Skip to main content

Advertisement

SpringerLink
Log in

Climate change in the Western Bug river basin and the impact on future hydro-climatic conditions

  • Thematic Issue
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Within the IWRM research project IWAS, we generated regional climate projections via dynamic downscaling for the catchment area of the Western Bug river in the border area of Poland, Belarus, and Ukraine. Data sources used are WMO meteorological station data and global climate ERA40 reanalysis data for an evaluation run, as well as global simulations from the ECHAM5 model for a twentieth-century control run and for the IPCC emission scenarios A2 and B1. We evaluated the performance of the regional climate model CCLM on the basis of simulated 2m temperature and precipitation. Furthermore, we analyzed the hydro-climatic conditions of the past and their projected future changes in the catchment based on 2m temperature, precipitation, potential evaporation and climatic water balance. The latter is discussed as an indicator for potential water availability in the region. Our evaluation, like many other studies, attests that the CCLM performs well for 2m temperature. Precipitation is not modelled adequately for the Western Bug basin. Remarkably, the precipitation bias is five times higher in the ECHAM5-driven control run than in the ERA40-driven evaluation run. Despite all the uncertainties, the significance of the modelled changes clearly suggests robust model results for the last three decades of this century. Up to the end of the century, both scenarios A2 and B1 lead to highly significant warming for each month in the long-term mean, with highest warming rates in winter. Instead, precipitation does not change significantly in the long-term yearly mean, but the intra-annual distribution of monthly precipitation sums shifts, with an increase in winter and a strong decrease in summer. Combined, this leads to a changed climatic water balance with a stronger deficit in summer and a higher gain in winter. Particular in the south-eastern part, the summer deficit cannot be compensated within the annual cycle. This might have serious implications for many socio-economic sectors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Bachner S, Kapala A, Simmer C (2008) Evaluation of daily precipitation characteristics in the CLM and their sensitivity to parameterizations. Meteorol Z 17:407–419

    Article  Google Scholar 

  • Blumensaat F, Pavlik D, Schubert K, Tönnies A, Bernhofer C, Krebs P (2012) Temporal rainfall disaggregation under minimum data requirements. In: Molnar P, Burlando P, Einfalt T (eds) 9th International Workshop on precipitation in urban areas. ETH Zürich, St. Moritz, pp 16–21

    Google Scholar 

  • Chen J, Brissette FP, Leconte R (2011) Uncertainty of downscaling method in quantifying the impact of climate change on hydrology. J Hydrol 401:190–202. doi:10.1016/j.jhydrol.2011.02.020

    Article  Google Scholar 

  • Christensen JH, Christensen OB (2007) A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Clim Change 81:7–30. doi:10.1007/s10584-006-9210-7

    Article  Google Scholar 

  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon WT, Laprise R, Magaña Rueda V, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. Climate Change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York, pp 847–940

  • Conradt T, Kaltofen M, Hentschel M, Hattermann FF, Wechsung F (2007) Impacts of global change on water-related sectors and society in a trans-boundary central European river basin—part 2: from eco-hydrology to water demand management. Adv Geosci 11:93–99. doi:10.5194/adgeo-11-93-2007

    Article  Google Scholar 

  • Déqué M, Rowell DP, Lüthi D, Giorgi F, Christensen JH, Rockel B, Jacob D, Kjellström E, de Castro M, van den Hurk B (2007) An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections. Clim Change 81:53–70. doi:10.1007/s10584-006-9228-x

    Article  Google Scholar 

  • Dierer S, Arpagaus M, Seifert A, Avgoustoglou E, Dumitrache R, Grazzini F, Mercogliano P, Milelli M, Starosta K (2009) Deficiencies in quantitative precipitation forecasts: sensitivity studies using the COSMO model. Meteorol Z 18:631–645

    Article  Google Scholar 

  • Dietrich O, Steidl J, Pavlik D (2012) The impact of global change on the water balance of large wetlands in the Elbe Lowland. Reg Environ Change 12:701–713. doi:10.1007/s10113-012-0286-5

    Article  Google Scholar 

  • DVWK (1996) Ermittlung der Verdunstung von Land- und Wasserflächen. Bonn (in German)

  • Feldmann H, Früh B, Schädler G, Panitz HJ, Keuler K, Jacob D, Lorenz P (2008) Evaluation of the precipitation for South-western Germany from high resolution simulations with regional climate models. Meteorol Z 17:455–465

    Article  Google Scholar 

  • Fischer S, Pluntke T, Pavlik D, Bernhofer C (2014) Impact of climate change on various socio-economic sectors in a sub basin of Western Bug. Environ Earth Sci (this issue)

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578. doi:10.1002/joc.1556

    Article  Google Scholar 

  • Frei C, Christensen JH, Déqué M, Jacob D (2003) Daily precipitation statistics in regional climate models: evaluation and intercomparison for the European Alps. J Geophys Res. doi:10.1029/2002JD002287

    Google Scholar 

  • Frei C, Schöll R, Fukutome S, Schmidli J, Vidale PL (2006) Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate models. J Geophys Res. doi:10.1029/2005JD005965

