February 01, 2021

Interactive MODFLOW MT3D transport model visualization with Flopy, Ipywidgets and Voila - Tutorial

February 01, 2021/ Saul Montoya

Representation and analysis of flow and transport results is a challenge for groundwater modelers. Aspects such as speed, compatibility, data format and visualization options are key in the 2D/3D representation of head and concentration on model cells. Under the Jupyterlab framework new tools have been developed that can be useful to represent model results on a user friendly way .

This time we have done a tutorial for the interactive representation of a contaminant plume in Jupyterlab; modeling was done with Modflow Nwt and Mt3d, representation was done with Matplolib, Ipywidgets and Voila.

January 28, 2021

Interactive Shapefile exploration in Jupyterlab with Ipyleaflet and Voila - Tutorial

January 28, 2021/ Saul Montoya

Whether you want to explore or visualize a Shapefile without leaving the Jupyterlab environment or you just want a better tool for the spatial representation this tutorial might be of your interest. We have developed an interactive application on Jupyterlab with Ipyleaflet and Voila that represent a selected shapefile on a canvas with options for basemaps, zoom and others.

January 26, 2021

How to convert a Raster to Contours with Python and GDAL - Tutorial

January 26, 2021/ Saul Montoya

On the way to discover the analogy of the common desktop GIS procedures to Python we assumed that the process of extracting contours from raster was well documented or there were many tutorials on the topic. We found that there weren't many options to complete this process successfully or with few amount of pain, therefore we have done a complete tutorial on the process to create contours from a elevation raster with Python and GDAL that includes input data, scripts, and a discussion over the main steps of processing.

January 18, 2021

Which are the challenges for model calibration in MODFLOW 6?

January 18, 2021/ Saul Montoya

MODFLOW 6 is the latest version of MODFLOW; we can’t frame this version as new because it has been released in May 2017 when QGIS 3 wasn’t even released or Python 3.6 was the latest version. On the hydrogeological perspective changes don't come as fast as expected and the amount of users of MODFLOW 6 is increasing but there are limitations on the pre/post processing tools that can take the best of the software for the general public.

Besides the philosophical discussion if a model can be “calibrated” or just “validated” there are some changes on the structure of MODFLOW 6 that bring challenges on the traditional way of model calibration.

January 06, 2021

Online Voronoi Modflow 6 groundwater modeling with Hakuchik - Tutorial

January 06, 2021/ Saul Montoya

Because a new year has come with a new way to model groundwater flow using the latest developments of Modflow 6 Disv. We are not exactly sure that we have done a tutorial, or a procedure or a bunch of code and tools together but we are sure that we have done something that can model geospatial groundwater flow online with awesome 3d representations. At the time we launched all the code on the Hakuchik server, we had a feeling of "we did it" and you are entitled to see if our work is good, bad or in progress. We are sure that more development needs to be done but this will be the way of groundwater modeling in the future, hoping that improving the capacities of professionals and concern of the general population will lead to a sustainable management of our groundwater resources.

December 23, 2020

Variable density groundwater flow modeling with MODFLOW 6 and BUY package - Tutorial

December 23, 2020/ Saul Montoya

Coastal aquifers and the interaction among brine / fresh groundwater need to be evaluated with a modeling code that can deal with variable density flow. For more than 18 years, SEAWAT was the prefered (or only) open source solution implemented in Modflow 2000 with some limitations* on its use with Flopy. Now in Modflow 6 the concept of simulation involves flow and transport modeling together with exchange among them. We have done a tutorial with a simple case of variable density flow from a saline lake into an acuifer. The transient model has a duration of 50 days where the saline water "intrudes" the aquifer at the bottom part of the lake.

