Example of Transient Groundwater Flow Modeling with MODFLOW 6 - Tutorial

Based on the new file format and keywords from MODFLOW 6 it is more simple to understand a model while inspecting the input files. This tutorial show a example of a steady and transient flow model in MODFLOW 6 for a period of 30 days divided into 4 stress periods. The tutorial has a introduction to the model geometry, input files and boundary conditions, a model simulation in transient flow conditions and output visualization as VTU files in Paraview. The tutorial also includes a discussion on the water balance from the groundwater flow system at the end of the simulation.

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Basic Example of Groundwater Modeling in MODFLOW 6 and Visualization with Paraview and Flopy

Basic tutorial to learn the procedure to build, simulate and represent a MODFLOW 6 model. The tutorial shows a introduction to the model file system on steady state conditions. The model for this tutorial is implemented with the following boundary conditions: Drains, Recharge, Wells, and Constant Head. The grid is regular with a width of 50 meters and it has 30 rows and 24 columns; the model has 4 layers and a total thickness of 130 meters. The model is called "hatari01" and is inspired in the "twri" model from the MODFLOW 2005 documentation adapted to MODFLOW 6. The model defines a constant horizontal hydraulic conductivity as well as vertical conductivity. After the simulation a Python code is run on a Jupyter Notebook to create the Unstructured VTK files for the heads, water table and boundary conditions representation as 3D objects in Paraview.

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Non Overlapping Areas Determination from Multiple Layers with QGIS and PyQGIS - Tutorial

Geospatial process are involved in most part of our activities; because of that it is important to optimize the time spent by the GIS specialist and to improve the quality of the spatial analysis. PyQGIS is the Python extension in QGIS, this framework allows us to manage the QGIS tools together with Python functions and even with external Python packages improving the speed and quality of our geoprocessing and spatial representation. 

In this tutorial we will show the complete procedure to determine the non overlapping areas of an area of interest from 7 different layers.

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Clip Multiple Layers in QGIS with PyQGIS - Tutorial

Interesting tutorial to clip multiple polygon layers in QGIS with the Python console. The tutorial also shows a code to upload all files from a directory and store them as objects in a Python dictionary.

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Enhanced MODFLOW Result Representation with Python, VTK and Paraview - Tutorial

MODFLOW model output representation is key to understand the groundwater flow regime, to study the interaction with surface water and depending ecosystems and to evaluate the impact to anthropogenic and climate change requirements. Until now, there has been few open source software capable of generating3D representations and those software had limited options for color scales, cross sections and other graphical tools. On the research for more options we found Paraview, a open source software for data representation designed to analyze extremely large datasets using distributed memory computing resources.

In order to represent MODFLOW output into Paraview, a VTK file for unstructured grids is needed, this VTK type is called VTU where the "U" comes from unestructured. The tutorial show the complete procedure to process a MODFLOW model output into a VTU file and the representation in Paraview.

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How to plot MODFLOW Head Output in Paraview with Python - Tutorial

MODFLOW computes the groundwater heads over a porous / fractured media upon a series of boundary conditions as recharge, evapotranspiration, drains, well and others on steady and transient conditions. Free and commercial software is available for the MODFLOW model construction and MODFLOW output representation. Despite the fact the capabilities of these softwares, there are some gaps in data processing and representation; isometric views, animation and custom cross sections are still difficult to achieve under the existing tools, specially on multilayered models with transient conditions over series of time steps and stress periods.

There is a particular open source software for data representation that is of our interest, it is called Paraview (paraview.org). This visual application was designed to analyze extremely large datasets using distributed memory computing resources, in fact the term "para" in Paraview comes from the parallelization of computer cores.
 

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Introduction to GeoJSON and its advantages compared to ESRI Shapefile

When dealing with spatial data for a project or a study sometimes the data format and data interoperatibility can be key to the success of the research or the map quality. For decades the ESRI Shapefile has been the most used format to exchange and to work with spatial data. From the Internet development a new geospatial data interchange format has been created to represent geographic features, their properties, and their spatial extends. This tutorial is a introduction to the GeoJSON data format with a practical work in QGIS 3 and a comparison of spatial data in both GeoJSON and ESRI Shapefile formats.

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How to import a Water Table from MODFLOW in QGIS with Python - Tutorial

Advances in groundwater modeling with MODFLOW allow us to have higher refinements on the representation of the water heads and water table as well as more capabilities in the representation of physical process related to groundwater flow. On a regional scale, we can deal with models of more than 500K elements and most times we need to represent this data on a GIS software for further study or the creation of figures for the end users, stakeholders and reports. By the use of Python scripts we can speed up the process of model output representation on a GIS software as QGIS.

Python scripts can be a little bit long and very declarative, but the process time is much smaller than the traditional clicking process on the GUI interface. The purpose is to store these scripts and use then every time one have to process the MODFLOW output data. 

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Fill Missing Precipitation Data with Artificial Intelligence (Python Keras) - Tutorial

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 the hydrological modeling need to be accurate and must be completed over the period of study. Many times historical data from hydrological stations are incomplete and present many gaps that can be filled by the use of Artificial Intelligence tools as the Keras library in Python.

This tutorial show the 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 Python script is done on a Jupyter Notebook.

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Sedimentation Tank Design with OpenFOAM - Tutorial

Drinking and residual water treatment, water intake into hydroelectric power stations or water treatment for industrial processes require the removal of suspended particles by sedimentation tanks. These hydraulic structures have a slow speed water inlet and a geometry that allows the decantation or precipitation of sediments along the settler path.