    Google Scholar 

  • Giorgi F, Bi X, Pal J (2004) Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100). Clim Dyn 23:839–858. doi:10.1007/s00382-004-0467-0

    Article  Google Scholar 

  • Graham LP, Andréasson J, Carlsson B (2007) Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods—a case study on the Lule River basin. Clim Change 81:293–307. doi:10.1007/s10584-006-9215-2

    Article  Google Scholar 

  • Haslinger K, Anders I, Hofstätter M (2012) Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region. Clim Dyn. doi:10.1007/s00382-012-1425-7

    Google Scholar 

  • Hattermann FF, Post J, Krysanova V, Conradt T, Wechsung F (2008) Assessment of water availability in a Central-European River Basin (Elbe) under climate change. Adv Clim Change Res 4:42–50

    Google Scholar 

  • Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095–1107. doi:10.1175/2009BAMS2607.1

    Article  Google Scholar 

  • Helm B, Tavares Wahren F, Pluntke T (2014) Integrated water quantity and quality modelling of river basins: strategy for a transdisciplinary approach under data scarce conditions. Environ Earth Sci (this issue)

  • Jacob D, Bärring L, Christensen OB, de Castro M, Déqué M, Giorgi F, Hagemann S, Hirschi M, Jones R, Kjellström E, Lenderink G, Rockel B, Sánchez E, Schär C, Seneviratne SI, Somot S, van Ulden A, van den Hurk B (2007) An inter-comparison of regional climate models for Europe: model performance in present-day climate. Clim Change 81:31–52. doi:10.1007/s10584-006-9213-4

    Article  Google Scholar 

  • Jaeger EB, Anders I, Lüthi D, Rockel B, Schär C, Seneviratne SI (2008) Analysis of ERA40-driven CLM simulations for Europe. Meteorol Z 17:349–367. doi:10.1127/0941-2948/2008/0301

    Article  Google Scholar 

  • Kalbus E, Kalbacher T, Kolditz O, Krüger E, Seegert J, Teutsch G, Borchardt D, Krebs P (2012) Integrated water resources management under different hydrological, climatic and socio-economic conditions. Environ Earth Sci 65:1363–1366. doi:10.1007/s12665-011-1330-3

    Article  Google Scholar 

  • Kjellström E, Bärring L, Jacob D, Richard J, Lenderink G, Schär C (2007) Modelling daily temperature extremes: recent climate and future changes over Europe. Clim Change 81:249–265. doi:10.1007/s10584-006-9220-5

    Article  Google Scholar 

  • Knote C, Heinemann G, Rockel B (2010) Changes in weather extremes: assessment of return values using high resolution climate simulations at convection-resolving scale. Meteorol Z 19:11–23. doi:10.1127/0941-2948/2010/0424

    Article  Google Scholar 

  • Koch H, Vögele S (2009) Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change. Ecol Econ 68:2031–2039. doi:10.1016/j.ecolecon.2009.02.015

    Article  Google Scholar 

  • Koch H, Kaltofen M, Schramm M, Grünewald U (2006) Adaptation strategies to global change for water resources management in the Spree river Catchment, Germany. Int J River Basin Manag 4:273–281. doi:10.1080/15715124.2006.9635296

    Article  Google Scholar 

  • Leidel M, Niemann S, Hagemann N (2012) Capacity development as a key factor for integrated water resources management (IWRM): improving water management in the Western Bug River Basin, Ukraine. Environ Earth Sci 65:1415–1426. doi:10.1007/s12665-011-1223-5

    Article  Google Scholar 

  • Li H, Sheffield J, Wood EF (2010) Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching. J Geophys Res 115:D10101. doi:10.1029/2009JD012882

    Article  Google Scholar 

  • Lipinskyy VM, Dyachuk VA, Babichenko VM (2003) Climate of Ukraine. Rayevskyy Publishing, Kyiv, p 343 (in Ukraine)

    Google Scholar 

  • Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, Brienen S, Rust HW, Sauter T, Themeßl M, Venema VKC, Chun KP, Goodess CM, Jones RG, Onof C, Vrac M, Thiele-Eich I (2010) Precipitation downscaling under climate change. Recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48:34. doi:10.1029/2009RG000314

    Article  Google Scholar 

  • Middelkoop H, Daamen K, Gellens D, Grabs W, Kwadijk JCJ, Lang H, Parmet BWAH, Schädler B, Schulla H, Wilke K (2001) Impact of climate change on hydrological regimes and water resources management in the Rhine Basin. Clim Change 49:105–128. doi:10.1023/A:1010784727448

    Article  Google Scholar 

  • Nakicenovic N, Swart R (2000) IPCC special report on emission scenarios. Cambridge University Press, Cambridge

    Google Scholar 

  • Olesen JE, Carter TR, Díaz-Ambrona CH, Fronzek S, Heidmann T, Hickler T, Holt T, Minguez MI, Morales P, Palutikof JP, Quemada M, Ruiz-Ramos M, Rubæk GH, Sau F, Smith B, Sykes MT (2007) Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models. Clim Change 81:123–143. doi:10.1007/s10584-006-9216-1

