[GRASS-user] Global Hydrological modeling with r.watershed, r.stream.extract, r.stream.extract
giuseppe.amatulli at gmail.com
Thu Jun 11 08:12:26 PDT 2020
after several tests and a bit of inverse-engineering, Longzhu and I have
understood the reason of such as a small difference in the delineation of
the polygons basins.
All the process beyond r.watershed are computed in 3x3 moving window (e.g.
slope, flow accumulation, etc.), therefore if we change the extent of study
area we change the starting point of the mowing window and of course the
values of the flow accumulation change a bit. These changes in the flow
accumulation cause variation on the delineations of the basin borders, of
The reason, it is a bit obvious but did not come into my mind, immediately.
Now I'm trying to figure out a clever way to merge these flow accumulations
that come from different tiles and that are slightly different.
On Fri, 5 Jun 2020 at 02:21, Markus Neteler <neteler at osgeo.org> wrote:
> Hi Giuseppe,
> On Wed, May 13, 2020 at 2:16 AM Giuseppe Amatulli
> <giuseppe.amatulli at gmail.com> wrote:
> > Hi Markus,
> > I use GRASS 7.6.0
> > under a HPC running
> > Distributor ID: RedHatEnterpriseServer
> > Description: Red Hat Enterprise Linux Server release 7.7 (Maipo)
> > Release: 7.7
> > Codename: Maipo
> > The compression is:
> > GRASS 7.6.0 (nc_spm_08_grass7):~ > r.compress -p map=flow
> > <flow> is compressed (method 5: ZSTD). Data type: DCELL
> > <flow> has a compressed NULL file
> > [Raster MASK present].
> > My option in selecting r.watershed with out the -m is manly due to be
> able to use the -b option and also be able to run the tile-computation in 6
> hours vs several days (probably weeks) of the full globe (or continents)
> run in segmentation mode - made quit hard to do debugging and re-running.
> > Do you have any suggestions for the mismatching of the borders?
> I have no idea but it is recommended to update to GRASS GIS 7.8.3.
Giuseppe Amatulli, Ph.D.
Research scientist at
School of Forestry & Environmental Studies
Center for Research Computing
New Haven, CT, USA
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