December 14, 2020

Hatarilabs presents its study area for integrated and sustainable groundwater management

December 14, 2020/ Saul Montoya

Because field work and numerical models are just tools for the sustainable management of our groundwater resources we have searched a study place to develop a long-term project on a high-stressed aquifer that will lead to sustainable and effective groundwater policies. The study area is an alluvial aquifer that was primarily used for agriculture production with an neighboring unplanned urban development that has increased the domestic / industrial water demand. Several pumping schemas were implemented on the area and have affected the groundwater levels and the water availability for agriculture.

December 04, 2020

How to geolocate drone imagery from a csv table with Python and Piexif - Tutorial

December 04, 2020/ Saul Montoya

If your drone doesn´t write the GPS position on the image metadata, this is a tutorial that might be of your interest. When you have the images without any location reference and the image location on another text file you can use the code described below to generate geolocated drone imagery compatible with OpenDroneMap. The tutorial shows all the steps involved besides it has some sample data to practice.

November 27, 2020

How to create a geospatial Raster from XY data with Python, Pandas and Rasterio - Tutorial

November 27, 2020/ Saul Montoya

Another tutorial done under the concept of “geospatial python”. The tutorial shows the procedure to run a Scipy interpolation over a Pandas dataframe of point related data having a 2D Numpy array as an output. With some procedures of Rasterio the Numpy array was transformed into a monoband geospatial Tiff raster.

November 23, 2020

How to join lines and densify vertices with Python, Fiona, Shapely - Tutorial

November 23, 2020/ Saul Montoya

We have done a tutorial under the concept of "applied geospatial Python". This is an example that deals with a selective filtering of a determined road from a road geopackage. The selected road is composed of a group of lines that are merged into a Shapely LineString. Based on a Numpy linspace with the Shapely interpolate function, a set of points were distributed along the merged line path and later interpreted as a LineString. Resulting line was saved as a ESRI Shapefile file with Fiona.

November 19, 2020

Convert from Excel Spreadsheet to Point Shapefile with Python, Pandas & Fiona - Tutorial

November 19, 2020/ Saul Montoya

We have done a tutorial with a workaround procedure in Python with Pandas and Fiona of a common and but multi-step process to create point shapefiles from excel spreadsheets. The process involve some lines of code to read the excel file, define the output shapefile structure and write the point data.

November 16, 2020

Machine Learning Supported Groundwater Model Calibration with Modflow, Flopy, PySal and Scikit Learn - Tutorial

November 16, 2020/ Saul Montoya

We have done a tutorial on a low-level-complexity model with rivers, lakes, recharge and regional groundwater flow done in Model Muse in a previous tutorial. The model was imported as an object in Python with Flopy. A sensibility analysis was done with SALib to assess the response for the object model groundwater flow to a different sample of parameters and a resulting set of parameters and corresponding heads (parameters -> heads) were recorded. Then a machine learning regression was performed with Scikit-Learn with the inverse set (heads->parameters) to get the predicted parameters for the observed data. Different error measurements were performed for two model cases to assess the overall quality of the neural network regressor.

November 10, 2020

How to set a multiuser Jupyterlab server with Jupyterhub (in Windows with Docker)

November 10, 2020/ Saul Montoya

When teaching or working with Python there is a challenge to have and work simultaneously with the same Python version and Python packages. Jupyterhub is a great solution to bring notebooks to a group of users with admin tools and many more features. We have done a tutorial to install Jupyterhub with Jupyterlab in a local lan or wifi network. The tutorial shows the procedure to run Jupyterhub from Docker in Windows, set up a native authenticator and configure an admin and users.

November 04, 2020

How to do a simulated groundwater head difference map in MODFLOW and ModelMuse - Tutorial

November 04, 2020/ Saul Montoya

This is a tutorial about some functionalities of Model Muse to analyze and process layer heads or parameters. The applied example was done based on a previous tutorial of a model with 3 stress periods, one static and two transient periods of 10 days. The simulated map shows the head difference in the last 10 days.

