February 09, 2022

Modeling Land Evolution at Basin Scale with Python and Landlab - Tutorial

February 09, 2022/ Saul Montoya

Climate changes, people change and land also changes with time. We can`t believe that the river networks will remain the same over the next 1000 years or that mountains and depressions will have the same elevation in the next 10000 years. But changes are not related to huge time frames, they can occur in decades or years at lower rates as well. In order to evaluate those changes we need some formulation of the key components of land evolution: fluvial, hillslope and uplift. We have developed a tutorial with Python and the Landlab library to simulate the land evolution at basin scale for 100 thousand years; inputs come from geospatial rasters and output data is exported as Ascii raster files.

January 11, 2022

How to export MODFLOW head contours as Shapefiles with Flopy - Tutorial

January 11, 2022/ Saul Montoya

The quality of a groundwater model as a tool for sustainable management of our groundwater resources doesn´t on the quality of the input data, the accuracy of the calibration but also on the visualization of the output data and analysis of the water budget. There are several options to export contours from MODFLOW GUIs as Model Muse, however when analyzing several stress periods the graphical steps could be time consuming therefore a Python script would be helpful to export heads or water table as shapefiles.

December 28, 2021

VOCs and PFAs Interactive Spatiotemporal Representation with Python and Folium - Tutorial

December 28, 2021/ Saul Montoya

Analysis of groundwater chemistry is a difficult task for the limited set of monitoring samples, the limited samples and the limited analized components. In order to assess the actual extension of a contamination plume or the efficiency of remediation techniques we need new and innovative methods to plot and analyze water chemistry data with open source data. We have done an applied case of interactive VOCs and PFAs representation on a Jupyter notebook with Python, Folium and Ipywidgets. The dataset has more than 3300 samples of 127 points over a period of 30 years and corresponds to a contaminated site of a former airfield.

December 16, 2021

Mplleaflet vs Folium to plot your weather stations on a Jupyter Notebook

December 16, 2021/ Saul Montoya

When analyzing climate data or any other geospatial data on a Jupyter Notebook, we need to plot points, lines and polygons interactively. Based on our own way to learn Python, most probably we will use a library that we found on Google or Stackoverflow however there are some undercover issues on the library selection that we will discuss in this article.

December 10, 2021

How to install Python - Geopandas in Windows on a Conda Environment - Tutorial

December 10, 2021/ Saul Montoya

Geopandas is an amazing library for spatial analysis since in combines the spatial tools from Shapely and Fiona with the versatily of Pandas Dataframes. We are aware that most geoscientists, water resources specialists and related professionals work on Windows, therefore we are always in the search of new ways to get Python working with all its geospatial capabilities in every computer. We have created a tutorial that shows the installation process of Geopandas and other Python geospatial libraries in Windows by the use of a Conda environment.

December 03, 2021

Radial plots for exploratory analysis of climate data with Python and Matplotlib - Tutorial

December 03, 2021/ Saul Montoya

On the development of hydrological evaluations, there is a need to assess which weather stations will be used for the numerical modeling stage. The main acceptance criteria would be the amount of climate variables and records available however huge areas could have docens or hundreds of stations delivered in one text file. This tutorial shows the procedure to plot climate variable records from a single text file on a polar plot with aperture angle related to value statistics. The tutorial is done with standar Python packages as Matplotlib, Numpy and Pandas.

December 01, 2021

Applied case of hydrogeological conceptual modeling on a hillslope area with QGIS

December 01, 2021/ Saul Montoya

In order to understand the relationship between groundwater flow and slope stability, a study area over a hotspot in the US. Landslide Inventory was selected. The geology, groundwater wells, elevation, and climate conditions were reviewed to develop a hydrogeological conceptual model that will be the basis for a numerical model of the groundwater flow regime. This webinar deals with the review of available spatial data related to the groundwater flow regime on a hillslope area at Mukilteo city, Washington, US. Information from geology, meteorology, observation data and boundary conditions will be discussed in a QGIS session with regards to the construction of a groundwater numerical model in MODFLOW.

November 10, 2021

Data extraction and spatial / 3D representation from BGS borehole data in AGS format with Python

November 10, 2021/ Saul Montoya

Open lithology datasets are scarce and most times they come in certain exchange formats that can´t be easily coupled with other softwares. Python has the tools to read and extract data from those files and provide them in more friendly formats as csv or xlsx. With the use of spatial libraries as Fiona or 3D visualization libraries as Pyvistas we can go one step further and process our data as shapefiles or vtks.

November 08, 2021

Two open geological modeling softwares that you should know about

November 08, 2021/ Saul Montoya

For geologists, hydrogeologists, geostatistics, petroleum engineers, and other related professionals the choice for 3D geological modeling software was related to expensive and restrictive software that was in fact a “de facto” choice in several companies and institutions.

Although it is a choice of any company or professional to select the software anyone will use to model the geological units, a great gap subsides (using a geological term) on the use of this expensive software. If the software is expensive, how expensive will it be to get trained on this software? If few people have skills with certain software, how easy would it be to change to another software? How people can assess the quality of one software if they have no full capability on managing several softwares. As you have seen, restrictions on the licenses lead to these subsiding gaps, faults on quality, and an intrusion of professional ignorance.

November 03, 2021

The best Youtube channels in QGIS (and open source GIS tools)

November 03, 2021/ Saul Montoya

Education is aimed to acquire knowledge and it's based on the learning process and as any process has some steps and means that have to be analyzed. Traditionally, if you want to get knowledge you can go to a university, get a degree, visit a library, but why don’t you just check a Youtube channel; will you get the same knowledge? Will you do better research with what you learned on video? Those are excellent questions to pose in these times where we need knowledge that shapes our future in the context of climate change.

