Overview

This project aims to provide visualizations of reliable values of macrodispersivity from field tracer tests.

Target Parameters

• longitudinal macrodispersivity
• transverse horizontal dispersivity
• transverse vertical dispersivity

Data source

The data collection is based on the meta-studies (and references therein):

Evidence based Estimation of Macrodispersivity for Groundwater Transport Applications Alraune Zech, Sabine Attinger, Alberto Bellin, Vladimir Cvetkovic, Gedeon Dagan, Peter Dietrich, Aldo Fiori, and Georg Teutsch; Groundwater, under revision, 2022

A Critical Analysis of Transverse Dispersivity Field Data; Alraune Zech, Sabine Attinger, Alberto Bellin, Vladimir Cvetkovic, Gedeon Dagan, Peter Dietrich, Aldo Fiori, and Georg Teutsch; Groundwater, 57 (4), 632-639, 2019 https://doi.org/10.1111/gwat.12838

Is unique scaling of aquifer macrodispersivity supported by field data?; Alraune Zech, Sabine Attinger, Vladimir Cvetkovic, Gedeon Dagan, Peter Dietrich, Aldo Fiori, Yoram Rubin, and Georg Teutsch; Water Resources Research 51, 7662–7679; 2015 https://dx.doi.org/10.1002/2015WR017220

Structure

The project is organized as follows:

• README.md - description of the project
• results/ - folder with plots
• data/ - folder containing table with field data
• src/ - folder containing the Python scripts of the project:
  • 00_Table_HeterogeneityClasses.py - load macrodispersivity data from table and identify averages for heterogeneity classes (Tab 1, Zech et al., 2022)
  • 01_plot_AL.py - visualize longitudinal macrodispersivity data (Fig 4, Zech et al., 2015)
  • 02_plot_AT_AV.py - visualize transverse dispersivity data (Fig 1b, Zech et al., 2019)
  • 03_plot_AL_CDFs.py - visualize cumulative density functions of dispersivity for heterogeneity classes (Fig 1, Zech et al., 2022)
  • 04_plot_CapeCod.py - visualize illustration example for an instantaneous injection in a low heterogeneous aquifer with comparison to observations from the Cape Cod experiment. (Fig 3, Zech et al., 2022)
  • 05_plot_AL-preasymptotic.py - visualize evolution of pre-asymptotic longitudinal macrodistispersivity as function of travel distance L relative to integral scales (Fig 4, Zech et al., 2022)

Python environment

To make the example reproducible, we provide the following files:

• requirements.txt - requirements for pip to install all needed packages

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 © 2022