November 03, 2020

How to clip polygon layers with Python, Fiona and Shapely - Tutorial

November 03, 2020/ Saul Montoya

This tutorial shows the entire procedure to clip a polygon layer to an area of interest in Python with the use of spatial libraries as Fiona and Shapely. The tutorial opens the polygon and clip layer as fiona elements, interpret the geometries as shapely Polygon datatypes, clip the polygons and store results as an output shapefile with the corresponding metadata.

October 30, 2020

Review of the latest functionalities of the new release of MODFLOW 6 (mf6.2.0)

October 30, 2020/ Saul Montoya

Modflow6 is the latest version of the USGS code for groundwater modeling MODFLOW. This version has been coupled with another USGS open source software as Model Muse and Flopy and can implement diverse spatial discretization structures on a complete rearrangement of packages and keywords. We feel that there is a gap on the capabilities from a common groundwater modeler to adopt all the new development on Modflow and other open source groundwater software therefore we have prepared a video with the summary of this new release.

October 26, 2020

How to clip Sentinel 2 bands to an area of interest with Python, Rasterio and Fiona - Tutorial

October 26, 2020/ Saul Montoya

Under the concept of “Python spatial” we have developed a tutorial for the spatial processing of multiple bands from a Sentinel 2 image. The tutorial shows the procedure to read the set of bands, import a shapefile, clip each band and export the clipped version in another folder. The spatial process is independent from raster resolution and can be easily modified for Landsat images.

October 21, 2020

How to set a Multi Aquifer Well (MAW) in MODFLOW 6 and Model Muse - Tutorial

October 21, 2020/ Saul Montoya

Modeling the dynamic of the groundwater flow related to pumping was a challenge with the traditional Wel package in MODFLOW since wells are screened on the most part of the well depth crossing multiple layers of a groundwater flow model. The Multi Aquifer Well (MAW) package came as a solution for this complex behaviour of layer interaction in Modflow. Model Muse with Modflow6 can implement the MAW package with ease.

This tutorial shows the complete procedure to set up a MAW well on a 3 layer groundwater flow model, gives an overview of the package options and represents the well heads and well rates with scripts in Flopy.

October 16, 2020

Geospatial triangular interpolation with Python, Scipy, Geopandas and Rasterio - Tutorial

October 16, 2020/ Saul Montoya

Under the concept of “applied geospatial Python” we have developed some procedures / tutorials of some common spatial analysis tasks done on desktop GIS software. The aim isn’t to reinvent the wheel but to explore the current Python tools and libraries that can create, analyze and represent both vector and raster spatial data.

Triangular interpolation is one of several types of interpolation techniques available in both Python and GIS software, however the advantage of working with Python is that the interpolation is a function where you can get the interpolated value on a specific point while in GIS software you are required to create a raster and sample values from the raster (.. as far as we know).

We have created a tutorial with a complete procedure in Python to import points with elevation as a attribute, creates a triangular interpolation function and has two spatial outputs: an interpolated geospatial raster in TIFF format and a shapefile with elevation attribute for another set of points. The tutorial uses several Python libraries as Matplotlib, Rasterio, Geopandas, Scipy.

October 08, 2020

Geospatial crop counting from drone orthophotos with Python, Scikit Learn and Scikit Image

October 08, 2020/ Saul Montoya

Orthophoto from drones provide us aerial imagery with spatial resolution in the scale of centimeters. With this high definition and cheap ortophotos we can interpret, analyze and quantify objects on a horizontal distribution by means of machine learning libraries for image recognition and cluster analysis. We have done an applied example of plant recognition and counting from a drone orthophoto with Python and the machine learning libraries Scikit Learn and Scikit Image. The whole process is geospatial, as it works with raster and shapefiles and results are finally displayed on QGIS.

May 9, 2024

Diploma in Groundwater Modeling with Python and FloPy - Asynchronous

FloPy is the Python library that builds and executes MODFLOW models; this library has been enhanced to provide full support of MODFLOW 6 with most of its recent development is related to functionality for MODFLOW 6, tools to use vector and raster spatial data and common plotting and export functionality.

