1r.watershed(1)                Grass User's Manual               r.watershed(1)
2
3
4

NAME

6       r.watershed  - Calculates hydrological parameters and RUSLE factors.
7

KEYWORDS

9       raster,  hydrology,  watershed, accumulation, drainage, stream network,
10       stream power index, topographic index
11

SYNOPSIS

13       r.watershed
14       r.watershed --help
15       r.watershed [-s4mab]  elevation=name   [depression=name]    [flow=name]
16       [disturbed_land=name]    [blocking=name]    [retention=name]   [thresh‐
17       old=integer]        [max_slope_length=float]        [accumulation=name]
18       [tci=name]        [spi=name]        [drainage=name]        [basin=name]
19       [stream=name]   [half_basin=name]   [length_slope=name]   [slope_steep‐
20       ness=name]    [convergence=integer]    [memory=integer]   [--overwrite]
21       [--help]  [--verbose]  [--quiet]  [--ui]
22
23   Flags:
24       -s
25           SFD (D8) flow (default is MFD)
26           SFD: single flow direction, MFD: multiple flow direction
27
28       -4
29           Allow only horizontal and vertical flow of water
30
31       -m
32           Enable disk swap memory option: Operation is slow
33           Only needed if memory requirements exceed available RAM; see manual
34           on how to calculate memory requirements
35
36       -a
37           Use positive flow accumulation even for likely underestimates
38           See manual for a detailed description of flow accumulation output
39
40       -b
41           Beautify flat areas
42           Flow direction in flat areas is modified to look prettier
43
44       --overwrite
45           Allow output files to overwrite existing files
46
47       --help
48           Print usage summary
49
50       --verbose
51           Verbose module output
52
53       --quiet
54           Quiet module output
55
56       --ui
57           Force launching GUI dialog
58
59   Parameters:
60       elevation=name [required]
61           Name of input elevation raster map
62
63       depression=name
64           Name of input depressions raster map
65           All non-NULL and non-zero cells are considered as real depressions
66
67       flow=name
68           Name of input raster representing amount of overland flow per cell
69
70       disturbed_land=name
71           Name of input raster map percent of disturbed land
72           For USLE
73
74       blocking=name
75           Name of input raster map blocking overland surface flow
76           For  USLE. All non-NULL and non-zero cells are considered as block‐
77           ing terrain.
78
79       retention=name
80           Name of input raster map with percentages for flow accumulation.
81
82       threshold=integer
83           Minimum size of exterior watershed basin
84
85       max_slope_length=float
86           Maximum length of surface flow in map units
87           For USLE
88
89       accumulation=name
90           Name for output accumulation raster map
91           Number of cells that drain through each cell
92
93       tci=name
94           Name for output topographic index ln(a / tan(b)) map
95
96       spi=name
97           Name for output stream power index a * tan(b)
98           Name for output raster map
99
100       drainage=name
101           Name for output drainage direction raster map
102           Directions numbered from 1 to 8
103
104       basin=name
105           Name for output basins raster map
106
107       stream=name
108           Name for output stream segments raster map
109
110       half_basin=name
111           Name for output half basins raster map
112           Each half-basin is given a unique value
113
114       length_slope=name
115           Name for output slope length raster map
116           Slope length and steepness (LS) factor for USLE
117
118       slope_steepness=name
119           Name for output slope steepness raster map
120           Slope steepness (S) factor for USLE
121
122       convergence=integer
123           Convergence factor for MFD (1-10)
124           1 = most diverging flow, 10 = most converging flow. Recommended: 5
125           Default: 5
126
127       memory=integer
128           Maximum memory to be used with -m flag (in MB)
129           Default: 300
130

DESCRIPTION

132       r.watershed generates a set of maps indicating: 1)  flow  accumulation,
133       drainage  direction,  the location of streams and watershed basins, and
134       2) the LS and S factors of the Revised  Universal  Soil  Loss  Equation
135       (RUSLE).
136

