From the latest developments in our codes, MF6 and Flopy we have created tools in Tupac Cloud for 3d mesh generation as Vtk files. This is an applied example of this functionality based on a dataset for river - aquifer interaction where the resulting Vtk are plotted on Paraview.
Read MoreTupac Cloud is our developing online groundwater modeling platform. Models on Tupac Cloud are based on Voronoi meshes and constructed in MODFLOW 6 DISV from Flopy scripts. The whole project will have lot of tools and integrations with QGIS and Paraview, this is just an example of mesh generation for an applied case of river aquifer interaction.
Read MoreQuadtree refinements are available for Modflow 6 models in the latest versions of Model Muse. This tool can be inplemented for many spatial objects as points, lines or polygons where you can specify the refinement level for each layer separately. We have done an applied case of mesh refinement of a regional model where the river network, observation points and tunnel aligment were defined as refinement objects.
Read MoreModel Viewer for Modflow 6 was launched in April 2022 and it is a version of Model Viewer customized to display the features, grid and results of MODFLOW 6 models. We have done an applied case for the visualization of a MODFLOW 6 DISV model that has a voronoi mesh. The tutorial covers the steps to visualize the model grid lines, grid shell, isosurfaces, color grid, flow directions among other visualization options.
Read MoreWe are allways on the research of new visualization tools for groundwater models and that would imply the review of different apis, codes and backends. This time we have done an applied example for the interactive generation of cross section from a Modflow 6 model with a voronoi mesh on a Jupyter notebook. The cross section shows the model grid, head distribution as a color grid and contours and its generated from the line delineation over the 2d view of the model grid. The code can be easily adapted to any Modflow model by editing the Python and Flopy code.
Read MoreWe have developed a version of our Angascancha basin case study that runs on MODFLOW 6 with discretized by vertices (DISV). The model implements a Voronoi mesh that is generated from the basin boundary and river network and the refinement levels are defined by a minimum and maximum cell size together with determined refinement steps. The tutorial is complete in all the steps involving the model discretization, construction, simulation and visualization.
Read MoreThis is an applied example of a fully geospatial groundwater flow model with the MODFLOW 6 Disv discretized by vertices option. Model was constructed with Python and Flopy from a series of shapefiles and it has a progressive refinement for well and river boundary conditions. Regional flow has been simulated as a General Head Boundary and plotting options were developed for the grid and model output representation on areal view and cross section.
Read MoreUntil 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.
Read MoreMODFLOW 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.
Read MoreThis 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.
Read MoreRepresentation 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.
Read MoreModflow 6 has a new approach in setting up observation points and it's essentially different to the previous versions. The OBS6 package works not only with heads and drawdowns but also with flows, so it's also possible to calibrate the model against baseflow or any other recorded flow from a boundary condition directly. We have created an applied case of the implementation of piezometers in a hillslope groundwater flow model in Modflow 6 and Model Muse. The tutorial covers all the steps related to the implementation of the observed points in Model Muse as well as the comparison among simulated and observed heads through scripts in Flopy.
Read MoreA normal distribution of the core versions of MODFLOW as well as its variants, and Modflow-Based particle tracking and solute transport models includes not only the executables for Windows, but also the documentation, source code, test problems and other utility programs. Working with the multiple tools of Modflow implies a huge collection of files that aren’t useful for the simulation itself if you are working on Windows. Modelers working on Mac or Linux had to compile our executable by themselves.
Read MoreUsually we dedicate much time to developing tutorials and sometimes, just a few times, we actually write an article on this blog. Lately, our aim to discover and code is much greater than our impulse to give our opinion. This post is a special case where we write something without knowing if it is written because we are motivated or because there is something that needs to be written. In any case, writing this post doesn’t make us more free or happy... “Es macht uns nicht mehr zufrieden”... because we don´t know much about some things related to human nature.
Read MoreRepresentation 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.
Read MoreMODFLOW 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.
Read MoreBecause 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.
Read MoreCoastal 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.
Read MoreWe 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.
Read MoreThis 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.
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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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.
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.
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.
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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.