Table of Contents

• Goals of the Exercise
• Computer and Data Requirements
• Getting the Data Needed for the Assignment
• Assignment Procedure

1. Getting Acquainted with the Basin
2. Annual Precipitation in the Basin
3. Create a Runoff Grid
4. Linking Land Use to Expected Mean Concentration (EMC) of Pollutants
5. Estimating Annual Loadings
6. Cleaning Up

Goals of the Exercise

The purpose of this exercise is to show how the Arc/Info GRID system and Arcview 3.0 with Spatial Analyis and the Hydrology Extensions can be used to provide estimates of nonpoint source pollutant loads to a receiving body of water. For this exercise, the receiving water is Copano Bay in South Texas, which the Aransas River, Mission River, and Copano Creek all drain into. These streams are all contained within the San Antonio-Nueces coastal basin, a 7000 sq km basin which is bounded by the San Antonio River and Nueces River basins (hence the name).

You will use a coverage of land uses in the Mission Basin and associate Estimated Mean Concentration (EMC) values of various pollutant constituents with those land uses. Then, for a selected pollutant, you will create an EMC grid and multiply it by a grid of average annual rainfall runoff in the basin. The result will be the annual loading of the constituent to each grid cell in the basin, i.e.

Finally, you'll perform a flow accumulation on the cell-based loads to determine average annual loads to Copano Bay.

Computer and Data Requirements

All the data needed for the exercise is also available via anonymous ftp from ftp.crwr.utexas.edu/pub/gisclass/ex7. Instructions on how to use anonymous ftp. All the coverages are in export format so you will need to import them using the arc IMPORT command.

Getting the Data Needed for the Assignment

$: mkdir ex7
$: cd ex7
$: arc

All files are in the directory ../alpha62/maidment/corpus/.

Copy the filled DEM, and coverages of the basin border, stream network, bay network, and sub-basin watersheds:

Arc: copy ../../maidment/corpus/dem dem
Arc: copy ../../maidment/corpus/strms strms
Arc: copy ../../maidment/corpus/bay bay
Arc: copy ../../maidment/corpus/misbasin misbasin

Get the precipitation grid from the directory:

Arc: copy ../../maidment/corpus/precip precip

You will need six Avenue scripts to complete the exersise:

Arc:quit

$cp ../../maidment/corpus/*.ave ./
> and if that does not work, copy them one by one as follows:

$cp ../../maidment/corpus/concgrid.ave concgrid.ave
$cp ../../maidment/corpus/connect.ave connect.ave
$cp ../../maidment/corpus/loadgrid.ave loadgrid.ave
$cp ../../maidment/corpus/pickload.ave pickload.ave
$cp ../../maidment/corpus/rogrid.ave rogrid.ave
$cp ../../maidment/corpus/wfacgrid.ave wfacgrid.ave

You will need the land use coverage and the data tables for the EMC values.

$ cp ../../maidment/corpus/lanuses.e00 lanuses.e00
$ cp ../../maidment/corpus/emc.txt emc.txt
$ cp ../../maidment/corpus/emca.dat emca.dat

Assignment Procedure

1. Getting Acquainted with the Basin

Starting the Project:

$arcview &

Goto File/Extensions and add the Hydrology and Spatial Analysis Extensions by checking the appropriate boxes.

Check out the Digital Elevation Model (DEM) of the region:

Goto the Project Window and Open a new view. By going to the View/Properties, change the name of the view to ProjArea.

Add the DEM grid to the view by clicking on , change the Data Source Type to Grid Data Source, highlight dem, and click OK. Once the theme has been added, make the DEM grid active and check the box next to the theme to view the DEM of the area.

You can see in the shaded image, part of the Nueces River to the South and the end of the San Antonio River to the North, both flowing into the Texas coastal waterways to the East. The Mission basin which we are going to study in this exercise is the drainage area for the Mission River.

Now, lets take a look at some cell elevations within the grid:

Make the DEM theme active by clicking on its display in the Legend bar of the View window.
Click on the inquiry (i) tool.
Goto the view and click on some points on the grid, e.g.:.

The cell containing point (1227870,690314) has value 48
The cell containing point (1224170,729514) has value 91
The cell containing point (1244470,702414) has value 45
The cell containing point (1198570,734814) has value 156
The cell containing point (1206670,700114) has value 106

These are land surface elevations in meters above mean sea level.

