Overview

This project provides a python scripts to simulate the wave propagation from an open water body into an aquifer. Simulations can be performed via the numerical solver ModFlow throught the Python API flopy or using a semi-analytical solution. The code comes along three input waves: a tidal wave, an artifical square wave and the time series of a river.

Structure

The project is organized as follows:

• README.md - description of the project
• LICENSE - the default license is MIT
• results/ - folder with simulation results and plots
• data/ - input data of waves in open water bodies and summarized numerical simulation results
• src/ - folder containing the Python scripts of the project:
  • WavePropagationAquifers.py - central class file containign class "WavePropagationAquifers" for 1D aquifer model (confined, leaky) with all characterizing properties and routines for input wave handling, fft wave decomposition and analytical solution calculation, inverse estimation and running numerical simulation
  • flopy_model.py - functions to start 1D Modflow models (via flopy) for simulating wave propagation in aquifers with time dependent boundary condition under various aquifer conditions (confined, leaky, barrier)
  • 01_run_num_model.py - Settings of three examples, including the command for starting the numerical simulation with the selected aquifer setting and boundary condition; simulation results are saved as pickle-files in the results directory saved results are used for plot preparation (Fig 3 and S3)
  • 02_impact_observation_loc.py - script to process numerical simuation data for studying impact of observation location on inverse estimation procedure saved results are used for plot preparation of Fig 5
  • 03_run_num_resistance.py - script to prepare inverse estimation results for various values of resistances for the aquifer setting of leakage and barrier and save results for files: - running numerical simulations for range of resistance values - postprocess simuation data by selecting head values at specified spatial locations - perform inverse estimation of diffusivity from numerical results with confined aquifer solution - perform inverse estimation of diffusivity from numerical results with leakage aquifer solution saved results are used for plot preparation Fig 6 & 7
  • F02_Input_BC_Waves.py - reproducing Figure 2 of the manuscript: settings of three example, including plotting of input waves
  • F03_Solution_Performance.py - reproducing Figure 3 of the manuscript: comparing analytical solution to numerical simulation results from pickle-file
  • F04_Fit_Confined.py - reproducing Figure 4 of the manuscript: fitting analytical solution to numerical simulation results from pickle-file
  • F05_Impact_Location.py - reproducing Figure 5 of the manuscript: values of relative differences of diffusivity estimate as function of piezometer location (distance x to open water body) using results prepared with 02impactobservation_loc.py
  • F06_Impact_Resistance.py - reproducing Figure 6 of the manuscript: relative difference for diffusivity estimates when fitting the confined aquifer solution to complex aquifer settings with leakage and flow barrier as function of the resistance value using results prepared with 03runnum_resistance.py
  • F07_Fit_Leakage.py - reproducing Figure 7 of the manuscript: relative difference for diffusivity and resistance factor estimates when fitting the analytical solution to numerical simulation results for the leaky aquifer setting as function of the confining layer resistance value using results prepared with 03runnum_resistance.py
  • SF01_Input_Wave_Reconstruction.py - reproducing Figure S1 of the supporting information:
    comparing input BC time series to FFT reconstructions
  • SF02_Model_Fitting_Max_Wave - reproducing Figure S2 of the supporting information: fitting analytical solution to numerical simulation results from pickle-file (similar to Fig 4) with fit of dominant wave component
    

Python environment

To make the example reproducible, we provide the following files: - requirements.txt - requirements for pip to install all needed packages

Contact

You can contact us via a.zech@uu.nl.

License

MIT © 2021