Bayesian hydrograph separation in a minimally gauged alpine catchment
Published in Journal of Hydrology, 2019
This study examines the question of how much information one can extract from a tracer-based hydrograph separation in a remote and minimally gaged alpine catchment in Chile. We combine PCA-based endmember mixing analysis to identify the sources of flow contribution to the Diguillín River with a hierarchical Bayesian mixing model to integrate spatial and temporal variability in endmember concentration and quantify the source contributions to streamflow over time.’
Recommended citation: Markovich, K.H., Dahlke, H.E., Arumi, J.L., Maxwell R.M., and Fogg. G.E., 2019. Bayesian hydrograph separation in a minimally gauged alpine catchment, Journal of Hydrology, 575, 1288–1300. https://doi.org/10.1016/j.jhydrol.2019.06.014.
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