Using GRASS for stream-network extraction and basins delineation
Methodological procedure described in:
Amatulli, Giuseppe, et al. Hydrography90m: A new high-resolution global hydrographic dataset. Earth System Science Data Discussions 2022 (2022): 1-43.
Install python libraryes and softwares
[1]:
! pip install rasterio
! pip install geopandas
Collecting rasterio
Downloading rasterio-1.4.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (9.1 kB)
Collecting affine (from rasterio)
Downloading affine-2.4.0-py3-none-any.whl.metadata (4.0 kB)
Requirement already satisfied: attrs in /usr/local/lib/python3.11/dist-packages (from rasterio) (25.3.0)
Requirement already satisfied: certifi in /usr/local/lib/python3.11/dist-packages (from rasterio) (2025.4.26)
Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.11/dist-packages (from rasterio) (8.2.1)
Collecting cligj>=0.5 (from rasterio)
Downloading cligj-0.7.2-py3-none-any.whl.metadata (5.0 kB)
Requirement already satisfied: numpy>=1.24 in /usr/local/lib/python3.11/dist-packages (from rasterio) (2.0.2)
Collecting click-plugins (from rasterio)
Downloading click_plugins-1.1.1-py2.py3-none-any.whl.metadata (6.4 kB)
Requirement already satisfied: pyparsing in /usr/local/lib/python3.11/dist-packages (from rasterio) (3.2.3)
Downloading rasterio-1.4.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (22.2 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 22.2/22.2 MB 37.6 MB/s eta 0:00:00
Downloading cligj-0.7.2-py3-none-any.whl (7.1 kB)
Downloading affine-2.4.0-py3-none-any.whl (15 kB)
Downloading click_plugins-1.1.1-py2.py3-none-any.whl (7.5 kB)
Installing collected packages: cligj, click-plugins, affine, rasterio
Successfully installed affine-2.4.0 click-plugins-1.1.1 cligj-0.7.2 rasterio-1.4.3
Requirement already satisfied: geopandas in /usr/local/lib/python3.11/dist-packages (1.0.1)
Requirement already satisfied: numpy>=1.22 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.0.2)
Requirement already satisfied: pyogrio>=0.7.2 in /usr/local/lib/python3.11/dist-packages (from geopandas) (0.11.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from geopandas) (24.2)
Requirement already satisfied: pandas>=1.4.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.2.2)
Requirement already satisfied: pyproj>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (3.7.1)
Requirement already satisfied: shapely>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from geopandas) (2.1.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.4.0->geopandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.4.0->geopandas) (2025.2)
Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas>=1.4.0->geopandas) (2025.2)
Requirement already satisfied: certifi in /usr/local/lib/python3.11/dist-packages (from pyogrio>=0.7.2->geopandas) (2025.4.26)
Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas>=1.4.0->geopandas) (1.17.0)
[28]:
! lss
/bin/bash: line 1: lss: command not found
[2]:
%%bash
apt install gdal-bin python3-gdal grass grass-dev pktools
Reading package lists...
Building dependency tree...
Reading state information...
The following additional packages will be installed:
fonts-dejavu-core fonts-droid-fallback fonts-lyx fonts-noto-mono
fonts-urw-base35 ghostscript grass-core grass-doc grass-gui libalgorithms1
libfann2 libfftw3-double3 libfileclasses1 libglu1-mesa libgs9 libgs9-common
libgsl27 libgslcblas0 libidn12 libijs-0.35 libimageclasses1 libimagequant0
libjbig2dec0 liblbfgsb0 libnotify4 libpdal-plugin-e57 libpdal-plugin-faux
libpdal-plugin-hdf libpdal-plugin-icebridge libpdal-plugin-pgpointcloud
libpdal-plugins libpdal16 libraqm0 libwxbase3.2-1 libwxgtk-gl3.2-1
libwxgtk3.2-1 libxsimd-dev libxtst6 libxxf86dga1 poppler-data proj-bin
python-matplotlib-data python3-appdirs python3-attr python3-beniget
python3-brotli python3-bs4 python3-chardet python3-cycler python3-dateutil
python3-decorator python3-fonttools python3-fs python3-gast python3-html5lib
python3-kiwisolver python3-lxml python3-lz4 python3-matplotlib
python3-mpmath python3-numpy python3-olefile python3-packaging python3-pil
python3-pil.imagetk python3-ply python3-pythran python3-scipy
python3-soupsieve python3-sympy python3-tz python3-ufolib2
python3-unicodedata2 python3-webencodings python3-wxgtk4.0 unicode-data
x11-utils xbitmaps xterm
Suggested packages:
fonts-noto fonts-freefont-otf | fonts-freefont-ttf fonts-texgyre
libgdal-grass ghostscript-x e00compr avce00 gnuplot gpsbabel gpstrans netpbm
python3-rpy2 python3-termcolor subversion grass-dev-doc libfann-dev
libfann-doc libfftw3-bin libfftw3-dev gsl-ref-psdoc | gsl-doc-pdf
| gsl-doc-info | gsl-ref-html gnome-shell | notification-daemon libxsimd-doc
poppler-utils fonts-japanese-mincho | fonts-ipafont-mincho
fonts-japanese-gothic | fonts-ipafont-gothic fonts-arphic-ukai
fonts-arphic-uming fonts-nanum python-attr-doc python-cycler-doc
python3-genshi python-lxml-doc dvipng fonts-staypuft gir1.2-gtk-3.0 inkscape
ipython3 librsvg2-common python-matplotlib-doc python3-cairocffi
python3-gi-cairo python3-gobject python3-pyqt5 python3-sip python3-tornado
texlive-extra-utils texlive-latex-extra python-mpmath-doc python3-gmpy2
python-numpy-doc python3-pytest python-pil-doc python-ply-doc
python-scipy-doc texlive-fonts-extra python-sympy-doc wx3.2-doc mesa-utils
xfonts-cyrillic
The following NEW packages will be installed:
fonts-dejavu-core fonts-droid-fallback fonts-lyx fonts-noto-mono
fonts-urw-base35 gdal-bin ghostscript grass grass-core grass-dev grass-doc
grass-gui libalgorithms1 libfann2 libfftw3-double3 libfileclasses1
libglu1-mesa libgs9 libgs9-common libgsl27 libgslcblas0 libidn12 libijs-0.35
libimageclasses1 libimagequant0 libjbig2dec0 liblbfgsb0 libnotify4
libpdal-plugin-e57 libpdal-plugin-faux libpdal-plugin-hdf
libpdal-plugin-icebridge libpdal-plugin-pgpointcloud libpdal-plugins
libpdal16 libraqm0 libwxbase3.2-1 libwxgtk-gl3.2-1 libwxgtk3.2-1
libxsimd-dev libxtst6 libxxf86dga1 pktools poppler-data proj-bin
python-matplotlib-data python3-appdirs python3-attr python3-beniget
python3-brotli python3-bs4 python3-chardet python3-cycler python3-dateutil
python3-decorator python3-fonttools python3-fs python3-gast python3-gdal
python3-html5lib python3-kiwisolver python3-lxml python3-lz4
python3-matplotlib python3-mpmath python3-numpy python3-olefile
python3-packaging python3-pil python3-pil.imagetk python3-ply
python3-pythran python3-scipy python3-soupsieve python3-sympy python3-tz
python3-ufolib2 python3-unicodedata2 python3-webencodings python3-wxgtk4.0
unicode-data x11-utils xbitmaps xterm
0 upgraded, 84 newly installed, 0 to remove and 35 not upgraded.
