r.wrat(1)	       Grass User's Manual		r.wrat(1)



NNAAMMEE
       wwrraatt - Water Resource Assessment Tool



UUSSAAGGEE
       This module must be used interactively.



IINNPPUUTT MMAAPP CCOODDEESS
       elevation:	meters, as well as cell resolution


       rainfall maps:	100ths of an inch


       K factor:	K factor times 100  K of .35 = 35



IInnttrroodduuccttiioonn
       The Water Resource Assessment Tool is a collection of pro-
       grams run within the GRASS GIS. These programs are an  aid
       in  understanding  the  nature  of  runoff in a study area
       based on information typically available for  a	GIS.  The
       programs  analyze the terrain to define drainage direction
       and areas, simulate runoff and peak runoff and model  non-
       point  source  pollution  and map contaminant source areas
       and contaminant pathways. This users  guide  outlines  the
       typical analytical sequence, describes input data require-
       ments and possible output. Some suggestion for  interpret-
       ing  output are included. It is assumed the user is famil-
       iar with the basics of GRASS.



IInnppuutt
       Map layers required: digital elevation model, land  cover,
       soil  maps  of  hydrologic  soil  group, soil texture, and
       erodiblity factor (K factor). Optional maps describe  best
       managment practices for sediment, nitrogen phosphorous and
       chemical oxygen demand (COD).



TTyyppiiccaall AAnnaallyyssiiss
       Three interrelated areas of analysis are  available:  ter-
       rain  analysis,	hydrology  and pollution (see figure X1).
       Because these areas are not distinct, analysis should pro-
       ceed  in a logical order since some portions build on pre-
       vious results. Terrain analysis and runoff generation must
       proceed routing peak discharge, which in turn must proceed
       contaminant routing. The following steps provide a natural
       sequence of analysis through all of the tools.  However, a
       great deal of valuable information may be gained executing
       only  a	portion of the available programs. This is a tool
       kit, not a prescription for studying every area.



       Terrain Analysis    Hydrology	  Pollution
       _________________   _________________   _________________
       |	       |       |	  |    |	 |
       | Elevation     |   | Land Cover   |    | Land Cover   |
       | Model	       |   |	     |	  |	    |
       --------+--------   | Hydrologic   |    | Soils	      |
	       |      | Soil Group   |	  | K factor	 |
       ________V________   --------+--------   | Texture |
       |	 |	      |      --------+--------
       | Idealized    | 	|	       |
       | Elevation    | 	|	       |
       | Model	      | 	|	       |
       |	 |	   |		  |
       | Drainage     | 	|	       |
       | Direction    | 	|	       |
       |	 |	   |		  |
       | Drainage     |    ________V________	    |
       | Accumulation |    |	     |	       |
       |	 |    | Runoff Map   |	       |
       | Slope	      |    -+------+--------	    |
       --------+--------    |	|	       |
	    |	      +----	|	       |
	    --------+----(-------|<-----------------------
		 |    |    ________V________   _________________
		 |<---+    |	     |	  |	    |
		 |    | Contaminant   |   | Best	 |
		 |    | Source Areas  |   | Management	 |
		 |    --------+--------   | Practices	 |
	    ________V________	|	  --------+--------
	    |	      |    |		  |
	    | Peak	   |	------------+------------
	    | Discharge    |		 |
	    -----------------	    ________V________
			       |	      |
			       | Contaminant   |
			       | Routing      |
			       -----------------

		      figure X1.





DDeeffiinniinngg tthhee ssttuuddyy aarreeaa
       GRASS looks at the world through a  rectangular	"window".
       The  window  should  be	set to include the entire area of
       interest with several cells to spare  in  all  directions.
       Because	of difficulty interpreting terrain at the edge of
       the window, the analysis moves in from  the  window  edge.
       The  extra  area is particularly important if the top of a
       watershed of interest is not marked  by	a  steep  decline
       into the adjacent watershed.


