Towards a global water scarcity risk assessment framework: incorporation of probability distributions and hydro-climatic variability

• Published in: Environmental research letters Vol. 11; no. 2; pp. 24006 - 24017
• Main Authors: Veldkamp, T I E, Wada, Y, Aerts, J C J H, Ward, P J
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01-02-2016
• Subjects: Climate change; Climate variability; Environmental impact; Fresh water; Freshwater resources; global hydrological modeling; Population growth; Population studies; probabilistic methods; Probability distribution functions; Risk assessment; Risk levels; socioeconomic developments; Socioeconomic factors; Socioeconomics; Statistical analysis; Water resources; Water scarcity
• ISSN: 1748-9326; 1748-9326
• DOI: 10.1088/1748-9326/11/2/024006

Changing hydro-climatic and socioeconomic conditions increasingly put pressure on fresh water resources and are expected to aggravate water scarcity conditions towards the future. Despite numerous calls for risk-based water scarcity assessments, a global-scale framework that includes UNISDR's definition of risk does not yet exist. This study provides a first step towards such a risk-based assessment, applying a Gamma distribution to estimate water scarcity conditions at the global scale under historic and future conditions, using multiple climate change and population growth scenarios. Our study highlights that water scarcity risk, expressed in terms of expected annual exposed population, increases given all future scenarios, up to >56.2% of the global population in 2080. Looking at the drivers of risk, we find that population growth outweigh the impacts of climate change at global and regional scales. Using a risk-based method to assess water scarcity, we show the results to be less sensitive than traditional water scarcity assessments to the use of fixed threshold to represent different levels of water scarcity. This becomes especially important when moving from global to local scales, whereby deviations increase up to 50% of estimated risk levels.