Building Regional Water-Use Scenarios Consistent with Global Shared Socioeconomic Pathways View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-03

AUTHORS

Mingtian Yao, Sylvia Tramberend, Pavel Kabat, Ronald W.A. Hutjes, Saskia E. Werners

ABSTRACT

Water use projections are crucial to safeguard sustainable access to freshwater in the future. The Water Futures and Solution initiative (WFaS) has developed a set of global water-use scenarios consistent with the recent Assessment Report framework of the Intergovernmental Panel on Climate Change, notably the Shared Socioeconomic Pathways (SSPs), and applying a hydro-economic classification that links a socioeconomic dimension with hydrologic complexity. Here we present regional water use projections for the Pearl River Delta (PRD) in China consistent with the WFaS global assessment. Using two different downscaling techniques for developing regional water-use scenarios based on the national assumptions made for China in the WFaS assessment, we investigate PRD’s water-use projections. The findings indicate significant differences in the PRD’s regional development trends compared to China’s national SSP. The regionalized scenarios project lower water use because of the PRD’s lower share of the manufacturing sector in total Gross Domestic Product (GDP) and higher rates of technological improvement, compared to national development trend assumptions. Nevertheless, hydrological challenges remain for the PRD. Its total water use would still increase by up to 54% in 2030 under the regionalized scenarios. Although uncertainties related to scarce data remain, we provide a scientifically sound and feasible method to generate regional scenarios that can capture the regional sectorial water uses development as well as being consistent with national water-use scenarios developed by global assessment. More... »

PAGES

15-31

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40710-016-0203-x

DOI

http://dx.doi.org/10.1007/s40710-016-0203-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1007718347


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