Now lets describe this grid:

$:Arc

Arc:describe DEM

Make note of the following: grid cell-size, elevation range in the basin, and the projection. The parameters of this projection are defined by the Texas State Mapping System (TSMS).

To Be Turned In: What is the cell size of the grid? Now many rows and columns does the grid have. What is the total number of cells in this grid? What land surface area is covered by this grid? What is the maximum, minimum and average elevation of the cells in this grid?

Now overlay the basin border, stream network, and bay network:

Make the ProjArea view active. Click on the button, chage the Data Source Type to Feature Data Sources, and highlight the three feature data sources, misbasin, strms, and bay, by using the shift key (use the Polygon version of Misbasin and Bay). Click OK.

Check the three boxes for the newly added themes. Change the colors of the themes as desired by double clicking on the theme symbol to activate the legend editor. Once in the legend editor, double click on the theme symbol again and use the Color Palette to change to the desired color. Remember to click the button when you are done changing the color. It is particularly useful to make the colored interior of the Misbasin theme transparent so that you can see the streams and the DEM within the basin. In the Fill Palette, the transparent option is the clear box in the top left corner of the fill shading options available.

To view all the themes at once, have the Strms theme on top, with Bay below it followed by Misbasin and finally DEM.

Note that Copano Bay is the interior bay that is enclosed almost all the way around. It looks somewhat like a hammer head. The stream network was created using the watershed delineation process that you used in Exercise 2. The threshold value for this particular network was 8000 cells. The basin border was created by delineating all the subwatersheds in the basin, converting those grids to coverages (using the gridpoly command) and then combining the coverages with the Arc/Info mapjoin command. The 3 largest streams that drain to Copano Bay are the Aransas River, Mission River, and Copano Creek.

2. Annual Precipitation in the Basin

Save the project so if you have a crash you don't have to recreate it later. Quit Arcview and go to Arc so that you can use the describe command to query the statistics of the precipitation grid.

Arc: describe precip

The size of these squares is approximately 5 km. From this description of the grid, you can identify the range of precipitation values (min to max) over the basin. Note that the units of these values are in millimeters/year. Also verify cell-size and projection of the grid to check its compatibility with the DEM.

To Be Turned In: What is the range of the precipitation across the basin in mm/yr? What is the basin mean precipitation (mm/yr). What are the corresponding values in in/yr? What grid cell size is used?

3. Create a Runoff Grid

A detailed explaination of this process is discussed in Seann Reed's paper:
Spatial Water Balance of Texas.

Q = 0.00064 * P (mm/yr) * exp(0.0061 * P)    if P < Po
Q = 0.51 * P (mm/yr)  - 339.1                if P >= Po

Where Q is runoff (mm/year) and P is precipitation (mm/year). An exponential function was fit to the data in drier areas with mean annual rainfall less than Po (801 mm/year). It turns out that a linear function yields a better fit to the wetter watersheds with rainfall above Po.

A script has been written for you to calculate the runoff for the Mission River Basin. The script inserts the precip grid into the rainfall/runoff equations discussed earlier to calculate the runoff grid (mm/yr).

Goto the Project Window, click on the Scripts window and and open a new script window (labelled Script1). From the Menu Bar, select Script/Load Text File. Click on rogrid.ave, and click OK. Using Script/Properties change the name of the script to Rogrid.Within the script, there is a line that states to which file the result will be saved:

rogrid.savedataset("/home1/alpha62/maidment/ex7/runoff".asfilename)

Edit this path name in the Script so that the result will be saved to the correct location on your directory. Compile the script by clicking on the check button, and run it on top of the Precip/Runoff view. Make the View active, then click on the Rogrid script window and hit the Running man next to the check button to initiate the script. You will be asked to select the View whose themes will be used for the computation (Precip/Runoff) and the theme within that view (Precip) which will be used as the precipitation input.

You may get two error messages when running the Rogrid script. This is a machine dependent error, and does not effect the results of the calculation.

Once the runoff grid is calculated and added to the view, change the legend colors the same way as the precipitation grid was changed. You may use a different color scheme if desired. Here is an example of what the image should look like.