OpenFOAM is a open source software for Computational Fluid Dynamics (CFD) modeling with a series of solvers for different flow conditions. In this case we have used the driftFluxFoam solver to represent sediment precipitation in a sedimentator in a transient simulation of 6400 seconds. The tutorial contains 2 videos with the model description and its simulation.

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Basic Example of a MODFLOW Model Creation and Simulation with Flopy - Tutorial

Flopy is the Python library to create, run and represent results from MODFLOW models, including support for MODFLOW 6. With Flopy, the model definition and set up of boundary conditions can be done with lines of Python code, and some Python tools of optimization and machine learning can interact with the MODFLOW models. This tutorial show a basic example of model creation, configuration and simulation in Python 3 on a Jupyter Notebook. The tutorial also shows the procedure to import the MODFLOW results done with Flopy in Model Muse.

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Crop Yield Assessment from Photos with Python and Scikit-Learn

Evaluation of crop yield can be tedious because sampling methods requires the actual counting of fruits for a whole tree or canopy area. If we want to optimize this time demanding task we can use new and open source machine learning algorithms available. We have selected Scikit-Learn for this tutorial, a machine learning library in Python for it ease to use, the available documentation and the sort of available tools. 

The tutorial covers the whole procedure of image representation, point of interest selection, template matching, cluster analysis and fruit counting. Python scripting was done in Jupyter Notebook, it is interactive and allows the user to add more points of interest or remove inaccurate points.

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How to Convert a Matrix in a Geospatial Tiff in QGIS with PyQGIS - Tutorial

Raster are matrices with geospatial reference. In order to make a finite difference model or any other model compatible with QGIS we have to process the matrix with its parameters to be represented as a spatially referenced raster. The process involves some Python scripting on the QGIS console, processing time is low and the process can be applied for many matrices without visual representation of intermediate files that saves computational time and resources.

This tutorial show the complete process of matrix construction, parameter calculation and spatially representation in the Python console of QGIS.

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How to convert GTIFF to STL for Topography Representation in OpenFOAM Models

For OpenFOAM modelers the representation of topography can be painful due to the unstabilities and complexities of the Bezier Surfaces in Salome Platform. It is more stable to create the mesh by importing a full textured surface on a format file compatible with Salome. This tutorial show the process to create a STL file from a GeoTiff(.tif) file by scripts in Python. We have used the OSGeo4W Shell that comes with the normal QGIS instalation because it comes with the gdal library already installed.

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How To Create Line From Points in QGIS with PyQGIS and Pandas - Tutorial

Python scripting allows us to enhance the data management and spatial analysis in QGIS. Most times, spatial data comes from a variety of data providers in a sort of formats and data types that we have to be adapted to the GIS standard. Big data and continuos monitoring create large datasets that have to indexed, sorted and manipulated in a effective way.

QGIS has a Python console and the capability to install external Python packages that run on QGIS session. This time we have installed Pandas in QGIS to handle the data from a sensing device made on a Raspberry Pi 3 and then we have defined the path as a succession of points with PyQGIS scripting.

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Spatio-Temporal Hurricane Tracking in the Gulf of Mexico with QGIS and PyQGIS - Tutorial

This tutorial show a mixed procedure with native QGIS tools and PyQGIS commands for the data representation, styling and plotting with spatio-temporal criteria with the TimeManager plugin. Data for this tutorial was downloaded from the National Hurricane Center's Tropical Cyclone Reports that contains information as six-hourly positions and intensities. You can access the whole hurricane database o

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How to add multiple Vector Layers and group them in QGIS with PyQGIS - Tutorial

QGIS is a great software for the processing/analysis of spatial data, Python is a clear, powerful programming lenguaje; together they can enhance the spatial analysis to solve more complex or more dedicated problems in less time. PyQGIS is the Python environment inside QGIS with a set of QGIS libraries plus the Python tools with the potential of running other powerful libraries as Pandas, Numpy or Scikit-learn. 

This tutorial shows the whole procedure to upload multiple files from a certain pattern and group them on the Layer Panel using PyQGIS commands.

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How to Upload a Shapefile in QGIS with PyQGIS - Tutorial

QGIS is a great software for the processing/analysis of spatial data, Python is a clear, powerful programming lenguaje; together they can enhance the spatial analysis to solve more complex or more dedicated problems in less time. PyQGIS is the Python environment inside QGIS with a set of QGIS libraries plus the Python tools with the potential of running other powerful libraries as Pandas, Numpy or Scikit-learn. This tutorial show the basic procedure to upload a shapefile in QGIS with PyQGIS.

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Tree / Crop Counting and Classification with Python and Scikit-Image - Tutorial

Lately there has been a wide source of spatial photogrametry available for agriculture. Available submetric images can be found in Google Earth, and drone images can increase the ortophoto resolution to the order of centimeters. Most of this data gives us a new perspective of the spatial distribution and stage of the crops, however a real spatial analysis of crop metrics have not been widely performed due to limitations on the images and software involved. 

We tried to make this tutorial with the popular library OpenCV, however the installation process was tedious in Windows. Then we shifted to Scikit-Image, a image processing library in Python that comes already installed on the Anaconda software. The process for image analysis required intermediate Python and GIS skills, but most important a strong criteria of the algorithm inputs, options and results.

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How to join tables in QGIS - Tutorial

QGIS is a powerful open source software for spatial analysis and management of spatial data. User experience with QGIS is great and most users find QGIS easier to use than other free and commercial GIS software. This time we will show how simple is the process to join tables in QGIS. Spatial data of sanitary quality of beaches in Lima was used to show the join table process.

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