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        Assessment of regional threats to human water security adopting the global framework: A case study in South Korea

        Kim, Yeonjoo,Kong, Inhye,Park, Hyesun,Kim, Heey Jin,Kim, Ik Jae,Um, Myoung-Jin,Green, Pamela A.,,,smarty, Charles J. Elsevier 2018 Science of the Total Environment Vol.637 No.-

        <P><B>Abstract</B></P> <P>Water resources have been threatened by climate change, increasing population, land cover changes in watersheds, urban expansion, and intensive use of freshwater resources. Thus, it is critical to understand the sustainability and security of water resources. This study aims to understand how we can adequately and efficiently quantify water use sustainability at both regional and global scales with an indicator-based approach. A case study of South Korea was examined with the framework widely used to quantify global human water threats. We estimated the human water threat with both global and local datasets, showing that the water security index using global data was adequately correlated with the index for regional data. However, particularly poor associations were found in the investment benefit factors. Furthermore, we examined several different aspects of the index with the local datasets as they have relatively high spatial and temporal resolution. For example, we used cropland percentage, population and moderate water use as surrogate indicators instead of employing the approximately 20 original indicators, and we presented a regression model that was able to capture the spatial variations from the original threat index to some extent. This finding implies that it would be possible to predict water security or sustainability using existing indicator datasets for future periods, although it would require regionally developed relationships between water security and such indicators.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Strong correlations were found between global and regional indicators except for investment benefits. </LI> <LI> Three key indicators represent the majority of the spatial variation in incident threat. </LI> <LI> R25° is the most appropriate spatial resolution for regional analysis. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

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