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To run MODFLOW model you have to have the following general information: They might be grouped in to physical and hydrologic.

Physical Framework

  1. Topography
  2. Geology
  3. Types of aquifers
  4. Aquifer thickness and lateral extent
  5. Aquifer boundaries
  6. Lithological variations within the aquifer
  7. Aquifer characteristics

Hydrological Framework

  1. Water table elevation
  2. Type and extent of recharge areas
  3. Rate of recharge
  4. Type and extent of discharge areas
  5. Rate of discharge

The data required for a groundwater flow modelling study under physical framework are:

  • Geologic map and cross section or fence diagram showing the areal and vertical extent and boundaries of the system.
  • Topographic map at a suitable scale showing all surface water bodies and divides. Details of surface drainage system, springs, wetlands and swamps should also be available on map.
  • Land use maps showing agricultural areas.
  • Contour maps showing the elevation of the base of the aquifers and confining beds.
  • Isopach maps showing the thickness of aquifers and confining beds.

These data are used for defining the geometry of the groundwater domain under investigation, including the thickness and areal extent of each hydro stratigraphic unit.

Under the hydrogeological framework, the data requirements for a groundwater flow modelling study are:

  • Water table and potentiometric maps for all aquifers.
  • Hydrographs of groundwater head and surface water levels.
  • Maps and cross-sections showing the hydraulic conductivity and/or transmissivity distribution.
  • Maps and cross-sections showing the storage properties of the aquifers and confining beds.
  • Spatial and temporal distribution of rates of evaporation, groundwater recharge, groundwater pumping etc.
  • Initial Conditions: The initial conditions refer to initial values of elements that may increase or decrease in the course of the time inside the model domain.

In simple term: you need

 Geometry:

  • shape of the model area
  • Elevation of aquifer bottom and top
  • Thickness of the aquifer

Aquifer Parameters

Distributions of Hydraulic conductivity (K), Transmissivity, storage coefficient, specific storage, etc.

Inflows/Outflows

  • Pumping Well location, well discharge/Recharge
  • Groundwater recharge by precipitation
  • Mountain front recharge, if any
  • Boundary flows

Observed heads and discharge:

  • Monitoring well location and piezometer head
  • Spring discharge if any
  • Initial head

During conceptual model preparation: strongly define the following with evidence

MODFLOW time

  • Be sure how many stress periods are you going to use in your study, why?

Boundary conditions

  • Define your study area well and specify the correct hydraulic boundary conditions

BY: Dr.Kedir Mohammed

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Classification of images provides useful information about land cover, based on the spectral radiometric response of the cover type.This is done by one of two basic methods: unsupervised or supervised classification. Unsupervised classification categorizes continuous raster data into discrete thematic groups having similar spectral-radiometric values. Supervised classification allows the analyst to define classes of interest. The computer then calculates training statistics based on the definitions found in signature files and assigns each pixel of the image to the class that it most closely resembles.
For unsupervised training and classification, ERDAS Imagine employs the (ISODATA) clustering technique which uses the statistics of the data to evaluate the similarities or differences of the pixel values then groups the pixels into separate classes. This process takes several passes, or iterations, until it reaches a convergence threshold. The groups are then defined by a signature file, which can be used to create a new raster layer of discrete class values.

For more, please download the attached tutorial manual.

Video Tutorial

Unsupervised Classification and Recode in Erdas Imagine@WEHA LABS - YouTube

Download link:

Tutorial manual

Lab03_Image_Classification_Unsupervised-2013-1wr5uve

Input-data

26_29_dak_sub.img-2in59zs

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WEHA LABS by Dr.kedir Mohammed - 5M ago

How to calculate NDVI using Erdas Imagen

A vegetation index is a transformation that can be used to map the “greenness” of vegetation.

The Normalized Difference Vegetation Index (NDVI) is a normalized ratio of two bands, NIR and red (typically, TM bands 4 and 3), where NIR and Red are the DN values in the near IR and red spectral bands.

