Skip to content

v1.1

Latest
Compare
Choose a tag to compare
@MuellerSeb MuellerSeb released this 19 May 12:44
· 1 commit to master since this release

The eGRF model and its application to effective conductivity for TPL variograms

Description

The extended generalized radial flow (eGRF) model is an extension to the GRF model
by allowing radial variable transmissivity and storativity values.
The GRF model was derived by:

Barker, J.A., 1988.
A generalized radial flow model for hydraulic tests infractured rock.
Water Resources Research 24, 1796–1804. https://doi.org/10.1029/WR024i010p01796

In this workflow, we demonstrate the abilities of the eGRF model and numerically
prove, that the effective transmissivity for truncated power law (TPL) variograms
reproduces the ensemble mean drawdown of pumping tests on synthetic aquifers.

Structure

The workflow is organized by the following structure:

  • src/ - here you should place your python scripts
    • 00_ext_theis_tpl.py - plotting the effective head for TPL variograms
    • 01_est_run.sh - bash file running 02_para_estimation.py in parallel
    • 01_convergence.py - demonstating the convergence of the effective TPL solution
    • 02_step_function.py - plot different step function approximations
    • 03_literature_transmissivities.py - comparision of drawdowns for different
      transimissivites from literature
    • 04_trans_plot.py - plot a realization of a TPL transmissivity field
    • 05_KTPL_plot.py - plot K_TPL for different dimensions
    • 06_tplgaussian_vs_matern.py - comparison of TPL-Gaussian and Matern models
    • comparison/ - scripts for the comparison of ensemble mean to effective TPL heads
      • 00_run_sim_mpi.sh - bash file running 01_run_sim.py in parallel
      • 01_run_sim.py - run all ensemble simulations for pumping tests on TPL aquifers
      • 02_compare_mean.py - generate comparision plots for the ensemble means
  • results/ - all produced results

Python environment

Main Python dependencies are stored in requirements.txt:

gstools==1.3.0
anaflow==1.0.1
ogs5py==1.1.1
matplotlib

You can install them with pip (potentially in a virtual environment):

pip install -r requirements.txt

Contact

You can contact us via [email protected].

License

MIT © 2021