       Routing	routines  assume  that	the  entire  watershed is
       within the current window. This is not always true or even
       practical.  For	instance, an analysis along the side of a
       long river will provide valuable information  about  local
       contributions  to  the  larger resource. However, calcula-
       tions in the long river itself can not take  into  account
       upstream  effects  outside the current window and are thus
       invalid. Yet those local contributions may be of consider-
       able  interest.	 Great	care  must  be taken interpreting
       results of watersheds only partially contained within  the
       operating window.


       Cell  resolution,  the size of each cell, should be set as
       large as is appropriate for  your  purposes.  In  no  case
       should  the resolution be smaller than the spatial resolu-
       tion of your best input layer. Doubling	the  cell  length
       and  width  will cut computation times by 3/4s!	The east-
       west resolution need not match the north-south resolution.
       However,  large	deviations from square cells will distort
       some of the neighbor concepts used by some  algorithms  to
       "feel their way" across the terrain.


       Once  the  analysis  is	begun, the same window, including
       cell resolution, must be maintained  throughout	the  pro-
       ject.   The interface program tries to insure this. Chang-
       ing the boundaries invalidates the  drainage  accumulation
       maps.   Changing  the  cell resolution can have disastrous
       effects on the drainage direction map,  such  as  creating
       dead  end  and circular drainages. The idealized elevation
       model will lose its "ideal" character if resampled. If the
       window must be changed, start the analysis from the begin-
       ning.


       Some of the output maps may be resampled to a smaller win-
       dow or different cell size after the analysis is finished.
       Contaminant source area maps are produced in units of mass
       per unit area and may be resampled. This may be useful for
       presentation of results or  incorporation  within  another
       GIS analysis.



TTeemmppoorraall ssccaallee
       Hydrologic simulations are based on single storms, presum-
       ably one day  events.  Actual  or  design  storms  may  be
       employed.



TTeerrrraaiinn aannaallyyssiiss
       The  actual analysis may begin using the digital elevation
       model to produce an idealized elevation model.  Real  data
       has, for a number of reasons, sections which are difficult
       to drain. The idealized elevation model has no cells which
       can not drain to the edge of the window. This assumes com-
       plete surface drainage  is  possible.  This  condition  is
       never  completely  true and in some regions, such as those
       with karst topography, so far from the case as to  invali-
       date the peak discharge and contaminant routing results.


       The  idealized  elevation  model  is used to determine the
       direction in which each cell will drain. This is  done  by
       searching  the edge of the window for the lowest point and
       draining the watershed that leads there.   Then	the  next
       lowest  outlet  is found and its watershed drained, and so
       on until the entire area is drained.


       The drainage direction map is used to produce  a  drainage
       accumulation  map.  The	values in a drainage accumulation
       map are the total number of  cells  including  that  cell,
       which  drain  through that cell. If multiplied by the area
       of a cell, the drainage accumulation map  will  yield  the
       area of the watershed above and including each cell.



HHyyddrroollooggyy
       Two  programs  contribute to the hydrology section: runoff
       and peak discharge. The runoff section  is  based  on  the
       Soil  Conservation Services Curve number method (Soil Con-
       servation Service, USDA, 1971).	Curve numbers, from 0  to
       100,  describe the potential for runoff. Curve numbers are
       inferred from the land cover map and the map of hydrologic
       soil  groups.  A depth of precipitation for a design storm
       or a rainfall map is required to produce a runoff map.


       To this point the terrain analysis and the hydrology could
       progress  independently.  From  this point on the distinc-
       tions between terrain analysis, hydrology  and  pollution,
       as  separate  lines  of	analysis begin to fade.  Actually
       pollution analysis will always be dependent to some extent
       on  hydrology  but that will be dealt with in a later sec-
       tion. Peak discharge combines the results of  the  terrain
       analysis and runoff sections.


       Peak  discharge, the volume of water passing out of a cell
       per unit time, is calculated with an  empirical	relation-
       ship  developed	by Smith and Williams (1980) and employed
       in CREAMS and AGNPS. Watershed characteristics are  inter-
       preted  from  several  all of the results from the terrain
       analysis. The resulting map of peak discharge, significant
       by itself, is also used in the routing of contaminants.



