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The impact of dam flushing event on dissolved trace elements concentrations: Coupling integrative passive sampling and discrete monitoring.

Sediments accumulation in reservoirs induces water storage capacities reduction and flood risks increases rendering dam flushing or dredging events compulsory for security reasons. Short transient events like dam flushing monitoring is still a great challenge because the suspended sediments and contaminants concentrations increases could occur over only few hours/days and cover tens of kilometres. Since 1942, 21 dam flushing events have been performed on the Upper Rhône River (from Lake Geneva in Switzerland to Lyon in France) in order to evacuate accumulated sediments behind the Verbois dam (Switzerland). We designed an original sampling strategy to assess the 2016 dam flushing event consequences on the spatio-temporal dynamics of dissolved trace elements concentration and to reveal how passive sampling monitoring (Diffusive Gradient in Thin films, DGT) could improve this evaluation. Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, Pb, As and Hg dissolved concentrations were monitored by discrete and passive sampling at 3 stations over 160 km downstream the Verbois dam. Since dissolved Fe, Cu, Cd, Cr, Pb, Zn and Hg concentrations did not show great variations during the flushing event, the DGT efficiency was not fully demonstrated for these elements. In contrast, a sharp increase of Mn, Ni, Co and As dissolved concentrations (up to 22 times) was recorded, resulting mainly from a release from resuspended sediment. The dissolved As increase was mainly caused by reduced arsenic (AsIII ) increase, even monitored 160 km downstream the Verbois dam. The DGT measurements were highly representative of trace elements concentrations and As speciation dynamics in comparison with discrete sampling. Although relatively high dispersion was highlighted for some elements DGT measurements during the flushing event, we showed that DGTs are robust and powerful time-integrative tools to monitor many trace elements more efficiently than discrete sampling during a short transient event on a large spatial scale.

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