Uncertainty in Estimates of Global Water Use

estimates of agricultural water use

Water management by necessity relies heavily on quantitative information on water use, whether for a city, region, country, or the globe. But water-use data suffer from two issues. First, as discussed in Chapter 4 of the book, there are many different definitions of water use. Second, water-use estimates - whether derived from measurements or models - are just that: estimates, with significant uncertainties associated with them, even when (as in Figures 4-3 and 4-4), those uncertainties are ignored and the data are presented as simple points or lines. 

The figure to the left illustrates this uncertainty, and shows that estimates for consumptive water use in agriculture differ by about three-fold depending on the model and dataset used! Given that agriculture accounts for the vast majority of water use, this large range in estimates implies significant uncertainty about humanity’s impact on the global hydrologic cycle. 

The technical details: The Shiklomanov/AQUASTAT line is based on the same dataset as Figures 4-3 and 4-4, while references for the other sources are provided below. Each estimate is plotted against the midpoint year of the time period for which consumption was estimated. Gordon et al. (2005) and Rosa et al. (2020), which were presented as estimates of “current” water use, are plotted at five years before the publication date. All estimates except Shiklomanov/AQUASTAT and Hoekstra and Mekonnen (2012) do not include livestock watering. 

Citations

Gordon, L. J., W. Steffen, B. F. Jonsson, C. Folke, M. Falkenmark, and A. Johannessen (2005). “Human modification of global water vapor flows from the land surface.” Proceedings of the National Academy of Sciences of the United States of America 102(21): 7612-7617.DOI: 10.1073/pnas.0500208102.

Hanasaki, N., T. Inuzuka, S. Kanae, and T. Oki (2010). “An estimation of global virtual water flow and sources of water withdrawal for major crops and livestock products using a global hydrological model.” Journal of Hydrology 384(3-4): 232-244.DOI: 10.1016/j.jhydrol.2009.09.028.

Hoekstra, A. Y., and M. M. Mekonnen (2012). “The water footprint of humanity.” Proceedings of the National Academy of Sciences of the United States of America 109(9): 3232-3237.DOI: 10.1073/pnas.1109936109.

Jagermeyr, J., D. Gerten, J. Heinke, S. Schaphoff, M. Kummu, and W. Lucht (2015). “Water savings potentials of irrigation systems: global simulation of processes and linkages.” Hydrology and Earth System Sciences 19(7): 3073-3091.DOI: 10.5194/hess-19-3073-2015.

Rosa, L., D. D. Chiarelli, M. C. Rulli, J. Dell’Angelo, and P. D’Odorico (2020). “Global agricultural economic water scarcity.” Science Advances 6(18): 10.DOI: 10.1126/sciadv.aaz6031.

Siebert, S., and P. Döll (2010). “Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation.” Journal of Hydrology 384(3-4): 198-217.DOI: 10.1016/j.jhydrol.2009.07.031.

Wada, Y., L. P. H. van Beek, and M. F. P. Bierkens (2011). “Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability.” Hydrol. Earth Syst. Sci. 15(12): 3785-3808.DOI: 10.5194/hess-15-3785-2011.