Climate and human development impacts on municipal water demand: A spatially-explicit global modeling framework

Municipal water systems provide crucial services for human well-being, and will undergo a major transformation this century following global technological, socioeconomic and environmental changes. Future demand scenarios integrating these drivers over multi-decadal planning horizons are needed to de...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2016-11, Vol.85, p.266-278
Hauptverfasser: Parkinson, Simon C., Johnson, Nils, Rao, Narasimha D., Jones, Bryan, van Vliet, Michelle T.H., Fricko, Oliver, Djilali, Ned, Riahi, Keywan, Flörke, Martina
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Sprache:eng
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Zusammenfassung:Municipal water systems provide crucial services for human well-being, and will undergo a major transformation this century following global technological, socioeconomic and environmental changes. Future demand scenarios integrating these drivers over multi-decadal planning horizons are needed to develop effective adaptation strategies. This paper presents a new long-term scenario modeling framework that projects future daily municipal water demand at a 1/8° global spatial resolution. The methodology incorporates improved representations of important demand drivers such as urbanization and climate change. The framework is applied across multiple future socioeconomic and climate scenarios to explore municipal water demand uncertainties over the 21st century. The scenario analysis reveals that achieving a low-carbon development pathway can potentially reduce global municipal water demands in 2060 by 2–4%, although the timing and scale of impacts vary significantly with geographic location. •Future global municipal water demand scenarios generated for coupled RCP-SSP pathways.•Integration of climate and socioeconomic drivers to downscale long-term scenarios to 1/8°.•Climate change impacts to annual global demand in 2060s ranges from 2 to 4%.•Mapped climate change impacts to peak daily demand in 2060s range from 0 to 12%.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2016.08.002