What we dont see in the development of open source software for groundwater modeling

Usually 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.

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5 tutorials for crop detection and vegetation delineation with Python and QGIS

Over the last months we have researched the different tools in Python and QGIS available to recognize crops and vegetation as geospatial vector files. We have used a variety of techniques that range from machine learning algorithms with Scikit Learn and Scikit Image to just more innovative band combinations and reclassifications in QGIS. This article shows the summary of the tutorials produced so far that we are sure will be very helpful for GIS professionals and geoscientists.

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Mixing groundwater and seawater geochemical modeling with Phreeqc and Python - Tutorial

Phreeqc can solve geochemical simulations for a specific solution and simulations relying on previous results. We have developed a tutorial that goes through the Example 3 from the Phreeqc documentation in a stepwise approach to simulate groundwater, seawater, the mixing from both and cases regarding the equilibrium with calcite and dolomite. There is a Python class capable of running the input files and parse results incluided on the scripting part of the input files.

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A geospatial Python class for crop recognition over drone orthophoto - Tutorial

Spatial analysis and machine learning sometimes require massive coding in order to achieve decent results such as identifying plants from a drone orthophoto. We wanted to create a simple workflow for beginner and intermediate Python users to work with these libraries without much pain or frustration. This tutorial has the complete procedure to use a Python class that recognizes plants from an orthophoto based on sample points and creates intermediate plots and identifies plants as point shapefiles.

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How to delineate crops from Drone Orthophotos with QGIS - Tutorial

While doing research on machine learning algorithms for drone orthophotos we found that crops can be delineated with just standard QGIS with excellent performance. Based on the addition of the blue and red band divided by the green band we can have a new vegetation index where the most healthy crops have low index values (0-1.5) and the dry crops / barren soil have high values (more than 1.9). This tutorial shows the complete procedure on QGIS to perform the delineation from bean plants on a drone orthophoto with a resolution of 5cm.

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How to make a geological map with QGIS - Tutorial

This tutorial deals with the representation of geological information at regional scale from the Central Beaverhead Mountains, Idaho, US and creates a geological map through a series of processing and representation steps as:

  • Applying styles to geological units

  • Representation of contacts and normal / thrust faults

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How to interpolate geospatial points to contours with Python and GDAL - Tutorial

We have developed an alternative to a common procedure in GIS that is to create contours from a point shapefile but just with Python commands. By the use of Python and the GDAL library we can store this process into a function and perform contours from several point sets or different point queries.

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How to download well info and groundwater levels from the NWIS server with Python - Tutorial

We have developed an applied example to download information and groundwater levels for one well and multiple wells with Python and the dataretrieval package. The tutorial stores information and levels on a csv file an can be easily applied for streamflow and water quality data stored on the NWIS.

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How to make a lake/reservoir volume-elevation curve with Python - Tutorial

Python is a programming language capable of performing calculations for hydrological studies and water resources evaluations. We have done a tutorial for the volume-elevation curve determination of the lake Patillas in Puerto Rico with Python and numerical / spatial libraries as Numpy and Rasterio. Finally, results were compared to the volume-elevation curve form a USGS survey. The procedure was done this time for a lake, but can be easily applied to any reservoir or water body when the bottom elevation is available as a raster file.

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How to make a lake bathymetric map with QGIS - Tutorial

Bathymetric data requires some spatial processing to represent lake bottom elevation contours and lake depth. This tutorial shows the complete procedure to analyse a bathymetric survey on the Lake Patillas in Puerto Rico with QGIS to generate:

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How to make a wind rose with Python - Tutorial

Python is a useful tool for data analysis but also for data representation and as a graphic tool. This is an applied tutorial for the representation of a wind rose with Python from wind speed and direction stored on an Excel spreadsheet. The tutorial explores the options of the library to represent windroses as bars, boxes, polygons or contours.