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Theoretical background
The first step towards modeling hydrological features is delineating a comprehensive hydrography network. DEMs at different spatial resolutions allow for the identification of stream channels, using a variety of flow-routing algorithms. Such algorithms are based on the observation that water follows the steepest and shortest route along a relief, and accumulates in valleys, lowlands, flat areas and depressions. Several algorithms have been proposed for stream network routing. These algorithms proceed in several stages: determining flow directions, resolving depressions and flat areas, and finally, calculating flow accumulation.
Flow accumulation
Flow accumulation refers to the process of accumulating the flow of water across a terrain, often used in GIS to model drainage patterns and identify streams. Single flow direction (SFD) assumes water flows in only one direction, while multi-flow direction (MFD) allows water to flow in multiple directions, potentially more accurately representing terrain features.
[3]:
from IPython.display import display, HTML
display(HTML('<img src="https://github.com/selvaje/SE_docs/blob/master/source/images/flowaccumulation_algorithm.png?raw=true" width="1000">'))
Methodology
Below we describe how we will extract a new high-resolution hydrography (stream-network and basins) from the 1KM DEM. In this exercise we simulate a case that we can not run the full South America continent in one tile because we reach RAM limitation. Therefore we compute the analysis in 3 tiles and then we combine the results.
We are going to use 3 GRASS commands: * r.watershed to derive flow accumulation * r.stream.extract to extract-stream network * r.stream.basins to delineate basins
Download the input dataset
[29]:
# mask sea-land
!wget -O SA_msk.tif https://raw.githubusercontent.com/selvaje/SE_data/53a02ab19e45d1a16cbc63ad5fb30da4ae67839f/exercise/geodata/dem/SA_msk_1km.tif
# area for each pixel in km2
!wget -O SA_area.tif https://raw.githubusercontent.com/selvaje/SE_data/b21ed1b52e67f2633cb9a685c8cae9422ec42948/exercise/geodata/dem/SA_are_1km_msk.tif
# elevation
!wget -O SA_elevation.tif https://raw.githubusercontent.com/selvaje/SE_data/b21ed1b52e67f2633cb9a685c8cae9422ec42948/exercise/geodata/dem/SA_elevation_mn_GMTED2010_mn_msk.tif
# depresssion
!wget -O SA_dep.tif https://raw.githubusercontent.com/selvaje/SE_data/66617b33f3704a532d9fc0f39953235ce43cd5b1/exercise/geodata/dem/SA_all_dep_1km.tif
# computation tiles
!wget -O tilesComp.gpkg https://raw.githubusercontent.com/selvaje/SE_data/66617b33f3704a532d9fc0f39953235ce43cd5b1/exercise/geodata/dem/tilesComp.gpkg
--2025-06-13 09:21:50-- https://raw.githubusercontent.com/selvaje/SE_data/53a02ab19e45d1a16cbc63ad5fb30da4ae67839f/exercise/geodata/dem/SA_msk_1km.tif
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 389386 (380K) [image/tiff]
Saving to: ‘SA_msk.tif’
SA_msk.tif 100%[===================>] 380.26K --.-KB/s in 0.03s
2025-06-13 09:21:50 (12.4 MB/s) - ‘SA_msk.tif’ saved [389386/389386]
--2025-06-13 09:21:50-- https://raw.githubusercontent.com/selvaje/SE_data/b21ed1b52e67f2633cb9a685c8cae9422ec42948/exercise/geodata/dem/SA_are_1km_msk.tif
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 693593 (677K) [image/tiff]
Saving to: ‘SA_area.tif’
SA_area.tif 100%[===================>] 677.34K --.-KB/s in 0.04s
2025-06-13 09:21:50 (17.6 MB/s) - ‘SA_area.tif’ saved [693593/693593]
--2025-06-13 09:21:50-- https://raw.githubusercontent.com/selvaje/SE_data/b21ed1b52e67f2633cb9a685c8cae9422ec42948/exercise/geodata/dem/SA_elevation_mn_GMTED2010_mn_msk.tif
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.110.133, 185.199.111.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 30715408 (29M) [application/octet-stream]
Saving to: ‘SA_elevation.tif’
SA_elevation.tif 100%[===================>] 29.29M --.-KB/s in 0.1s
2025-06-13 09:21:51 (223 MB/s) - ‘SA_elevation.tif’ saved [30715408/30715408]
--2025-06-13 09:21:51-- https://raw.githubusercontent.com/selvaje/SE_data/66617b33f3704a532d9fc0f39953235ce43cd5b1/exercise/geodata/dem/SA_all_dep_1km.tif
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.110.133, 185.199.111.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 286077 (279K) [image/tiff]
Saving to: ‘SA_dep.tif’
SA_dep.tif 100%[===================>] 279.37K --.-KB/s in 0.02s
2025-06-13 09:21:52 (11.7 MB/s) - ‘SA_dep.tif’ saved [286077/286077]
--2025-06-13 09:21:52-- https://raw.githubusercontent.com/selvaje/SE_data/66617b33f3704a532d9fc0f39953235ce43cd5b1/exercise/geodata/dem/tilesComp.gpkg
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 106496 (104K) [application/octet-stream]
Saving to: ‘tilesComp.gpkg’
tilesComp.gpkg 100%[===================>] 104.00K --.-KB/s in 0.02s
2025-06-13 09:21:52 (6.52 MB/s) - ‘tilesComp.gpkg’ saved [106496/106496]
[30]:
import rasterio
