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TitleStochastic correlated hydraulic conductivity tensor calibration using gradual deformation
AuthorBenoit, N; Marcotte, D; Molson, J W
SourceJournal of Hydrology vol. 594, 125880, 2020 p. 1-14,
Alt SeriesNatural Resources Canada, Contribution Series 20190320
PublisherElsevier B.V.
Mediapaper; on-line; digital
File formatpdf; html
AreaSimcoe County; Bethesda
Lat/Long WENS -79.3175 -79.2961 43.9833 43.9717
Subjectshydrogeology; Nature and Environment; Science and Technology; groundwater flow; hydraulic analyses; hydraulic conductivity; hydraulic head; computer simulations; models; water wells; recharge rates; statistical analyses; PEST; Water supply
Illustrationsflow diagrams; 3-D diagrams; plots; location maps; cross-sections; 3-D models; tables; bar graphs; geoscientific sketch maps; models; profiles
ProgramGroundwater Geoscience Aquifer Assessment & support to mapping
Released2020 12 25
AbstractQuasi-point hydraulic properties (K) measured locally under laboratory or field conditions need to be upscaled to block scale K-tensors for use in flow simulator. The upscaled model also needs to be calibrated to hydraulic head observations. The calibration must preserve spatial covariance, cross-covariance and non-linear relations between tensor components. We apply a new upscaling method that allows to compute and model the covariance between bloc K-tensor components. We use gradual deformation method for calibration of simulated K-tensor fields to measured head data. Our method incorporates a new bivariate transform that preserves the non-linear relations between K-tensor components. The ensemble of calibrated realizations allows quantification of uncertainty of groundwater flow models. A comparison with PEST on a test case shows that our method calibrates better to measured heads than PEST, provides more realistic K-tensors and results in larger capture zones.
Summary(Plain Language Summary, not published)
This paper describes the development of an efficient calibration approach of simulated K-tensors in a stochastic framework for hydrogeological modelling and its application within the Innisfil Creek Watershed in Ontario. The focus of this study is to explore and assess the uncertainty related to the K-tensor heterogeneities for regional groundwater flow models. The findings point out six challenging steps involved in the process of stochastic calibration of equivalent groundwater flow models. To illustrate the capacity of the suggested workflow, it was tested and validated in a case study in Southern Ontario. Current results point out the method efficiency in assessing the K-tensor uncertainties and their impact on the regional groundwater flow models. This research was carried out within the Groundwater Geoscience Program - Geological Survey of Canada in collaboration with Polytechnique Montréal and Université Laval.

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