Skip to Main content Skip to Navigation
Journal articles

Use of gaseous tracers (CFCs and SF6) and transit-time distribution spectrum to validate a shallow groundwater transport model

Abstract : Catchment-scale solute transport models constitute potentially powerful tools of water resources management for predicting the evolution of water quality in response to land use modifications. Validation of the models remains a crucial step in order to get reliable prediction. However, pertinent data for the validation step are lacking. When catchment solute transport models are applied to shallow groundwater catchments, catchment-scale model validation relies on the validation of the groundwater solute transport model. Here we studied the interests of two approaches for groundwater solute transport model validation: the use of (i) gaseous atmospheric tracers and (ii) of spectral properties of transit time distributions derived from tracer concentration time series of rainfall and stream base-flow. The Kervidy-Naizin catchment, a 5 km2 catchment in Western France was chosen as case application. Three simulations with a shallow groundwater transport model were performed using three sets of effective porosity, respectively. We then investigated the ability of four gaseous tracers (CFC-11, CFC-12, CFC- 113 and SF6) and transit time distribution spectra to identify the most realistic simulations. The three simulations led to mean transit times that varied over a wide range of values, from 1.2 to 12.1 yr. Simulated groundwater mixing ratio differences for the three simulations did not exceed 5% for CFC-11, regardless of the groundwater location. The values of the SF6, CFC-12 and CFC-113 mixing ratio differences between the two simulations that contained the two shortest mean transit times were within expected measurement error of the tracer concentrations, regardless of the groundwater location. In contrast, the mixing ratio differences between the two simulations with the shortest mean transit times and the simulation containing the largest one exceeded 28% at all groundwater locations for SF6 and 9% in groundwater discharging into the stream for CFC-12 and CFC-113. The spectra of the three simulated transit time distributions do not match the transit time distribution spectrum derived from chloride concentration time series. So these results show that transit time distribution spectrum, and in much less extend SF6, CFC-12 and CFC-113 mixing ratios are sensitive enough to effective porosity values to be used as validation variables in shallow groundwater transport modelling. Transit time distribution spectrum constitutes an integrative variable able to discriminate between shallow groundwater transport simulations leading to very close mean transit times. In the present work, the discrepancy between the simulated spectra and the spectrum derived from the chloride concentration may come from other catchment processes than groundwater transport process, or from a wrong modelling of the groundwater transport process. Globally, deriving reliable transit time distribution spectrum requires high-frequency and extensive time series of a conservative tracer measured in stream water and rainfall, which is not straightforward to collect. The low sensitivity of simulated CFC-11 tracer mixing ratios to simulated groundwater transit times, and thus to model parameters, constituted a shortcoming to use it as a validation variable of groundwater solute transport models.
Document type :
Journal articles
Complete list of metadatas

https://hal-insu.archives-ouvertes.fr/insu-00811817
Contributor : Isabelle Dubigeon <>
Submitted on : Thursday, April 11, 2013 - 10:43:06 AM
Last modification on : Wednesday, September 16, 2020 - 5:08:15 PM

Identifiers

Citation

Jérôme Molenat, Chantal Gascuel-Odoux, Luc Aquilina, Laurent Ruiz. Use of gaseous tracers (CFCs and SF6) and transit-time distribution spectrum to validate a shallow groundwater transport model. Journal of Hydrology, Elsevier, 2013, 480, pp.1-9. ⟨10.1016/j.jhydrol.2012.11.043⟩. ⟨insu-00811817⟩

Share

Metrics

Record views

324