from rasterio.plot import show
import matplotlib.pyplot as plt
import geopandas as gpd
Plotting the input dataset
[31]:
# Open raster datasets
msk = rasterio.open("/content/SA_msk.tif")
dem = rasterio.open("/content/SA_elevation.tif")
area = rasterio.open("/content/SA_area.tif")
# Create a figure and subplots
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(15, 5)) # 1 row, 3 columns
# Plot each raster on a subplot
show(msk, ax=ax1, title="Mask")
show(dem, ax=ax2, title="Elevation")
show(area, ax=ax3, title="Area")
# Adjust layout and display
plt.tight_layout()
plt.show()
Plotting the elevation and the computational tiles
[7]:
# Open raster datasets
dem = rasterio.open("/content/SA_elevation.tif")
# Open the vector dataset
tiles = gpd.read_file("/content/tilesComp.gpkg")
# Create a figure and an axes
fig, ax = plt.subplots(figsize=(5, 5))
# Plot the DEM raster
show(dem, ax=ax, cmap='terrain') # Use a terrain colormap
# Plot the vector data on top of the DEM
tiles.boundary.plot(ax=ax, color="red", linewidth=2, alpha=1) # Plot the boundaries in red
tiles.plot(ax=ax, alpha=0.5, color='none', edgecolor='red') # Transparent fill with red outline
# Add a title and labels
# ax.set_title("DEM with Irregular Tiling System Overlay")
ax.set_xlabel("Longitude")
ax.set_ylabel("Latitude")
plt.tight_layout()
plt.show()
Install the grass add-on
[8]:
%%bash
grass --exec g.extension extension=r.stream.basins
Your branch is up to date with 'origin/grass8'.
Fetching <r.stream.basins> from <https://github.com/OSGeo/grass-addons/>
(be patient)...
Already on 'grass8'
Compiling...
Installing...
Updating extensions metadata file...
Updating extension modules metadata file...
Installation of <r.stream.basins> successfully finished
Compute continental seamless flow accumulation
[26]:
%%bash
cd /content/
# use -c create loctation/project to using the SA_elevation.tif file as reference
rm -fr /content/hydrographySA_1
grass --text -c /content/SA_elevation.tif /content/hydrographySA_1 --exec <<'EOF'
g.gisenv set="GRASS_VERBOSE=-1","DEBUG=0"
## import the layers
r.external input=/content/SA_elevation.tif output=elv --o --q # dem
r.external input=/content/SA_dep.tif output=dep --o --q # depression
r.external input=/content/SA_area.tif output=are --o --q # area-pixel
r.external input=/content/SA_msk.tif output=msk --o --q # land-ocean mask
g.region -m
for tile in 1 2 3 ; do # loop for each tile
r.mask raster=msk --o --q # usefull to mask the flow accumulation
# extract tile extent from the tilesComp.gpkg
wL=$(ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $2 }')
nL=$(ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $3 }')
eL=$(ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $4 }')
sL=$(ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $7 }')
g.region w=$wL n=$nL s=$sL e=$eL res=0:00:30 --o
g.region -m
### maximum ram 66571M for 2^31 -1 (2 147 483 647 cell) / 1 000 000 * 31 M
#### -m Enable disk swap memory option: Operation is slow
#### -b Beautify flat areas
#### threshold=8 8 km2
echo "############# compute the flow accumulation using MFD for tile $tile ##############"
r.watershed -b elevation=elv depression=dep accumulation=flow drainage=dir_rw flow=are memory=4000 --o --q
echo "############# extract stream ##################"
r.stream.extract elevation=elv accumulation=flow depression=dep threshold=8 direction=dir_rs stream_raster=stream memory=2000 --o --q
echo "############# delineate basin ##################"
r.stream.basins -l stream_rast=stream direction=dir_rs basins=lbasin memory=2000 --o --q
r.colors -r stream --q ; r.colors -r lbasin --q ; r.colors -r flow --q
r.out.gdal --o -c -m createopt="COMPRESS=DEFLATE,ZLEVEL=9" type=UInt32 format=GTiff nodata=0 input=lbasin output=/content/lbasinTmp1_$tile.tif
echo "###### create a small zone flow binary for later use ###########"
r.mapcalc " small_zone_flow = if( !isnull(flow) && isnull(lbasin) , 1 , null()) " --o --q
echo "##### create a smaller box ########"
CropW=$( ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep " CropW" | awk '{print $4 }')
CropE=$( ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep " CropE" | awk '{print $4 }')
CropS=$( ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep " CropS" | awk '{print $4 }')
CropN=$( ogrinfo -al -where "id = '$tile'" /content/tilesComp.gpkg | grep " CropN" | awk '{print $4 }')
nS=$(g.region -m | grep ^n= | awk -F "=" -v CropN=$CropN '{ printf ("%.14f\n" , $2 - CropN ) }' )
sS=$(g.region -m | grep ^s= | awk -F "=" -v CropS=$CropS '{ printf ("%.14f\n" , $2 + CropS ) }' )
eS=$(g.region -m | grep ^e= | awk -F "=" -v CropE=$CropE '{ printf ("%.14f\n" , $2 - CropE ) }' )
wS=$(g.region -m | grep ^w= | awk -F "=" -v CropW=$CropW '{ printf ("%.14f\n" , $2 + CropW ) }' )
# set a smaller region to avoid border effect
g.region w=$wS n=$nS s=$sS e=$eS res=0:00:30 save=smallext --o --q # smaller region
