Evaluation of Very High-Resolution Climate Model Data for Simulating Flood Hazards in the Upper Danube Basin

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Evaluation of Very High-Resolution Climate Model Data for Simulating Flood Hazards in the Upper Danube Basin Journal of Hydrology (2007) 347, 319– 331 available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/jhydrol Evaluation of very high-resolution climate model data for simulating flood hazards in the Upper Danube Basin Rutger Dankers a,*, Ole Bøssing Christensen b, Luc Feyen a, Milan Kalas a, Ad de Roo a a European Commission DG Joint Research Centre, Institute for Environment and Sustainability, TP261, I-21020, Ispra, Italy b Danish Climate Center/Danish Meteorological Institute, Lyngbyvej 100, DK-2100 Copenhagen Ø, Denmark Received 8 March 2007; received in revised form 22 June 2007; accepted 11 September 2007 KEYWORDS Summary For the purpose of assessing flood hazard in the Upper Danube Basin in Central Climate change; Europe under current and projected future climate conditions, we evaluated data from a Regional climate recent experiment with the regional climate model HIRHAM at a horizontal resolution of models; approximately 12 km. The climate simulations were used to drive the hydrological model Precipitation; LISFLOOD and the results were compared with observations of precipitation and river dis- Floods; charge in the area. To explore the benefits of using these very high-resolution data, we Danube also included the results of two HIRHAM experiments at a lower resolution of 50 km in our comparison. It was found that the 12-km data represent the orographic precipitation patterns and the extreme rainfall events over the Upper Danube Basin better than the low- resolution 50-km data. However, the average precipitation rates are generally higher than observed, while the extreme precipitation levels are mostly underestimated. Using the HIRHAM data as input into the LISFLOOD model resulted in a realistic simulation of the average discharge regime in the Upper Danube. In most rivers the 12-km data also led to a better representation of extreme discharge levels, although the performance was still poor in two relatively small rivers originating in the Alps. At larger spatial scales much of the differences and uncertainties between the high- and low-resolution climate data and the observations are averaged out, resulting in a more or less similar performance of the hydrological model, but at the local and sub-basin scale the 12-km data yield better results. The scenario simulations suggest that future climate changes will have an influ- ence on the discharge regime and may increase the flood hazard in large parts of the Upper Danube Basin. ª 2007 Elsevier B.V. All rights reserved. * Corresponding author. Tel.: +39 0332 786361; fax: +39 0332 785230. E-mail address: [email protected] (R. Dankers). 0022-1694/$ - see front matter ª 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2007.09.055 320 R. Dankers et al. Introduction available in sufficient detail or for a long enough period to be able to derive meaningful statistical relationships. These In the past few decades flood damages in Europe have in- disadvantages can be overcome by dynamical downscaling creased considerably (Munich Re, 2005). In a large part, this using regional climate models (RCMs). upward trend can probably be attributed to human causes In recent years, the horizontal resolution of RCM experi- such as progressing urbanisation in flood plains. Whether ments has increased considerably and now approaches a le- changes in climate have also played a role is far from cer- vel that allows a realistic simulation of the amount and tain, as huge natural variability and long-term persistence intensity of precipitation at the scale of river basins and make it difficult to discern any trends in extreme weather small catchments. Of the studies mentioned above, only events that are, by definition, rare (Kundzewicz et al., Kay et al. (2006a) used data from an RCM, in their case Had- 2005). In the future the influence of climate change is likely RM3, at a spatial resolution of 25 km, as direct input into a to become more prominent. As a consequence of an in- catchment-based rainfall-runoff model. To take account of crease in greenhouse gas concentrations and the conse- the spatial variability they combined the precipitation fields quent rise in atmospheric temperatures, the hydrological of the RCM with high-resolution, standard average annual cycle will intensify, and extreme precipitation events are rainfall data to calculate the catchment-average rainfall. expected to become more frequent and more intense (Ben- They found that direct use of the RCM data into the hydro- iston et al., 2007; Christensen and Christensen, 2003; logical model resulted in relatively good estimates of flood Semmler and Jacob, 2004). Due to higher winter tempera- frequency (Kay et al., 2006b). Graham et al. (2007) used the tures less precipitation will temporarily be stored as snow, results of seven different RCM simulations, with spatial