NOTES

138       Without flag -m set, the entire analysis is run in memory maintained by
139       the operating system. This can be limiting, but is very  fast.  Setting
140       this flag causes the program to manage memory on disk which allows very
141       large maps to be processed but is slower.
142
143       Flag -s force the module to use single flow direction (SFD, D8) instead
144       of multiple flow direction (MFD). MFD is enabled by default.
145
146       By  -4  flag the user allow only horizontal and vertical flow of water.
147       Stream and slope lengths are approximately the  same  as  outputs  from
148       default surface flow (allows horizontal, vertical, and diagonal flow of
149       water).  This flag will also make the drainage basins look more homoge‐
150       neous.
151
152       When  -a  flag is specified the module will use positive flow accumula‐
153       tion even for likely underestimates. When this flag is not  set,  cells
154       with  a  flow  accumulation value that is likely to be an underestimate
155       are converted to the negative. See below for a detailed description  of
156       flow accumulation output.
157
158       Option  convergence  specifies convergence factor for MFD. Lower values
159       result in higher divergence, flow is more  widely  distributed.  Higher
160       values  result  in higher convergence, flow is less widely distributed,
161       becoming more similar to SFD.
162
163       Option elevation specifies the elevation data on which entire  analysis
164       is based. NULL (nodata) cells are ignored, zero and negative values are
165       valid elevation data.  Gaps in  the  elevation  map  that  are  located
166       within  the  area  of  interest  must  be  filled beforehand, e.g. with
167       r.fillnulls, to avoid distortions.   The  elevation  map  need  not  be
168       sink-filled because the module uses a least-cost algorithm.
169
170       Option  depression  specifies the optional map of actual depressions or
171       sinkholes in the landscape that are large enough to slow and store sur‐
172       face  runoff  from  a storm event.  All cells that are not NULL and not
173       zero indicate depressions. Water will flow into but not out of  depres‐
174       sions.
175
176       Raster  flow  map specifies amount of overland flow per cell.  This map
177       indicates the amount of overland flow units that each  cell  will  con‐
178       tribute to the watershed basin model. Overland flow units represent the
179       amount of overland flow each cell contributes to surface flow. If omit‐
180       ted, a value of one (1) is assumed.
181
182       Raster  retention  map  specifies  correction factors per cell for flow
183       distribution. This map indicates the percentage of overland flow  units
184       leaving each cell. Values should be between zero and 100. If omitted, a
185       value of 100 is assumed.
186
187       Input Raster map or value containing  the  percent  of  disturbed  land
188       (i.e.,  croplands,  and  construction  sites) where the raster or input
189       value of 17 equals 17%.  If no  map  or  value  is  given,  r.watershed
190       assumes  no  disturbed  land. This input is used for the RUSLE calcula‐
191       tions.
192
193       Option blocking specifies terrain  that  will  block  overland  surface
194       flow.  Blocking  cells and streams stop the slope length for the RUSLE.
195       All cells that are not NULL and not zero indicate blocking terrain.
196
197       Option threshold specifies the minimum size of  an  exterior  watershed
198       basin  in cells, if no flow map is input, or overland flow units when a
199       flow map is given.  Warning: low threshold  values  will  dramactically
200       increase  run  time and generate difficult to read basin and half_basin
201       results.  This parameter also controls  the  level  of  detail  in  the
202       stream segments map.
203
204       Value  given by max_slope_length option indicates the maximum length of
205       overland surface flow in meters. If overland flow travels greater  than
206       the  maximum length, the program assumes the maximum length (it assumes
207       that landscape characteristics not discernible in the digital elevation
208       model  exist  that  maximize the slope length).  This input is used for
209       the RUSLE calculations and is a sensitive parameter.
210
211       Output accumulation map contains the absolute value of  the  amount  of
212       overland  flow  that traverses each cell. This value will be the number
213       of upland cells plus one if no overland flow  map  is  given.   If  the
214       overland  flow  map is given, the value will be in overland flow units.
215       Negative numbers indicate that those cells possibly have surface runoff
216       from  outside  of  the  current geographic region. Thus, any cells with
217       negative values cannot have  their  surface  runoff  and  sedimentation
218       yields calculated accurately.
219
220       Output tci raster map contains topographic index TCI, computed as ln(α
221       / tan(β)) where α is the cumulative upslope area draining  through  a
222       point per unit contour length and tan(β) is the local slope angle. The
223       TCI reflects the tendency of water to accumulate at any  point  in  the
224       catchment  and the tendency for gravitational forces to move that water
225       downslope (Quinn et al. 1991).  This value will be  negative  if  α  /
226       tan(β) < 1.
227
228       Output spi raster map contains stream power index SPI, computed as α *
229       tan(β) where α is the cumulative  upslope  area  draining  through  a
230       point per unit contour length and tan(β) is the local slope angle. The
231       SPI reflects the power of water flow at any point in the catchment  and
232       the  tendency  for  gravitational  forces  to move that water downslope
233       (Moore et al. 1991).  This value will be negative if α < 0,  i.e.  for
234       cells  with  possible  surface  runoff from outside of the current geo‐
235       graphic region.
236
237       Output drainage raster map contains drainage direction.   Provides  the
238       "aspect" for each cell measured CCW from East.
239       Figure:  Drainage  is  8 directions numbered counter-clockwise starting
