1. World Water Week 2011, Workshop 6: The Urban Shadow Virtual (green and blue) watersheds of cities Holger Hoff, Petra Döll, Marianela Fader, Dieter Gerten, Felix Portmann, Stefan Siebert Stockholm Environment Institute, Potsdam Institute for Climate Impact Research, University of Frankfurt, University of Bonn

2. Food production and even more so food trade are dominantly based on green water, so are the fluxes of virtual water into cities, however a few commodities also come with high blue water footprints, in particular rice Trade with agricultural commodities is growing faster than agricultural production, hence water footprints are growing in size and virtual water is often „flowing“ over very large distances, however only a few selected commodities are long-rangers Virtual (green and blue) watersheds of cities There are major differences in the sizes and compositions of virtual watersheds and per-capita footprints between cities in the north vs. south (tentative)

3. yield (t DM ha–1) 1 3 2 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 maize rainfed plus irrigated Global Crop – Vegetation - Water Models (LPJml, GCWM) calculating biomass production, crop yields, consumptive water use, and virtual water contents Bondeau et al 2007

4. Global Crop – Vegetation - Water Model total consumptive (green) crop water use mm per year

5. Global Crop – Vegetation - Water Model total consumptive (blue) crop water use

6. Global Crop – Vegetation - Water Model surplus and deficit areas of green water consumption / use mm per year deficit pixels fulfill their demands from the closest available surplus within the respective country after all domestic demands are met, remaining surpluses (pixels) are available for export per-capita demands within any one country are the same for cities and rural areas (based on calculated total domestic production plus imports minus exports – COMTRADE) Rules:

7. Global Crop – Vegetation - Water Model surplus and deficit areas of blue water consumption / use mm per year

8. Fader et al 2011 Global Crop – Vegetation - Water Model combined with trade data external vs. internal footprint livestock products not included m 3 water per capita and year

9. Fader et al 2011 Global Crop – Vegetation - Water Model combined with trade data green & blue external vs internal footprint (m 3 per capita and year) livestock products not included m 3 water per capita and year

10. Berlin virtual (green) watershed < 0.10.1 - 11 - 1010 - 100> 100 mm per year where is the virtual water coming from?

11. < 0.10.1 - 11 - 1010 - 100> 100 Delhi virtual (green) watershed mm per year

12. Lagos virtual (green) watershed < 0.10.1 - 11 - 1010 - 100> 100 mm per year

13. Berlin virtual (green) water origin - distance Akica: differentiate !

14. Berlin virtual (blue) water origin - distance

15. Delhi virtual (green) water origin - distance

16. Delhi virtual (blue) water origin - distance

17. Lagos virtual (green) water origin - distance

18. Lagos virtual (blue) water origin - distance

19. Green and blue virtual water imports – how much and how far? Population (million) Green Volume (MCM) Blue Volume (MCM) Green Distance (km) Blue Distance (km) Berlin3.522005044004200 Delhi16.540003000600200 Lagos810000608009000

20. Water productivities across all crops Gerten et al 2011 m 3 for producing 1,000 kcal

21. Cities‘ footprints are not limited to water Thank you ! Carbon balance Erb et al 2009