A framework for parameter estimation using sharp-interface seawater intrusion models

Cécile Coulon* (Corresponding Author), Alexandre Pryet, Jean-Michel Lemieux, Ble Jean Fidele Yrro, Abderrezak Bouchedda, Erwan Gloaguen, Jean-Christophe Comte, J. Christian Dupuis, Olivier Banton

*Corresponding author for this work

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18 Citations (Scopus)
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Sharp-interface seawater intrusion models present shorter run times than variable density codes, which makes them practical for regional, decision-support groundwater modeling. Although parameter estimation and uncertainty analyses are essential steps for model-based decision making, their implementation in seawater intrusion models has remained limited. Few guidelines are available and it is unclear which observations should be used, what processing they require and what weighting strategy should be used. A framework has been developed for parameter estimation using a regional sharp-interface decision-support model applied to a real-world example in the Magdalen Islands (Quebec, Canada). This framework included the assimilation of head observations collected from shallow wells, deep open wells and pumping wells, as well as freshwater-seawater interface observations derived from deep open wells, TDEM (time-domain electromagnetic) and ERT (electrical resistivity tomography) geophysical surveys. A model was developed using MODFLOW-SWI2 in which fast model run times allowed the estimation of numerous parameters, including a heterogeneous hydraulic conductivity field with pilot points. Following parameter estimation with PEST, the uncertainty of several model forecasts, i.e. the volume of freshwater and the interface elevation near municipal pumping wells, was examined with the first-order second moment (FOSM) approach and a data worth analysis was carried out. While the observations presented a low signal-to-noise ratio, parameter estimation was effective to reduce the uncertainty of model forecasts. Interface observations, and particularly geophysical observations, were most useful to reduce predictive uncertainties. Head and interface observations from deep open wells were biased and could not be suitably reproduced by the model. The framework developed here is relatively straightforward and could be implemented more systematically. The study also provides recommendations to guide future data collection strategies in coastal aquifers.
Original languageEnglish
Article number126509
Number of pages16
JournalJournal of Hydrology
Publication statusPublished - 1 Sept 2021

Bibliographical note

Funding : This work was supported by Quebec’s Ministère de l'Environnement et de la Lutte contre les changements climatiques (MELCC) [project « Acquisition de connaissances sur les eaux souterraines dans la région des Îles-de-la-Madeleine » (Groundwater characterization project in the Magdalen Islands region)]; and the Fonds québécois de la recherche sur la nature et les technologies (FRQNT) [International internship program accessed through CentrEau, the Quebec Water Research Center]. The authors would like to thank the Municipality of Les Îles-de-la-Madeleine for providing pumping datasets and information on current and historical groundwater management. They would also like to thank the team at Université Laval working on the Magdalen Islands project, for their help acquiring datasets and for field logistics, John Molson, for proofreading, and finally the two anonymous reviewers for their valuable comments. The authors would also like to thank Vincent Post for discussions on deep open boreholes, and Francesca Lotti and John Doherty for discussions on seawater intrusion modeling and data assimilation. J-C Comte and O Banton acknowledge the financial support from the Fonds d'Action Québécois pour le Développement Durable for the ERT data collection, undertaken as part of the Madelin'Eau consortium (Ageos-Enviro'Puits-Hydriad), and further thank the Municipality of Les Îles-de-la-Madeleine for fieldwork logistical and technical support.


  • Seawater Intrusion
  • Sharp Interface
  • Parameter Estimation
  • Uncertainty Analysis
  • Data Worth
  • Geophysics


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