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A bibliometric analysis on the performance and underlying dynamic patterns of water security research

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Abstract

Water security has been an emerging and rapidly developing new research area. A bibiometric study is very helpful. By sufficiently analyzing the data from all related items between 1998 and 2015 obtained in Web of Science databases, we found the publications in overall scopes, various subjects, countries or journals all matched logistic growths with large value of K (maximum possible publication) and small value of b (related to growth rate). The most promising subjects were environmental sciences and water resources, and Zipf’s law of publication distribution in all subjects was satisfied. USA owned maximum publications, whereas Canada had a more latent capacity. USA and UK dominated the collaborative network. With “Water Science and Technology” as the most active journal, the Bradford’s scattering distribution of publications in all journals was elucidated. The productivity of the authors showed a rough Lotka’s distribution. Besides “water security” and “water safety”, “climate change” was the hottest keyword. The co-words patterns revealed the wide mutual influences between water security and climate change. No significant aging for the highly cited publications implied the past, future and vitality of rapidly-developing water security research. Our findings drawn from a suite of bibliometric indicators are instructive for the future studies of researchers, the strategy/policy of countries and the efforts of publishing organizations, altogether prompting the global water security research.

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Acknowledgments

The paper was supported by National Natural Science Foundation of China (Grant No. 71071110).

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  1. School of Environmental Science and Engineering, Tianjin University, Tianjin, 300354, China

    Cuiqian Huai & Lihe Chai

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  1. Cuiqian Huai
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  2. Lihe Chai
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Correspondence to Lihe Chai.

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Huai, C., Chai, L. A bibliometric analysis on the performance and underlying dynamic patterns of water security research. Scientometrics 108, 1531–1551 (2016). https://doi.org/10.1007/s11192-016-2019-x

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