    Article  Google Scholar 

  • Pavlik D, Söhl D, Pluntke T, Mykhnovych A, Bernhofer C (2012) Dynamic downscaling of global climate projections for Eastern Europe with a horizontal resolution of 7 km. Environ Earth Sci 65:1475–1482. doi:10.1007/s12665-011-1081-1

    Article  Google Scholar 

  • Penman HL (1948) Natural evaporation from open water, bare soil and grass. Proc Royal Soc Lond Ser A 193:120–145

    Article  Google Scholar 

  • Piani C, Haerter JO, Coppola E (2010) Statistical bias correction for daily precipitation in regional climate models over Europe. Theor Appl Climatol 99:187–192

    Article  Google Scholar 

  • Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17:347–348

    Article  Google Scholar 

  • Roeckner E, Bäuml G, Bonaventura L, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kirchner I, Kornblueh L (2003) The atmospheric general circulation model ECHAM5. MPI-report No. 349, p 127

  • Roesch A, Jaeger EB, Lüthi D, Seneviratne SI (2008) Analysis of CCLM model biases in relation to intra-ensemble model variability. Meteorol Z 17:369–382

    Article  Google Scholar 

  • Rowell DP (2005) A scenario of European climate change for the late twenty-first century: seasonal means and interannual variability. Clim Dyn 25:837–849. doi:10.1007/s00382-005-0068-6

    Article  Google Scholar 

  • Rummukainen M (2010) State-of-the-art with regional climate models. Wiley Interdiscip Rev: Clim Change 1:82–96. doi:10.1002/wcc.8

    Google Scholar 

  • Schanze J, Trümper J, Burmeister C, Pavlik D, Kruhlov I (2012) A methodology for dealing with regional change in integrated water resources management. Environ Earth Sci 65:1405–1414. doi:10.1007/s12665-011-1311-6

    Article  Google Scholar 

  • Steppeler J, Doms G, Schättler U, Bitzer HW, Gassmann A, Damrath U, Gregoric G (2003) Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteorol Atmos Phys 82:75–96

    Article  Google Scholar 

  • Suklitsch M, Gobiet A, Leuprecht A, Frei C (2008) High resolution sensitivity studies with the regional climate model CCLM in the Alpine Region. Meteorol Z 17:467–476

    Article  Google Scholar 

  • Uppala SM, Kållberg PW, Simmons AJ, Andrae U, Da Costa Bechtold V, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Vande Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof F, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hòlm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf JF, Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012

    Article  Google Scholar 

  • Von Storch H, Zwiers F (2012) Testing ensembles of climate change scenarios for “statistical significance”. Clim Change 117:1–9. doi:10.1007/s10584-012-0551-0

    Article  Google Scholar 

  • Vörösmarty CJ, Green P, Salisbury J, Lammers RB (2000) Global water resources: vulnerability from climate change and population growth. Science 289:284–288. doi:10.1126/science.289.5477.284

    Article  Google Scholar 

  • Wendling U, Müller J, Schwede K (1991) Bereitstellung von täglichen Informationen zum Wasserhaushalt des Bodens für die Zwecke der agrarmeteorologischen Beratung. Meteorol Z 41:468–475 (in German)

    Google Scholar 

  • Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Elsevier, London

    Google Scholar 

  • Yokohata T, Annan JD, Collins M, Jackson CS, Tobis M, Webb MJ, Hargreaves JC (2011) Reliability of multi-model and structurally different single-model ensembles. Clim Dyn 39:599–616. doi:10.1007/s00382-011-1203-1

    Article  Google Scholar 

  • Zebisch M, Grothmann T, Schröter D, Hasse C, Fritsch U, Cramer W (2005) Climate change in Germany—vulnerability and adaptation of climate sensitive sectors. Umweltbundesamt, Dessau

    Google Scholar 

Download references

Acknowledgments

This work was supported by main funding from the Federal Ministry for Education and Research (BMBF) in the framework of the project “IWAS—International Water Research Alliance Saxony” (grant 02WM1028) and partially by the Helmholtz Association with HIGRADE. The authors would like to thank the Centre for Information Services and High Performance Computing in Dresden (ZIH) for providing the high-performance computer resources and for support, the German High Performance Computing Centre for Climate and Earth System Research (DKRZ) for providing the ERA40 and ECHAM5 data sets, the State Environment Agency Rheinland-Pfalz, Germany, for providing the software package InterMet and the CLM-Community for providing access to and support for the CCLM as well as for scientific discussions and valuable advice. Special thanks to all colleagues and partners of the project IWAS for successful cooperation and support.

Author information

Authors and Affiliations

  1. Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität Dresden, Dresden, Germany

    Dirk Pavlik, Dennis Söhl, Thomas Pluntke & Christian Bernhofer

Authors
  1. Dirk Pavlik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dennis Söhl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thomas Pluntke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christian Bernhofer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dirk Pavlik.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pavlik, D., Söhl, D., Pluntke, T. et al. Climate change in the Western Bug river basin and the impact on future hydro-climatic conditions. Environ Earth Sci 72, 4787–4799 (2014). https://doi.org/10.1007/s12665-014-3068-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12665-014-3068-1

Keywords

Search

Navigation