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GEO 371C GIS and GPS Applications and Earth Sciences
Bull Creek Watershed
Impacts of urbanization on water chemistry in flowing streams of the Bull Creek Watershed
Austin, Texas
INTRODUCTION
The Bull Creek watershed is located in north West Austin, its 25 square miles drain into the
Colorado River at Lake Austin. It has an 11 mile creek with scenic cliffs and waterfalls. The
watershed includes limestone seeps, springs, and waterways, which makes it the perfect home
to a number of indigenous species of flora and fauna. All of these characteristics make the Bull
Creek Watershed a very attractive area for land developers. Land development has increased
in the last several years, according to the City of Austin in 2000 the population of Bull Creek was
43,709 and they project that by 2030 the population will be 69,716. Urban development
increases surface impervious area, which decreases infiltration rates. The recharge of urban
ground water is heavily affected by extensive sealing of surfaces and leaky water mains. At the
same time that urbanization increases so does the underground pipe network used to carry
potable and wastewater, the risk of leaky pipes increases with the condensation of water pipe
networks. This paper deals with the assessment of potential risks due to damaged main water
pipes, and to find a correlation between the damaged water pipes systems and underground
water chemistry. The main focus of this paper is to analyze how main water pipes densities
within sub-water sheds of the Bull Creek watershed affect the concentrations of Na+Cl and
Ca+HCO3.
Figure 1. Picture of one of the few flowing springs (Picture by Daniel Reyes).
DATA GATHERING
Data for this study was collected from the following sources:
1- City of Austin
ftp://ftp.ci.austin.tx.us/GIS-Data/Regional/coa_gis.html
Creek Lines: Shapefile (vector digital data) Geographic coordinate system name: GCS North American 1983.
Combination of stream centerlines created from aerial orthography,
planimetrics based on LIDAR data “Hydro_L ”(a non-continuous stream) and
construction plans which has been updated and edited to be continuous stream.
Data created by TWDB.
Water Shed: Shapefile (Poligon vector digital data) Geographic coordinate system name: GCS North American 1983
Polygon shape file showing areas of all of the major watersheds in
central Texas.
I was unable to access metadata for this shapefile thus it was not
specified who the author is.
Main Water Pipe: Shapefile (vector digital data)
Map Projection Name: GCS North American 1983
Geographic coordinate system name: GCS North American 1983
of all installed water pipes, year installed, and length of pipe network within the
Bull Creek watershed.
In order to obtain these data I had to contact Kevin J. Smith, Sr. GIS
Analyst from City of Austin, Watershed Engineering Division.
Kevin.smith@austintexas.gov
2- Daniel Reyes (Variations in springwater geochemistry in a rapidly urbanizing watershed)
Water Shed Deliniation: shape files (Poligon vector digital data)
Map Projection Name: GCS North American 1983 Harn
Shapefile was created by using flow direction, flow accumulation, stream
definition, stream segmentation, catchment grid delineation. It separates Bull
Creek into smaller subwatersheds, these subwatersheds are assumed to be
the main contributor to each of the sampled sites.
Daniel Reyes constructed this shapefile with the help a lab from the class
GIS in Water Resources, thought by David R. Maidment. The linear unit for
this file was in meters in contrast with to the rest of the shapfiles from city of
Austin which uses feet.
Water Spring Sites: shape files (Point vector digital data)
Map Projection Name: GCS North American 1983 Harn
This shape file has all of the geographic locations of all of the springs
that were tested for this study.
The linear unit for this file was in meters in contrast with to the rest of
the shapfiles from city of Austin which uses feet.
Water Chemistry: excel file
Data showing chemical compositions of all of the sites tested.
The University of Texas at Austin. Cation (Sr, B, Ca, Mg, K, Na)
concentrations have been measured by quadrupole Inductively coupled
plasma mass spectrometer (ICP-MS) at the Lower Colorado River Authority
(LCRA) facility in west Austin. Anion (F, NO3, Cl, SO4) concentrations have
been measured by Ion Chromatography at the LCRA. The soil samples have
not yet been analyzed in the TIMS.
METHODS
Project data in common predefined coordinate system
Using analysis tools create a shapefile which contains the Bull Creek area by itself
Using analysis tools crate a shapefile with streams contained within Bull Creek watershed
Join Water Chemistry Excel file with the Water Spring Sites
Find sub-watershed areas by using the select by location tools
Find pipe total length within sub-watershed using the select by attributes tools
Find pipe density by dividing total pipe density by the area of its correspondent sub-watershed
In three different maps show pipe density, Ca+HCO3 and Na+Cl conentrations
Create two graphs, Pipe density vs Ca+HCO3 and Pipe density vs Na+Cl concentrations
An increase in Na+Cl concentration should be evident in relation to Ca+HCO3, mainly due to water softening treatment by the city water management
H2O + CaCO3 + CO2 = Ca2+ + 2HCO3
-
Data Processing
Projections
There were some issues with projecting all of the layer files at the beginning of the project. This
was mainly due to unknown metadata coordinate systems from some of the files. This could be
easily fixed by choosing the correct coordinate system. No changes adjustments of the
coordinate system were made, since the problematic files were not needed for to solve the
problem of this project.