res- and for a shorter period of time. All this will likely increase olutions ranging from 25 to 50 km, as input into a hydrolog- flood hazard in many areas of Europe, although the risk of ical model of the Lule River Basin in Sweden. They snowmelt floods and ice jams in spring may actually be re- compared the delta-change approach of applying only the duced (Kundzewicz et al., 2006). climate change signal on observations with a ‘scaling ap- To date, relatively few studies have appeared that made proach’, i.e. a more direct use of regional climate model a quantitative assessment of the potential impacts of cli- data after correction for systematic bias. They concluded mate change on extreme river flows in Europe. Among these that the largest differences between the two methods oc- studies, there has been a geographical preference for catch- curred in the simulation of extreme runoff events, and that ments located in the UK (e.g. Kay et al., 2006a), the Bene- the results of the scaling approach were more consistent lux countries (e.g. Booij, 2005), Germany (e.g. Shabalova with the changes in extremes in the RCMs themselves (Gra- et al., 2003), and Scandinavia (e.g. Graham et al., 2007). ham et al., 2007). While most studies found an increase in flood frequency In this paper, we present data from a recent experiment and intensity, others found a decreasing trend. Different cli- with the regional climate model HIRHAM at an even higher mate scenarios and hydrological models that have been ap- spatial resolution of approximately 12 km. Our main pur- plied, as well as different ways of linking them make it pose was to evaluate these very high-resolution data for difficult to compare the results and to paint an overall pic- application in impact studies of flood hazard under changing ture at the European scale. So far only Lehner et al. (2006) climatic conditions. To this end, the 12-km HIRHAM model made an integrated, pan-European assessment of the was coupled in an off-line mode to a hydrological model changes in flood frequencies due to global climate change, of the Upper Danube basin in Central Europe. The perfor- and found northern to north-eastern Europe to be most mance of both the climate model and the hydrological mod- prone to a rise in flood risk. However, their analysis was el was validated against observations of climate and river based on applying the climate change signal of two different discharge, looking specifically at the simulation of hydrolog- general circulation models (GCMs) to an observation-based ical extremes. To evaluate the benefits of using high spatial dataset (i.e. a delta-change approach), and did not take resolution climate information, we compared the results into account a potential increase in climate variability with a second climate model experiment in which HIRHAM (see Lehner et al., 2006). was driven by the same global atmosphere model and green- Due to their coarse horizontal resolution and inability to house gas emission scenario, but run at a lower horizontal resolve important sub-grid scale hydroclimatological pro- resolution of 50 km. The significance of the differences cesses, GCMs are generally unable to capture the extreme in the results due to the increase in resolution was further weather conditions that may cause flooding. For these rea- tested by including a third experiment with the same cli- sons, hydrological impact studies commonly rely on statisti- mate model, also at 50 km but driven by a different scenario cal downscaling techniques (e.g. Wood et al., 2004)or of greenhouse gas emissions. sensitivity studies with hydrological models in which mete- This paper is organised as follows: after introducing orological observations were simply perturbed by some arbi- the Study area and explaining the Methodology the cli- trary amount (e.g. Kwadijk, 1993). However, the implicit matology simulated by HIRHAM in the high- and low-res- assumption that the statistical relationships developed for olution experiments will be validated against the present-day climate also hold under the different forc- observations, and the differences in the climate change ing conditions of possible future climates cannot be veri- signal between the three RCM runs will be discussed. fied. Empirical techniques cannot account for systematic Next, the performance of the hydrological model, when changes in regional forcing conditions or feedback pro- driven by the HIRHAM data, will be evaluated and the cesses. Furthermore, in remote regions or areas with com- differences in climate change impacts on simulated plex topography observational data are mostly not flood risks will be assessed. Evaluation of very high-resolution climate model data for simulating flood hazards in the Upper Danube Basin 321 Study area a grid size of 12 km and covering the whole of Europe. The HIRHAM experiment consisted of simulations for two The catchment of the Danube River is the second largest in 30-year time slices: a 30-year control run with a greenhouse Europe, covering 18 countries.
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