Leaf Area Calculation from Drone Ortophotos with Python and Scikit-Learn - Tutorial

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Besides counting crops we can also delineate plants and calculate its leaf area by using methods that fit open or closed splines to lines or edges in an image. These methods are implemented on the Python library Scikit-Image and applied for the delineation of tree canopies over a geospatial raster image. The exercise is developed in a Jupyter notebook and covers all steps from image import, apply grayscale,  explore gaussian filter, calculate active contour and export polygons as ESRI shapefile. Finally, there is an histogram generation to determine the distribution of leaf area from plants.

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Geospatial Crop Recognition from Drone Orthophotos with Python and HatariTools - Tutorial

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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 new Python package called hatariTools that recognizes plants from an orthophoto based on sample points and creates intermediate plots and identifies plants as point shapefiles.

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Representation of Flow Direction Vectors from a Model Muse / MODFLOW6 model with mf6Voronoi - Tutorial

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This tutorial show the complete workflow to determine flow directions from a MODFLOW model done with Model Muse with the Mf6Voronoi utility FlowVectorGenerator that represent flow direction vectors in a Matplotlib figure. The function works not only with normal Modflow6 Dis models like the generated by Model Muse but also with Voronoi based Modflow6 Disv models. There is a capability to insert background images and other functionalities, however the styling options are closed in order to preserve the artistic style of the plot.

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Land Cover Dynamic Analysis for Climate Change Impact Assessment with Python and Rasterio - Tutorial

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This is an applied of land cover dynamic analysis over some regions of Turkey for the evaluation of land aridification and land abandonment due to climate change on the last decade. The case covers all the steps in Python with related geospatial libraries to process Sentinel 2 images for an area of study with considerations of hydrological conditions and reduction of outlier values.

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Create 3D objects (Vtks) from a groundwater model in Model Muse with mf6Voronoi - Tutorial

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Model Muse is an awesome tool for groundwater model construction and output visualization, however its graphical capabilities are quite limited. Since we are always on the search of bringing groundwater model ‘close’ to the stakeholder, normal audience and coming generations, there is a special interest in providing complementary tools for the normal workflow with Model Muse and Modflow6 that allows the normal user to create awesome 3D objects representing:

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Paraview and mf6Voronoi for Modflow 6 model 3D visualization - Tutorial

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Because an image is worth a thousand words, and 3D visualization is key for explaining, sharing, and analyzing groundwater model parameters, boundaries and results. The Python package mf6Voronoi offers a structured workflow to generate 3D spatial files on VTK format for the representation of the model parameters, water table, head distribution and others that can be plotted on Paraview. This is an applied case of 3D representation for a andean basin groundwater flow model where we are going to explore the relevant tools and options of mf6Voronoi and Paraview.

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Underground mine inflow modeling with MODFLOW6, Flopy and Mf6Voronoi - Tutorial

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An applied example of modeling the development of underground mine works with time based on a Voronoi mesh MOFLOW 6 model. The case consists of 5 mine levels developed over 5 years that cross the underground water body at determined lengths. The numerical model is developed with Python, Flopy and Mf6Voronoi for spatial discretization, implementation of the boundary conditions based on geospatial data, model build/simulation and 3d representation on Paraview.

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Accelerate MF6 Disv model creation using mf6Voronoi templates - Tutorial

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You can work faster and have more time to analyze model results if the process of model creation takes less time. The design of the mf6Voronoi package is oriented to create an improved user experience by optimizing the options of mesh creation and by the implementation of Python script templates for meshing, model construction, and others. This is an applied case of groundwater modeling on a regional scale with Voronoi mesh built on MF6 Disv. The template can be easily customizable to other boundary conditions and will be the basis of coming tutorials and webinars.

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Watershed and River Network Delineation from ESA GLO-30 elevations and Hatari Utils - Tutorial

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There is a new dataset from the European Space Agency (ESA) called Copernicous DEM (GLO-30) that has global coverage with raster resolution of 30m available to download from the Copernicous Dataspace. We have prepared an applied case to access this dataset, download and clip for an area of study and process it into Hatari Utils that provides the watershed and river network delineation on spatial format. The example also covers the options to determine the accumulation area and explore other outputs from the platform.