The formula for NDVI is:

NDVI= (NIR-Red) / (NIR + Red)

Looking at your NDVI image result, note the NDVI values for different areas of the image:

  • Pixels with values less than 0 are usually water
  • Pixels with low values close to 0 are bare areas (soils, pavement, etc.)
  • Pixels with higher values are vegetation

Video Tutorial

How to calculate NDVI using Erdas Imagen - YouTube

Download link: one click will drop the following document on your PC

 Lab02_Image_Enhancement & NDVI-2013-1opkmj0

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Runoff Generation Raster Calculation in ArcGIS

Runoff generation at a point depends on

  • Rainfall intensity or amount
  • Antecedent conditions
  • Soils and vegetation
  • Depth to water table (topography)
  • Time scale of interest

These vary spatially which suggests a spatial geographic approach to runoff estimation. Map algebra/Raster calculator is a powerful tool to calculate.

Map Algebra is a simple and powerful algebra with which you can execute all ArcGIS Spatial Analyst extension tools, operators, and functions to perform geographic analysis.

The Raster Calculator tool allows you to create and execute Map Algebra expressions in a tool. Like other geoprocessing tools, the Raster Calculator can be used in ModelBuilder, allowing the power of Map Algebra to be more easily integrated into your workflows.

Tutorial Video

Runoff Generation Raster Calculation In ArcGIS - YouTube

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In this lab we will start using the ERDAS Imagine version 2013 image processing software package to learn some basic operations. We will also become familiar with the sentinel data to be used in future labs as well as gain experience using the USGS browsers to download Landsat satellite imagery(you can get this part in the attached tutorial document).

Google Chrome has been known to be incompatible with ERDAS help as well as the USGS Glovis site. Be prepared to try use of other browsers such Firefox or Internet Explorer if you experience unexplained problems.

Avoid having spaces in any input paths or output path names including the file name itself- some tools will not work properly if spaces are found. This has been known to affect ArcGIS products as well.

The European Space Agency (ESA), through the Copernicus program of the European Commission (http://www.copernicus.eu/main/overview), has launched three satellite sensors (Sentinels-1, 2, and 3A) providing free satellite images for the scientific community, government agencies, the private sector.Image downloaded from  Sentinel-2  was used for layer stacking in this tutorial.

Landsat Enhanced Thematic Mapper (ETM+) data was used for introducing Erdas imagen software in the first part of the  tutorial. The image used in this lab is a subset image cut from an entire Landsat “scene” acquired August 18, 2002 over southern Dakota County and northern Goodhue County. The subset images are roughly 666 pixels by 666 pixels, while an entire Landsat scene is about 6,500 by 6,500 pixels. The subset images are about 3 MB while a full scene is about 250 MB. These ETM+ data are 30 meter spatial resolution with six multispectral bands. The pan-sharpened ETM+ data are 15 meter spatial resolution with three multispectral bands. Later in the lab you will download another image from the USGS Glovis web site.

Different satellites have different band composites.

Band combinations for Sentinel-2. They can be found in SNAP menu, the RGB composite is as follows:

Natural Colors: 4 3 2
False color Infrared: 8 4 3
False color Urban: 12 11 4
Agriculture: 11 8 2
Atmospheric penetration: 12 11 8a
Healthy vegetation: 8 11 2
Land/Water: 8 11 4
Natural Colors with Atmospheric Removal: 12 8 3
Shortwave Infrared: 12 8 4
Vegetation Analysis: 11 8 4

Landsat 8 band combinations:
Natural Color 4 3 2
False Color (urban) 7 6 4
Color Infrared (vegetation) 5 4 3
Agriculture 6 5 2
Atmospheric Penetration 7 6 5
Healthy Vegetation 5 6 2
Land/Water 5 6 4
Natural With Atmospheric Removal 7 5 3
Shortwave Infrared 7 5 4
Vegetation Analysis 6 5 4

Landsat 4-7 band combinations

Standard false color composite 4, 3, 2 [from top to bottom]

True color composite 3, 2, 1

False color composite 4, 5, 3

Video Tutorial

Introduction and creating a Layer Stack in ERDAS Imagen - YouTube

Download links: just one click to download

Lab01_Tutorial Manual-19a5m96

EX1-data-1dez92d

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WEHA LABS was selected one of the Top 10 Hydrology blog & Top 60 GIS Blogs by Feedspot

I am just started WEHA LABS back in December of this year with the aim of creating a technical blog about software in water resources and numerical modeling for my students in Arba minch university, Ethiopia. There wasn’t any specific plan or strategy to increase the relevance of the blog globally, just the desire to create a space for promoting open source software on hydrology, hydrogeology and GIS. When time goes the external numBer of viewerS in my you tube channel is increasing which gives me a hope that my blog will become one of the best educational blog.  The  number of visits for my blog  still its  scary because the audience is so small.

