Groundwater flow direction representation is useful to understand the actual and predicted conditions of the groundwater flow regime. The arrow direction and magnitude give a quick perspective of the main groundwater flow directions and the interconexion between sources and discharge points. This tutorial show the complete workflow to determine the flow directions from a MODFLOW model done with Model Muse. The scripting insert a background image, georeference the model from parameters exported as comments, and export the resulting figure as a PNG file. The tutorial is done in Python 3 on a Jupyter Notebook.

Karst systems are characterized by underground drainage systems formed by the dissolution of soluble rocks. The behaviour of these systems is hard to be conceptualized due to the uncertainty in the location and geometry of these underground caves and its connection with the porous media.

In order to be able to model these systems, the Conduit Flow Process (CFP) package (developed by the United States Geological Survey – USGS) can simulate turbulent ground-water flow by coupling the groundwater flow equation with formulations for a discrete network of cylindrical pipes.

The following tutorial explains how to set up a simple karst conduit system in a previously existing MODFLOW model and the analysis of the results.

Making hydrogeological models can take a long time, from construction, visualization of results and calibration. It is important to use tools that can optimize these tasks and allow the time saved to be used in the analysis of the system.

In this opportunity we will use Flopy to replicate a 2D transport model from a previous post. Flopy is a versatile set of Python scripts which can be used to run MODFLOW and MT3D, amongst other MODFLOW-related groundwater programs in a simple and efficient way. It will be seen how useful this tool is to automate the process of creating groundwater models since modifications of the boundary conditions can be done just by changing the text file.

In addition, MT3D-USGS will be used for the transport modelling. It is an updated release of the groundwater solute transport code MT3DMS, which has new transport modeling capabilities that provide a greater flexibility in the simulation of solute transport and reactive solute transport.

Aquifers can be porous, fractured or karstic. Due to the geological setup and processes related to the formation of the porous media, these acuifers can present a high degree of heterogeneity that affect/impact the groundwater flow patterns and contaminant transport and distribution.

Contaminant plumes for puntual/aerial sources interact with aquifer heterogeneities and anisotropies. Understanding and conceptualizing the distribution of the different hydrogeological units and their properties on the subsurface is a challenge for hydrogeologist, numerical modelers and remediation specalists.

MT3D-USGS is the one of the latest software for contaminant transport developed by the USGS. The initial release was on 2016 as a updated release of MT3DMS. The software has new capabilities for transport modeling coupled with the current MODFLOW packages, it can model unsaturated-zone transport, reactions and remediation schemas.

This transport modeling code is implemented in the pre and postprocessing software for groundwater modeling Model Muse, also developed by the USGS. This tutorial show a basic example of contaminant transport from a point source in a groundwater flow regime controlled by regional flow and discharge to ponds and rivers.

Seawater intrusion is an issue in coastal aquifer management especially on arid environments. Overexplotation of groundwater resources by high production wells on intensive irrigation schemes could lead to an intrusion of saline water from sea and an impact to the quality of water sources.

Available options to assess the behaviour and impact of seawater intrusion are limited in both open source and commercial software; there is also a need of highly skilled groundwater modelers to understand the complex model setup and model output that can provide useful information about the groundwater flow regimen and the risks to water quality posed by seawater intrusion.

Seawater Intrusion Package 2 (SWI2) is a modeling software developed by the USGS and coupled on MODFLOW-2005. SWI2 allows three-dimensional variable-density groundwater flow and seawater intrusion in coastal aquifer systems. This tutorial deals with a basic example of the implementation of SWI2 on a MODFLOW model contructed on Model Muse. The tutorial show the whole procedure of model setup, datasets implementation, conceptualization of boundary conditions and result evaluation.

Assessing the groundwater flow regime in coastal aquifers is a challenge for numerical modelers. In order to have a complete set of parameters and input data for a valuable numerical simulation we need to compile several hydrogeological studies, reconstruct datasets and proof the accuracy of hydraulic tests. Still some parameter would be missing but the experience and criteria of the groundwater modeler would achieve adequate simulations and predictions required by an adaptive sustainable groundwater resources management.

Aquifer modeling requires understanding and expertise on the different boundary conditions available to represent the physical process related to the groundwater flow regime on determined spatial and temporal discretizations. MODFLOW has a set of boundary conditions of specified head, specified flux and mixed. There is a particular boundary condition created for the representation of the interaction between a river and the surrounding aquifer: the River Package (RIV). This tutorial show the implementation procedure of a River Package (RIV) on a regional model with a discussion on the model output and water balance.

On a normal groundwater modeling workflow the hydraulic parameters, observed data and boundary conditions are preprocessed on a GIS software as QGIS, and then imported on a compatible format (vector or raster) into the modeling software. However, Model Muse has a set of different tools to process point, and tabular data into model parameters increasing the speed in the model construction and simulation. This tutorial show the procedure to interpolate hydraulic conductivity from a table into Modflow from a different set of interpolation methods in Model Muse.

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.