Understanding and predicting the propagation, deposition and re-suspension of suspended particulate matter (SPM) in river networks is important for managing water resources, ecological habitat, pollution, navigation, hydropower generation, reservoir sedimentation, etc. Observational data are scarce and costly, and there is little feedback on the efficiency of numerical simulation tools for compensating the lack of data on a river scale of several hundreds of kilometres.

The objective of this article is to investigate the major issues associated with the calibration of the pollutant dispersion in 1-D hydraulic models applied to river networks, especially large, complex, artificialized ones where ecological and socio-economical threats are important. Such issues are illustrated and discussed using the results of five fluorescent tracer experiments conducted in contrasted open-channel systems, ranging from a simple trapezoidal canal to a more complex river network. Experimental dispersion values were quantified using both the change of moment method and a simple fit-by-eye procedure for eight river reaches with homogeneous hydraulic conditions and an achieved tracer mixing and dispersive equilibrium. Since dispersion coefficient values depend on the assumed dispersion model, ideally they should be calibrated using the same model in which they are to be used, as was done in this study. We also derived concurrent longitudinal dispersion values using the velocity field measured by hydro-acoustic profilers (ADCP), which appears as a promising and cost-efficient technique for documenting dispersion in large river systems. It appears that the formulae for which the fit was mainly based on the cross-sectional aspect ratio are generally more appropriate for field data than those which are sensitive to the velocity to shear velocity ratio. The interpretation of complex dispersion and mixing processes, along with the selection of relevant dispersion coefficient predictors are key to minimizing errors in the numerical simulation of pollution dynamics in river networks.

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