Articles | Volume 7, issue 2
https://doi.org/10.5194/esurf-7-515-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-7-515-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jun 2019
Research article |
| 04 Jun 2019
| 04 Jun 2019
An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland
IRD, Toulouse, 31400, France
Laboratoire GET, CNRS, IRD, UPS, OMP, Toulouse, 31400, France
Benoît Camenen
Irstea, UR RiverLy, Lyon-Villeurbanne, 69625 Villeurbanne, France
Jérôme Le Coz
Irstea, UR RiverLy, Lyon-Villeurbanne, 69625 Villeurbanne, France
Philippe Vauchel
IRD, Toulouse, 31400, France
Laboratoire GET, CNRS, IRD, UPS, OMP, Toulouse, 31400, France
Jean-Loup Guyot
IRD, Toulouse, 31400, France
Laboratoire GET, CNRS, IRD, UPS, OMP, Toulouse, 31400, France
Waldo Lavado
SENAMHI, Lima, Lima 11, Peru
Jorge Carranza
SENAMHI, Lima, Lima 11, Peru
Marco A. Paredes
SENAMHI, Iquitos, Peru
Jhonatan J. Pérez Arévalo
SENAMHI, Iquitos, Peru
Nore Arévalo
Facultad de Ingeniería Agrícola, UNALM, La Molina, Lima 12, Peru
Raul Espinoza Villar
Facultad de Ingeniería Agrícola, UNALM, La Molina, Lima 12, Peru
IGP, Ate, Lima 15012, Peru
Frédéric Julien
Laboratoire ECOLAB, CNRS, INPT, UPS, Toulouse, 31400, France
Jean-Michel Martinez
IRD, Toulouse, 31400, France
Laboratoire GET, CNRS, IRD, UPS, OMP, Toulouse, 31400, France
Data sets
Hydro-sedimentary data collected between 2010 and 2017 within the framework of the Critical Zone Observatory HYBAM in the Amazonian foreland of Peru W. Santini, J.-M. Martinez, P. Vauchel, J.-L. Guyot, G. Cochonneau, W. Lavado, J. Carranza, M. A. Paredes, J. Pérez Arévalo, R. Espinoza-Villar, N. Arévalo, and K. Arévalo https://doi.org/10.6096/DV/CBUWTR
Short summary
A simple model is proposed to improve the sediment concentration monitoring in the large rivers of the Peruvian Amazon from an index concentration sampled in the flow. This powerful tool for optimizing the concentration sampling would allow for detailed uncertainty analysis on the sediment fluxes. It could be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.
A simple model is proposed to improve the sediment concentration monitoring in the large rivers...
