Future global water scarcity including quality under climate and socioeconomic change

Inadequate availability of clean water presents systemic risks to human health, food production, energy generation and ecosystem functioning. While future alterations to water demands and availability are widely projected to exacerbate water scarcity, the impact of changing water quality is largely unknown. Leveraging a newly-developed global surface water quality model (DynQual¹) which is coupled to a global hydrological model (PCR-GLOBWB2), we make the first projections of future global water scarcity including both water quantity and quality aspects.

We consider three combined RCP-SSP scenarios (SSP1-RCP2.6, SSP3-RCP7.0 and SSP5-RCP8.5), each of which simulated with bias-corrected CMIP6 climate input from five GCMs provided within ISIMIP3b, to encompass a range of possible future conditions and to capture uncertainty inherent in the climatological (GCM) projections. Simulated monthly sectoral water demands (domestic, industrial, livestock and irrigation), water availability (e.g. discharge) and water quality (total dissolved solids, biological oxygen demand and fecal coliform) for 2005-2100² are used as basis for quantifying clean water scarcity, which we express in terms of population exposure.

We find that 57% of the global population (~4 billion people) are currently exposed to clean water scarcity at least one month per year, increasing to 58 – 68% by the end of the century based on different plausible scenarios for climate change and socioeconomic development. Increases in exposure are largest in developing countries – particularly in Sub-Saharan Africa – driven by a combination of water quantity and quality issues. Strong reductions in both human water use and pollution are therefore necessary to minimise the impact of future water scarcity on humans and the environment.

 

References

¹ Jones, E.R., M.F.P. Bierkens, N. Wanders, E.H. Sutanudjaja, L.P.H. van Beek,  M.T.H. van Vliet (2023), DynQual v1.0: A high-resolution global surface water quality model, Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023

² Jones, E.R., M.F.P. Bierkens, P.J.T.M. van Puijenbroek, L.P.H. van Beek, N. Wanders, E.H. Sutanudjaja, M.T.H. van Vliet (2023) Sub-Saharan Africa will increasingly become the dominant hotspot of surface water pollution, Nature Water, 1, 602–613, https://doi.org/10.1038/s44221-023-00105-5