Isolating Bull Creek
Isolating Bull Creek shape feature was relatively easy using analysis tools from the ArcToolbox
pull down menu. The best and easiest way to extract Bull Creek is to extract the data by its
attributes, in this case by a query that specifies its name has to be created.
Figure 2. ArcTollbox for selecting features
The Select tool under the Extract tools brings up a new window where an input feature has to be
specified, in this case the watershed polygon file. The output feature class pull down menu allows
specifying where the new shape file will be saved. For selecting the Bull Creek water shed a simple query
had to be created: DCM_NAME=Bull Creek, this query tells the computer to only extract the polygon
with the attribute name Bull Creek. This Polygon will be used in the next step.
Figure 3. Query Builder from Extract-Select Toolbox.
Figure 4 shows Bull Creek watershed before selection. Figure 5 shows Bull Creek after extraction.
Cliping Streams
In this step the Clip tool is used to clip the features within the Bull Creek watershed polygon. With this
technique the polygon created in the previous step is used to specify the area of interest. The impute
data to be extracted must meet some criteria, it must fall completely within the Bull Creek watershed.
Figure 6. Clip tool from the Extrct Toolbox.
The following window (fig. 7) is prompted by selecting the Clip tool. In this window the input features
and the clip features must be specified. A new feature is created by preassing the OK button, the new
feature contains all of the same attribute values as the input features.
Figure 7.
Figures 8 shows the Creeks data file before being clipped and figure 9 shows the same data after
clipping.
Figure 8
Figure 9
Joining Tables
Joining tables is a very simple process by using the joins and relates tool. The following window is
prompted, this window allow to brown for the excel table containing the chemical data for all of the
springs that where analyzed. All of the fields used to create the joint must be identical otherwise the
new attribute table will show null values for all the non-matching cells.
Figure 10
Calculating Densities
As the class progressed it became clearer that ArcMap has many different ways of analyzing
data. It is important to know that some ways of analyzing data are more efficient than others,
you can save time and get better results by choosing the correct technique. The selection menu
is one of those tools which allows to select features in many different ways. In this step two
selection techniques were used. Select by attributes allows to selects each of the
subwatersheds individually. The purpose of selecting each watershed individually is to highlight
those water pipe lines that fall within each area.
Figure 11 Selecting Subwatersheds by Attributes.
Figure 12 Selecting water pipes by location.
Figure 12 shows the highlighted pipe length within a specific subwatershed. The same data is highlighted
in the attribute table for the same layer. The total length of the highlighted water pipe within each
subwatershed was obtained from the attribute table. The attribute table has a selection tool, under the
selection tool there is a statics option which gives you a list of statistical values (see figure 13).
Figure 13
The cell containing the sum of the total pipe length is then copied in an excel table in order to calculate
the pipe density in relation to the area of each sub watershed.
RESULTS
Table one was used to create the results of figures 14 and 15. Figures 16, 17 and 18 were color labeled
to with the same colors to represent density chemical concentrations. The purpose of using same colors
was to show differences within each of the sub-watersheds.
ID Na+Cl(mg/l) Ca+HCO39(mg/l) areaft pipelenght (ft) pipedensity
Tubb 47.4 618.68 158957.6579 2691.965005 0.016935107
Fern Gully 30.8 472.8 172209.1729 0 0
Tanglewood 91 614.48 2169085.083 25679.85251 0.011839025
Trib. No.6 126.4 527.72 16704028.7 127328.2486 0.007622607
Trib No. 5 55.4 452.7 10166940.75 82606.01135 0.008124962
Franklin 24.88 445.04 2746798.363 0 0
Troll 60.1 545.04 1622852.608 16539.27481 0.010191483
Trib No. 3 97.7 403.9 8388432.662 60518.8221 0.007214557
Lanier 26.12 436.06 13502549.45 37507.29507 0.002777794
Lower Ribelin 25.82 460.24 6868435.733 22985.12374 0.003346486
Stillhouse Hollow 128.9 573.48 453045.8908 190.02411 0.000419437
Barrow 98.3 493.56 1569744.12 12269.06727 0.007815966 Table 1
Figure 14
Figure 15
R² = 0.0354
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0 20 40 60 80 100 120 140
Pip
e D
en
sity
Na+Cl
Pipe Density vs Na+Cl
R² = 0.3253
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0 100 200 300 400 500 600 700
Pip
e D
en
sity
Ca+HCO3
Pipedensity vs Ca+HCO3
Figure 16
Figure 17
Figure 18
CONCLUSION
Assuming the following: H2O + CaCO3 + CO2 = Ca2+ + 2HCO3
- The dominant ions in natural water are Ca and HCO3 the addition of municipal water increases
concentration Na and Cl relative to Ca and HCO3.To prove my hypothesis a positive correlation should
be exist by plotting pipe densities vs chemical concentrations. The results obtained in this study do not
show any correlation between pipe density and chemical concentrations. In conclusion water pipe
density does not reflect an influence on the water chemistry of the springs tested.
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