Regional Environmental Change

, Volume 12, Issue 1, pp 69–80 | Cite as

Downscaling nonclimatic drivers for surface water vulnerabilities in the Elbe river basin

  • Jürgen BlazejczakEmail author
  • Martin Gornig
  • Volkmar Hartje
Original Article


Aggregated consideration of both climate and socio-economic change in a coarse spatial resolution is a central feature for scenario development in global change research. Downscaling of the supposed aggregated changes is a necessary prerequisite for the assessments of global change at the regional scale. The present paper describes the method and results of an approach to develop and to apply scenarios of socio-economic change at a sub-national level, which are consistent with global change scenarios. National and regional models of economic and demographic development are used to regionalise drivers of socio-economic change. Scenario results are subsequently applied in order to analyse the impacts of socio-economic and climatic changes on water management issues in the Elbe river basin. Starting from global IPCC-Emissions Scenarios and taking up their key points, we formulate two scenarios for the German and Czech parts of the Elbe catchment areas. We present a system of demographic and economic models, designed to consistently project socio-economic developments at a national and sub-national level and, thus, to quantitatively illustrate our scenarios. The results show that in a scenario that assumes continued globalisation and emphasis on economic growth, export orientation will result in a comparatively high share of manufacturing. Growth spreads from centres to peripheral regions. Still, at the national level, the increase in population and employment will be modest and create little additional pressure, but water stress will be considerably stronger on a regional basis, namely in metropolitan areas such as Prague, Berlin and Hamburg. In a scenario where economic goals are balanced with ecologic and social ones, growth is weaker and the weight of the service sector increases more rapidly, thus easing the driving forces for overall water demand and pollution. However, as in this scenario regional metropolitan centres develop at the cost of peripheral regions, regional development is more selective and the driving forces for potential water stress will diverge spatially.


Scenario analysis Modelling socio-economic development Industry level structural change Regional structural change 



This study has been funded by the German Federal Ministry of Education and Research within the project GLOWA-Elbe II. We are indebted to two anonymous referees for valuable comments.


