March 30, 2020

Basic Example of Particle Tracking Modeling with Modpath 7 on MODFLOW6 - DISV

March 30, 2020/ Saul Montoya

We have developed a tutorial on particle tracking with Modpath7 on grid with local refinement made by the Discretized by Vertices (DISV) option of Modflow6. Model constrution, boundary condition setup, groundwater flow simulation and particle tracking simulation was done on Model Muse 4. Groundwater flow conditions were conceptualized as steady state, and the particle tracking was simulated on forward and backwards tracking direction.

March 05, 2020

Web 3D Representation of a MODFLOW Model with Hataripy, Paraview and Steno3D

March 05, 2020/ Saul Montoya

Groundwater can’t be seen (because its on the ground, obviously) and groundwater flow is extremely hard to understand unless we have a bigger scope of the theory and main features of the hydrogeological flow regime. One of the limitations for the understanding is the lack of interactive tools that provides user friendly environments for the representation of recharge zones, discharge zones, wells, wetlands, and other hydrogeological features.

We have developed a tutorial for the web representation of a MODFLOW model main features and head results in a combined process with the use of the Hataripy library, Paraview, Python and Steno3D.

February 26, 2020

How to insert a 3D Geology into a MODFLOW Model with Python and Flopy - Tutorial

February 26, 2020/ Saul Montoya

Finite difference method as well as any other discretization method allows the conceptualization of a geological media into cells or other volumes. Geological models come in diverse formats in binary or text format and need to be “translated” to the cell extension of a groundwater model.

This tutorial has a applied example of the implementation of a 3D geological model from a neural network into a groundwater model with determined horizontal discretization and layer thickness. The tutorial covers all the steps for model construction and hydrogeological unit determination with scripts in Python with Flopy and other libraries. Comparisons of the original and translated geological model were done as Matplotlib plots and Vtk files in Paraview.

February 23, 2020

3D Geological Models using Neural Networks with Python Scikit Learn and Vtk - Tutorial

February 23, 2020/ Saul Montoya

We have done tutorial in Python and recent and powerful libraries as Scikit Learn to create a geological model based on lithology from drillings on the Treasure Valley (Idaho, USA). The tutorial generates a point cloud of drillings lithologies that are transformed and scaled for the neural network. The selected neural network classifier is Multi-layer Perceptron classifier implemented on the Scikit Learn library as sklearn.neural_network.MLPClassifier. An analysis of the confusion from the neural network is performed. The tutorial also includes a georeferenced 3D visualization from well lithology and interpolated geology as Vtk format in Paraview.

February 14, 2020

3D Visualization of Well Lithology with Python, Pyvista and VTK - Tutorial

February 14, 2020/ Saul Montoya

There are standards for the lithology descriptions, but there are no standards about how to store lithological information and relate it to the drilling position. This disorder leads to the use of many formats and data files related to open and proprietary software.

In the search of “one tool that manages all tools”, as a similar concept of the “one ring that rule them all” from the Lord of the Rings (J.R.R Tolkien), we found that Python and its libraries: Pandas, Pyvista and VTK can do a decent job on the compilation, geotransformation, spatial location, and 3d geometry generation.

This tutorial deals with the 3D visualization as Vtk files on Paraview of the lithological information from hundreds of wells located on the Snake River - Idaho. The tutorial covers all steps from the download of the raw information processing to the list and arrays generation for the vtk file. The scripting work was done on a Jupyter Nobebook and the output 3D files were plotted on Paraview.

February 04, 2020

How to translate Coordinate Systems for XY Point Data tables with Python Pandas and Pyproj

February 04, 2020/ Saul Montoya

Spatial information is linked to the position and a system of reference. There are many coordinate systems worldwide with different length units, projections and origins. Somehow, spatial analysis is always linked to information stored on different coordinate systems and we have to provide effective ways to translate them to a specific CRS (coordinate reference system).

We have developed a tutorial for the coordinate system translation of XY point location stored in tables. The tutorial shows the procedure to change coordinate systems from geographic and planar coordinates using the Pyproj library over a Pandas dataframe on a Jupyter notebook.