Make sure the runoff theme is active. Now use the inquiry tool to investigate values of runoff throughout the basin:

Click on a number of different locations in the basin to identify values of average annual runoff at those points.

Let's describe the runoff grid.

Arc: describe runoff

To Be Turned In: What is the mean runoff from the basin (mm/yr)? What is the range in the runoff (mm/yr)? If you convert the mean annual precipitation value that you got previously with the rainfall - runoff relation used to produce the runoff data, do you get the mean runoff value provided by this grid? If not, why not (think about the effects of nonlinear transformation of data).

4. Linking Land Use to Expected Mean Concentration (EMC) of Pollutants

This land use classification the United States was made in the late 1970's and land use has changed somewhat in the years since then, particularly as cities have grown. But, the LULC files are still the standard land use classification of the United States taken as a whole. Files based on 1:250,000 map sheet names can be downloaded from the USGS Land Use/Land Cover site. These files are in UTM coordinates which can cause problems because adjacent land use maps can be in different UTM zones. A more convenient source for land use files in Texas is the TNRIS ftp server site under the heading Land Use/Land Cover (ascii data)..

Import the land use coverage from the lanuses.e00 file.
Arc: import cover lanuses lanuses

  Importing lanuses from interchange file lanuses.e00...

Delete the interchange file to save space. This rm command is executed from within Arc but it drops back to the basic Unix system to be executed because Arc has no rm function:

Arc: rm lanuses.e00

  Submitting command to Operating System ...

Then call up Arcplot to view the coverage:
Arc: arcplot
Arcplot: display 9999
Arcplot mape lanuses
Arcplot: arcs lanuses

Wow! A pretty detailed coverage. Notice that the parallels and meridians intersect some of the landuse polygons. These lines arise from the fact that a number of maps were joined to form the coverage that you see here. You can get rid of the parallels and meridians by using the Arc/Info dissolve command. This command removes all arcs separating polygons with equal values for a particular attribute:

Arcplot: quit
Arc: dissolve lanuses luse lanuses-id poly

  Dissolving lanuses by lanuses-id to create luse

  Creating luse.PAT format...

  Creating dissolve table...

  Dissolving...

 Number of Polygons (Input,Output) =       7039       6513

 Number of Arcs     (Input,Output) =      16003      14710

  Creating luse.PAT...

Make note of the 4 arguments in the dissolve command. What this command says is:
(1) dissolve the coverage lanuses to create a new coverage called luse.
(2) Use the coverage attribute lanuses-id as the item to decide which arcs to remove. Arcs are removed between any two polygons which have the same lanuses-id.
(3) Define the new coverage as a polygon coverage.

Now view the dissolved coverage in Arcplot:

Arc: arcplot
Arcplot: mape luse
Arcplot: arcs luse

You'll see that nearly all the straight map borders have been dissolved. Overlay the Mission Basin border:

Arcplot: linecolor 2
Arcplot: arcs misbasin Arcplot: linecolor 4
Arcplot: arcs bay

For this study, we are only interested in the land uses within the basin boundary. The land uses outside of this boundary can be trimmed away using the clip command:

Arcplot: quit
Arc: clip luse misbasin mislu poly

(this may take a couple of minutes.

This clip command uses the misbasin polygon coverage as a "cookie cutter". In English, this command says, "Clip the luse coverage with the misbasin template to create the mislu coverage which is made up of polygons." Now, lets free up some file space.

Arc: kill luse all
Arc: kill lanuses all

In Arcview, Close the Rogrid Script window and the Precip/Runoff View, and open a new View. Use View/Properties to name it Land/Load, and add the mislu polygon land use coverage of the Mission basin as a theme. To display the individual land uses, double-click on the mislu theme symbol and, in the Legend Editor, change the Legend Type to Graduated Color and the Classification Field to lanuse-id. Click on the Classify button and change the number of classes to 8. Click on the Value buttons to change the values of each category. Click on the Label buttons to change the labels of each category. Use the Fill Palette to color-code each of the symbols into land use categories. The following color scheme works pretty well, but feel free to use your own:

        Value   Label           Symbol Color

	0 	Unknown 	White (or transparent)
	10-17 	Urban  		Red
	20-24 	Agriculture 	Tan
	30-33 	Rangeland 	Yellow
	40-43 	Forestland 	Green
	50-54 	Water  		Medium Blue
	60-62 	Wetlands 	Light Blue 
	70-76 	Barren  	Gray

Close the Fill Palette and select in the Legend Editor before closing it. Now select for the mislu theme in your view and note where all the different land use categories in the basin are. Save the project for future use.

