EGU22-8455, updated on 21 Jun 2024
https://doi.org/10.5194/egusphere-egu22-8455
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

High-frequency, multi-elemental stream concentration timeseries as a tool for catchment flowpath identification

Nicolai Brekenfeld1, Ophélie Fovet1, Arnaud Blanchouin2, Laure Cordier3, Solenn Cotel4, Mikaël Faucheux1, Paul Floury5, Colin Fourtet4, Yannick Hamon1, Hocine Henine2, Patrice Petitjean6, Anne-Catherine Pierson-Wickman6, Marie-Claire Pierret4, and Jérôme Gaillardet3
Nicolai Brekenfeld et al.
  • 1INRAE, UMR SAS, Rennes, France
  • 2INRAE, UR HYCAR, Antony, France
  • 3IPGP, Paris, France
  • 4Université de Strasbourg, Strasbourg, France
  • 5Extralab, Paris, France
  • 6Université Rennes 1, Rennes, France

Stream water chemistry at catchment outlets is commonly used to infer the flowpaths of water through the catchment and to quantify the relative contributions of various flowpaths. High-frequency and multi-elemental timeseries could shed light on the dynamic activation/deactivation and the changing relative contributions of different flowpaths during storm events or diel cycles in summer. Here, we present multi-year, high-frequency (< 60 minutes) timeseries of the major cations and anions from the outlet of three small (0.8 – 40 km²) french catchments with contrasting land-use (forest, field crops and mixed farming-cropping productions). Instead of analysing the concentration dynamics of individual elements, we use elemental ratios in order to identify the contrasting temporal variations of different elements during storm events. We try to link the dynamics of the elemental ratios to specific flowpaths, constrained by the processes likely to modify the ratios. Then, we compare the inferred flowpath contributions with our perceptual understandings of the three catchments. These findings contribute to our understanding of dynamic flowpath activation in catchments and the value of high-frequency, multi-elemental stream concentration timeseries.

How to cite: Brekenfeld, N., Fovet, O., Blanchouin, A., Cordier, L., Cotel, S., Faucheux, M., Floury, P., Fourtet, C., Hamon, Y., Henine, H., Petitjean, P., Pierson-Wickman, A.-C., Pierret, M.-C., and Gaillardet, J.: High-frequency, multi-elemental stream concentration timeseries as a tool for catchment flowpath identification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8455, https://doi.org/10.5194/egusphere-egu22-8455, 2022.

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