1. The Effects of Land Cover Change on the Brushy Creek Watershed
CE 397 Statistics for Water Resources
By Ruth Haberman

2. AGENDA: Introduction to Brushy Creek Watershed Overall Goal
Data and the Lack Thereof
How Statistics can Help
Conclusions
Future Work

3. Brushy Creek Watershed
Getting Oriented
Texas
Williamson County
Brushy Creek Watershed

4. Source: http://www.upperbrushycreekwcid.com/Dams/maps/ETJ.pdf
WILLIAMSON COUNTY
27th most rapidly growing county in the US between 2000 and 2005
30.4% Growth rate (U.S. Census Bureau)
Round Rock 41.2%
Cedar Park 84.8%
Leander 135.0%
Source:

5. Project Goal: Enhance previously developed watershed model.
Find two similar rain events in two different years.
Compare the runoff from the two events.
Define the change in land cover between those two years.
See if there is any correlation between change in runoff and land cover change.

6. Data Sources (land cover and rainfall):
National Land Cover Dataset (NLCD) – Available for the geographical area for 1992 and 2001.
USGS Rainfall/Streamflow Gages – None within the watershed for the time period.
Daymet Rainfall Data – Available for the time period. Accessible using Weather Downloader (Ernest To)

7. NLCD 1992 Land Cover 2001 Land Cover
(Don’t forget that this is just 2001!
Can you imagine what this looks like now?)

8. Brushy Creek Watershed NHDPlus Catchments and USGS Gages

9. Incorporated Rainfall Data to correspond with NLCD

10. Sorted through Daymet Data using MS Excel Pivot Tables and Charts

11. Hypothesis Tests H0 = No difference in mean or variance
p>α , t<2, coefficient of variance are equal
Cannot reject null hypothesis

12. How does it look spatially? (Hint: not so good)
Precipitation over Brushy Creek on Feb. 22, 1992
(Heaviest rain on the east side of the watershed)
Precipitation over Brushy Creek on Jan. 11, 2001
(Heaviest rain on the west side of the watershed)

13. Some more analysis:

14. Conclusions:
Brushy Creek lacks historical rainfall and streamflow data.
In order to develop an accurate hydrologic model, I will have to get creative.
I need to continue looking for two rain events that are statistically and spatially similar.
Once I have good rainfall data, I can correlate them to land cover statistics.

15. Future Work: Continue to refine and calibrate model.
Streamflow
-Use local regression equations to estimate initial abstraction and constant loss (USGS, Asquith).
-Use local unit hydrographs (USGS, Asquith)
-Calibrate model with current rain event.
Water quality
-Look at SPARROW data for 1992 and 2001.
-Calibrate model with gage water quality data.
Model future development scenarios

16. QUESTIONS?

20. SAMPLE OF CLARK LABS LAND CHANGE MODELER
(Thanks Virginia Smith!)