240       from 1 in north-east direction (source) Multiplying positive values  by
241       45  will  give  the  direction  in degrees that the surface runoff will
242       travel from that cell.  The value 0 (zero) indicates that the cell is a
243       depression area (defined by the depression input map).  Negative values
244       indicate that surface runoff is leaving the boundaries of  the  current
245       geographic  region.   The  absolute value of these negative cells indi‐
246       cates the direction of flow. For MFD, drainage indicates the  direction
247       of maximum flow.
248
249       The  output  basin  map contains unique label for each watershed basin.
250       Each basin will be given a unique positive even integer.   Areas  along
251       edges  may  not  be large enough to create an exterior watershed basin.
252       NULL values indicate that the cell is not part of a complete  watershed
253       basin in the current geographic region.
254
255       The  output  stream  contains stream segments. Values correspond to the
256       watershed basin values.  Can be vectorized after thinning (r.thin) with
257       r.to.vect.
258
259       The  output  half_basin  raster  map  stores each half-basin is given a
260       unique value. Watershed basins are divided into left and  right  sides.
261       The  right-hand side cell of the watershed basin (looking upstream) are
262       given even values corresponding to the values in basin.  The  left-hand
263       side  cells  of  the watershed basin are given odd values which are one
264       less than the value of the watershed basin.
265
266       The output length_slope raster map stores slope  length  and  steepness
267       (LS)  factor  for  the  Revised  Universal  Soil Loss Equation (RUSLE).
268       Equations taken from Revised Universal Soil Loss Equation  for  Western
269       Rangelands  (Weltz  et al. 1987). Since the LS factor is a small number
270       (usually less than one), the GRASS output map is of type DCELL.
271
272       The output slope_steepness raster map stores slope steepness (S) factor
273       for  the  Universal  Soil  Loss Equation (RUSLE).  Equations taken from
274       article entitled Revised Slope Steepness Factor for the Universal  Soil
275       Loss Equation (McCool et al. 1987).  Since the S factor is a small num‐
276       ber (usually less than one), the GRASS output map is of type DCELL.
277
278   AT least-cost search algorithm
279       r.watershed uses an AT least-cost search algorithm (see REFERENCES sec‐
280       tion)  designed  to minimize the impact of DEM data errors. Compared to
281       r.terraflow, this algorithm provides more accurate results in areas  of
282       low  slope  as  well  as  DEMs constructed with techniques that mistake
283       canopy tops as the ground elevation. Kinner et al. (2005), for example,
284       used  SRTM  and  IFSAR  DEMs to compare r.watershed against r.terraflow
285       results in Panama. r.terraflow was unable to replicate stream locations
286       in the larger valleys while r.watershed performed much better. Thus, if
287       forest canopy exists in valleys, SRTM, IFSAR, and similar data products
288       will  cause  major  errors  in r.terraflow stream output. Under similar
289       conditions, r.watershed will  generate  better  stream  and  half_basin
290       results.  If  watershed  divides contain flat to low slope, r.watershed
291       will generate better basin results than r.terraflow. (r.terraflow  uses
292       the  same  type  of algorithm as ESRI’s ArcGIS watershed software which
293       fails under these conditions.) Also, if watershed divides contain  for‐
294       est  canopy  mixed with uncanopied areas using SRTM, IFSAR, and similar
295       data products, r.watershed will  generate  better  basin  results  than
296       r.terraflow.  The  algorithm produces results similar to those obtained
297       when running r.cost and r.drain on every cell on the raster map.
298
299   Multiple flow direction (MFD)
300       r.watershed offers two methods to calculate surface flow:  single  flow
301       direction  (SFD, D8) and multiple flow direction (MFD). With MFD, water
302       flow is distributed to all neighbouring  cells  with  lower  elevation,
303       using slope towards neighbouring cells as a weighing factor for propor‐
304       tional distribution. The AT least-cost path is always  included.  As  a
305       result,  depressions  and  obstacles are traversed with a graceful flow
306       convergence before the overflow. The  convergence  factor  causes  flow
307       accumulation  to  converge  more  strongly with higher values. The sup‐
308       ported range is 1 to 10, recommended  is  a  convergence  factor  of  5
309       (Holmgren,  1994).  If  many  small sliver basins are created with MFD,
310       setting the convergence factor to a higher value can reduce the  amount
311       of small sliver basins.
312
313   In-memory mode and disk swap mode
314       There  are  two  versions of this program: ram and seg.  ram is used by
315       default, seg can be used by setting the -m flag.
316
317       The ram version requires a maximum of 31 MB of RAM for 1 million cells.
318       Together  with  the amount of system memory (RAM) available, this value
319       can be used to estimate whether the current  region  can  be  processed
320       with the ram version.
321
322       The  ram version uses virtual memory managed by the operating system to
323       store all the data structures and is faster than the seg  version;  seg
324       uses  the  GRASS segmentation library which manages data in disk files.
325       seg uses only as much system memory (RAM) as specified with the  memory
326       option,  allowing  other  processes to operate on the same system, even
327       when the current geographic region is huge.
328
329       Due to memory requirements of both programs, it is quite  easy  to  run
330       out  of  memory  when working with huge map regions. If the ram version
331       runs out of memory and the resolution size of  the  current  geographic
332       region cannot be increased, either more memory needs to be added to the
333       computer, or the swap space size needs to be increased. If seg runs out
