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           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
221       ln(α / tan(β)) where α is the  cumulative  upslope  area
222       draining through a point per unit contour length and tan(β) is the
223       local slope angle. The TCI reflects the tendency of water to accumulate
224       at any point in the catchment and the tendency for gravitational forces
225       to move that water downslope (Quinn et al. 1991).  This value  will  be
226       negative if &#945; / tan(&#946;) < 1.
227
228       Output  spi  raster  map  contains  stream power index SPI, computed as
229       &#945; * tan(&#946;) where &#945; is the cumulative upslope area drain‐
230       ing  through  a  point  per  unit contour length and tan(&#946;) is the
231       local slope angle. The SPI reflects the power  of  water  flow  at  any
232       point  in  the  catchment  and the tendency for gravitational forces to
233       move that water downslope (Moore et al. 1991).  This value will be neg‐
234       ative  if  &#945; < 0, i.e. for cells with possible surface runoff from
235       outside of the current geographic region.
236
237       Output drainage raster map contains drainage direction.   Provides  the
238       "aspect"  for  each  cell measured CCW from East.  Multiplying positive
239       values by 45 will give the direction in degrees that the surface runoff
240       will travel from that cell.  The value 0 (zero) indicates that the cell
241       is a depression area (defined by the depression input  map).   Negative
242       values  indicate  that  surface runoff is leaving the boundaries of the
243       current geographic region.  The absolute value of these negative  cells
244       indicates the direction of flow. For MFD, drainage indicates the direc‐
245       tion of maximum flow.
246
247       The output basin map contains unique label for  each  watershed  basin.
248       Each  basin  will be given a unique positive even integer.  Areas along
249       edges may not be large enough to create an  exterior  watershed  basin.
250       NULL  values indicate that the cell is not part of a complete watershed
251       basin in the current geographic region.
252
253       The output stream contains stream segments. Values  correspond  to  the
254       watershed basin values.  Can be vectorized after thinning (r.thin) with
255       r.to.vect.
256
257       The output half_basin raster map stores  each  half-basin  is  given  a
258       unique  value.  Watershed basins are divided into left and right sides.
259       The right-hand side cell of the watershed basin (looking upstream)  are
260       given  even values corresponding to the values in basin.  The left-hand
261       side cells of the watershed basin are given odd values  which  are  one
262       less than the value of the watershed basin.
263
264       The  output  length_slope  raster map stores slope length and steepness
265       (LS) factor for the  Revised  Universal  Soil  Loss  Equation  (RUSLE).
266       Equations  taken  from Revised Universal Soil Loss Equation for Western
267       Rangelands (Weltz et al. 1987). Since the LS factor is a  small  number
268       (usually less than one), the GRASS output map is of type DCELL.
269
270       The output slope_steepness raster map stores slope steepness (S) factor
271       for the Universal Soil Loss Equation  (RUSLE).   Equations  taken  from
272       article  entitled Revised Slope Steepness Factor for the Universal Soil
273       Loss Equation (McCool et al. 1987).  Since the S factor is a small num‐
274       ber (usually less than one), the GRASS output map is of type DCELL.
275
276   AT least-cost search algorithm
277       r.watershed uses an AT least-cost search algorithm (see REFERENCES sec‐
278       tion) designed to minimize the impact of DEM data errors.  Compared  to
279       r.terraflow,  this algorithm provides more accurate results in areas of
280       low slope as well as DEMs  constructed  with  techniques  that  mistake
281       canopy tops as the ground elevation. Kinner et al. (2005), for example,
282       used SRTM and IFSAR DEMs to  compare  r.watershed  against  r.terraflow
283       results in Panama. r.terraflow was unable to replicate stream locations
284       in the larger valleys while r.watershed performed much better. Thus, if
285       forest canopy exists in valleys, SRTM, IFSAR, and similar data products
286       will cause major errors in r.terraflow  stream  output.  Under  similar
287       conditions,  r.watershed  will  generate  better  stream and half_basin
288       results. If watershed divides contain flat to  low  slope,  r.watershed
289       will  generate better basin results than r.terraflow. (r.terraflow uses
290       the same type of algorithm as ESRI’s ArcGIS  watershed  software  which
291       fails  under these conditions.) Also, if watershed divides contain for‐
292       est canopy mixed with uncanopied areas using SRTM, IFSAR,  and  similar
293       data  products,  r.watershed  will  generate  better basin results than
294       r.terraflow. The algorithm produces results similar to  those  obtained
295       when running r.cost and r.drain on every cell on the raster map.
296
297   Multiple flow direction (MFD)
298       r.watershed  offers  two methods to calculate surface flow: single flow
299       direction (SFD, D8) and multiple flow direction (MFD). With MFD,  water
300       flow  is  distributed  to  all neighbouring cells with lower elevation,
301       using slope towards neighbouring cells as a weighing factor for propor‐
302       tional  distribution.  The  AT least-cost path is always included. As a
303       result, depressions and obstacles are traversed with  a  graceful  flow
304       convergence  before  the  overflow.  The convergence factor causes flow
305       accumulation to converge more strongly with  higher  values.  The  sup‐
306       ported  range  is  1  to  10,  recommended is a convergence factor of 5
307       (Holmgren, 1994). If many small sliver basins  are  created  with  MFD,
308       setting  the convergence factor to a higher value can reduce the amount
309       of small sliver basins.
310
311   In-memory mode and disk swap mode
312       There are two versions of this program: ram and seg.  ram  is  used  by
313       default, seg can be used by setting the -m flag.
314
315       The ram version requires a maximum of 31 MB of RAM for 1 million cells.
316       Together with the amount of system memory (RAM) available,  this  value
317       can  be  used  to  estimate whether the current region can be processed
318       with the ram version.
319
320       The ram version uses virtual memory managed by the operating system  to
321       store  all  the data structures and is faster than the seg version; seg
322       uses the GRASS segmentation library which manages data in  disk  files.
