Evaluation of temporal concentration profiles for ungauged rivers following pollution incidents

Abstract

In order to predict the impact of pollution incidents on rivers, it is necessary to predict the dispersion coefficient and the flow velocity corresponding to the discharge in the river of interest. This paper explores methods for doing this, particularly with a view to applications on ungauged rivers, i.e. those for which little hydraulic or morphometric data are available. An approach based on neural networks, trained on a wide-ranging database of optimized parameter values from tracer experiments and corresponding physical variables assembled for American and European rivers, is proposed. Tests using independent cases showed that the neural networks generally gave more reliable parameter estimates than a second-order polynomial regression approach. The quality of predictions of temporal concentration profiles was heavily influenced by the accuracy of the velocity prediction.

Citation Piotrowski, A. P., Napiorkowski, J. J., Rowinski, P. M. & Wallis, S. G. (2011) Evaluation of temporal concentration profiles for ungauged rivers following pollution incidents. Hydrol. Sci. J. 56(5), 883–894.