g.region region=smallext --o --q
g.region -m
# at this point we want remove all no-entire basins. To do this we create 4 stripes of 1 pixel allong the tile borders.
echo "######## left stripe ########"
eST=$(g.region -m | grep ^e= | awk -F "=" '{ print $2 }')
wST=$(g.region -m | grep ^e= | awk -F "=" '{ printf ("%.14f\n" , $2 - ( 1 * 0.00833333333333 )) }' )
g.region n=$nS s=$sS e=$eST w=$wST res=0:00:30 --o
r.mapcalc " lbasin_wstripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## right stripe ########"
wST=$(g.region -m | grep ^w= | awk -F "=" '{ print $2 }' )
eST=$(g.region -m | grep ^w= | awk -F "=" '{ printf ("%.14f\n" , $2 + ( 1 * 0.00833333333333 )) }' )
g.region n=$nS s=$sS e=$eST w=$wST res=0:00:30 --o
r.mapcalc " lbasin_estripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## top stripe ########"
nST=$(g.region -m | grep ^n= | awk -F "=" '{ print $2 }' )
sST=$(g.region -m | grep ^n= | awk -F "=" '{ printf ("%.14f\n" , $2 - ( 1 * 0.00833333333333 )) }' )
g.region e=$eS w=$wS n=$nST s=$sST res=0:00:30 --o
r.mapcalc " lbasin_nstripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## bottom stripe ########"
sST=$(g.region -m | grep ^s= | awk -F "=" '{ print $2 }' )
nST=$(g.region -m | grep ^s= | awk -F "=" '{ printf ("%.14f\n" , $2 + ( 1 * 0.00833333333333 )) }' )
g.region e=$eS w=$wS n=$nST s=$sST res=0:00:30 --o
r.mapcalc " lbasin_sstripe = lbasin " --o --q
g.region region=smallext --o --q
# the 1 pixel strip is used to have the ID of the truncated basin.
echo "######## remove incompleate basins ########"
cat <(r.report -n -h units=c map=lbasin_estripe | awk '{ gsub ("\\|"," " ) ; { print $1 } } ' | awk '$1 ~ /^[0-9]+$/ { print $1 } ') \
<(r.report -n -h units=c map=lbasin_wstripe | awk '{ gsub ("\\|"," " ) ; { print $1 } } ' | awk '$1 ~ /^[0-9]+$/ { print $1 } ') \
<(r.report -n -h units=c map=lbasin_sstripe | awk '{ gsub ("\\|"," " ) ; { print $1 } } ' | awk '$1 ~ /^[0-9]+$/ { print $1 } ') \
<(r.report -n -h units=c map=lbasin_nstripe | awk '{ gsub ("\\|"," " ) ; { print $1 } } ' | awk '$1 ~ /^[0-9]+$/ { print $1 } ') \
<(r.report -n -h units=c map=lbasin | awk '{ gsub ("\\|"," " ) ; { print $1 } } ' | awk '$1 ~ /^[0-9]+$/ { print $1 } ') \
| sort | uniq -c | awk '{ if($1==1) {print $2"="$2 } else { print $2"=NULL"} }' > /content/lbasin_${tile}_reclass.txt
# use the r.reclass command to reclass ID basin to NULL
r.reclass input=lbasin output=lbasin_rec rules=/content/lbasin_${tile}_reclass.txt --o --q
rm -f /content/lbasin_${tile}_reclass.txt
r.mapcalc " lbasin_clean = lbasin_rec" --o --q
g.remove -f type=raster name=lbasin_rec,lbasin_estripe,lbasin_wstripe,lbasin_nstripe,lbasin_sstripe --q
echo "############ export basin only for visual inspection ############"
r.mask raster=lbasin_clean --o --q
r.out.gdal --o -c -m createopt="COMPRESS=DEFLATE,ZLEVEL=9" type=UInt32 format=GTiff nodata=0 input=lbasin_clean output=/content/lbasinTmp2_$tile.tif
echo "############ output the flow accumulation ############"
r.mask raster=msk --o --q
r.mapcalc " lbasin_flow_clean = if ( !isnull(lbasin_clean ) || !isnull(small_zone_flow) , 1 , null() ) " --o --q
r.grow input=lbasin_flow_clean output=lbasin_flow_clean_grow radius=4 --o --q
r.mask raster=lbasin_flow_clean_grow --o --q
r.out.gdal --o -f -c -m createopt="COMPRESS=DEFLATE,ZLEVEL=9" nodata=-9999999 type=Float32 format=GTiff input=flow output=/content/flow_${tile}.tif
gdal_edit.py -a_ullr $wS $nS $eS $sS /content/flow_${tile}.tif
gdal_edit.py -tr 0.00833333333333333333333333333333333 -0.00833333333333333333333333333333333 /content/flow_${tile}.tif
done
EOF
projection=3
zone=0
n=14
s=-56
w=-83
e=-34
nsres=923.44150551
ewres=703.7149865
rows=8400
cols=5880
cells=49392000
projection=3
zone=0
n=-12
s=-56
w=-76.4
e=-43
nsres=924.52244935
ewres=710.89449752
rows=5280
cols=4008
cells=21162240
############# compute the flow accumulation using MFD for tile 1 ##############
############# extract stream ##################
############# delineate basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=-14
s=-56
w=-75.8
e=-45
nsres=924.64630106
ewres=707.62000721
rows=5040
cols=3696
cells=18627840
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin only for visual inspection ############
############ output the flow accumulation ############
projection=3
zone=0
n=1
s=-38
w=-73.9
e=-34.6
nsres=922.66504302
ewres=826.93226998
rows=4680
cols=4716
cells=22070880
############# compute the flow accumulation using MFD for tile 2 ##############
############# extract stream ##################
############# delineate basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=-1.8
s=-35.2
w=-71.1
e=-34.6
nsres=922.59157279
ewres=840.84791606
rows=4008
cols=4380
cells=17555040
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin only for visual inspection ############
############ output the flow accumulation ############
projection=3
zone=0
n=12.7
s=-24.5
w=-81.7
e=-41.7
nsres=921.8619211
ewres=872.86703289
rows=4464
cols=4800
cells=21427200
############# compute the flow accumulation using MFD for tile 3 ##############
############# extract stream ##################
############# delineate basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=12.7
s=-21.7
w=-81.4
e=-44.5
nsres=921.77907927
ewres=882.26518613
rows=4128
cols=4428
cells=18278784
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin only for visual inspection ############
############ output the flow accumulation ############
Starting GRASS GIS...