323       seg  uses only as much system memory (RAM) as specified with the memory
324       option, allowing other processes to operate on the  same  system,  even
325       when the current geographic region is huge.
326
327       Due  to  memory  requirements of both programs, it is quite easy to run
328       out of memory when working with huge map regions. If  the  ram  version
329       runs  out  of  memory and the resolution size of the current geographic
330       region cannot be increased, either more memory needs to be added to the
331       computer, or the swap space size needs to be increased. If seg runs out
332       of memory, additional disk space needs to be freed up for  the  program
333       to  run.   The  r.terraflow  module was specifically designed with huge
334       regions in mind and may be useful here as an alternative, although disk
335       space requirements of r.terraflow are several times higher than of seg.
336
337   Large regions with many cells
338       The  upper  limit  of  the  ram  version  is 2 billion (231 - 1) cells,
339       whereas the upper limit for the seg version is 9 billion-billion (263 -
340       1 = 9.223372e+18) cells.
341       In  some situations, the region size (number of cells) may be too large
342       for the amount of time or memory  available.  Running  r.watershed  may
343       then  require  use  of  a  coarser resolution. To make the results more
344       closely resemble the finer terrain data, create a map layer  containing
345       the lowest elevation values at the coarser resolution. This is done by:
346       1) Setting the current geographic region equal  to  the  elevation  map
347       layer  with g.region, and 2) Use the r.neighbors or r.resamp.stats com‐
348       mand to find the lowest value for an area equal in size to the  desired
349       resolution.  For example, if the resolution of the elevation data is 30
350       meters and the resolution of the geographic region for r.watershed will
351       be 90 meters: use the minimum function for a 3 by 3 neighborhood. After
352       changing to the resolution at which r.watershed will be  run,  r.water‐
353       shed  should  be  run using the values from the neighborhood output map
354       layer that represents the minimum elevation within the  region  of  the
355       coarser cell.
356
357   Basin threshold
358       The  minimum  size of drainage basins, defined by the threshold parame‐
359       ter, is only relevant for those watersheds with a single stream  having
360       at least the threshold of cells flowing into it.  (These watersheds are
361       called exterior basins.)  Interior drainage basins contain stream  seg‐
362       ments  below  multiple tributaries.  Interior drainage basins can be of
363       any size because the length of an interior stream segment is determined
364       by the distance between the tributaries flowing into it.
365
366   MASK and no data
367       The  r.watershed  program does not require the user to have the current
368       geographic region filled with elevation values.  Areas  without  eleva‐
369       tion  data  (masked  or NULL cells) are ignored. It is NOT necessary to
370       create a raster map (or raster reclassification) named  MASK  for  NULL
371       cells.  Areas without elevation data will be treated as if they are off
372       the edge of the region. Such areas will reduce the memory necessary  to
373       run  the  program.   Masking  out  unimportant  areas can significantly
374       reduce processing time if the watersheds of  interest  occupy  a  small
375       percentage of the overall area.
376
377       Gaps (NULL cells) in the elevation map that are located within the area
378       of interest will heavily influence the analysis: water will  flow  into
379       but  not  out of these gaps. These gaps must be filled beforehand, e.g.
380       with r.fillnulls.
381
382       Zero (0) and negative values will be treated  as  elevation  data  (not
383       no_data).
384
385   Further processing of output layers
386       Problem  areas, i.e. those parts of a basin with a likely underestimate
387       of flow accumulation, can be easily identified with e.g.
388         r.mapcalc "problems = if(flow_acc < 0, basin, null())"
389       If the region of interest contains such problem areas, and this is  not
390       desired,  the computational region must be expanded until the catchment
391       area for the region of interest is completely included.
392
393       To isolate an individual river network using the output of this module,
394       a number of approaches may be considered.
395
396       1      Use a resample of the basins catchment raster map as a MASK.
397              The  equivalent  vector  map method is similar using v.select or
398              v.overlay.
399
400       2      Use the r.cost module with a point in the river  as  a  starting
401              point.
402
403       3      Use  the v.net.iso module with a node in the river as a starting
404              point.
405
406       All individual river networks in the  stream  segments  output  can  be
407       identified  through  their ultimate outlet points. These points are all
408       cells in the stream segments output with negative  drainage  direction.
409       These  points  can  be  used  as  start  points  for  r.water.outlet or
410       v.net.iso.
411
412       To create river mile segmentation from a vectorized  streams  map,  try
413       the v.net.iso or v.lrs.segment modules.
414
415       The stream segments output can be easily vectorized after thinning with
416       r.thin. Each stream segment in the vector map will have  the  value  of
417       the  associated  basin.  To  isolate subbasins and streams for a larger
418       basin, a MASK for the larger basin can be created with  r.water.outlet.
419       The  stream segments output serves as a guide where to place the outlet
420       point used as input to r.water.outlet.  The basin threshold  must  have
421       been  sufficiently  small  to  isolate  a  stream network and subbasins
422       within the larger basin.
423
424       Given that the drainage  is  8  directions  numbered  counter-clockwise
425       starting  from  1 in north-east direction, multiplying the output by 45
426       (by 45. to get a double precision floating point raster map  in  r.map‐
427       calc)  gives  the  directions  in degrees. For most applications, zeros
428       which indicate depressions specified by depression and negative  values
429       which  indicate  runoff  leaving  the region should be replaced by NULL
430       (null() in r.mapcalc).  The following command performs  these  replace‐
431       ments:
432       r.mapcalc "drainage_degrees = if(drainage > 0, 45. * drainage, null())"
433       Alternatively, the user can use the -a flag or later the abs() function
434       in r.mapcalc if the runoff is leaving the region.
435