December 18, 2019

How to smooth a Aster DEM elevation raster with QGIS 3 - Tutorial

December 18, 2019/ Saul Montoya

In developed parts of the world there are online elevation repositories with current and historical elevation data from field surveys, lidar, etc. However, for the rest of the world, the availability of online resources for elevation with adequate resolution are scarce. The ASTER Global Digital Elevation Model 1 arc second (ASTGTM v003) is one of the most reliable sources for elevation worldwide with a cell resolution of 30m and interpreted from "recent" images (from 2000 to 2013). In flat or vegetated areas the procedure to interpreted elevations face some complexities and the Aster DEM images show some bumps or high elevation spots that are not coherent when contrasting the elevation model with satellite panchromatic images. This tutorial shows a procedure to smooth the Aster elevation models with standard QGIS 3 tools on a practical exercise over a study area. The procedure can be applied to Alos Palsar images or any other noisy elevation raster.

December 06, 2019

Fault Zone Groundwater Flow Modeling with MODFLOW6 DISV and Model Muse -Tutorial

December 06, 2019/ Saul Montoya

Conceptualization and simulation of groundwater flow in the area of influence of geological faults is really a challenge for numerical modelers. Besides the complexities and variety of faults there were some limitations of the numerical codes to simulate the mixed behaviour of faults and altered zones. We have developed an example tutorial to represent the main characteristics of groundwater flow in the fault zone for an applied case. The tutorial is developed in Model Muse with the MODFLOW DISV option for unstructured grid generation. Groundwater flow was analyzed on the water balance and a particle tracking simulation was done with MODPATH 7.

December 02, 2019

How to create an Elevation Raster from Contour Lines with Python, Geopandas, Numpy and Gdal - Tutorial

December 02, 2019/ Saul Montoya

Spatial analysis is such an interesting discipline because it allows the evaluation of every phenomena related to their location. However, for some parts of the data processing the workflow on a GIS Graphical Computer Interface (GUI) can be repetitive and time consuming. Researchers need better and more efficient tools to process more amount of data in less amount of time and even with less quantity of software tools.

We have create a innovative script to generate an elevation raster file from a contour line with several steps of data processing. The script recognizes invalid geometries, simplify the polylines and extract vertices while creates a point geodataframe that is interpolated and geotransformed as a geospatial raster in .tiff format.

November 29, 2019

How to define cell / layer confinement in MODFLOW 6 with Model Muse

November 29, 2019/ Saul Montoya

The process and options to define the cell / layer confinement has changed in MODFLOW 6 with respect to MODFLOW 2005. We have done an explanatory video about the process to setup the confinement for cells in MODFLOW 6 with Model Muse. There is also a discussion on the influence of the confined / convertible option on the aquifer response on an example model.

November 25, 2019

Produced Water Chemistry and Isotope Analysis with Python and Pandas - Tutorial

November 25, 2019/ Saul Montoya

On hydrocarbon extraction, water is a byproduct that comes from the geologic formations that have also oil and gas. Produced water can be defined as fossil water, or water with a high residence time on the earth, with a particular water chemistry that is important to analyze when we deal with the treatment methods, disposal techniques or safety to drinking water sources. The USGS has developed a produced water geochemical database with more than 100K points that includes spatial information, well description, rock properties, water chemistry and isotopes.

November 18, 2019

Basic Example of Stream Flow Routing (SFR) Package with MODFLOW and Model Muse

November 18, 2019/ Saul Montoya

The disconnexion of surface groundwater flow it is fact very common on highly exploited aquifers or under impacts from climate change. Many rivers are disconnected from the groundwater flow regime decreasing their flow amount due to infiltration losses. For the simulation of this surface flow, unsaturated flow and groundwater flow phenomena the MODFLOW package Streamflow Routing (SFR) was developed.

This tutorial develops an numerical model of disconnected surface groundwater flow with MODFLOW SFR and Model Muse. The study case has regional flow and a river network with monthly flow on transient conditions over 2 years.

November 06, 2019

Geochemical Speciation Modeling and Analysis with Phreeqc and Julia - Tutorial

November 06, 2019/ Saul Montoya

The speciation modeling allows to calculate the distribution of aqueous species in a solution. Phreeqc is capable to simulate this speciation calculation and we are going to demonstrate this capability on a study case of aqueous species in seawater. Modeling was done with a Phreeqc executable and results were analysed on a interactive Julia script. Both parts were done on a Jupyter Lab session.

