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.
The workflow is organized by the following structure:
src/- here you should place your python scripts00_ext_theis_tpl.py- plotting the effective head for TPL variograms01_est_run.sh- bash file running02_para_estimation.pyin parallel01_convergence.py- demonstating the convergence of the effective TPL solution02_step_function.py- plot different step function approximations03_literature_transmissivities.py- comparision of drawdowns for different transimissivites from literature04_trans_plot.py- plot a realization of a TPL transmissivity field05_KTPL_plot.py- plot K_TPL for different dimensions06_tplgaussian_vs_matern.py- comparison of TPL-Gaussian and Matern modelscomparison/- scripts for the comparison of ensemble mean to effective TPL heads00_run_sim_mpi.sh- bash file running01_run_sim.pyin parallel01_run_sim.py- run all ensemble simulations for pumping tests on TPL aquifers02_compare_mean.py- generate comparision plots for the ensemble means
results/- all produced results
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.txtYou can contact us via [email protected].
MIT © 2021