  1. Barjak F, Franz P, Heimpold G, Rosenfeld M (2000) Regionalanalyse Ostdeutschland: Die wirtschaftliche Situation der Länder, Kreise und kreisfreien Städte im Vergleich. In: Institut für Wirtschaftsforschung Halle (ed) Wirtschaft im Wandel 2/02. IWH, HalleGoogle Scholar
  2. Barrell R, Dury K, Hurst I, Pain N (2001a) Modelling the world economy: the NIESR model NIGEM. In: Paper presented at an ENEPRI workshop, July 2001, ParisGoogle Scholar
  3. Barrell R, Dury K, Holland D (2001b) Macro-models and the medium term: the NIESR experience with NiGEM. In: Paper presented at the EU/ULB/AEA conference, July 2001, BrusselsGoogle Scholar
  4. BBR—Bundesamt für Bauwesen und Raumordnung (2004) Laufende Raumbeobachtung—Raumabgrenzungen, Raumordnungsregionen (Analyseräume). (30.06. 2010)
  5. BBR (Bundesamt für Bauwesen und Raumordnung) (2006) Raumordnungsprognose 2020/2050. Berichte, vol 23. BonnGoogle Scholar
  6. Brenke K, Eickelpasch A, Geppert K, Gornig M (2007) Beschäftigungspotenziale in ostdeutschen Dienstleistungsmärkten. In: DIW Berlin (ed) DIW—Politikberatung kompakt 30. Deutsches Institut für Wirtschaftsforschung, BerlinGoogle Scholar
  7. Bucksteeg M, Astor M, Bornemann H, Maier F (2005) Perspektive Ostdeutschland 2030. Gutachten im Auftrag des Bundesamtes für Bauwesen und Raumordnung. Prognos AG, BaselGoogle Scholar
  8. Burda MC (2005) What kind of shock was it? Regional integration of Eastern Germany after unification. In: Paper presented at the annual meetings of AEA, 8 Jan 2006, BostonGoogle Scholar
  9. Carone G (2005) Long-term labour projections for the 25 EU member states: a set of data for assessing the economic impact of ageing. Eur Econ 235, BrusselsGoogle Scholar
  10. Carter TR, Jones RN, Lu X, Bhadwal S, Conde C, Mearns LO, O’Neill BC, Rounsevell MDA, Zurek MB (2007) New assessment methods and the characterisation of future conditions. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 133–171Google Scholar
  11. DIW (Deutsches Institut für Wirtschaftsforschung), IfW (Institut für Weltwirtschaft an der Universität Kiel), IAB (Institut für Arbeitsmarkt—und Berufsforschung), IWH (Institut für Wirtschaftsforschung Halle), ZEW (Zentrum für Europäische Wirtschaftsforschung) (2002) Fortschrittsbericht wirtschaftswissenschaftlicher Institute über die wirtschaftliche Entwicklung in Ostdeutschland. HalleGoogle Scholar
  12. EC (European Commission) (2004) Nomenclature of territorial units for statistics NUTS 2003, methods and nomenclatures, theme 1. LuxembourgGoogle Scholar
  13. EUROSTAT (European statistical office) (2007) Long-term population projection at regional level. Statistics in focus, 28/07, LuxembourgGoogle Scholar
  14. Flörke M, Alcamo J (2004) European outlook on water use. Center for Environmental Systems Research, University of KasselGoogle Scholar
  15. GEFRA (Gesellschaft für Finanz—und Regionalanalysen), GWS (Gesellschaft für wirtschaftliche Strukturforschung), IAB (Institut für Arbeitsmarkt—und Berufsforschung) (2009) Strukturwandel in der deutschen Wirtschaft: Kommt es zu einer De- oder Re-Industrialisierung? Münster, Osnabrück, NürnbergGoogle Scholar
  16. Geppert K, Gornig M, Werwatz A (2008) Economic growth of agglomerations and geographic concentration of industries: evidence for West Germany. Reg Stud 42:413–421. doi: 10.1080/00343400701291518 CrossRefGoogle Scholar
  17. Gömann H, Kreins P, Heidecke C (2010) How global conditions impact regional agricultural production and nitrogen surpluses in the German Elbe River Basin. Reg Environ Change. doi: 10.1007/s10113-010-0198-1
  18. Gornig M, Görzig B, Schulz E (1999) Perspektiven der Beschäftigungs—und Bevölkerungsentwicklung in Deutschland und in den Bundesländern. In: Informationen zur Raumentwicklung, Heft 11/12Google Scholar
  19. Görzig A, Gornig M, Werwatz A (2008) Firm-wage differentiation in east in Germany—non-parametric analysis of the wage spread. Econ Transit 16(2):273–292CrossRefGoogle Scholar
  20. Greenpeace, DIW (Deutsches Institut für Wirtschaftsforschung) (1999) Wirtschaft ohne Wachstum Dr. Th. Gabler, WiesbadenGoogle Scholar
  21. Grübler A, O’Neill B, Riahi K, Chirkov V, Goujon A, Kolp P, Prommer I, Scherbov S, Slentoe E (2007) Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES. Technol Forecast Soc Change 74:980–1029CrossRefGoogle Scholar
  22. Hoymann J (2010) Accelerating urban sprawl in depopulating regions: a scenario analysis for the Elbe River Basin. Reg Environ Change 11(1):73–86Google Scholar
  23. IAB (Institut für Arbeitsmarkt—und Berufsforschung) (2003) Die Entwicklung der ostdeutschen Regionen. In: Blien U (ed) Beiträge zur Arbeitsmarkt—und Berufsforschung, vol 267. NürnbergGoogle Scholar
  24. IKSE (Internationalen Kommission zum Schutz der Elbe) (2005) Internationale Flussgebietseinheit Elbe. Anlage 2 zum Bericht an die Europäische Kommission zur Schaffung eines Ordnungsrahmens für Maßnahmen der Gemeinschaft im Bereich Wasserpolitik, DresdenGoogle Scholar
  25. IW (Institut der Deutschen Wirtschaft) (2005) Vision D. Wege aus der Wachstumsfalle. KölnGoogle Scholar
  26. Nakicenovic N, Swart R (eds) (2000) Special report emissions scenarios. Cambridge University Press, CambridgeGoogle Scholar
  27. Sartorius C, Hillenbrand T, Walz R (2010) Impact and cost of measures to reduce nutrient emissions from wastewater and stormwater treatment in the German Elbe river basin. Reg Environ Change. doi: 10.1007/s10113-010-0140-6
  28. Schulz E (2004) Bevölkerungsentwicklung in West—und Ostdeutschland—Vorausschätzung bis 2050. In: DIW Berlin (ed) Wochenbericht des DIW, vol 33. Deutsches Institut für Wirtschaftsforschung, Berlin, pp 471–485Google Scholar
  29. Snower DJ, Merkl C (2006) The caring hand that cripples: the East German labour market after reunification. Working Paper 1263, The Kiel Institute for the World Economy, KielGoogle Scholar
  30. StaBuA (Statistisches Bundesamt) (2006) Leben in Deutschland. Haushalte, Familien und Gesundheit. Ergebnisse des Mikrozensus 2005. WiesbadenGoogle Scholar
  31. StaBuA (Statistisches Bundesamt) (2010) Volkswirtschaftliche Gesamtrechnungen. Input–Output-Rechnung 2007, Fachserie 18, Reihe 2. WiesbadenGoogle Scholar
  32. Südekum J (2006) Concentration and specialisation trends in Germany since re-unification. Reg Stud 40:861–873CrossRefGoogle Scholar
  33. Van Vuuren DP, Smith SJ, Riahi K (2010) Downscaling socio-economic and emission scenarios for global environmental change research: a review. Wiley Interdiscip Rev Clim Change 1:393–404Google Scholar
  34. Wechsung F, Kaden S, Behrendt H, Klöcking B (2008) Integrated analysis of the impacts of global change on environment and society in the Elbe River Basin. Weißensee-Verlag, BerlinGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Jürgen Blazejczak
    • 1
    • 2
    Email author
  • Martin Gornig
    • 2
    • 3
  • Volkmar Hartje
    • 3
  1. 1.University of Applied Sciences MerseburgMerseburgGermany
  2. 2.German Institute for Economic Research (DIW) BerlinBerlinGermany
  3. 3.Technical University (TU) BerlinBerlinGermany

Personalised recommendations