An Approach to Include Hydrogeologic Barriers With Unknown Geometric Properties in Groundwater Model Inversions

S. K. Marshall, P. G. Cook, C. T. Simmons, L. F. Konikow, S. Dogramaci

Research output: Contribution to journalArticlepeer-review

Abstract

Hydrogeological barriers can significantly impact groundwater model predictions. They are, however, often excluded from, or misrepresented in, groundwater models if their presence is unknown or their properties are poorly constrained. Here we show that sharp barriers can be included in groundwater model inversion, even where their presence is uncertain. We describe an approach utilizing "phantom structures"—randomly located, linear groups of model cells assigned a unique hydraulic conductivity value—to improve identifiability of barriers. Algorithmic parameter estimation using model-independent parameter estimation code (PEST) is implemented to determine model structures that best match the hydraulic head and groundwater age observation data from a hypothetical aquifer. Our results show that for a series of case studies, this method was successful in inferring the appropriate location and properties of hydrogeological barriers, when that barrier was not aligned with the dominant flow direction. We compare these results to model inversion using traditional pilot points. The phantom structures approach shows promise in identifying hydrogeological structures and in reproducing groundwater flow across a model domain. Our results demonstrate that the geometric properties of geological structures can remain flexible in a model inversion. This is a step toward reducing conceptual model uncertainty where the presence and properties of hydrogeologic barriers are undefined.

Original languageEnglish
Article numbere2021WR031458
Number of pages22
JournalWater Resources Research
Volume58
Issue number7
Early online date30 Jun 2022
DOIs
Publication statusPublished - Jul 2022

Keywords

  • faulting
  • geological structure
  • groundwater
  • groundwater age
  • hydrogeology
  • model calibration

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