Now you are going to associate Estimated Mean Concentration (EMC) values of various pollutant constituents to the land use types. The Natural Resources Conservation Service of the US Dept. of Agriculture (USDA-NRCS) has provided us with a table of some EMC values for 18 different constituents. You can view this table by bringing up a text editor window and loading the emc.txt file that you previously downloaded from my area.

The values in this table are typical concentrations of pollutants found in runoff water from each particular land use. The values are compiled from many field studies done by the US Geological Survey and other organizations.

Expand the text editor window so that all columns in the table are visible. Note that there are different EMC values for each of the Urban Land Use codes (residential, commercial, industrial, transportation, mixed) but only one EMC value for the Agriculture, Rangeland, and Barren Land Use categories. In addition to this table, we will use the Rangeland EMC values for Forest Land Uses. When you are done viewing this table, minimize it.

For this exercise, we will be interested in estimating annual loadings of nutrients to the Copano Bay, however we will limit this study to Phosphorus.

Open a new file emca.dat in the text editor. This is an edited version of the emc table that you previously viewed which has two columns of numbers representing, respectively: lanuses-id, and total phosophorus.

You'll need to join these EMC values to the mislu polygon attribute table in order to associate them with land use. From the Arc prompt, open the Tables module and define the following attribute data fields in a new table called attrib.dat.

Arc: tables
Enter Command: define attrib.dat

      1

     10

This completes the definition of the table. To check that you got your table created correctly, you can look at the directory of available tables:

Enter Command: dir

 TYPE NAME                            INTERNAL NAME    NO. RECS LENGTH EXTERNL
------------------------------------------------------------------------------
  DF  ATTRIB.DAT                         ARC0000DAT          47      14
  DF  MISBASIN.TIC                       ARC0002DAT           4      12    XX
  DF  MISBASIN.AAT                       ARC0003DAT          49      60    XX
  DF  MISBASIN.BND                       ARC0004DAT           1      16    XX
etc ....

To list the items in this table:

Enter Command: select attrib.dat
0 Records Selected.

[There are no records selected because you have not entered the data yet]

Enter Command: items

COLUMN   ITEM NAME        WIDTH OUTPUT  TYPE N.DEC  ALTERNATE NAME     INDEXED?
    1  LANUSES-ID             4     5     B      -                        -
    5  TP                     5     5     N      2                        -

Adding Data to the Table from an External File:

Now you have a table template created to which data can be added. The values from the table have been prepared in a data file for you (emca.dat). You can just fill these values into the new table using the "add from" command in tables:

Enter Command: add from emca.dat

  Real value expected.   (don't know why this occurs)

Enter Command: quit
Arc: list attrib.dat

You should see a table with one land use type per record and EMC values for Phosphorus associated with each land use type.

Check these values against the table emc.txt to verify their accuracy. Now use the joinitem command to join these EMC values to the appropriate polygons in the sanlu coverage:

Arc: joinitem mislu.pat attrib.dat mislu.pat lanuses-id lanuses-id

  Joining mislu.pat and attrib.dat to create mislu.pat

In English, this command says, "join the mislu polygon attribute table (pat) with the corresponding data from the attrib.dat table, creating a new mislu.pat table. Use the lanuses-id field as the item with which to relate the items from the two tables, and add the new data after the lanuses-id field in the mislu attribute table."

Now list the attributes of the mislu polygon attribute table:

Arc: items mislu.pat

Your result should look like this:

COLUMN   ITEM NAME         WIDTH OUTPUT  TYPE N.DEC  ALTERNATE NAME     INDEXED?
    1   AREA                  4    12     F      3                        -
    5   PERIMETER             4    12     F      3                        -
    9   MISLU#                4     5     B      -                        -
   13   MISLU-ID              4     5     B      -                        -
   17   LANUSES-ID            4     5     B      -                        -
   21   TP                    5     5     N      2                        -

Now use ArcView to look at a map of EMC values in the basin. In the view Land/Load, add the mislu coverage again. Change the name of the new Mislu theme to EMC by highlighting it and clicking on Theme/Properties. Then, double Click on the EMC theme symbol to bring up the Legend Editor. In the Legend Editor, select the Legend Type to be Graduated Color, the Classification Field to be Tp, and select 8 classification fields. This will cause the symbol color to ramp from a light color for 0 mg/L to a darker color for the Max EMC. Again, close the Fill Palette and your changes from the Legend Editor window. Select for the EMC theme in your the view to get a look at the Phosphorus EMC map for the Mission Basin.