334       of  memory,  additional disk space needs to be freed up for the program
335       to run.  The r.terraflow module was  specifically  designed  with  huge
336       regions in mind and may be useful here as an alternative, although disk
337       space requirements of r.terraflow are several times higher than of seg.
338
339   Large regions with many cells
340       The upper limit of the ram version  is  2  billion  (231  -  1)  cells,
341       whereas the upper limit for the seg version is 9 billion-billion (263 -
342       1 = 9.223372e+18) cells.
343       In some situations, the region size (number of cells) may be too  large
344       for  the  amount  of  time or memory available. Running r.watershed may
345       then require use of a coarser resolution.  To  make  the  results  more
346       closely  resemble the finer terrain data, create a map layer containing
347       the lowest elevation values at the coarser resolution. This is done by:
348       1)  Setting  the  current  geographic region equal to the elevation map
349       layer with g.region, and 2) Use the r.neighbors or r.resamp.stats  com‐
350       mand  to find the lowest value for an area equal in size to the desired
351       resolution. For example, if the resolution of the elevation data is  30
352       meters and the resolution of the geographic region for r.watershed will
353       be 90 meters: use the minimum function for a 3 by 3 neighborhood. After
354       changing  to  the resolution at which r.watershed will be run, r.water‐
355       shed should be run using the values from the  neighborhood  output  map
356       layer  that  represents  the minimum elevation within the region of the
357       coarser cell.
358
359   Basin threshold
360       The minimum size of drainage basins, defined by the  threshold  parame‐
361       ter,  is only relevant for those watersheds with a single stream having
362       at least the threshold of cells flowing into it.  (These watersheds are
363       called  exterior basins.)  Interior drainage basins contain stream seg‐
364       ments below multiple tributaries.  Interior drainage basins can  be  of
365       any size because the length of an interior stream segment is determined
366       by the distance between the tributaries flowing into it.
367
368   MASK and no data
369       The r.watershed program does not require the user to have  the  current
370       geographic  region  filled with elevation values.  Areas without eleva‐
371       tion data (masked or NULL cells) are ignored. It is  NOT  necessary  to
372       create  a  raster  map (or raster reclassification) named MASK for NULL
373       cells.  Areas without elevation data will be treated as if they are off
374       the  edge of the region. Such areas will reduce the memory necessary to
375       run the program.   Masking  out  unimportant  areas  can  significantly
376       reduce  processing  time  if  the watersheds of interest occupy a small
377       percentage of the overall area.
378
379       Gaps (NULL cells) in the elevation map that are located within the area
380       of  interest  will heavily influence the analysis: water will flow into
381       but not out of these gaps. These gaps must be filled  beforehand,  e.g.
382       with r.fillnulls.
383
384       Zero  (0)  and  negative  values will be treated as elevation data (not
385       no_data).
386
387   Further processing of output layers
388       Problem areas, i.e. those parts of a basin with a likely  underestimate
389       of flow accumulation, can be easily identified with e.g.
390         r.mapcalc "problems = if(flow_acc < 0, basin, null())"
391       If  the region of interest contains such problem areas, and this is not
392       desired, the computational region must be expanded until the  catchment
393       area for the region of interest is completely included.
394
395       To isolate an individual river network using the output of this module,
396       a number of approaches may be considered.
397
398       1      Use a resample of the basins catchment raster map as a MASK.
399              The equivalent vector map method is similar  using  v.select  or
400              v.overlay.
401
402       2      Use  the  r.cost  module with a point in the river as a starting
403              point.
404
405       3      Use the v.net.iso module with a node in the river as a  starting
406              point.
407
408       All  individual  river  networks  in  the stream segments output can be
409       identified through their ultimate outlet points. These points  are  all
410       cells  in  the stream segments output with negative drainage direction.
411       These points  can  be  used  as  start  points  for  r.water.outlet  or
412       v.net.iso.
413
414       To  create  river  mile segmentation from a vectorized streams map, try
415       the v.net.iso or v.lrs.segment modules.
416
417       The stream segments output can be easily vectorized after thinning with
418       r.thin.  Each  stream  segment in the vector map will have the value of
419       the associated basin. To isolate subbasins and  streams  for  a  larger
420       basin,  a MASK for the larger basin can be created with r.water.outlet.
421       The stream segments output serves as a guide where to place the  outlet
422       point  used  as input to r.water.outlet.  The basin threshold must have
423       been sufficiently small to  isolate  a  stream  network  and  subbasins
424       within the larger basin.
425
426       Given  that  the  drainage  is  8 directions numbered counter-clockwise
427       starting from 1 in north-east direction, multiplying the output  by  45
428       (by  45.  to get a double precision floating point raster map in r.map‐
429       calc) gives the directions in degrees.  For  most  applications,  zeros
430       which  indicate depressions specified by depression and negative values
431       which indicate runoff leaving the region should  be  replaced  by  NULL
432       (null()  in  r.mapcalc).  The following command performs these replace‐
433       ments:
434       r.mapcalc "drainage_degrees = if(drainage > 0, 45. * drainage, null())"
435       Alternatively, the user can use the -a flag or later the abs() function
436       in r.mapcalc if the runoff is leaving the region.
437

