Water scarcity has been on the international agenda for a few years now (OECD, 2012; UNEP, 2012). Overuse of freshwater resources has already caused environmental degradation in many locations, and causes significant economic and health risks as well. However, the problem can get much worse in the future, with continued population growth and economic development. That’s why researchers like me build computer models: to get a better idea of how water demand and availability may change in the future.
I built a model for future water demand in the electricity, industry and municipal sectors. Although agriculture uses much more water, the non-agricultural sectors seem to be growing faster. My water model is added into a much larger so-called Integrated Assessment Model: a model that integrates knowledge on a diverse range of topics, from energy to agriculture and from ocean temperature to CO2-emissions. The model we work with is called IMAGE (PBL, 2014). We use scenarios to explore the range of possible futures, each having different rates of population growth and economic development, as well as different energy technologies and efficiency improvements over time.
As you can see in the figure above, global non-agricultural water demand could increase a lot this century. The baseline or ‘middle of the road’ scenario projects 40% more withdrawal (water taken out of rivers and lakes) and 120% more consumption (mainly evaporation) compared to 2010. The bulk of the growth will take place before 2050, in developing countries.
Remember that we are projecting demand. Final water use depends on the local and timely availability of fresh water. For the cooling of some types of electrical power plants and industrial processes, the water temperature can’t be too either. Regardless of all these details, projected demand serves as an indication of how vulnerable a sector could be to water shortages.
Can efficiency save us?
One way to reduce the risk of future water shortages is to need less water for the same activities. Households can use waterless toilets, recycling showers (which also save energy), less thirsty garden plants, and wash their car less often. Electrical power plants can be built with evaporative cooling or even air cooling systems. Industrial processes are very diverse, but their water could be recycled more often and in some cases be eliminated completely (e.g. Dyecoo, 2015). In the model we average and aggregate all such changes and make educated guesses about the time it would take for these efficiency improvements to be applied at a large scale.
For more details, read my first research publication (Bijl et al., 2016)! (free download until 10 November 2015 with this link: http://authors.elsevier.com/a/1Rl2a5Ce0rKQk9)
- Bijl, D.L., Bogaart, P.W., Kram, T., de Vries, B.J.M., van Vuuren, D.P., 2016. Long-term water demand for electricity, industry and households. Environ. Sci. Policy 55, 75–86. doi:10.1016/j.envsci.2015.09.005
- Bondeau, A., Smith, P.C., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W., Gerten, D., Lotze-Campen, H., MüLler, C., Reichstein, M., Smith, B., 2007. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob. Change Biol. 13, 679–706. doi:10.1111/j.1365-2486.2006.01305.x
- Dyecoo, 2015. A breakthrough in textile dyeing [WWW Document]. URL http://www.dyecoo.com/ (accessed 10.21.15).
- OECD, 2012. OECD Environmental Outlook to 2050: The Consequences of Inaction. OECD.
- PBL, 2014. Integrated assessment of global environmental change with IMAGE 3.0: model description and policy applications. PBL Netherlands Environmental Assessment Agency, The Hague.
- UNEP, 2012. Global Environment Outlook 5: Environment for the future we want. United Nations Environment Programme.
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About the author
David Bijl has been working as PhD candidate at Utrecht University, Faculty of Geosciences, since March 2013. With a BSc in Mathematics and MSc in Policy Analysis, he has a very broad view on complex transdisciplinary issues such as Climate Change, and the ability to investigate these further using computer models. Currently David is building models for long-term worldwide demand for Food, Water and Energy and the links between these. (university profile, linkedin, twitter)