PPoolllluuttiioonn
       Contaminant  sources  are mapped as the contaminant origi-
       nating per unit area.  Sediment, nitrogen, phosphorous and
       COD may be modeled. The algorithms used to predict contam-
       inant mobilization depend on the  landcover  of	the  cell
       involved. The universal soil loss equation and adaptations
       from AGNPS and CREAMS are employed for rural, agricultural
       and  open  lands.  An  algorithm  from SWMM is adopted for
       urban areas. Land cover, soil texture and erodibility fac-
       tors,  rainfall,  runoff  and  peak discharge maps are the
       required inputs for this section.


       The final part of the  analysis	routes	contaminants.  It
       requires  the results of the preceding sections. Sediment,
       nitrogen and phosphorous nutrients and COD may be modeled.
       The  routing  is  done  as  a  mass balance accounting for
       imports of contaminants into a cell,  contaminants  origi-
       nating within the cell, losses to infiltration and deposi-
       tion and  exports  to  the  next  cell.	Figure	X2  is	a
       schematic representation.



			      rainfall with
			      contaminants
				    |
			      ______________
       imports	 from		 /		 /	  Surface
       exports
       up gradient	-   /		  /  -	  down gradient
			   /_____________/

				  |

			  losses to infiltration
			  and deposition

					 figure X2.





SSoommee pprraaccttiiccaall ccoonnssiiddeerraattiioonnss::
       GRASS only stores integers, assuming values less then  one
       to be equal to zero. Therefore small units of measure have
       been employed. Rainfall and runoff are described  in  hun-
       dredths	of  inches,  while  quantities of sediment are in
       kilograms with nutrients in grams. Flows are  measured  in
       cubic  feet  per  second. The mixing of english and metric
       units employs those units in  common  usage  in	the  U.S.
       Maps  may  be  converted  to  any appropriate set of units
       using "r.mapcalc" to multiply the map by  the  appropriate
       conversion factor.



PPrreeppaarriinngg mmaapp llaayyeerrss
       GRASS  associates  numeric  values  with  cells	as  their
       attributes. Sometimes these numbers have real meanings, as
       in  an  elevation  model  in which the cell's value is its
       elevation. Some	are  more  arbitrary  codes  representing
       qualitative  categories,  such as landcover. The following
       tables provide guides to units and codes used in the water
       resource  assessment  tools.  The  GRASS  tool "r.reclass"
       allows speedy recoding of map layers to these codes.



IInnppuutt llaayyeerrss aanndd ddaattaa
EElleevvaattiioonn
       Values in the digital elevation model represent the  alti-
       tude above mean sea level expressed in meters.



RRaaiinnffaallll
       Rainfall  maps  should  be rainfall for a single day, mea-
       sured in hundredths of an inch. Thus a one and  a  quarter
       inch  rainfall would be represented as 125. The GRASS com-
       mand "s.surf.idw" can be used to  interpolate  a  rainfall
       map between observation stations, however, s.surf.idw does
       not understand the effects of terrain on rainfall and will
       make  significant  mistakes in hilly country and for thun-
       derstorms passing through a widely scattered set of obser-
       vation  points.	A  design  storm  may  be  preferable for
       assessment purposes.



SSooiill,, tteexxttuurree
       Values are a code for the dominant texture.

	    1 = clay soils
	    2 = silt soils
	    3 = sandy soils
	    4 = peat
	    5 = water




SSooiill,, hhyyddrroollooggiicc ssooiill ggrroouupp
       Hydrologic soil group is primarily dependent on	the  soil
       texture.  However  depth  to  bed  rock and depth to water
       table may strongly influence a soil's classification.



	    1 = hydrologic soil group A
	    2 = hydrologic soil group B
	    3 = hydrologic soil group C
	    4 = hydrologic soil group D
	    5 = water




SSooiill,, eerrooddiibbiilliittyy KK ffaaccttoorr
       K factors are a decimal value greater then zero and  typi-
       cally  less then .5. Formally they represent the soil loss
       rate per unit of per erosion index unit	for  a	specified
       test  plot.  (Agriculture  Handbook Number 537 "Predicting
       Rainfall Erosion Losses",  USDA	1978)  Information  about
       local  soils should be available from your local Soil Con-
       servation Service office. Because GRASS uses only  integer
       values,	multiply K factors by 100. Thus a K factor of .37
       would be coded as 37. Use a code of 100 for water.



