This data set includes the average concentrations of chemical species (Na+, K+, Mg2+, Ca2+ and TDS) in meltwater runoff draining 77 glaciers worldwide, annual glacial runoff from eight mountain ranges in Asia, and the mineral compositions of glacial deposits in some typical glacial catchments within Asia. This data set comes from the field monitoring of 19 glaciers in Asia by the data set provider, the previous published data worldwide, and the data shared by the authors of published papers. This data set can be used to evaluate the impact of climate warming on glacier erosion process and chemical weathering process, and the impact of glacier melt caused by climate warming on downstream ecosystems and element cycles.

File naming and required software

File name: Global glacier hydrochemical dataset. Data reading method: open excel file to read directly.

Data Citations Data citation guideline What's data citation?

Cite as:

Li, X. (2021). Global glacier meltwater hydrochemical data set. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Glacio.tpdc.271705. CSTR: 18406.11.Glacio.tpdc.271705. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Li, X., Wang, N., Ding, Y. et al. (2022). Globally elevated chemical weathering rates beneath glaciers. Nature Communications, 13, 407. https://doi.org/10.1038/s41467-022-28032-1.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

Open Foundation of State Key Laboratory of Frozen Soil Engineering (No:SKLFSE201901)

National Natural Science Foundation of 737 China (No:42171053)

Second Tibetan Plateau Scientific Expedition Program

National Natural Science Foundation of China (91647102) (No:91647102)

National Natural Science Foundation of 737 China (No:41671053)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)