 1. (A) the 69 gauges with long-term records from unregulated rivers across Sweden. Table 2. past, and in modelledof time-series the of reference 100 years periodannual for (1961–1990) high the flows, and future. frequency trends Deviation ofnumbers (slope (%) 10-year show as flood, against a and significance percent the spring level mean per of and decade) autumn are flood, respectively. given Bold for Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | : calibration (A) 7580 7579 : validation period (1988–1998). (B) Observed annual high flow (1911–2010) vs. reference period (1961–1990) for the Observed vs. predicted annual high flow using the S-HYPE model for Figure 3. Figure 2. 69 rivers: Fractionsmagnitude of of annual stations daily maximum exceeding discharge;discharge during Mean the March–June deviation and in July–February, 10-year magnitude respectively. The offilter. line flood daily shows maximum a each 10-year Gauss year; mean deviation in period (1999–2008) and Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 7582 7581 Spatial patterns of climate change impact across Sweden, when using two Modelled deviation in annual regional estimates 1961–2100 vs. the reference period Figure 5. (1961–1990) using S-HYPEprecipitation, for daily annual annual-high mean flow and temperatureresults number and are of precipitation, sites filtered exceeding maximumdata using the based daily a 10-years on flood. observations, 10-year while Annual climate dotted Gauss models. lines filter. represents modeling Solid with lines forcing data represent based on modeling with forcing downscaled and bias-corrected climate(2035–2065) and projections End of in century(1981–2010). S-HYPE. (2071–2100) Red are Mean means compared values to warmer/dryer the atfor and mean highly blue mid-century of regulated means a rivers colder/wetter. reference (yellow). Results period are not shown Figure 4. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 7584 7583 Modelled annual maximum daily flows of spring flood (on top) and autumn/winter Merged time-series of deviations (%) against the mean of the reference period in Figure 7. observations (1910–2010) andhigh-flows modelling in (2010–2100) Sweden. of past and future maximum annual Figure 6. flood (bottom) for(1961–1990). the The line period shows a 1961–2100. 10-year Deviation Gauss filter. (%) in magnitude vs. reference period