LLaannddccoovveerr
       The landcover map must be  coded  so  the  water  resource
       assessment  tools  can recognize the landcovers indicated.
       The following table illustrates the 15 landcover  category
       codes  expected.   When attempting to make the best fit of
       available data to this encoding scheme, remember to  think
       of the areas both in terms of their ability to slow runoff
       and their contributions to water quality.   Some  creative
       lies  may be useful for special purposes.  For instance, a
       development built to the performance  standard  that  peak
       discharge is not to exceed a field in good condition could
       be coded as an old field for hydrologic analysis and built
       up for pollution analysis.



	  1 = corn
	  2 = rye
	  3 = oats
	  4 = soybeans
	  5 = hay
	  6 = grass
	  7 = old field (grass)
	  8 = old field (shrub)
	  9 = pasture
	  10 = forest
	  11 = wetlands
	  12 = fens
	  13 = water
	  14 = built up
	  15 = barren


OOuuttppuutt MMaapp llaayyeerrss
       Many  maps can be produced with the water resource assess-
       ment tools. The following sections outline how these  maps
       are  prepared,  the  units  of  measure and codes employed
       along with some notes as to how they should and should not
       be  used.  More	complete  information is available in the
       model documentation. The source code is also provided  and
       contains  a  great  deal of internal documentation. Output
       maps are presented in the approximate order in which  they
       would be produced.


       The  idealized elevation file is a digital elevation file.
       Cell values represent elevation in meters.  This elevation
       model will differ from the input DEM provided by the user,
       in that depressions in the data	are  filled  in  so  that
       water  landing  anywhere on the idealized surface can flow
       to the edge. Although useful for  analyzing  terrain,  and
       employed  for  slope measurements, the idealized elevation
       model is probably further removed from  reality	then  the
       original data upon which it is based. The idealized eleva-
       tion data may not be resampled to a different cell resolu-
       tion and retain its desired "idealized" characteristics.



DDrraaiinnaaggee DDiirreeccttiioonn
       Cells  in the drainage direction map are coded to indicate
       the neighboring cell into  which  they  drain.  The  eight
       nearest	neighbors  are	represented  by  the  integers	1
       through 8 as depicted in figure X3.



				   4 3 2
				   5   1
				   6 7 8

				   figure X3.

       Drainage direction is similar to aspect. However they  are
       not  exactly  the same thing.  In an aspect map, the cells
       at the bottom of a V shaped valley  may	face  each  other
       without	draining into each other. This map is produced by
       searching the border of the window for the lowest cell and
       draining  all  cells in that drainage. The algorithm moves
       up through the drainage one unit of elevation  at  a  time
       until  all  adjacent  cells of that elevation are drained,
       trying to assign the most direct drainage direction.  Then
       the  next  lowest  undrained border cell is found and that
       watershed is drained until the entire map is drained.  The
       routine	sometimes has difficulty at the top of watersheds
       if the next valley does not clearly drop away.



DDrraaiinnaaggee AAccccuummuullaattiioonn
       Values in the drainage accumulation map represent the num-
       ber  of	cells,	including  the	cell with the value, that
       drain through the cell. Thus the minimum drainage  accumu-
       lation is one, while the maximum is the number of cells in
       the largest watershed in  the  study  area.  The  drainage
       accumulation  map  is  used to find the watershed area for
       each cell in the study area and to guide a search  up  the
       watershed  to  find  the length of the longest stream. The
       drainage accumulation map can be used to define the stream
       networks  by reclassifying the cells below a minimum accu-
       mulated drainage to zero.  The  remainder  represents  the
       streams.  Drainage  accumulation  is  drainage area repre-
       sented in cells. Multiplying a  drainage  accumulation  by
       the  area  of  a  cell yields the drainage area above that
       cell.



