Python can communicate with other softwares through standards in Windows (COMs) and thus provides a higher level of interoperability for river flow models made in HEC-RAS. The amount of tools provided by HEC-RAS through the COM is huge; in this tutorial we will cover some examples of HEC-RAS model interaction for two applied cases from Python scripts in Jupyter Lab.
Read MoreThis is an applied case were we build a geological model only with lithology information stored as a point shapefile. The tutorial covers all steps from raster (array) generation for all surfaces together with the orientation sampling and format of surfaces/orientations as Gempy input files. The generated data was inserted in the Aquifer App that implements an interface to create Gempy models. Finally the lithology and layer surface geometry was exported as Vtk to be represented on Paraview with the initial data to evaluate the accuracy of the simulation.
Read MoreAquifer App offers a friendly, clean and powerful way to create Gempy scripts for geological modeling. We have developed an applied case of a 3D petroleum system model for a part of the Williston Basin, USA that contains the Nesson Anticline. Top layer information was provided as raster format where elevation and orientation for random points were extracted with Python codes using the Gemgis package and exported in Gempy input file format. On Aquifer App the processed CSV files were inserted and the geological model was set up with the corresponding geological sequence.
Read MoreNetCDF has become a popular choice for storing and delivering precipitation and water resources related data. Its capacities to store multiple geospatial raster layers over time allow another level of abstraction on data analysis, however the format is of limited use on normal desktop applications and most times we are required to use a programming language such as Python or R.
Read MoreAquifer App offers a friendly, clean and powerful way to create Gempy scripts for geological modeling. The platform also allows users to run the scripts and download the whole modeling project that has the 3D geometry of the geological units and faults in Vtk format. This tutorial shows an applied case of geological data visualization, model creation, model run, export and representation of the Vtk files in Paraview.
Read MoreThe coupling of Python scripts with the Aquifer App platform allows us to generate geological models with a versatility not seen before. This is a basic example of regional geological modeling in Aquifer App with surface topography from a digital elevation model in TIF format. The tutorial also makes a 3D representation of the contacts and orientations of the one layer geology in a Jupyter notebook for better analysis of the geological sequence.
Read MoreThe coupling of Python scripts with the Aquifer App platform allows us to generate geological models with a versatility not seen before. This is a basic example of geological modeling of an recumbent fold in Aquifer App that can create models using Gempy. The tutorial also makes a 3D representation of the contacts and orientations of the layers in a Jupyter notebook for better analysis of the geological sequence.
Read MoreSimulation of direct precipitation events over a surface is important to assess the impacted areas and manage disaster situations. Response to precipitation is evaluated over cells in a 2D model and runoff is routed to the stream networks. Landlab is a Python library for a variety of surface processes and can model shallow water flow over topography with a variety of algorithms. We have developed an applied case of direct rainfall for flood modeling over a geospatial raster where an initial water height is applied and then flows over the surface. Resulting water heights are exported as geospatial rasters.
Read MoreThe coupling of Python scripts with the Aquifer App platform allows us to generate geological models with a versatility not seen before. This is a basic example of geological modeling of an anticline structure in Aquifer App that can create models using Gempy. The tutorial also makes a 3D representation of the contacts and orientations of the layers in a Jupyter notebook for better analysis of the geological sequence.
Read MoreAn applied case for the recognition of missing crop vegetation areas based on a drone orthophoto. Contours have been identified from an enhanced combination of raster bands with a marching squares method to find constant valued contours and then exported as geospatial polygons.
Read MoreWatershed delineation and stream network determination are common tasks on the hydrological analysis for any area of interest. There is a parameter on the stream network determination that allows us to have simple stream networks that resemble the main water courses or dense stream networks that map all the permanent / temporary streams. This is an applied example of stream network determination on our online platform Hatari Utils where you can specify the number of upstream cells and interactively review the result.
Read MoreThe coupling of Python scripts with the Aquifer App platform allows us to generate geological models with a versatility not seen before. This is a basic example of geological modeling of two horizontal layers in Aquifer App that can create models using Gempy. The tutorial also makes a 3D representation of the contacts and orientations of the layers in a Jupyter notebook for better analysis of the geological sequence.
Read MoreGroundwater model creation requires a complete set of spatial data for the different hydraulic parameters, boundary conditions and other model items. Vector and raster data need to be preprocessed, converted, reprojected to fit the requirements of Model Muse.
This tutorial covers an applied case of raster and vector data processing for a basin.