Creating new GRASS GIS project <hydrographySA_1>...
__________ ___ __________ _______________
/ ____/ __ \/ | / ___/ ___/ / ____/ _/ ___/
/ / __/ /_/ / /| | \__ \\_ \ / / __ / / \__ \
/ /_/ / _, _/ ___ |___/ /__/ / / /_/ // / ___/ /
\____/_/ |_/_/ |_/____/____/ \____/___//____/
Welcome to GRASS GIS 8.4.1
GRASS GIS homepage: https://grass.osgeo.org
This version running through: Bash Shell (/bin/bash)
Help is available with the command: g.manual -i
See the licence terms with: g.version -c
See citation options with: g.version -x
Start the GUI with: g.gui wxpython
When ready to quit enter: exit
WARNING: Color table of raster map <stream> not found
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
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r.out.gdal complete. File </content/lbasinTmp1_1.tif> created.
0% 3% 0% 0% 3% 6% 0% 6% 0% 3% 9% 9% 3% 3% 12% 6% 12% 6% 6% 15% 9% 15% 9% 9% 18% 12% 18% 21% 12% 15% 12% 21% 24% 15% 18% 15% 27% 24% 21% 18% 30% 27% 18% 24% 21% 27% 30% 30% 33% 21% 33% 24% 36% 33% 36% 27% 24% 39% 36% 30% 39% 42% 27% 33% 45% 39% 42% 36% 30% 42% 48% 45% 39% 33% 51% 45% 42% 48% 36% 48% 45% 54% 51% 39% 51% 57% 48% 54% 54% 42% 60% 51% 57% 57% 63% 45% 54% 60% 60% 66% 48% 63% 57% 69% 63% 51% 66% 60% 66% 72% 69% 54% 63% 69% 75% 72% 66% 57% 72% 78% 69% 75% 75% 60% 81% 72% 78% 78% 84% 63% 75% 81% 81% 87% 66% 78% 84% 84% 90% 81% 69% 87% 87% 93% 84% 90% 90% 72% 96% 87% 93% 93% 75% 99% 90% 100%
96% 96% 93% 78% 99% 100% 96%
99% 81% 100%
99% 100%
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WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasinTmp2_1.tif> created.
WARNING: MASK already exists and will be overwritten
WARNING: MASK already exists and will be overwritten
WARNING: Precision loss: Float32 can not preserve the DCELL precision of
raster <flow>. This can be avoided by using Float64
WARNING: Forcing raster export
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <Float32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
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r.out.gdal complete. File </content/flow_1.tif> created.
WARNING: MASK already exists and will be overwritten
WARNING: Color table of raster map <stream> not found
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasinTmp1_2.tif> created.
0% 3% 6% 0% 0% 0% 9% 0% 12% 3% 3% 15% 18% 3% 3% 6% 21% 6% 6% 6% 9% 24% 9% 9% 9% 27% 12% 12% 12% 12% 15% 30% 15% 15% 18% 15% 18% 33% 18% 21% 21% 36% 18% 21% 24% 21% 24% 24% 39% 24% 27% 27% 27% 27% 42% 30% 30% 30% 30% 33% 45% 33% 33% 36% 39% 33% 48% 42% 36% 36% 45% 51% 36% 39% 48% 39% 54% 42% 39% 51% 42% 57% 42% 60% 45% 54% 63% 45% 66% 48% 45% 48% 57% 69% 51% 48% 60% 51% 72% 54% 51% 54% 63% 75% 54% 57% 57% 66% 60% 57% 78% 60% 63% 69% 60% 81% 63% 66% 72% 63% 66% 84% 69% 75% 66% 69% 87% 72% 78% 72% 90% 75% 69% 81% 93% 78% 75% 72% 84% 81% 96% 78% 87% 75% 84% 90% 99% 87% 81% 100%
78% 84% 93% 90% 81% 87% 93% 96% 84% 90% 99% 96% 100%
93% 87% 96% 99% 100% 99%
100%
90% 93% 96% 99% 100%
WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasinTmp2_2.tif> created.
WARNING: MASK already exists and will be overwritten
WARNING: MASK already exists and will be overwritten
WARNING: Precision loss: Float32 can not preserve the DCELL precision of
raster <flow>. This can be avoided by using Float64
WARNING: Forcing raster export
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <Float32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/flow_2.tif> created.
WARNING: MASK already exists and will be overwritten
WARNING: Color table of raster map <stream> not found
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasinTmp1_3.tif> created.
0% 3% 6% 0% 0% 0% 3% 6% 0% 9% 3% 3% 12% 9% 6% 3% 6% 15% 12% 6% 18% 9% 15% 9% 9% 21% 12% 18% 24% 12% 21% 12% 15% 27% 24% 15% 15% 18% 27% 30% 30% 21% 18% 18% 33% 33% 24% 21% 21% 36% 36% 27% 24% 24% 30% 39% 39% 33% 36% 39% 27% 27% 42% 42% 42% 45% 30% 30% 45% 48% 45% 51% 48% 33% 33% 54% 48% 51% 36% 36% 57% 51% 54% 39% 60% 54% 39% 57% 63% 42% 57% 42% 60% 66% 45% 60% 45% 69% 63% 48% 51% 63% 54% 48% 72% 66% 57% 66% 60% 69% 51% 75% 69% 72% 54% 63% 72% 78% 66% 75% 57% 75% 69% 81% 78% 78% 60% 84% 87% 72% 81% 63% 81% 90% 75% 84% 66% 84% 87% 93% 90% 93% 78% 69% 96% 96% 87% 81% 99% 99% 100%
72% 100%
90% 75% 84% 78% 93% 81% 87% 96% 84% 90% 99% 100%
87% 93% 90% 96% 93% 99% 100%
96% 99% 100%
WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasinTmp2_3.tif> created.
WARNING: MASK already exists and will be overwritten
WARNING: MASK already exists and will be overwritten
WARNING: Precision loss: Float32 can not preserve the DCELL precision of
raster <flow>. This can be avoided by using Float64
WARNING: Forcing raster export
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <Float32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/flow_3.tif> created.
Done.