Still, I can not declare that I have a huge blog, but its growing.  There is a lot of tutorials to post in the future, and I will do it with passion. I receive this recognition by Feedspot with great humility and the compromise to improve our content everyday to provide a platform for the capacity building of professionals in water resources.

Please have a look on the complete post and the criteria used by Feedspot to create this ranking on this link:

Best 10 hydrology blog

https://blog.feedspot.com/hydrology_blogs/

Best 60 GIS blog

https://blog.feedspot.com/gis_blogs/

Please continue enjoying our great and specific content in:

http://agualabs.edublogs.org/

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This tutorial is a class exercise at Arba minch university, Ethiopia to show postgraduate students how to build, run and import/export a MODFLOW model using ModelMuse GUI.

Tutorial Video

Tutorial on Regional Groundwater Modeling Using MODFLOW with ModelMuse GUI - YouTube

Problem for the tutorial

The problem we will be solving in this tutorial is a Basin. The model grid will be discretized uniformly to 100 m. Assume the elevation of the top and bottom of the aquifer will be flat.

Packages;

DRN Package: use the river shapefiles attributes field values for elevation and bed conductance

RCH Package: Recharge rate = 3.80E-9, recharge location= Top active cell

EVT Package: EVT Rate = 3.17E-8, EVT surface =Model Top, EVT depth = 0.5, EVT location=Top layer

Aquifer Properties

4 aquifer layers:

Model_ Top (0 m),

Alluvial (ModelTop-15 m),

Layer 2((Model_Top – 100m) * 0.85))

Layer 3(Model_Top – 300m)

Layer 4 =800 m

Variable Horizontal Hydraulic Conductivity of, 5E-5, 5E-7, 8E-8, 1E-8 from the 1st to 4th layer and assume Isotropic aquifer.

Aquifer type: The last aquifer is confined and the others are convertible

Spatial datasets:

In this MODFLOW Exercise you are provided the following spatial datasets:

  1. A polygon shapefile of the Basin, called Basin.shp
  2. A line shapefile of the river, called River.shp

MODFLOW Initial head = 200m

  1. Run a steady state model using no flow boundary and find the distributions of hydraulic head at the end of the steady state period. Was the budget converging with acceptable limit?
  2. Run the model by assuming a GHB at the south of the study area. Compare the results with 1. Use a constant boundary head 200 m and conductance of 0.002.

Input files link to download

basin-1y9dbhb

river-1fvs7gx

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WEHA LABS by Dr.kedir Mohammed - 5M ago

QGIS (previously known as Quantum GIS) is a free and open-source cross-platform desktop geographic information system (GIS) application that supports viewing, editing, and analysis of geospatial data.

Similar to other software GIS systems, QGIS allows users to create maps with many layers using different map projections. Maps can be assembled in different formats and for different uses. QGIS allows maps to be composed of raster or vector layers. Typical for this kind of software the vector data is stored as either point, line, or polygon-feature. Different kinds of raster images are supported and the software can perform georeferencing of images.
Download Link: 
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ERDAS IMAGINE is a remote sensing application with raster graphics editor abilities designed by ERDAS for geospatial applications. The latest version is 2018. ERDAS IMAGINE is aimed primarily at geospatial raster data processing and allows the user to prepare, display and enhance digital images for mapping use in geographic information system (GIS) or in computer-aided design (CAD) software. It is a toolbox allowing the user to perform numerous operations on an image and generate an answer to specific geographical questions.
By manipulating imagery data values and positions, it is possible to see features that would not normally be visible and to locate geo-positions of features that would otherwise be graphical. The level of brightness, or reflectance of light from the surfaces in the image can be helpful with vegetation analysis, prospecting for minerals etc. Other usage examples include linear feature extraction, generation of processing work flows (“spatial models” in ERDAS IMAGINE), import/export of data for a wide variety of formats,orthorectification, mosaicking of imagery, stereo and automatic feature extraction of map data from imagery.

This tutorial shows the full installations of ERDAS IMAGEN 9. Thanks to AMANAT ALI

Erdas Imagen 9 software file: click on Download Link:

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WEHA LABS by Dr.kedir Mohammed - 5M ago

Welcome to a brand new blog called Agua Labs by Dr. Kedir Mohammed: applications of free and open source software for water resources management.
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