Read MoreHydrological basins could have a diversity of shapes due to the morphology and it´s a challenge to have a process that can delineate basins with different characteristics in a short amount of time. Hatari Utils is an online platform for hydrogeological analysis that has a tool for basin delineation, in this tutorial we have tested the capabilities of Hatari Utils to delineate a basin that has an internal lake.
Read MoreComplex geochemical simulations are entirely possible to be performed with Phreeqc coupled with Aquifer App and Python. Brines can be simulated at different concentrations to obtain relations that are input of other variable density flow models. In this case we have model one brine, sodium bicarbonate, with the REACTION keyword with moles values that range from 0.5 to 12 moles. Values of mass, volume, concentration, and density were processed in Python from the dataframes generated from Aquifer App.
Read MoreWe define evaporation as the process of removing water from the chemical system in Phreeqc and this can be achieved with the REACTION keyword and a negative reaction coefficient. We have developed an applied case of water evaporation from precipitation water and the mix of the resulting water to restore the original volume. The whole Phreeqc setup, simulation and result analysis process has been in Aquifer App.
Read MoreWater resurces management requires not only some direct values as precipitation amounts but also more elaborated data as days without rain. Based on the CHIRPS dataset for year 2022 stored on NetCDF format we have elaborated a map of days without rain for a given country and exported the results as a fully geospatial raster. There is a particular discussion about the data type and the data value to calculate and store value just for the selected location.
Read MoreDelineation of watershed and river network is one of the most common tasks in modern hydrology but it might comprise a group of steps on a desktop software that take several minutes to perform. We wanted to recreate the process in an mostly automated workflow in an online platform that substantially reduces the amount of time involved in the process.
We came up with a solution on Hatari Utils (utils.hatarilabs.com) that allows us to delineate a basin of 530 km2 in just 52 seconds. Results from the platform also include the river network and the main river and are available as geospatial ESRI shapefiles.
Read MoreEven though that the version 5.2 was released on March 22 2024 we just found time to make a video explaning the new features of this version and where they are implemented on the graphical user interfase. This new version of Model Muse allows to simulate variable density and variable viscosity flow among other features of Modflow 6. Have a look on the video and wait for our comming applied tutorials related to these new features.
Read MoreMachine learning can be applied to many fields as land cover classification from remote sensing imagery. The performance and accuracy of classification will depend on the number of raster bands, the image resolution, the land cover type and the algorithm used. This tutorial will perform an applied case of land cover classification from a panchromatic image in Python using the Naives Bayes algorithm implemented on the Scikit Learn package. The classification will cover four categories as: rivers, river beaches, woods and pastures; coding is performed under a Jupyter Notebook with Python running from a geospatial Conda environment. Some graphics and statistics about the classification precision are also included on the tutorial.
Read MoreHatarilabs presents its educational program designed for mastering Python in real professional and academic environments. The program has an extensive practical work that goes from the basic concepts of Python, Numpy and Pandas to specific applications in water resources and geosciences coupled with geospatial analysis and machine learning.
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.
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.
ONLINE COURSES:
Phreeqc is a software developed by the USGS written in C++ capable of modeling a variety of aqueous geochemical processes such as mixing of waters, modeling equilibrium between solid and aqueous phase, modeling impact of temperature, calculation of element concentration among others.
Hatarilabs has developed an applied and unique course of Phreeqc integrated with Python undes a class (object type) that can run, parse and provide Phreeqc output as Pandas dataframes and integrate it to plots and further analysis with other Python libraries on a Jupyter notebook.
HEC-RAS is a software designed to perform hydraulic 1D and 2D calculations on river channels either natural or man constructed. It allows steady flow, unsteady flow, sediment transport and water quality modelling. It is developed by the US army corps of engineers, US Department of defence and it is openly available software. The HEC-RAS steady flow is based on one dimensional energy equation, while for the unsteady flow, HEC-RAS uses an implicit, finite difference method to solve the fully dynamic Saint-Venant equations.
The objective of HEC-RAS is to solve river dynamics and river engineering problems. Applications are delimitation of flood areas, embankment and protection work design, river restoration, emergency plans for dam break, optimization of hydraulic work and risk assessment and management.
This course develops the main functions and applications of the latest version of the MODFLOW 6 groundwater modeling code through the ModelMuse interface, both developed by the United States Geological Survey (USGS). This version includes innovative tools for the construction and simulation of hydrogeological models, mainly highlighting the incorporation of the discretization option for discretized by vertices grids.
The development of machine learning and geospatial libraries in Python as Scikit Image, Rasterio and Fiona gave us a new range of tools to analyze vegetation from traditional sources as satellite imagery and new sources as drone orthophotos. The appliance of Python programming for crop identification depends on many factors such as the image resolution, the vegetation stage and even the algorithm setup.
