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Field Test of a Hybrid Finite-Difference and Analytic Element Regional Model.

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Summary

This study introduces a hybrid model combining MODFLOW and GFLOW to improve well-stream interaction simulations. The hybrid approach offers cost-effective, accurate predictions without grid discretization errors.

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Area of Science:

  • Hydrogeology
  • Computational Hydrology
  • Environmental Modeling

Background:

  • Regional groundwater models often use coarse grids, limiting accurate simulation of well-stream interactions.
  • Existing finite-difference models like MODFLOW struggle with fine-scale processes due to large cell sizes.
  • Analytic element models (e.g., GFLOW) excel at representing discrete features like wells and streams.

Purpose of the Study:

  • To develop and test a steady-state hybrid model coupling MODFLOW and GFLOW for enhanced well-stream interaction modeling.
  • To evaluate the hybrid model's performance against a refined benchmark model in a real-world scenario.
  • To demonstrate the cost-effectiveness and accuracy of the hybrid approach for regional studies.

Main Methods:

  • Coupling a coarse MODFLOW model with the analytic element model GFLOW, replacing upper MODFLOW layers with GFLOW.
  • Transferring cell-by-cell leakage from MODFLOW to the GFLOW model for integrated simulation.
  • Applying the hybrid model to a subdomain of the Lake Michigan Basin model for validation.

Main Results:

  • The hybrid model and a refined benchmark model produced similar baseflow simulations.
  • Both models accurately predicted baseflow reductions due to pumping within GFLOW-represented layers.
  • The hybrid model avoided grid discretization errors inherent in refining the benchmark model's grid.

Conclusions:

  • The hybrid MODFLOW-GFLOW approach effectively simulates well-stream interactions, outperforming traditional refined grids.
  • This method is well-suited for retrofitting existing coarse MODFLOW models for regional studies.
  • The hybrid model leverages the strengths of both finite-difference and analytic element methods for efficient and accurate predictions.