Multivariate statistical analysis and geospatial approach for evaluating hydro‑geochemical characteristics of meltwater from Shaune Garang glacier, Himachal Pradesh, India

Ramesh Kumar, Rajesh Kumar* (Corresponding Author), Anshuman Bhardwaj, Atar Singh, Shaktiman Singh, Anupma Kumari, Ravindra Kumar Sinha

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


The study focuses on the hydro-geochemistry of Shaune Garang glacier’s meltwater concerning glacial geomorphology. Seventy-nine water samples (53 in 2016 and 26 in 2017) of ablation season were analysed. The cations were dominant in the order Ca2+ > Mg2+ > Na+ > K+, and the anions in the order HCO3− > SO42− > Cl− > NO3−. The result demonstrated that HCO3− were the abundant ions, accounting for 41.03 and 34.84% of the total ionic budget (TZ). The high ionic proportions of (Ca2+ + Mg2+) versus TZ+ and (Ca2+ + Mg2+) versus (Na+ + K+) were identified as the primary factors influencing dissolved ion chemistry in meltwater. Piper diagram shows that Ca2+–HCO3– type water is the most common, followed by Mg2+–HCO3–. In addition, a remote sensing approach has been used to find the possible source of the chemical constituents in the meltwater. The catchment geology has been mapped on various scales, including diverse rocks and unconsolidated surface materials containing “quartz and carbonate minerals”. Layered silicates (LS) and “hydroxyl-bearing minerals” are not as common as they used to be, but their availability varies greatly in the area where they are found. The distribution of LS minerals within the catchment are majorly found at lower altitudes, which implies the weathering mechanism due to the interaction of meltwater and parental rock. Multivariate analysis revealed that CO3 and SiO2 weathering, sulphate dissolution, and pyrite oxidation dominate dissolved ion concentrations. Chemometric analysis of meltwater hydro-geochemistry through principal component analysis explains 72.1% of the total variance of four PCs. PCs 1, 2, 3, and 4 explain 39.21%, 12.91%, 10.24%, and 9.74% of variance, respectively, in 2016. Similarly, in 2017, four PCs explain 69.91% of the total variance. PC 1, 2, 3, and 4 can explain 26.62%, 20.12%, 12.64%, and 10.52% of variance.
Original languageEnglish
Number of pages17
JournalActa Geophysica
Early online date11 Jul 2022
Publication statusPublished - 2022

Bibliographical note

The present support of the Department of Science and Technology as a research project (DST/CCP/NHC/159/2018(G)) became instrumental in utilizing the human resources for the analysis of the results. The financial support of the USAID project (CHARIS) for carrying out fieldwork is thankfully acknowledged. The analysis is made at the DST supported FIST Lab in the Department of Environmental Science, Central University of Rajasthan. The support is thankfully acknowledged. We would like to thank reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions which helped us to improve the quality of the manuscript.


  • Hydro-geochemistry
  • Geological mapping
  • Chemometric analysis
  • Shaune Garang glacier
  • Hydroxyl-bearing minerals


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