We have developed a course crop identification / delineation with geospatial and machine learning tools of Python, the course is aimed to GIS or related professionals that have basic Python knowledge. The course covers the introductory concepts of the geospatial libraries and a series of machine learning applications for crop indentification in olive trees, palms, agave and corn fields.
Note:
This course is for professionals with previous knowledge of Python. Basic concepts of Python programming will not be covered in the lessons and course material. In case you don’t have any knowledge of Python, we recommend you to take this online course.
The Hydrologic Modeling System (HEC-HMS) is a free program developed by the US Corps of Engineers that implements a series of hydrological methods to represent different physical processes of the water cycle.
HEC-HMS also includes procedures necessary for continuous simulation including evapotranspiration, infiltration, hydrological routing and soil moisture accounting. The tools and options of HEC HMS make it a very versatile and powerful software for the hydrological simulation of different scenarios such as extreme events in arid regions, or water balances in wet climates.
Hatarilabs offers the online course of Hydrological Modeling with HEC-HMS for students and professionals of any country. The course is focused on theory and practical to know the different HEC-HMS tools and its application to the hydrological modeling.
Hatarilabs offers the online course of Hydrological Modeling with QSWAT for students and professionals of any country. The course is focused on the acquisition and preprocessing of data for SWAT+ using QGIS 3.4 for develop hydrological watershed modeling.
This course covers the whole procedure of developing regional groundwater models through the ModelMuse interface, including the model construction, boundary conditions, parameter assignment, model simulation, results analysis and visualization, and model calibration. Flopy is also introduced in the course to import, create, refine and simulate the model as in ModelMuse. Two basins with different aquifer setting and boundary conditions are used as case studies to demonstrate the use of these tools so that the participants learn how to build these models and analyze the results for future decision-making.
Evaluation of long term impacts of the mining activity is a key topic on the public concern and regulatory and sustainability policies. Due to the scale of the mining projects and the different related activities, impacts could be made to several parts of the physical environment. Groundwater modeling is a useful tool for the simulation of mine closure impacts to the groundwater flow system and groundwater quality. Hatarilabs has developed an applied course about the simulation, calibration, representation and impact analysis of a waste dump closure on the environment and water bodies with a long term scope (closure and post closure). The course will be given on Model Muse for flow and contaminant transport modeling and scripts in Flopy for model calibration, water balance analysis and evaluation of remediation techniques performance.
This course is focused on how to use the different packages related to numerical tools, data analysis, representation of graphs, and others. Many of these tools are applicable to the field of Hydrology in the preparation of data for hydrological models, statistical analysis of hydrological parameters and model result representation.
Graphical user interfaces (GUIs) are commonly used to construct and post-process numerical groundwater flow. Flopy is the Python library that builds and executes MODFLOW models; this library has tools and options for the complete geo-referencing of a MODFLOW model.
Python is a simple and powerful programming language; its simplicity is remarkable compared to other programming languages and its power is based on the number of tools available for different areas of study.
Use of Python with the available scientific packages and FloPy, facilitates data exploration, alternative model evaluations and model analyses that can be difficult to perform with GUIs. One advantage of Flopy and Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis.
This course allows acquired knowledge of the open source programming language to construct model input files, run the model, and read and plot simulation results.
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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.
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.
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.
This applied example demonstrates the simulation of unsteady flow around a river island, guiding you through the complete numerical modeling workflow. It begins with pre-processing, covering spatial data import, boundary condition definition, and computational mesh generation. Next, the setup details importing hydraulic loading data from DSS files and optimizing the computational time step based on the Courant condition to ensure strict numerical stability and convergence. Finally, the example features a comprehensive post-processing review of the simulation results, analyzing velocity fields, water surface profiles (stages), particle tracking, and immersive 3D visualizations.
This tutorial walks hydrogeologists through the full workflow of automatic calibration of pumping test data using MODFLOW 6, ModelMuse, and PEST. A real pumping test scenario — comprising a 6-hour pumping phase and an 18-hour recovery phase — is set up in ModelMuse, where the well is conceptualized as a Multinode Aquifer Well (MAW) boundary condition to accurately represent multilayer aquifer interactions. PEST is then implemented to automatically estimate key hydraulic parameters including hydraulic conductivity, specific storage, and specific yield, eliminating tedious manual calibration and delivering reproducible, optimized results. Whether you're new to parameter estimation or looking to streamline your existing workflow, this tutorial offers a practical, hands-on guide to modern groundwater model calibration.
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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.