EXAMPLES

439       These examples use the Spearfish sample dataset.
440
441   Convert r.watershed streams map output to a vector map
442       If  you  want a detailed stream network, set the threshold option small
443       to create lots of catchment basins, as only one stream is presented per
444       catchment. The r.to.vect -v flag preserves the catchment ID as the vec‐
445       tor category number.
446         r.watershed elev=elevation.dem stream=rwater.stream
447         r.to.vect -v in=rwater.stream out=rwater_stream
448
449       Set a different color table for the accumulation map:
450         MAP=rwater.accum
451         r.watershed elev=elevation.dem accum=$MAP
452         eval `r.univar -g "$MAP"`
453         stddev_x_2=`echo $stddev | awk ’{print $1 * 2}’`
454         stddev_div_2=`echo $stddev | awk ’{print $1 / 2}’`
455         r.colors $MAP col=rules << EOF
456           0% red
457           -$stddev_x_2 red
458           -$stddev yellow
459           -$stddev_div_2 cyan
460           -$mean_of_abs blue
461           0 white
462           $mean_of_abs blue
463           $stddev_div_2 cyan
464           $stddev yellow
465           $stddev_x_2 red
466           100% red
467         EOF
468
469       Create a more detailed stream map using the accumulation map  and  con‐
470       vert it to a vector output map. The accumulation cut-off, and therefore
471       fractal dimension, is arbitrary; in this example we use the map’s  mean
472       number  of upstream catchment cells (calculated in the above example by
473       r.univar) as the cut-off value. This only works with SFD, not with MFD.
474         r.watershed elev=elevation.dem accum=rwater.accum
475         r.mapcalc ’MASK = if(!isnull(elevation.dem))’
476         r.mapcalc "rwater.course = \
477          if( abs(rwater.accum) > $mean_of_abs, \
478              abs(rwater.accum), \
479              null() )"
480         r.colors -g rwater.course col=bcyr
481         g.remove -f type=raster name=MASK
482         # Thinning is required before converting raster lines to vector
483         r.thin in=rwater.course out=rwater.course.Thin
484         r.colors -gn rwater.course.Thin color=grey
485         r.to.vect in=rwater.course.Thin out=rwater_course type=line
486         v.db.dropcolumn map=rwater_course column=label
487
488   Create watershed basins map and convert to a vector polygon map
489         r.watershed elev=elevation.dem basin=rwater.basin thresh=15000
490         r.to.vect -s in=rwater.basin out=rwater_basins type=area
491         v.db.dropcolumn map=rwater_basins column=label
492         v.db.renamecolumn map=rwater_basins column=value,catchment
493
494       Display output in a nice way
495         r.relief map=elevation.dem
496         d.shade shade=elevation.dem.shade color=rwater.basin bright=40
497         d.vect rwater_course color=orange
498

