We 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 MoreGeopandas is one of the most advanced geospatial libraries in Python because it combines the spatial tools of Shapely, it can create and read different OGC vector spatial data, it can couple the Pandas tools to manage, filter, and make operations over the columns of the metadata, it has the capability to plot geospatial data on Matplotlib and even to Folium among other features. We have developed a tutorial of Geopandas applied to the analysis of flooded areas over the Boise city for a return period of 200 years; the tutorial covers introductory concepts of Geopandas, it will work with point, line and polygon vector data, create plots, simplify vertices and perform geospatial queries over inundated facilities and highways.
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 MoreOne of the greatest new features of the latest Model Muse version is the implementation of the BUY package for variable density and seawater intrusion modeling. The BUY package was already available in Modflow 6 but the resources to build a model was limited to scripts in Flopy or to build the packages for Modflow by hand, now with Model Muse much stress and pain could be relieved to simulate this type of groundwater model much relevant on the current climate change scenarios.
This tutorial shows the complete procedure to implement variable density / seawater intrusion modeling on a simple coastal aquifer with regional flow. The model runs over two steady / transient stress periods of 50 year each and has a cell with of 20 on the intrusion and 15 layers.
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 MoreGempy is an open-source library for modeling geology written in Python. The library is capable of creating complex 3D geological models including structures, fault networks, and unconformities and it can be coupled with uncertainty analysis.
Hatarilabs have developed an online platform to create geological models with Gempy with minimal effort. The online tool is called GempyApp and runs under AquiferApp (aquifer.hatarilabs.com). This tutorial shows an applied example of geologic modeling of 4 layers with a fault. The tutorial covers the steps of point and orientation file input, definition of fault/strats and geological sequence, show data stats and tables, run the geological model interpolation and plot results.
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 MoreAn example that demonstrates the Phreeqc and Aquifer App capabilities to model ion exchange. This example uses the cation ion exchange approach where only the EXCHANGE keyword is used because EXCHANGE_MASTER_SPECIES and EXCHANGE_SPECIES are included in phreeqc.dat database. The model output is parsed as charts and tables and the solution composition and description are calculated and compared before and after the exchange.
Read MoreGenerating 3D visualizations of groundwater models is essential to analyze the flow regime, perform quality checks and see the interaction of the groundwater body with external factors / boundary conditions. The Flopy library has tools to export the parameters, boundary conditions and results that we have modified and compiled within a Python class. The use of this class allows the generation of Vtk files on a friendly way and in few steps. The tutorial also includes a representation of the parameters generated in ParaView.
Read MoreThis is an example of calcite dissolution with kinetics where a simplified rate and initial molality are defined. The tutorial covers creation of an input file for Phreeqc, database selection, Phreeqc simulation in Aquifer App and analysis of processed output data on a Jupyter notebook. Finally the molality of Calcium and pH are plotted with time.
Read MoreSometimes we want to reproduce or want to get something similar to a desktop GIS environment on a Jupyter notebook with options to show/hide layers and select background maps, but there was a missing part on our effort and it was the raster representation.
We have developed an applied case of single band raster representation on a Jupyter notebook with Rasterio and Folium. The raster has to be in WGS84 and the script can be coupled with more Folium features for the representation of vector data, background maps, menus and popups.
Read MoreThis is a tutorial of geochemical modeling in Phreeqc and Aquifer App that uses the REACTION keyword for the simulation of irreversible reactions that transfer a certain amount of elements to or from the solution. The selected example deals with the reaction of rainwater with NaCl and Calcite over 4 steps. Phreeqc simulation and model output analysis are performed on the Aquifer App that has great tools for the model setup and the analysis through interactive menus, tables and charts.
Read MoreSimple tutorial that demonstrates the geochemical simulation of surface water and groundwater, and the mixing of both in predetermined proportions. The tutorial shows the creation of an input file (*.in) for Phreeqc, which is then input into Aquifer App to obtain results for both solutions and for the mixture. The modeling and analysis process in Aquifer App are extremely straightforward since the tables and graphs are generated, allowing for quick comparison of data between simulations.
Read MoreThis tutorial cover all the steps to build and run a geochemical model of a water sample in equilibrium with Fluorite and Gypsum. The tutorial explains the parameters to setup a mineral together with and analysis of the element concentrations, the amount of dissolved phases and the final saturation indices.
Read MorePython has awesome packages for machine learning that can be coupled to groundwater models and perform automatic calibration of hydraulic parameters. This tutorial covers the procedure to implement a neural network based on a set of parameters set with corresponding head values; the study case is on a transient pumping test model with an observation point located around 10 meters away from the pump well. The analysis predicts the calibration parameters from the spatially interpolated observed head values.
Read MoreWe did this tutorial since the documentation or examples on the topic were not available. Flopy can export the model grid and model attributes to shapefile with a coordinate system of reference for the three types of discretizations of MODFLOW 6. We have done an applied example to export the grid of a discretized by vertices model (DISV) to the ESRI Shapefile model. The tutorial also show options for the final grid representation in geopandas.
Read MoreNo more installations, no more database link up, no more raw text data as model output. Aquifer App now can run Phreeqc with great tools for the geochemical model setup, database selection and tables / graphics for the different simulation components.
This applied example calculates the distribution of aqueous species in seawater and the saturation state of seawater relative to a set of minerals and is based on the Example 1 of the USGS Phreeqc example documentation.
Read MoreThis tutorial covers the whole procedure to perform a sensitivity analysis over a 72 hour pumping test plus recovery on the hydraulic response in an observation piezometer located at 11 meters from the well. the Since the study case it’s a transient model the sensitivities will vary over time and stage of pumping/recovery.
Read MoreHaving a geological model can enhance numerical models since it allows to represent higher accuracy the potential distribution of hydraulic parameters in the horizontal and vertical direction. The process to implement/insert a geological model into a Modflow model is a challenge due to restrictions on proprietary software and spatial tools; we have done the whole procedure to insert a geological model into a MODFLOW-NWT groundwater model with scripts in Python, Pyvista and others.
The code extracts the cell centroids of the modflow model and then compares its position with the different geological units exported from Leapfrog to Vtk. Once the corresponding lithology of the cell is identified a hydraulic parameter is assigned. The tutorial works from Vtks of a geological model done in Leapfrog, but it can work with any Vtk.
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