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.