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Gypsum and Anhydrite solubility calculation with Phreeqc and Python - Tutorial

Tutorial for the calculation of the solubility and thermodynamic stability of gypsum and anhydrite. The example simulates the dissolution of two minerals in a beaker at equilibrium, and the beaker is heated step-wise from 25ºC to 75ºC. Concentrations and saturation indices for the initial solution and the batch reaction are shown as Pandas dataframes and plotted as bar diagrams on a Jupyter Notebook. Finally a plot of the saturation index for anhydrite and gypsum with temperature is generated from an iteration over the batch reaction steps.

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How to display anticlines / synclines in QGIS - Tutorial

There are three essential things for the representation of geological data on QGIS: the spatial geological information, an appropriate symbology and the software knowledge. Once these three things are available, the potential of QGIS to represent geological maps is unlimited.

We have done a tutorial for the representation of synclines, anticlines, overturned synclines and overturned anticlines on the regional scale with QGIS.

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Advances in Modeling Groundwater Flow and Transport with MODFLOW

In 2017, the U.S. Geological Survey released a new core version of the MODFLOW program. This new version, called MODFLOW 6 (the sixth core version), extends the core MODFLOW capabilities to include robust solutions for complex water table problems, support for generalized meshes with focused resolution within areas of interest, and support for multiple models and multiple types of models within the same simulation. In addition to the Groundwater Flow Model, MODFLOW 6 now contains a Groundwater Transport Model, which can run simultaneously with the flow model or as a separate simulation using the results from a previous groundwater flow simulation.

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Seawater speciation modeling with Phreeqc coupled with Python and Pandas - Tutorial

The speciation modeling allows to calculate the distribution of aqueous species in a solution. Phreeqc is capable to simulate this speciation calculation and we are going to demonstrate this capability on a study case of aqueous species in seawater.

We have done a tutorial for the speciation modeling of seawater with Phreeqc that runs under Python in a Jupyter Lab enviroment. The code can run the Phreeqc executable, define the databases and stablish the output files. Results from simulation are available as Pandas dataframes and plots are made for the main components and the distribution of saturation indices.

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How to simulate and visualize output data from a SWAT+ hydrological model with QGIS and QSWAT+

We have done a tutorial that covers the simulation process and output visualization from a basin scale hydrological model in SWAT+. The tutorial imports an existing QSWAT+ project, reviews the main geospatial parts of the model, runs the SWATPlusEditor and imports model results into the database. Finally, the available options for output data visualization in QGIS are explored for HRUs, channels and the whole basin.

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Delineate water bodies (lakes) from Landsat 8 using machine learning with Python and QGIS - Tutorial

The process of retrieving information from satellite imagery could be time consuming and faces challenges like image resolution, feature recognition and user criteria. With the use of machine learning tools we can preprocess images and combine them with standard QGIS tools to delineate objects in a much efficient way.

We have done a tutorial for the delimitation of water bodies as lakes from a panchromatic Landsat 8 image. The tutorial shows a mixed procedure that detects edges with Python and Scikit Image , traces paths with QGIS and the Trace Raster plugin and finally gets the lake extension as a Shapefile.

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How to plot thrust and normal faults in QGIS - Tutorial

A good spatial representation of the geological features requires not only high quality field data but also the right symbology and graphical resources. We can define QGIS as the tool that can create awesome geologic maps but still some resources have to be developed for a massive use. This tutorial shows the procedure to represent normal and inverse faults with symbology included on the input data files.

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How to add a online topography basemap in QGIS - Tutorial

Latest developments in QGIS and online services allows us to create amazing maps in less time. Different types of layers are available XYZ tiles as terrain, satellite, road maps. This time we show the procedure to add 2 types of topograpy layers in QGIS 3 behind geological features.

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How to delineate crop rows with machine learning using Python and Scikit Learn - Tutorial

Drone imagery shows us features on the surface with high precision and machine learning tools allows us to understand and get information from those images. We present a tutorial in Python together with Scikit Learn and geospatial libraries that delineates crop rows on a corn field and provides results as a vector spatial file.

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