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Regional groundwater flow modeling with Voronoi mesh on MODFLOW6 DISV and Flopy - Tutorial

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This example develops a groundwater model in MODFLOW6 DISV that implements a Voronoi mesh generated from the basin boundary and river network with the mf6Voronoi packages that allow high performance meshing fully coupled with geospatial data. On the Voronoi mesh, the refinement levels are defined by a minimum cell size, maximum cell size and a multiplier. The applied case covers all steps on model discretization, construction, simulation and 2D visualization.

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Basic example of groundwater modeling with MODFLOW6 and Flopy in Google Colab - Tutorial

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Basic example of MODFLOW 6 groundwater flow modeling with Flopy. The model is multilayered and runs on transient conditions with the recharge, well and river boundary conditions implemented. The example also load model results and create head distributions with flow direction plots with Matplotlib.

The example runs entirely on the Google Colab platform with the use of a Github repository with the MODFLOW 6 executables. This workflow is intended to give a complete online experience of groundwater modeling without any particular computer/software requirement.

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Modeling Lithium brine pumping impact with Modflow 6 and Model Muse - Tutorial

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Lithium is present in some salt lakes along with other brines in different concentrations. In order to simulate the right groundwater flow regime of Lithium brine along other brines we need to model variable density flow from multiple species. This type of modeling is possible on the latest versions of Modflow 6 with the BUY package and Model Muse.

We have developed an applied case of variable density flow modeling on a andean salt lake that is pumped from 3 wells in 10 years. The model has a grid refinement close to the lake and works with 6 brines: B(OH)3, NaHCO3, NaCl, KHSO4, LiHSO4 and NaHSO4. The example implements the BUY package with all the required parameters together with the configuration of the boundary conditions and initial conditions. Concentration and water balances are processed with Python to evaluate the brine migration over time and the impact of pumping on the water balance.

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Topobathymetric elevation generation for flood modeling with geospatial Python

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Elevation maps that represent surface and river bathymetry are an essential input for flood modeling in software like HEC-RAS. Even with the latest version of high profile open source GIS software as QGIS the combination of a surface elevation map and a river bottom elevation map is a challenge that requires many turnaround, conversion and manual labour. We have developed a useful script that works with surface and river bottom elevation in a "smart" way and creates a geospatial raster with the topobathymetric elevation by the use of geospatial Python libraries as Shapely and Rasterio. The script also includes some key steps to identify the river body and treat the missing values on the bathymetry map.

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Introducing mf6Voronoi: A Python package for generating MODFLOW6 DISV Voronoi meshes

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Groundwater modeling with several boundary conditions and complex hydrogeological setups require advanced tools for mesh discretizacion that ensures adequate refinement in the zone of interest while preserving a minimal cell account. Type of mesh has to be engineered in a way to preserve computational resources and represent adequately the groundwater flow regime.

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Introduction to Water Reservoir System Modeling with HEC-ResSim - Tutorial

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HEC-ResSim is a tool that supports reservoir simulation models, aiding decision-making for improved reservoir operations. The nature of HEC-ResSim, its flexible framework for describing reservoir operations, and its new and powerful features make it applicable for modeling almost any multi-purpose storage system. The approach used by HEC-ResSim is based on rules to replicate the operational decision-making followed by reservoir operators. For water release processes from the reservoir, HEC-ResSim considers variables such as the time of year, hydrological conditions, water temperature, and simultaneous operations with other reservoirs within the system.

This tutorial covers an applied case of reservoir modeling at the discharge point of an andean basin. The example covers the steps to set up the watershed, define the reservoir network, simulate the hydrological alternative and explore output hydrographs and tables.

Tutorial

Input files

https://owncloud.hatarilabs.com/s/mj8eEm1QmX2A69m

Password to download data: Hatarilabs

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Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.