MT3DMS, a three-dimensional transport model, will be used in this tutorial to simulate two-dimensional transport in a radial flow field. The example consists on a well which is injecting a solution in a constant rate of 100 m3/d with a contaminant concentration of 10 g/m3 (10 mg/l). This model will run for a total of 27 days.

The following tutorial will explain how the model was build and the conditions considered.

MODFLOW itself do take into account the spatial referenciation of the groundwater flow regime. Main MODFLOW output are water heads on the cell centre and flow in between cells, additional packages calculate solute transport, zone budgets or pathlines; however on the model construction and simulation it doesnt matter where the model is.

Aquifer response to pumping is one of the most popular interactions between human and the groundwater flow regimen. On the complexity of the hydrogeological studies, pumping tests are the most controlled environments since the well construction details are known, geological logs are available and pumping rates and drawndows can be measured. There are uncertainties on this hydraulic test and these are mostly related to the aquifer heterogeneity, however, it is expected that a pumping test can be fully recreated on a numerical model.

MODFLOW is the groundwater flow model developed by the USGS based on finit

MODFLOW 6 is the last version of MODFLOW that brings a set of new tools and a complete rearrange of the model file system. To the date of this post (July 2018) there are limited options for MODFLOW 6 preprocessors and postprocessors; so, whether you construct the MODFLOW 6 files as text files or you use the Flopy options to build, run and visualize groundwater models in MODFLOW 6.

Flopy is the Python package to create, run and post-process MODFLOW models. Flopy supports MODFLOW-2005 and MODFLOW 6 modeling codes and MODFLOW-based models as MODPATH (for particle tracking) and MT3D-USGS (for contaminant transport).

This tutorial show the complete procedure to setup, run and visualize a basic groundwater model in MODFLOW 6 with Flopy.

MODPATH is a particle tracking post-processing package that computes and displays three-dimensional pathlines based on output from MODFLOW. These pathlines help us to see the expected transport trajectories coming from a specific contaminant source. In addition, we can also use this package to obtain the time that these pathlines will take to reach a particular point. 

In this tutorial, we will show how to set up MODPATH to see the movement of particles over time coming from a  contaminant source and how these can be influenced by factors like the presence of low permeability areas.

ModelMuse is a versatile software that helps us with the creation of MODFLOW input files, running the model and the visualization of simulation outputs. These results give us a valuable amount of information that, by analyzing it correctly, can be used to take management decisions regarding the sustainable use of aquifers. These analysis encompass many different types of information which complement the groundwater modeling results.

When studying the groundwater flow, one of the main factors that influence its behaviour is the topography. Nowadays, we can obtain this topography information from several sources, being GeoTiff one of the most popular elevation models format file.

Model Muse is a versatile MODFLOW graphical user interface (GUI) where it is possible to insert many boundary conditions and terrain characteristics in order to represent the real conditions of the groundwater flow in an accurate way.

In this tutorial, you will be able to learn how to import digital elevation model data into Model Muse so it can be assigned as the topography of the area and take part into the simulation.

One of the main boundary conditions of the groundwater flow systems is the recharge. This is a process where water from the surface moves downward reaching the groundwater. The rate of recharge can be influenced by several factors like water content of surface materials, type of soil, plant cover and precipitation rate.

Model Muse is a versatile MODFLOW graphical user interface (GUI) where it is possible to insert many boundary conditions and terrain characteristics in order to represent the real conditions of the groundwater flow in an accurate way.

In this tutorial, we are considering a case study where the recharge rate is correlated with the elevation which is a characteristic of Andean basins. We will show you how to insert this correlation of recharge-elevation values into Model Muse in order to have a better representation of the hydrological cycle of this basin.

Groundwater models are geospatial referenced (unless you are in a laboratory) since we represent the actual and future conditions of a certain porous / fractured media, however the actual model matrix resolution is spatially independent since it deals with a hydrogeological conceptualized array of columns, rows and layers. The nexus in between the matrix and the groundwater flow system has been a topic in the model development, even later versions of Model Muse ask for the model system of reference (as EPSG or Proj4 code), however the user has to keep in mind the water heads and where those water heads are located.  The USGS has developed a Python package called Flopy for the model construction, simulation and output representation; this package has interesting features for the interaction with the input and output data and for the georeferentiation of model data. This tutorial shows the complete procedure to geospatial reference a MODFLOW NWT model with some lines of Python code in a Jupyter Notebook and the representation of geospatial referenced model discretization data in QGIS 3.

Flopy is a package of tools written in Python for MODFLOW groundwater flow model construction, simulation and output analysis. Flopy is build on top of well know and powerful Python packages as Numpy and works with Matplotlib and Pandas that allows to do a great amount of analysis with few lines of code. Several new capabilities in the water balance analysis can be done with Flopy bringing a better control to the modeler in terms of a more available and user friendly information of the inputs, outputs and discrepancies of the model. This tutorial shows the complete procedure to read, simulate and output analysis of a MODFLOW NWT model of a tunnel development with time. The tutorial include a discussion and review of the different tools available in Flopy and the interaction with QGIS.

