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Improving calibration of groundwater flow models using headwater streamflow intermittence
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  • Ronan Abhervé,
  • Clément Roques,
  • Jean-Raynald de Dreuzy,
  • T Datry ,
  • Philip Brunner,
  • Laurent Longuevergne,
  • Luc Aquilina
Ronan Abhervé
Geosciences Rennes

Corresponding Author:[email protected]

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Clément Roques
Universite de Neuchatel Centre d'hydrogeologie et de geothermie
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Jean-Raynald de Dreuzy
Geosciences Rennes
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T Datry
Institut National de Recherche pour l'Agriculture l'Alimentation et l'Environnement Centre Lyon-Grenoble Auvergne-Rhone-Alpes
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Philip Brunner
Universite de Neuchatel Centre d'hydrogeologie et de geothermie
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Laurent Longuevergne
Geosciences Rennes
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Luc Aquilina
Geosciences Rennes
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Abstract

Non-perennial streams play a crucial role in ecological communities. However, the key parameters and processes involved in stream intermittence remain poorly understood. While climate conditions, geology and land use are well identified, assessing and modeling the groundwater controls on streamflow intermittence remains a challenge. In this study, we explore new opportunities to calibrate process-based 3D groundwater flow models designed to simulate stream intermittence in groundwater-fed headwaters. Streamflow measurements and stream network maps are jointly considered to constrain aquifer’s effective hydraulic properties in hydrogeological models. The simulations were then validated using visual observations presence/absence of water, provided by a national monitoring network in France (ONDE). We tested the methodology on two pilot catchments with unconfined shallow crystalline aquifer, the Canut and Nançon (Brittany, France). We found that streamflow and expansion/contraction dynamics of the stream network are both necessary to calibrate simultaneously hydraulic conductivity K and porosity θ with low uncertainties. Conversely, calibration resulted in accurate prediction of stream intermittence - in terms of flow and spatial extent. For the two catchments studied, the Canut and Nançon, hydraulic conductivity is close reaching 1.5 x 10 -5 m/s and 4.5 x 10 -5 m/s respectively. However, they differ more by their storage capacity, with porosity estimated at 0.1 % and 2.2 % respectively. Lower storage capacities lead to higher fluctuations in the water table, increasing the proportion of intermittent streams and reducing perennial flow. This new modeling framework allowing to predict streamflow intermittence in headwaters can be deployed to improve our understanding of groundwater controls in different geomorphological, geological, and climatic contexts. It will benefit from advances in remote sensing and crowdsourcing approaches that generate new observed data products with high spatial and temporal resolution.
24 Feb 2024Review(s) Completed, Editorial Evaluation Pending
21 Mar 20241st Revision Received
28 Mar 2024Submission Checks Completed
28 Mar 2024Assigned to Editor
28 Mar 2024Reviewer(s) Assigned
28 Mar 2024Reviewer(s) Assigned
29 Apr 20242nd Revision Received
29 Apr 2024Reviewer(s) Assigned