TY - JOUR

T1 - Data-based modelling of runoff and chemical tracer concentrations in the Haute-Mentue research catchment (Switzerland)

AU - Iorgulescu, Ion

AU - Beven, K. J.

AU - Musy, A.

PY - 2005/8/30

Y1 - 2005/8/30

N2 - 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.

AB - 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.

KW - Chemical tracers

KW - Equifinality

KW - Haute-Mentue research basin (Switzerland)

KW - Monte Carlo simulations

KW - Rainfall-runoff modelling

KW - Transfer function model

U2 - 10.1002/hyp.5731

DO - 10.1002/hyp.5731

M3 - Journal article

AN - SCOPUS:24644462256

VL - 19

SP - 2557

EP - 2573

JO - Hydrological Processes

JF - Hydrological Processes

SN - 0885-6087

IS - 13

ER -