Goodbye from GRASS GIS
Merge flow accumulation tiles
[10]:
%%bash
gdalbuildvrt -srcnodata -9999999 -vrtnodata -9999999 /content/flow_all.vrt /content/flow_?.tif
gdal_translate -co COMPRESS=DEFLATE -co ZLEVEL=9 /content/flow_all.vrt /content/flow_all.tif
0...10...20...30...40...50...60...70...80...90...100 - done.
Input file size is 5616, 8244
0...10...20...30...40...50...60...70...80...90...100 - done.
[11]:
flow = rasterio.open("/content/flow_all.tif")
# Create a figure and an axes
fig, ax = plt.subplots(figsize=(8, 8))
show(flow, ax=ax , cmap='gist_earth', vmin=-2000, vmax=20000 , interpolation='bicubic')
ax.set_xlabel("Longitude")
ax.set_ylabel("Latitude")
plt.tight_layout()
plt.show()
Compute continental seamless basins and streams
Redelineate the basin and streams using the same procedure then before but using the continental flow accumulation.
[12]:
%%bash
rm -fr /content/hydrographySA_2
grass --text -c /content/flow_all.tif /content/hydrographySA_2 --exec <<'EOF'
## import the layers
r.external input=/content/flow_all.tif output=flow --o --q # flow accumulation
r.external input=/content/SA_elevation.tif output=elv --o --q # dem
r.external input=/content/SA_dep.tif output=dep --o --q # depression
r.external input=/content/SA_msk.tif output=msk --o --q # land-ocean mask
g.region -m
for tile in 1 2 3 ; do # loop for each tile
r.mask raster=msk --o # usefull to mask the flow accumulation
wL=$(ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $2 }')
nL=$(ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $3 }')
eL=$(ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $4 }')
sL=$(ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep POLYGON | awk '{ gsub(/[(()),]/," ",$0 ); print $7 }')
g.region w=$wL n=$nL s=$sL e=$eL res=0:00:30 --o
g.region -m
### maximum ram 66571M for 2^63 -1 (2 147 483 647 cell) / 1 000 000 * 31 M
#### -m Enable disk swap memory option: Operation is slow
#### -b Beautify flat areas
#### threshold=1 = ~1 km2 = 0.9 m2
echo "############# extract stream ##################"
r.stream.extract elevation=elv accumulation=flow depression=dep threshold=8 direction=dir_rs stream_raster=stream memory=4000 --o --q
echo "############# delineate basin and sub-basin ##################"
r.stream.basins -l stream_rast=stream direction=dir_rs basins=lbasin memory=2000 --o --q
r.colors -r stream --q; r.colors -r lbasin --q ; r.colors -r flow --q
echo "###### create a small zone flow binary for later use ###########"
r.mapcalc " small_zone_flow = if( !isnull(flow) && isnull(lbasin) , 1 , null()) " --o --q
echo "##### create a smaller box ########"
CropW=$( ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep " CropW" | awk '{print $4}' )
CropE=$( ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep " CropE" | awk '{print $4}' )
CropS=$( ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep " CropS" | awk '{print $4}' )
CropN=$( ogrinfo -al -where " id = '$tile' " /content/tilesComp.gpkg | grep " CropN" | awk '{print $4}' )
nS=$(g.region -m | grep ^n= | awk -F "=" -v CropN=$CropN '{ printf ("%.14f\n" , $2 - CropN ) }' )
sS=$(g.region -m | grep ^s= | awk -F "=" -v CropS=$CropS '{ printf ("%.14f\n" , $2 + CropS ) }' )
eS=$(g.region -m | grep ^e= | awk -F "=" -v CropE=$CropE '{ printf ("%.14f\n" , $2 - CropE ) }' )
wS=$(g.region -m | grep ^w= | awk -F "=" -v CropW=$CropW '{ printf ("%.14f\n" , $2 + CropW ) }' )
g.region w=$wS n=$nS s=$sS e=$eS res=0:00:30 save=smallext --o --q # smaller region
g.region region=smallext --o --q
g.region -m --q
echo "######## left stripe ########"
eST=$(g.region -m | grep ^e= | awk -F "=" '{ print $2 }')
wST=$(g.region -m | grep ^e= | awk -F "=" '{ printf ("%.14f\n" , $2 - ( 1 * 0.00833333333333 )) }' )
g.region n=$nS s=$sS e=$eST w=$wST res=0:00:30 --o --q
r.mapcalc " lbasin_wstripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## right stripe ########"
wST=$(g.region -m | grep ^w= | awk -F "=" '{ print $2 }' )
eST=$(g.region -m | grep ^w= | awk -F "=" '{ printf ("%.14f\n" , $2 + ( 1 * 0.00833333333333 )) }' )
g.region n=$nS s=$sS e=$eST w=$wST res=0:00:30 --o --q
r.mapcalc " lbasin_estripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## top stripe ########"
nST=$(g.region -m | grep ^n= | awk -F "=" '{ print $2 }' )
sST=$(g.region -m | grep ^n= | awk -F "=" '{ printf ("%.14f\n" , $2 - ( 1 * 0.00833333333333 )) }' )
g.region e=$eS w=$wS n=$nST s=$sST res=0:00:30 --o --q
r.mapcalc " lbasin_nstripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## bottom stripe ########"
sST=$(g.region -m | grep ^s= | awk -F "=" '{ print $2 }' )
nST=$(g.region -m | grep ^s= | awk -F "=" '{ printf ("%.14f\n" , $2 + ( 1 * 0.00833333333333 )) }' )
g.region e=$eS w=$wS n=$nST s=$sST res=0:00:30 --o --q
r.mapcalc " lbasin_sstripe = lbasin " --o --q
g.region region=smallext --o --q
echo "######## remove incompleate basins ########"
cat <(r.report -n -h units=c map=lbasin_estripe | awk '{gsub ("\\|"," "); { print $1 }}' | awk '$1 ~ /^[0-9]+$/ {print $1} ' ) \
