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

Abstract

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.