RRuunnooffff
       The values in the runoff map represent the depth of  water
       expected  to  run  off that cell, from the input rainfall,
       based on the soil and landcover	maps  specified.   Values
       could  range between zero and the amount of rain that fell
       on that cell.  Runoff, like rainfall, is measured in  hun-
       dredths	of inches.  A value of 75 represents .75 inchs of
       runoff. Runoff values can be multiplied	by  the  area  of
       each cell to give a volume of runoff. However, care should
       be taken when converting units because cell sizes in GRASS
       are defined in meters. Upgradient values in the runoff map
       are summed during the peak discharge calculations and used
       in the contaminant source area and routing calculations.



PPeeaakk DDiisscchhaarrggee
       Peak  discharge	is the maximum rate at which water passes
       through a cell measured in cubic feet per  second.   These
       estimates  are  based  on  an empirical relationship which
       describes the entire upstream portion of the watershed. If
       the entire upstream portion of the watershed is not within
       the current window, the model assumes the upstream edge is
       the  top of the watershed. This is  wrong and estimates of
       peak discharge in streams which enter the window are mean-
       ingless as are routings of contaminants based on peak dis-
       charge. The calculations are retained so that  local  con-
       tributions  from  side  streams and slopes may be modeled.
       These local effects may be of  substantial  importance  to
       those  involved	in  the  local area regardless of distant
       conditions.



CCoonnttaammiinnaanntt SSoouurrccee AArreeaass
       Sediment, nitrogen and phosphorus nutrients and COD can be
       simulated.  The	algorithms  used  to  predict contaminant
       mobilization are dependent  on  the  contaminant  and  the
       landcover class. In non urban areas sediment production is
       based on the universal soil loss  equation.  Nitrogen  and
       phosphorous  are  modeled  both in solution and associated
       with sediment in rural areas and only  as  a  function  of
       sediment  in urban areas. COD is assumed to be soluble and
       is calculated by loading factors.


       Sediment loadings are expressed as kilograms per  hectare.
       Nutrients  and  COD  loadings  are  expressed as grams per
       hectare.


       These loadings are a function of the rainfall,  the  soil,
       slope  and  landcover.  They  do not represent the natural
       scatter found in natural events. Results may be used as	a
       relative  indicator  of	contaminant  generation.  As such
       these maps may highlight those areas in a  watershed  that
       would  benefit most from conservation efforts. Subtracting
       two source area maps  generated	for  different	scenarios
       would help locate the areas of greatest change.



RRoouuttiinngg ooff CCoonnttaammiinnaannttss
       Contaminants are routed down stream assuming total conser-
       vation unless a best management practice map for the  par-
       ticular contaminant is used. If a best management practice
       map is used contaminants flux across a BMP is  reduced  by
       the percentage indicated.


       The  output  maps  indicate  the totak mass of contaminant
       passing through a cell. These maps can be used as  indica-
       tors  of  the  contaminants  delivered  to  any point down
       stream.	Similar analysis for varying land  cover  regimes
       could  be  subtracted  with  "r.mapcalc"  to find areas of
       greatest positive and negative change resulting	from  the
       changes	in scenarios. Again these numbers represent rela-
       tive indicators.



IInntteerrffaaccee PPrrooggrraamm
       The Water resopurces assessment tool  is  run  through  an
       interface  program  invoked  from the grass environment at
       any GRASS prompt by typing wrat. Work is organized in pro-
       jects  which  should represent the investigation of a geo-
       graphic area. The user interface  is  a	series	of  menus
       which  guide  the user through the program. A project file
       is created which keeps track of the options used and input
       and  output  map  names.  The  project file also creates a
       database window based on the active window at the  time	a
       project is started.  The active window is returned to this
       active window for subsequent work sessions on the project.



FFiirrsstt MMeennuu
       At this menu the user can:


       1 start a new project

       2 start a project based on an existing project

       3 work on an existing project

       4 remove project files

       5 exit


       The  user  is  prompted for needed information such as the
       name of the project to work on with the option of  listing
       project	files if needeed.  Once a project is selected the
       secon menu is offered. The User may do:


       1 Terrain Analysis

       2 Runoff Analysis

       3 Contaminant Analysis

       4 return to main menu


       Choices 1, 2 or 3 lead to menus for each of  those  analy-
       sis.