October 25, 2019

Websites where you can download complete groundwater flow models in MODFLOW

October 25, 2019/ Saul Montoya

Learning groundwater modeling is a challenge for the complexities of the codes, the lack or scarce piezometric and water quality data, the heterogeneity of the porous media and the few resources to explore complete and applied groundwater models with different boundary conditions and predictive scenarios.

Just few websites had uploaded complete groundwater flow models in MODFLOW and are accessible to the general public. We have to admit that most of the websites come from public institutions in the US. We hope that in a near future we can have more resources to get model reports and the complete MODFLOW model.

October 18, 2019

Introducing Hataripy, the unofficial Flopy version that creates awesome VTKs

October 18, 2019/ Saul Montoya

A new unofficial version of the Flopy is available as Hataripy. This “fork” has tools for the representation of many features, boundary conditions and output with options for grid smoothing. Documentation for this library is on progress as we expect to introduce other features and identify some bugs.

Currently the library can:

Create the model mesh on the active zone with point and cell values
Create a shell of the water table
Create the geometry of any boundary condition

October 02, 2019

Unofficial MODFLOW flow and transport executables for Linux (Ubuntu tested)

October 02, 2019/ Saul Montoya

It might be that you are a talented groundwater modeler and very proficient with Python and Flopy that you start to realize that you don´t need to work in Windows anymore and want to migrate your favorite groundwater modeling code to other nice, soft, and warm Linux-based operating systems. Or, it might be the case that you want to configure and run MODFLOW models as a part of a webapp or in a web server. For the reasons mentioned before and other reasons that modern world could bring to us, a compiled version of MODFLOW in Linux is needed.

September 02, 2019

How to fill missing Elevations to empty Contour Lines with PyQGIS

September 02, 2019/ Saul Montoya

Elevation contour lines without the elevation attribute is common when we import contour lines from Autocad DXF files, but it has also happened that contour data was stored on a hard disk drive without elevation attribute and years later data is found and there is no one to ask to restore the missing information. This tutorial shows a practical procedure to fill missing elevations on contour lines with the use of PyQGIS on QGIS 3. The procedure uses an intersection line that crosses the contour lines where the base elevation and interval is known. There are some specific instructions to run the script that are well described on the video.

August 13, 2019

Temporal discretization impact on MODFLOW Model Heads and Water Budget

August 13, 2019/ Saul Montoya

For a transient model, a modeler needs to conceptualize a coherent and feasible time discretization approach, nevertheless searching for temporal discretization guidelines the Internet gives you digital noise: nothing relevant, nothing precise, nothing useful. These is the type of situation where you ask yourself: how many stress periods do I need, how many time steps do I require, which should be an appropriate size of the model output, or more important, will the size and number of stress periods and time steps have an effect on the model output?

August 08, 2019

How to Convert a PDF to ESRI Shapefile with Python, Geopandas and Inkscape - Tutorial

August 08, 2019/ Saul Montoya

In order to use the spatial data provided on a report we need procedures to extract the data on effective way. The amount of tools and techniques are quite advanced, and requires several open source software for specific procedures. We have done a complete tutorial with all the step required to extract the vector spatial data of a map reported as PDF into a ESRI shapefile. For this tutorial we have used Inkscape for the conversion of the PDF to DXF, QGIS to extract some information of the DXF, Python and Geopandas on a Jupyter Lab session for spatial translation and scaling.

July 24, 2019

The dark side of Python for Hydrology / Hydrogeology and the nightmare of unmet dependencies

July 24, 2019/ Saul Montoya

The near future of data processing for Hydrology / Hydrogeology is written in Python 3, and many universities and institutions are shifting from teaching C++, Matlab or Fortran to Python. It is surprising the amount of tools, packages, codes and Ipython notebooks available for the data processing and data analysis of water related data, even with high success in data analysis reproducibility.

However, there is not always a sunshine on working with Python, especially if you are working on Windows. After you have done your first steps in hydrological series plotting, statistical analysis or even run a neural network, you might want to do more with Python and there is when the situation can become unbearable.