<(r.report -n -h units=c map=lbasin_wstripe | awk '{gsub ("\\|"," "); { print $1 }}' | awk '$1 ~ /^[0-9]+$/ {print $1} ' ) \
<(r.report -n -h units=c map=lbasin_sstripe | awk '{gsub ("\\|"," "); { print $1 }}' | awk '$1 ~ /^[0-9]+$/ {print $1} ' ) \
<(r.report -n -h units=c map=lbasin_nstripe | awk '{gsub ("\\|"," "); { print $1 }}' | awk '$1 ~ /^[0-9]+$/ {print $1} ' ) \
<(r.report -n -h units=c map=lbasin | awk '{gsub ("\\|"," "); { print $1 }}' | awk '$1 ~ /^[0-9]+$/ {print $1} ' ) \
| sort | uniq -c | awk '{ if($1==1) {print $2"="$2 } else { print $2"=NULL"} }' > /content/lbasin_${tile}_reclass.txt
r.reclass input=lbasin output=lbasin_rec rules=/content/lbasin_${tile}_reclass.txt --o --q
rm -f /content/lbasin_${tile}_reclass.txt
r.mapcalc " lbasin_clean = lbasin_rec" --o --q
g.remove -f type=raster name=lbasin_rec,lbasin_estripe,lbasin_wstripe,lbasin_nstripe,lbasin_sstripe --q
echo "############ export basin sub-basin and stream ############"
r.mask raster=lbasin_clean --o --q
r.out.gdal --o -c -m createopt="COMPRESS=DEFLATE,ZLEVEL=9" type=UInt32 format=GTiff nodata=0 input=lbasin output=/content/lbasin_$tile.tif
r.out.gdal --o -c -m createopt="COMPRESS=DEFLATE,ZLEVEL=9" type=UInt32 format=GTiff nodata=0 input=stream output=/content/stream_$tile.tif
done
EOF
projection=3
zone=0
n=12.7
s=-56
w=-81.4
e=-34.6
nsres=923.4698013
ewres=706.8356204
rows=8244
cols=5616
cells=46298304
projection=3
zone=0
n=-12
s=-56
w=-76.4
e=-43
nsres=924.52244935
ewres=710.89449752
rows=5280
cols=4008
cells=21162240
############# extract stream ##################
############# delineate basin and sub-basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=-14
s=-56
w=-75.8
e=-45
nsres=924.64630106
ewres=707.62000721
rows=5040
cols=3696
cells=18627840
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin sub-basin and stream ############
projection=3
zone=0
n=1
s=-38
w=-73.9
e=-34.6
nsres=922.66504302
ewres=826.93226998
rows=4680
cols=4716
cells=22070880
############# extract stream ##################
############# delineate basin and sub-basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=-1.8
s=-35.2
w=-71.1
e=-34.6
nsres=922.59157279
ewres=840.84791606
rows=4008
cols=4380
cells=17555040
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin sub-basin and stream ############
projection=3
zone=0
n=12.7
s=-24.5
w=-81.7
e=-41.7
nsres=921.8619211
ewres=872.86703289
rows=4464
cols=4800
cells=21427200
############# extract stream ##################
############# delineate basin and sub-basin ##################
###### create a small zone flow binary for later use ###########
##### create a smaller box ########
projection=3
zone=0
n=12.7
s=-21.7
w=-81.4
e=-44.5
nsres=921.77907927
ewres=882.26518613
rows=4128
cols=4428
cells=18278784
######## left stripe ########
######## right stripe ########
######## top stripe ########
######## bottom stripe ########
######## remove incompleate basins ########
############ export basin sub-basin and stream ############
Starting GRASS GIS...
Creating new GRASS GIS project <hydrographySA_2>...
__________ ___ __________ _______________
/ ____/ __ \/ | / ___/ ___/ / ____/ _/ ___/
/ / __/ /_/ / /| | \__ \\_ \ / / __ / / \__ \
/ /_/ / _, _/ ___ |___/ /__/ / / /_/ // / ___/ /
\____/_/ |_/_/ |_/____/____/ \____/___//____/
Welcome to GRASS GIS 8.4.1
GRASS GIS homepage: https://grass.osgeo.org
This version running through: Bash Shell (/bin/bash)
Help is available with the command: g.manual -i
See the licence terms with: g.version -c
See citation options with: g.version -x
Start the GUI with: g.gui wxpython
When ready to quit enter: exit
All subsequent raster operations will be limited to the MASK area. Removing
or renaming raster map named 'MASK' will restore raster operations to
normal.
WARNING: Color table of raster map <stream> not found
0% 0% 0% 0% 0% 3% 3% 3% 3% 3% 6% 6% 6% 6% 6% 9% 9% 9% 9% 9% 12% 12% 12% 12% 12% 15% 15% 15% 15% 18% 15% 18% 18% 18% 21% 18% 21% 21% 21% 24% 21% 24% 24% 24% 27% 24% 27% 27% 27% 30% 27% 30% 30% 33% 33% 30% 33% 30% 36% 36% 39% 36% 33% 33% 42% 39% 36% 36% 39% 45% 42% 39% 39% 42% 48% 45% 42% 42% 45% 51% 48% 45% 48% 48% 45% 54% 51% 51% 51% 57% 48% 54% 60% 54% 54% 51% 57% 63% 57% 57% 60% 66% 54% 63% 60% 66% 60% 69% 69% 57% 63% 63% 66% 72% 66% 72% 60% 69% 75% 75% 63% 69% 72% 78% 78% 66% 69% 72% 81% 75% 72% 81% 78% 75% 84% 75% 84% 87% 90% 81% 78% 78% 87% 93% 84% 81% 81% 96% 90% 87% 84% 99% 84% 100%
93% 87% 87% 90% 90% 96% 93% 90% 93% 99% 96% 100%
93% 96% 96% 99% 99% 99% 100%
100%
100%
WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasin_1.tif> created.
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/stream_1.tif> created.
WARNING: MASK already exists and will be overwritten
All subsequent raster operations will be limited to the MASK area. Removing
or renaming raster map named 'MASK' will restore raster operations to
normal.