Stress periods are defined based on particular stages on the groundwater flow conditions and requirements to hidrogeological flow regime. Time steps are mostly defined based on the computational power, desired output and convergence objectives. It can be possible that boundary conditions varies at times different from the temporal discretization defined by the stress periods and time steps. MODFLOW 6 has a time-series functionality capable of distribute the transient boundary conditions on the determined time steps. The tutorial shows a model on transient flow conditions with boundaries conditions distributed at different time intervals. A comparison of the applied well rate vs. observed pumping rate and applied constant head vs observed head has been done on a Jupyter Notebook.

Example of the wetting/drying capabilities in MODFLOW 6 on a groundwater model on steady and transient flow conditions. The simulation represent the groundwater flow of a 2 layer model at the following stress periods: no pumping, pumping from 2 wells, recovery from pumping in 50 days. The model has been implemented with the recharge package (RCH), river package (RIV), and well package (WEL).

The tutorial also runs some Python script for the translation of model results and boundary conditions in VTK geometry. The Python script has a interactive feature for the representation of selected stress periods and time steps. A discussion of the water table at pumping and recovery was done on the last of the tutorial.

MODFLOW 6 has been compiled using gfortran on the Mac/OS operating systems. Because the program uses relatively new Fortran capabilities gfortran version 4.9 or newer must be used. If you have gfortran installed on your computer, you can tell which version it is by entering “gfortran --version” at a terminal window.

This tutorial show the procedure to compile and run MODFLOW 6 on a Terminal in MAC/OS operating sytem.

Based on the new file format and keywords from MODFLOW 6 it is more simple to understand a model while inspecting the input files. This tutorial show a example of a steady and transient flow model in MODFLOW 6 for a period of 30 days divided into 4 stress periods. The tutorial has a introduction to the model geometry, input files and boundary conditions, a model simulation in transient flow conditions and output visualization as VTU files in Paraview. The tutorial also includes a discussion on the water balance from the groundwater flow system at the end of the simulation.

Basic tutorial to learn the procedure to build, simulate and represent a MODFLOW 6 model. The tutorial shows a introduction to the model file system on steady state conditions. The model for this tutorial is implemented with the following boundary conditions: Drains, Recharge, Wells, and Constant Head. The grid is regular with a width of 50 meters and it has 30 rows and 24 columns; the model has 4 layers and a total thickness of 130 meters. The model is called "hatari01" and is inspired in the "twri" model from the MODFLOW 2005 documentation adapted to MODFLOW 6. The model defines a constant horizontal hydraulic conductivity as well as vertical conductivity. After the simulation a Python code is run on a Jupyter Notebook to create the Unstructured VTK files for the heads, water table and boundary conditions representation as 3D objects in Paraview.

MODFLOW model output representation is key to understand the groundwater flow regime, to study the interaction with surface water and depending ecosystems and to evaluate the impact to anthropogenic and climate change requirements. Until now, there has been few open source software capable of generating3D representations and those software had limited options for color scales, cross sections and other graphical tools. On the research for more options we found Paraview, a open source software for data representation designed to analyze extremely large datasets using distributed memory computing resources.

In order to represent MODFLOW output into Paraview, a VTK file for unstructured grids is needed, this VTK type is called VTU where the "U" comes from unestructured. The tutorial show the complete procedure to process a MODFLOW model output into a VTU file and the representation in Paraview.

MODFLOW computes the groundwater heads over a porous / fractured media upon a series of boundary conditions as recharge, evapotranspiration, drains, well and others on steady and transient conditions. Free and commercial software is available for the MODFLOW model construction and MODFLOW output representation. Despite the fact the capabilities of these softwares, there are some gaps in data processing and representation; isometric views, animation and custom cross sections are still difficult to achieve under the existing tools, specially on multilayered models with transient conditions over series of time steps and stress periods.

There is a particular open source software for data representation that is of our interest, it is called Paraview (paraview.org). This visual application was designed to analyze extremely large datasets using distributed memory computing resources, in fact the term "para" in Paraview comes from the parallelization of computer cores.
 

Flopy is the Python library to create, run and represent results from MODFLOW models, including support for MODFLOW 6. With Flopy, the model definition and set up of boundary conditions can be done with lines of Python code, and some Python tools of optimization and machine learning can interact with the MODFLOW models. This tutorial show a basic example of model creation, configuration and simulation in Python 3 on a Jupyter Notebook. The tutorial also shows the procedure to import the MODFLOW results done with Flopy in Model Muse.