Notice the large area in the north-east of the basin that contributes 0 mg/L of Total Phosphorus. This corresponds to forest and rangeland land uses which don't contribute much phosophorus to runoff because fertilizers are applied to this land and it is not disturbed by land cultivation. The main nonpoint source of phosophorus is from the agricultural lands in the South side of the basin. There can also be significant point sources of phosophorus from municipal treatment plant effluent.

We will now convert the land use theme to a equivalent grid showing the Total Phosporus concentrations in mg/l over the landscape. The Avenue script concgrid has been written for you to calculate the new grid. The new grid will be similar looking to the EMC coverage just shown, however it will be a grid rather than a coverage.

Open a new script and call it Concgrid. Click on Script/Load Text File and load in the script concgrid.ave.

**Remember to change the pathname for the saved data files to fit your directory.**

Open the Land/Load view. Click on Analysis/Properties and check that the analysis extent is Same as EMC, the Analysis Cell Size is 100. Compile the script. Finally, run the script on top of the Land/Load view (This means click on the Land/Load View, click on the Concgrid Script Window, then click on the Running Man in the Script GUI tool bar). Pick EMC as the land use theme and Tp as the concentration field. The concentration grid which is calculated by the script is added to the view and should be similar to the EMC coverage developed earlier in the exercise.

5.Estimating Annual Loadings

Open a new script and call it Loadgrid. Click on Script/Load Text File and load in the script loadgrid.ave.

**Remember to change the pathname in the script from /maidment to your directory for the saved data files to be placed your directory.**

Compile the Loadgrid script. Run the script on top of the Land/Load view (this means click on the Land/Load View, Click on the loadgrid Script Window, then hit the running man in the Script GUI tool bar). Pick concgrid as the concentration grid and runoff as the runoff grid.

The script makes a conversion of mg/l (concentration grid) * mm/yr (runoff grid) to the Kg/d (loading grid). This is a more conventional way of looking at loadings. The conversion constant of 1/36525 is because the input units are mm/yr for runoff and mg/l for concentration, the output units are kg/d for loading, there are 1,000,000 mg/kg, each cell has a 10,000 m2 area, and there are 365.25 days/year.

In effect, for each cell, the load is computed as

Load = Runoff * Concentration * Cell Area (1)

To Be Turned In: Do a units analysis of the above formula to show why dividing the product of the runoff (mm/yr) and concentration (mg/l) grids by 36525 leads to the correct units for the loading (Kg/d).

WATER

This part of the procedure includes a flow accumulation. In order to perform this, the river system needs to be connected to the bay system. This will allow for the nonpoint source pollution to be picked from a centroid in the bay polygon coverage. You will use the script connect.ave to do this. This script drops the elevation of the bays below the elevation of the adjacent land surface. The centroids of the bays are then dropped further so the flow accumulates at the centroid. The values can then be picked from the centroids.

From the Project Window, open a new script. Using Script/Properties rename the script to Connect. Click on Script/Load Text File, and load the Avenue Script connect.ave.

**Remember to change the pathname for the saved data to fit your file directory.**

There is more than one file which will be saved, and in turn, more than one directory which needs to be changed. Also, once the program is running it will ask you if you would like to save the temporary data sets. I recommend you don't due to limited file space. The temporary files are not needed.

Add to the Proj/Area view, the bay arc theme . Have the bay arc theme, the bay polygon theme and the DEM themes active. Compile the Connect script and run it on top of the Proj/Area view. A new grid is calculated and is called conngrid.

Next a flow direction must be done on congrid. Make the conngrid theme active and click on Hydro/Flow Direction.

Once the flow direction is done, click on the to see if the flow direction looks reasonable.