REFERENCES

500           ·   Ehlschlaeger C.  (1989).  Using  the  AT  Search  Algorithm  to
501               Develop Hydrologic Models from Digital Elevation Data, Proceed‐
502               ings of International  Geographic  Information  Systems  (IGIS)
503               Symposium ’89, pp 275-281 (Baltimore, MD, 18-19 March 1989).
504               URL: http://chuck.ehlschlaeger.info/older/IGIS/paper.html
505
506           ·   Holmgren  P.  (1994).  Multiple  flow  direction algorithms for
507               runoff modelling in grid based elevation models:  An  empirical
508               evaluation.  Hydrological Processes Vol 8(4), 327-334.
509               DOI: 10.1002/hyp.3360080405
510
511           ·   Kinner D., Mitasova H., Harmon R., Toma L., Stallard R. (2005).
512               GIS-based Stream Network Analysis for The Chagres River  Basin,
513               Republic  of  Panama. The Rio Chagres: A Multidisciplinary Pro‐
514               file of a Tropical Watershed, R. Harmon (Ed.), Springer/Kluwer,
515               p.83-95.
516               URL: http://www4.ncsu.edu/~hmitaso/measwork/panama/panama.html
517
518           ·   McCool  et  al.  (1987). Revised Slope Steepness Factor for the
519               Universal Soil Loss Equation,  Transactions  of  the  ASAE  Vol
520               30(5).
521
522           ·   Metz M., Mitasova H., Harmon R. (2011). Efficient extraction of
523               drainage networks from massive,  radar-based  elevation  models
524               with  least  cost path search, Hydrol. Earth Syst. Sci. Vol 15,
525               667-678.
526               DOI: 10.5194/hess-15-667-2011
527
528           ·   Moore I.D., Grayson R.B., Ladson A.R. (1991).  Digital  terrain
529               modelling:  a  review of hydrogical, geomorphological, and bio‐
530               logical applications, Hydrological Processes, Vol 5(1), 3-30
531               DOI: 10.1002/hyp.3360050103
532
533           ·   Quinn P., K. Beven K., Chevallier P., Planchon O.  (1991).  The
534               prediction of hillslope flow paths for distributed hydrological
535               modelling using Digital  Elevation  Models,  Hydrological  Pro‐
536               cesses Vol 5(1), p.59-79.
537               DOI: 10.1002/hyp.3360050106
538
539           ·   Weltz  M.  A., Renard K.G., Simanton J. R. (1987). Revised Uni‐
540               versal Soil Loss Equation for Western Rangelands, U.S.A./Mexico
541               Symposium  of  Strategies  for Classification and Management of
542               Native Vegetation for Food Production In  Arid  Zones  (Tucson,
543               AZ, 12-16 Oct. 1987).
544

SEE ALSO

546         g.region,  r.cost, r.drain, r.fillnulls, r.flow, r.mask, r.neighbors,
547       r.param.scale, r.resamp.interp, r.terraflow, r.topidx,  r.water.outlet,
548       r.stream.extract
549

AUTHORS

551       Original  version:  Charles  Ehlschlaeger, U.S. Army Construction Engi‐
552       neering Research Laboratory
553       Faster sorting algorithm and MFD support: Markus Metz <markus.metz.gis‐
554       work at gmail.com>
555       Retention for flow distribution by Andreas Gericke (IGB Berlin)
556

SOURCE CODE

558       Available at: r.watershed source code (history)
559
560       Main  index  | Raster index | Topics index | Keywords index | Graphical
561       index | Full index
562
563       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
564
565
566
567GRASS 7.8.2                                                     r.watershed(1)
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