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Hydraulics and Turbidity Generation in the Milandre Cave (Switzerland)

2021, Vuilleumier, Cécile, Jeannin, Pierre-Yves, Marc Hessenauer, Perrochet, Pierre

AbstractKarst aquifers may convey significant sediment fluxes, as displayed by the intense turbidity peaks commonly observed at karst springs. The understanding of the origin of the suspended solids discharged at springs is key in assessing spring vulnerability and securing drinking water quality. The mechanisms for turbidity generation and sediment transport in karst are however difficult to investigate because of the general lack of access to the karst conduits. These processes have been examined in the Milandre Cave, which hosts a karst drain of regional importance, for more than 10 years by means of turbidity monitoring both inside and at the outlets of this karst system. Additionally, the composition of the suspended load (particle‐size distribution and Escherichia coli content) has been monitored over the course of a flood event. These data are compared against a numerical simulation of the mean boundary shear stress inside the conduit network. The following conceptual model for sediment transport through the system is derived: during minor flood events, most of the turbidity comes from underground sediment remobilization, while during medium to intense flood events, soil‐derived turbidity also reaches the spring. Hydraulics in the epiphreatic zone is tightly linked with autochthonous turbidity generation (mostly during the flooding and the flushing of conduits). In comparison, allochthonous turbidity is associated with finer particles, higher E. coli, and higher UV fluorescence. This improves the overall understanding of turbidity generation and could help the monitoring and forecast of pollution events at drinking water supplies.

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Statistical metrics for the characterization of karst network geometry and topology

2021-1, Collon, Pauline, Bernasconi, David, Vuilleumier, Cécile, Renard, Philippe

The authors regret that six of the statistical metrics published in Tables 2, 5, and 6 in Collon et al. (2017) are incorrect. The errors were discovered while coding and testing the open-source python package Karstnet freely available at https://github.com/karstnet/karstnet. The errors are smaller than 2%, except for the correlation of vertex degree, and they do not affect the general conclusions of the paper. The corrected tables are provided in this corrigendum, and we summarize below the changes