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NAME - Compute the stream order of stream networks stored in a vector map at specific outlet vector points


vector, hydrology, stream network, stream order

SYNOPSIS --help input=name points=name output=name [threshold=float] [order=string[,string,...]] [columns=string[,string,...]] [recursionlimit=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]


Allow output files to overwrite existing files
Print usage summary
Verbose module output
Quiet module output
Force launching GUI dialog


input=name [required]
Name of input vector map
Name of the stream networks vector map
points=name [required]
Name of the input vector point map
Name of the points vector map that defines the water outlets of the stream networks
output=name [required]
Name of the vector output map
The name for the stream order vector output map
threshold in projection units used to search for outflow points at the stream network
Default: 25
The stream order to compute
Options: strahler, shreve, scheidegger, drwal
Default: strahler,shreve
The columns that should be copied from the input stream vector map. By default all will be copied.
Default: all
The Python recursion limit that should be used (Python default is 1000)
Default: 10000

Table of contents


The module is designed to compute different stream order approaches based on a stream network vector map and a water outlet vector point map. It requires two inputs:
  1. A vector line map with one or several independent stream networks
  2. A vector point map that defines the water outlet points in the stream network
A single output vector map containing all detected networks and all specified orders is generated as output.

The direction of the stream flow will be adjusted in outlet direction and stored in the output vector map.

To determine the outlet stream network segment, a nearest neighbor search is performed. The threshold of the search can be adjusted with the threshold option. It is required to specify the threshold as floating point value that is interpreted using the locations projection unit.

It is required that the vector line direction of the network segment that was found at the outlet point, is directed to the outlet point. Since, the depth-first search network traversing will be performed in upstream direction. Stream networks in downstream direction will be detected. However, the stream order will not be computed. The stream order table entries will be empty.

The output vector map contains a column for each specified order algorithm, the network id, the outlet category of the vector point input map and the column reversed. The column reversed indicates if the stream network segment was reversed in direction to point to the water outlet point (0 - not reversed, 1 - reversed).

In addition all columns from the stream network input map are copied to the output vector map. The input vector map columns that should be copied will be automagically renamed in the output vector map, if the column names are conflicting with each other. Use the columns parameter to specifiy a subset of columns that should be copied. The keyword all is used to copy all columns to the output vector map that are found in the input vector map (default).


Be aware that the stream network map must be topological correct. Each independent stream network must be properly connected. The implemented stream order algorithms rely on topological relations between lines and nodes and are not designed to handle loops and channels in the stream networks correctly.

The network traversing method, that is used to compute the stream order numbers, is recursively implemented. In case of large stream networks, or networks with many loops, the maximum recursion depth of Python may be reached. The module will stop then with an maximum recursion depth exceeded exception. This parameter can be adjusted with the recursionlimit option. The default in Python is 1000. The default in is 10000.

Supported stream order algorithms

The following algorithm examples are based on this stream network. Be aware of the wrong stream directions that will be adjusted by

Strahler's stream order

Strahler's stream order is a modification of Horton's streams order which fixes the ambiguity of Horton's ordering. In Strahler's ordering the main channel is not determined; instead the ordering is based on the hierarchy of tributaries. The ordering follows these rules:
  1. if the node has no children, its Strahler order is 1.
  2. if the node has one and only one tributuary with Strahler greatest order i, and all other tributaries have order less than i, then the order remains i.
  3. if the node has two or more tributaries with greatest order i, then the Strahler order of the node is i + 1.
Strahler's stream ordering starts in initial links which assigns order one. It proceeds downstream. At every node it verifies that there are at least 2 equal tributaries with maximum order. If not it continues with highest order, if yes it increases the node's order by 1 and continues downstream with new order.

Advantages and disadvantages of Strahler's ordering: Strahler's stream order has a good mathematical background. All catchments with streams in this context are directed graphs, oriented from the root towards the leaves. Equivalent definition of the Strahler number of a tree is that it is the height of the largest complete binary tree that can be homeomorphically embedded into the given tree; the Strahler number of a node in a tree is equivalent to the height of the largest complete binary tree that can be embedded below that node.

The disadvantage of that methods is the lack of distinguishing a main channel which may interfere with the analytical process in highly elongated catchments. It is not able to handle loops in the ordered graph correctly.

Shreve's stream magnitude

That ordering method is similar to Consisted Associated Integers proposed by Scheidegger. It assigns magnitude of 1 for every initial channel. The magnitude of the following channel is the sum of magnitudes of its tributaries. The number of a particular link is the number of initials which contribute to it.

Scheidegger's stream magnitude

That ordering method is similar to Shreve's stream magnitude. It assigns magnitude of 2 for every initial channel. The magnitude of the following channel is the sum of magnitudes of its tributaries. The number of a particular link is the number of streams -1 contributing to it.

Drwal's stream hierarchy

That ordering method is a compromise between Strahler ordering and Shreve magnitude. It assigns order of 1 for every initial channel. The order of the following channel is calculated according Strahler formula, except, that streams which do not increase order of next channel are not lost. To increase next channel to the higher order R+1 are require two channels of order R, or one R and two R-1 or one R, and four R-2 or one R, one R-1 and two R-2 etc. The the order of particular link show the possible value of Strahler'order if the network was close to idealized binary tree. Drwal's order is computed based on Shreve's magnitude with the formula: floor(log(shreve,2))+1.

Advantages and disadvantages of Drwal's hierarhy: The main advantages of Drwal's hierarchy is that it produces natural stream ordering with which takes into advantage both ordering and magnitude. It shows the real impact of particular links of the network run-off. The main disadvantage is that it minimize bifurcation ratio of the network.


Stream order computation based on North Carolina location

# We need to generate 4 outlet points that will lead to
# 4 stream networks and therefore 4 output vector maps
cat > points.csv << EOF
EOF output=streams_outlets input=points.csv x=1 y=2 input=streams@PERMANENT points=streams_outlets \
    output=streams_order threshold=25 order=strahler,shreve streams_order streams_order | less

Stream order computation based on testsuite data input=stream_network points=stream_network_outlets \
    output=stream_network_order threshold=25 \
    order=strahler,shreve,drwal,scheidegger stream_network_order stream_network_order | less


Depth first search at Wikipedia
Strahler number at Wikipedia


IGB-Berlin,Johannes Radinger; Implementation: Geoinformatikbüro Dassau GmbH , Soeren Gebbert

This tool was developed as part of the BiodivERsA-net project 'FISHCON' and has been funded by the German Federal Ministry for Education and Research (grant number 01LC1205).

Documentation of the implemented algorithms are in most parts copied from implemented by: Jarek Jasiewicz and Markus Metz


Available at: source code (history)

Latest change: Friday Mar 17 10:41:24 2023 in commit: 5e55dedb2919e99b95f240ed65768c8200c7c465

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