May 8, 2024

25% Off: Diploma in Applied Groundwater Modeling with MODFLOW and Model Muse - Asynchronous

We have designed a complete program on MODFLOW with Model Muse that ranges from the essential topics in flow and transport modeling to applied cases of regional modeling, infrastructure projects, and seawater intrusion. MODFLOW with Model Muse is a recent open-source software that provides various tools for simulating the groundwater flow regime in different environments.

30% Off: Program in Hydrological Modeling with SWAT+ and QGIS - Asynchronous

This program is designed to provide systematical learning from the most basic and general topics to intermediate and advanced topics, allowing the student to understand the various steps in developing hydrological models using the SWAT+ interface for QGIS. This program has a series of theoretical and practical concepts that allow the student to process spatial data, manage meteorological databases, build hydrological models, develop sensitivity analyses, and perform manual and automatic calibrations using versatile tools such as SWAT+ Toolbox, SQLite, and Python.

September 9, 2026

Benchmarking mf6Voronoi v0.0.38: Parallel Performance, Scaling Limits, and Mesh Refinement Dynamics

With the upcoming release of mf6Voronoi v0.0.38, optimizing mesh generation workflows remains a top priority. Constructing complex unstructured Voronoi grids for MODFLOW 6 can become computationally intensive as spatial resolution increases. To address this challenge, parallel execution capabilities were introduced into mf6Voronoi leveraging dask-geopandas.

August 20, 2026

Geopandas tools for the representation and analysis of water chemistry data - Tutorial

This tutorial explores a powerful interactive GeoPandas tool that facilitates the visual analysis and representation of water chemistry data. Through this Python workflow, you can display sampling points over satellite imagery and various basemaps, map concentrations using automatic color scales, and adjust marker sizes based on analyzed parameters. This direct integration allows you to customize the variables displayed on hover, streamlining data evaluation for baseline studies or water pollution diagnostics.

July 23, 2026

How to Interpolate Over 2 Million Points Quickly and Without Freezing - Tutorial

Interpolating large volumes of spatial data through the QGIS graphical interface is often a headache: the process takes too long or, even worse, the program freezes while consuming all system resources. In this tutorial, we will show you how to interpolate nearly 2 million points in less than two minutes using the OSGeo4W Shell and GDAL commands with the IDW method. By creating a virtual layer file (.vrt), you will learn a highly efficient, reliable, and lightweight workflow that enables you to work with millions of data points without being constrained by the limits of the GUI.

July 17, 2026

Plotting Water Surface Elevation from a 2D HEC-RAS Model using Python - Tutorial

This tutorial demonstrates how to accurately and efficiently extract the water surface elevation at a specific point from a HEC-RAS 2D unsteady flow model using Python in Jupyter Lab. Since water levels vary across the mesh and native software tools can limit automation, the author teaches how to open HDF5 output files (.hdf), load a point shapefile using GeoPandas, and apply a geospatial index K-d tree to locate the nearest computational cell. Finally, the time series data is processed to generate a water level hydrograph, which is essential for hydrogeological model calibration.

July 2, 2026

Advanced Crop Water Demand Modeling: Simulating ETo, ETc, and ETa with Python and pyfao56 - Tutorial

estimations of crop water requirements. This applied case offers a deep dive into modeling crop evapotranspiration using the standardized FAO-56 Dual Crop Coefficient methodology, implemented programmatically through Python.

Using a real-world case study of olive cultivation (Olea europaea) in the hyper-arid coastal desert of Bella Unión (Arequipa, Peru), we will demonstrate how to build an end-to-end hydrological data pipeline. Participants will learn how to integrate spatial data, process satellite-derived and weather station climate parameters, define soil-water-crop constraints, and simulate complex deficit drip-irrigation schedules.

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