       In the Terrain Analysis the options are:


       1 Create an idealized elevation model

       2 Create a drainage direction map

       3 Create a drainage accumulation map

       4 Create a slope map

       5 Return to the previous menu


       In  each  case  except  option  5 the user is prompted for
       needed information. where appropriate the  likely  choices
       are  supplied if not insisted upon. The drainage direction
       map must be based on  the  idealized  elevation	map.  The
       drainage  accumulation  map needs a drainage direction map
       which should be the output map from option 2. In this  way
       the user is guided along.


       In  the	rruunnooffff	aannaallyyssiiss  sseeccttiioonn  there  are  only three
       options:


       1 Create a runoff map

       2 Simulate peak discharge

       3 Return to the previous menu


       In this section the options are not  as	straight  forward
       and  the user is coached along.	The user must provide the
       names of several input maps and can obtain  a  listing  by
       entering  list  instead of a map name where requested. The
       user must also choose between a design storm and  rainfall
       map.  The most difficult information requested of the user
       is the anticeedent moisture condition. This  is	a  number
       between	1  and 3 inclusivly which describes the amount of
       moisture already in the soil which effects the  amount  of
       rain  which  can  be  absorbed during the current storm. 1
       represents extreemly dry conditions and 3  extreemley  wet
       conditions.   The concept comes from the Soil Conservation
       Service curve number  method  of  predicting  runoff.  The
       basic  guidance	from  the SCS is offered with the request
       and a value of 2 neither wet or dry is the  default.  Peak
       discharge  is quite sensative to thee anticeedent moisture
       condition so some care should be taken here.


       The ccoonnttaammiinnaanntt sseeccttiioonn has only three options as well:


       1 Model Contaminant source areas

       2 Rout contaminants through the watershed

       3 Return to the previous menu


       When modeling contaminant source areas the user may  model
       just sediment or sediment and any combination of nitrogen,
       phosphorpus and COD. Because nutrients are associated with
       sediment  sediment  predictions	are required for nutrient
       modeling. Most input for this section is straight  forward
       except the number of days since the last significant rain.
       The  amount of dirt available to wash off of  urban  areas
       accumulates  between  rainstorms.  Rain	storms wash urban
       areas clean. a default of 7 days is suggested because this
       puts  urban  and  rural areas on roughly even footings for
       comparison. To complicate the issue street  sweeping  also
       removes	contaminants  from  road ways and so if the study
       area has a regular streeet cla\aning program  that  should
       be  reflected  by  entering  fewer dry days. Several minor
       rain storms, especially short hard rains  will  accomplish
       the same cleaning as a long large rain.	SWMM assumes that
       a half inch of rain removes half of the available dirt and
       the  next half inch removes half of what is left an so on.
       A worst case for urban areas is a rain  ater  an  extended
       dry  period.  However the goal is to compare watersheds or
       source areas.  Agriculturlal  areas  contribute	the  most
       poultion with an anticeedent moisture condition of 3 since
       that is when the most runoff and erosion takes place.



SSuummmmaarryy
       The tools presented here run within the GRASS GIS. A  flow
       chart  of  input and analysis (figure X1) can be used as a
       guide for the order of analysis. The system of  units  and
       means  for  encoding  qualitative information are supplied
       for both input and output map layers. Careful  preparation
       of  input  maps	is  strongly encouraged since this effort
       will likely save time and trouble later in the analysis.


       The ultimate utility  of  analyses  performed  with  these
       water resource assessment tools is dependent on the inter-
       pretation of the user. Always  keep  in	mind  that  these
       results	are based on empirical relationships which repre-
       sent expectations over a long term average. For this  rea-
       son  numerical  results should be used only for comparison
       of areas and scenarios. Employing the entire set of  tools
       from  the  tool kit may be inappropriate, and or redundant
       information.


       You can't hurt the model by running it! So  feel  free  to
       experiment!   AUTHOR	Brian  R. Brodeur    Cook College
       Remote Sensing Center


       _L_a_s_t _c_h_a_n_g_e_d_: _$_D_a_t_e_: _2_0_0_2_/_0_1_/_2_5 _0_5_:_4_5_:_3_4 _$



GRASS 5.0						r.wrat(1)