October 25, 2021

How long does it take to develop a groundwater model for my research project / master thesis?

October 25, 2021/ Saul Montoya

Developing a hydrogeological research project that considers groundwater modeling for a bachelor thesis or a master thesis requires you to take into consideration several topics, such as input data, hydrogeological knowledge and time to learn the software in order to provide a numerical simulation that reaches the objectives of your research project.

Learning a software for groundwater modeling should be easy as developing some tutorials and playing around with your own data; however it is not that easy since it involves the review of lots of documentation, have strong knowledge in hydrogeology and numerical modeling and deal with uncertainties and numerical unconvergences.

October 21, 2021

Fill Missing Precipitation Data with Machine Learning in Python and Scikit-Learn - Tutorial

October 21, 2021/ Saul Montoya

Evaluation of hydrological processes as evapotranspiration, runoff, routing and infiltration require data as precipitation, flow, temperature and radiation on a daily basis. Required data for hydrological modeling need to be accurate and must be completed over the study period. It is common that historical data from hydrological stations are incomplete and has many gaps that can be filled by the use of machine learning algorithms like Scikit-Learn in Python3. This tutorial shows a applied procedure to run a complete script for the filling of missing precipitation in one station by the use of data from 2 nearby stations. The script will be run on Python 3.9 on a Anaconda Prompt environment.

October 04, 2021

New website! MODFLOW Questions and Answers: ask anything on groundwater modeling

October 04, 2021/ Saul Montoya

Until now we had limited options to provide specific support in groundwater modeling. We know that modeling requires the review of extensive documentation and practical work with the software and sometimes or most times we don't have the time to sort things out.

September 17, 2021

The Groundwater Project as a source of free books in basic and applied hydrogeology

September 17, 2021/ Saul Montoya

We usually received some emails and messages regarding basic or reference books and publications in Hydrogeology and we didn't have any reference of free and high quality material until we knew about the Groundwater Project. It´s true that we found the project website some months ago, but it was at the latest IAH conference where we had a presentation with a complete overview of the program.

September 15, 2021

Example of Seawater Intrusion Modeling with Modflow 6, Model Muse and Flopy - Tutorial

September 15, 2021/ Saul Montoya

MODFLOW 6 implements the Buoyancy package for the simulation of variable density and seawater intrusion cases. The tools are implemented in the Python package Flopy, however the workflow has changed substantially from the previous models of flow and transport. We have developed an applied case seawater intrusion model on a regular geometry model constructed with Model Muse for flow and Flopy for transport.

August 23, 2021

What to do when your MODFLOW MT3D contaminant plume doesn’t migrate?

August 23, 2021/ Saul Montoya

This is a problem that every hydrogeologist - numerical modeler has faced many times over his/her professional career independently from the theoretical background and skills with the code, graphical user interface or Python library.

We don’t know why groundwater “flows” and a contaminant plume “migrates” when both move on the aquifer system. After you construct you model geometry, setup the flow boundary condition, specify your transport package, define your contaminant sources, run your MODFLOW flow model and then run your MT3D model (or even your MT3DMS model) you will find that there is no plume, none, nada, nichts.

August 18, 2021

Open source groundwater software besides MODFLOW - Updated July 2023

August 18, 2021/ Saul Montoya

A special concern arises from the gap between the stage of development of open source groundwater software and the actual capabilities of the common groundwater modelers (we mean, the main group of modelers). Even though we are passionate about software we don’t find the time or the right momentum to have a real experience with those codes.

From our research, we have listed the top open source groundwater software with a brief summary of the capabilities and useful links. We have to mention that there are some packages that can simulate groundwater flow in software like OpenFoam; however, those variants are not listed here.

August 16, 2021

Is glTF an alternative to VTK for the representation of voronoi mesh Modflow6 models?

August 16, 2021/ Saul Montoya

Representation of geospatial objects in 2D are well covered by the GIS software and standards where we have powerful tools and interchangeable spatial files, however when we work on 3D objects the universe of software and tools is like a jungle with a wide variety of issues. We will always consider 3D as the ultimate representation of an object using a computer, by sure the holograms and augmented reality can improve the way we interact with a object geometry, but since we are not in the common near future we will give much effort to the representation of these objects in our computer screens, tables and cellphones.

August 10, 2021

How to reproject single and multiple rasters with Python and Rasterio - Tutorial

August 10, 2021/ Saul Montoya

Raster reprojection is a common task on GIS analysis however to do it with only Python commands has some challenges. We have done an applied example of raster reprojection for single and multiple rasters from WGS 84 UTM to WGS 84 Geographic. The codes work on monoband and multiband rasters and can reproject from to any projection by specifiyin it EPSG code.

The tutorial is done on a conda enviroment that has the geospatial libraries installed. You can set up the environment by following this tutorial:

https://hatarilabs.com/ih-en/how-to-install-python-geospatial-libraries-gdal-fiona-rasterio-etc-under-a-conda-env-in-windows

August 02, 2021

Tutorial to do a tutorial in open source software for water resources

August 02, 2021/ Saul Montoya

Let's have a look at the tutorial concept in its real dimension. A tutorial is a period of instruction that provides practical information about a specific topic. The tutorial can be given by an individual or institution and has a goal to teach you something or master you in something you didn't know before.

However in water resources software, we don’t see the tutorial as a part of the documentation or a key part of the learning experience. The tutorial is in fact an essential part needed to understand the whole capabilities of the software in practical exercises. It´s true that most software delivery exercises of different applied cases, but we can’t say they are tutorial in fact because those exercises lack a perspective of guided work.

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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