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Data-based modelling of runoff and chemical tracer concentrations in the Haute-Mentue research catchment (Switzerland)

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<mark>Journal publication date</mark>30/08/2005
<mark>Journal</mark>Hydrological Processes
Issue number13
Volume19
Number of pages17
Pages (from-to)2557-2573
Publication StatusPublished
<mark>Original language</mark>English

Abstract

This paper presents a model for simulating discharge as well as chemical tracer concentration (silica and calcium) in stream flow for the Haute-Mentue research basin (Switzerland). The model structure is based on a parameterization of the three components (acid soil, AS; direct precipitation, DP; deep groundwater, GW) of a hydrochemical mixing model. Each component is modelled through an identical structure consisting of a non-linear gain, expressed by a three-parameter logistic function, and a linear transfer function with two reservoirs (fast/slow) in parallel having a constant partition between them. The model is applied on an information-rich 5-week data set. Extensive Monte Carlo realizations (more than two billion models) have identified a representative sample of behavioural models able to satisfy quite stringent fit criteria on both discharges and tracers. A descriptive statistical analysis of the behavioural. parameter sets reveals significant differences between the components. In particular, the AS contribution is activated for higher catchment storages and shows a steep, almost threshold-like, increase. The partition coefficient (fast/ total) for the three components is ordered as DP>AS>GW. The fast constants of the three components have a similar order of magnitude, but also show DP>AS>GW. The slow time constant of the GW component is almost an order of magnitude higher than that of DP and AS. The latter are of similar magnitude and generate a highly non-linear interflow component.