EXAMPLES

437       These examples use the Spearfish sample dataset.
438
439   Convert r.watershed streams map output to a vector map
440       If you want a detailed stream network, set the threshold  option  small
441       to create lots of catchment basins, as only one stream is presented per
442       catchment. The r.to.vect -v flag preserves the catchment ID as the vec‐
443       tor category number.
444         r.watershed elev=elevation.dem stream=rwater.stream
445         r.to.vect -v in=rwater.stream out=rwater_stream
446
447       Set a different color table for the accumulation map:
448         MAP=rwater.accum
449         r.watershed elev=elevation.dem accum=$MAP
450         eval `r.univar -g "$MAP"`
451         stddev_x_2=`echo $stddev | awk ’{print $1 * 2}’`
452         stddev_div_2=`echo $stddev | awk ’{print $1 / 2}’`
453         r.colors $MAP col=rules << EOF
454           0% red
455           -$stddev_x_2 red
456           -$stddev yellow
457           -$stddev_div_2 cyan
458           -$mean_of_abs blue
459           0 white
460           $mean_of_abs blue
461           $stddev_div_2 cyan
462           $stddev yellow
463           $stddev_x_2 red
464           100% red
465         EOF
466
467       Create  a  more detailed stream map using the accumulation map and con‐
468       vert it to a vector output map. The accumulation cut-off, and therefore
469       fractal  dimension, is arbitrary; in this example we use the map’s mean
470       number of upstream catchment cells (calculated in the above example  by
471       r.univar) as the cut-off value. This only works with SFD, not with MFD.
472         r.watershed elev=elevation.dem accum=rwater.accum
473         r.mapcalc ’MASK = if(!isnull(elevation.dem))’
474         r.mapcalc "rwater.course = \
475          if( abs(rwater.accum) > $mean_of_abs, \
476              abs(rwater.accum), \
477              null() )"
478         r.colors -g rwater.course col=bcyr
479         g.remove -f type=raster name=MASK
480         # Thinning is required before converting raster lines to vector
481         r.thin in=rwater.course out=rwater.course.Thin
482         r.colors -gn rwater.course.Thin color=grey
483         r.to.vect in=rwater.course.Thin out=rwater_course type=line
484         v.db.dropcolumn map=rwater_course column=label
485
486   Create watershed basins map and convert to a vector polygon map
487         r.watershed elev=elevation.dem basin=rwater.basin thresh=15000
488         r.to.vect -s in=rwater.basin out=rwater_basins type=area
489         v.db.dropcolumn map=rwater_basins column=label
490         v.db.renamecolumn map=rwater_basins column=value,catchment
491
492       Display output in a nice way
493         r.relief map=elevation.dem
494         d.shade shade=elevation.dem.shade color=rwater.basin bright=40
495         d.vect rwater_course color=orange
496

REFERENCES

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

SEE ALSO

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

AUTHORS

549       Original version: Charles Ehlschlaeger, U.S.  Army  Construction  Engi‐
550       neering Research Laboratory
551       Faster sorting algorithm and MFD support: Markus Metz <markus.metz.gis‐
552       work at gmail.com>
553       Retention for flow distribution by Andreas Gericke (IGB Berlin)
554
555       Last changed: $Date: 2018-10-18 21:05:15 +0200 (Thu, 18 Oct 2018) $
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 7.6.0 Reference Manual
564
565
566
567GRASS 7.6.0                                                     r.watershed(1)
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