WARNING: Color table of raster map <stream> not found
WARNING: Color table of raster map <flow> not found
0% 0% 0% 0% 3% 3% 3% 3% 0% 6% 6% 6% 6% 3% 9% 9% 6% 9% 9% 12% 9% 12% 12% 12% 15% 15% 12% 15% 18% 15% 18% 15% 18% 21% 18% 21% 24% 18% 21% 24% 21% 21% 27% 27% 24% 24% 30% 24% 30% 27% 27% 33% 27% 33% 30% 30% 36% 36% 30% 39% 33% 33% 42% 33% 39% 36% 36% 45% 36% 42% 39% 39% 48% 39% 42% 45% 42% 51% 42% 45% 48% 45% 45% 48% 54% 51% 48% 48% 51% 57% 54% 57% 51% 51% 54% 60% 60% 54% 63% 57% 54% 57% 63% 57% 60% 60% 66% 66% 63% 60% 63% 69% 69% 66% 63% 72% 72% 66% 69% 66% 72% 69% 75% 75% 75% 69% 78% 72% 72% 78% 78% 81% 75% 75% 81% 84% 81% 78% 78% 84% 84% 81% 87% 81% 90% 84% 87% 87% 93% 87% 84% 90% 90% 96% 90% 87% 93% 93% 99% 93% 100%
90% 96% 96% 96% 93% 99% 99% 100%
99% 100%
100%
96% 99% 100%
WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasin_2.tif> created.
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/stream_2.tif> created.
WARNING: MASK already exists and will be overwritten
All subsequent raster operations will be limited to the MASK area. Removing
or renaming raster map named 'MASK' will restore raster operations to
normal.
WARNING: Color table of raster map <stream> not found
WARNING: Color table of raster map <flow> not found
0% 3% 6% 9% 12% 0% 0% 0% 0% 3% 3% 3% 3% 15% 6% 9% 6% 6% 18% 6% 12% 9% 15% 21% 9% 9% 18% 12% 21% 12% 24% 12% 24% 15% 27% 15% 15% 27% 30% 18% 30% 18% 18% 33% 36% 21% 33% 21% 21% 39% 24% 36% 24% 42% 27% 27% 24% 39% 30% 45% 30% 42% 27% 33% 33% 48% 30% 36% 36% 45% 33% 51% 39% 39% 54% 48% 57% 36% 42% 42% 60% 51% 45% 54% 39% 45% 63% 57% 48% 48% 42% 66% 60% 51% 51% 45% 69% 63% 54% 54% 48% 72% 57% 66% 57% 51% 75% 60% 60% 69% 54% 78% 63% 63% 72% 57% 81% 66% 66% 75% 60% 69% 84% 69% 78% 63% 72% 72% 87% 81% 66% 75% 75% 90% 84% 69% 78% 78% 93% 87% 72% 81% 81% 90% 96% 75% 84% 84% 93% 87% 78% 99% 100%
96% 87% 90% 81% 99% 100%
90% 93% 84% 93% 96% 87% 96% 90% 99% 100%
99% 93% 100%
96% 99% 100%
WARNING: MASK already exists and will be overwritten
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/lbasin_3.tif> created.
Checking GDAL data type and nodata value...
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
Using GDAL data type <UInt32>
Exporting raster data to GTiff format...
WARNING: Too many values, color table cut to 65535 entries
2% 5% 8% 11% 14% 17% 20% 23% 26% 29% 32% 35% 38% 41% 44% 47% 50% 53% 56% 59% 62% 65% 68% 71% 74% 77% 80% 83% 86% 89% 92% 95% 98% 100%
r.out.gdal complete. File </content/stream_3.tif> created.
Done.
Goodbye from GRASS GIS
Merge tiled basins and streams
[13]:
%%bash
for var in lbasin stream ; do
gdalbuildvrt -srcnodata 0 -vrtnodata 0 /content/${var}_all.vrt /content/${var}_?.tif
gdal_translate -co COMPRESS=DEFLATE -co ZLEVEL=9 /content/${var}_all.vrt /content/${var}_all.tif
pkstat --hist -i /content/${var}_all.tif | grep -v " 0" > /content/${var}_all.hist
wc=$(wc -l /content/${var}_all.hist | awk '{ print $1 -1 }' )
# create color table
paste -d " " <( awk '{print $1}' /content/${var}_all.hist) <(echo 0; shuf -i 1-255 -n $wc -r) <(echo 0; shuf -i 1-255 -n $wc -r) <(echo 0 ; shuf -i 1-255 -n $wc -r) | awk '{ if (NR==1) {print $0 , 0 } else { print $0 , 255 }}' > /content/${var}_all_ct.hist
echo " "
echo "color table"
head /content/${var}_all_ct.hist
echo " "
# apply color table to the stream and basins
gdaldem color-relief -co COMPRESS=DEFLATE -co ZLEVEL=9 -co TILED=YES -co COPY_SRC_OVERVIEWS=YES -alpha /content/${var}_all.tif /content/${var}_all_ct.hist /content/${var}_all_ct.tif
done
0...10...20...30...40...50...60...70...80...90...100 - done.
Input file size is 5616, 8244
0...10...20...30...40...50...60...70...80...90...100 - done.
color table
0 0 0 0 0
3271 170 118 174 255
4747 138 55 237 255
5069 246 183 166 255
8023 191 71 18 255
12022 6 254 211 255
12641 45 3 68 255
20626 204 44 255 255
32935 152 220 232 255
33148 31 117 38 255
0...10...20...30...40...50...60...70...80...90...100 - done.
0...10...20...30...40...50...60...70...80...90...100 - done.
Input file size is 5616, 8244
0...10...20...30...40...50...60...70...80...90...100 - done.
color table
0 0 0 0 0
1 96 24 211 255
2 86 16 213 255
3 143 127 55 255
4 47 212 147 255
5 205 143 208 255
6 163 134 115 255
7 24 14 205 255
8 15 240 128 255
9 199 154 203 255
0...10...20...30...40...50...60...70...80...90...100 - done.
[14]:
basins = rasterio.open("/content/lbasin_all.tif")
# Create a figure and an axes
fig, ax = plt.subplots(figsize=(8, 8))
show(basins, ax=ax, cmap='prism', interpolation='nearest')
ax.set_xlabel("Longitude")
ax.set_ylabel("Latitude")
plt.tight_layout()
plt.show()
[15]:
streams = rasterio.open("/content/stream_all.tif")
# Create a figure and an axes
fig, ax = plt.subplots(figsize=(10, 10))
show(streams, ax=ax, cmap='prism', interpolation='nearest')
ax.set_xlabel("Longitude")
ax.set_ylabel("Latitude")
plt.tight_layout()
plt.show()
