Theodore G. Cleveland, C. Amanda Garcia, Xin He, Xing Fang, and David B. Thompson

1. Comparison of Basin Characteristics for Small Watersheds in Texas using Automated and Manual Methods Theodore G. Cleveland, C. Amanda Garcia, Xin He, Xing Fang, and David B. Thompson 2005_ASCE_Fall_Meeting_El_Paso

2. Acknowledgements • This work was funded as part of Texas Department of Transportation RMC 3 research projects: • 0-4193 Regional Characteristics of Unit Hydrographs • 0-4194 Characteristics of Storm Hyetographs • 0-4696 Estimation of Timing Parameters for Unit Hydrographs. 2005_ASCE_Fall_Meeting_El_Paso

3. Disclaimer • The contents of this presentation reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein. • The contents do not necessarily reflect the official view or policies of the Texas Department of Transportation (TxDOT). • This presentation does not constitute a standard, specification, or regulation. The United States government and the State of Texas do not endorse products or manufacturers. 2005_ASCE_Fall_Meeting_El_Paso

4. Introduction • Four institution research team engaged in investigations of watershed unit hydrographs, rainfall hyetographs, and timing characteristics of watersheds in Texas. • Examined in 96 watersheds, 1600 storms with paired rainfall-runoff data. 2005_ASCE_Fall_Meeting_El_Paso

5. Introduction Results include: Asquith, W.H., Thomson, D.B., Cleveland, T.G., and X. Fang. 2005. “Unit Hydrograph Estimation for Applicable Texas Watersheds.” Texas Department of Transportation Research Report 0-4193-4 (in review) Cleveland, T.G., Thompson, D.B., Fang, X. 2005. “Timing parameter estimation using a particle tracking method.” Texas Department of Transportation Research Report 0-4696-3 (in review). Roussel, M.C., Thompson, D.B., Fang, X., Cleveland, T.G., and C.A. Garcia . 2005. “Timing parameter estimation for applicable Texas watersheds.” Texas Department of Transportation Research Report 0-4696-2 (in review). Fang, X., Cleveland, T.G., Garcia, C.A., Thompson, D.B., and R. Malla. 2005. “Literature review on time parameters for hydrographs.” Texas Department of Transportation Research Report 0-4696-1. Asquith, W.H., and Roussel, M.C., 2004. Atlas of depth-duration-frequency of precipitation annual maxima for Texas. U.S. Geological Survey Water-Resources Investigations Report 2004-5041, 106p. Asquith, W.H., and Roussel, M.C., 2003. Atlas of interoccurence intervals for selected thresholds of daily precipitation in Texas. U.S. Geological Survey Water-Resources Investigations Report 03-4281, 204p. Asquith, W.H., Thomson, D.B., Cleveland, T.G., and X. Fang. 2004. “Synthesis of Rainfall and Runoff Data Used for Texas Department of Transportation Research Projects 0-4193 and 0-4194.” U.S. Geological Survey Open-File Report 2004-103, 50p. Williams-Sether, T., Asquith, W.H., Thompson, D.B., Cleveland, T.G., and X. Fang. 2004. Empirical, Dimensionless, Cumulative-Rainfall Hyetographs for Texas. U.S. Geological Survey Scientific Investigations Report 2004-5075, 138p. 2005_ASCE_Fall_Meeting_El_Paso

6. Introduction • The University of Houston team assembled a set of watershed characteristics by manual analysis from paper-based maps. • Later the USGS team automatically analyzed the same watersheds in support of another research project. • Presented an unusual opportunity to compare manually and automatically determined physical characteristics. 2005_ASCE_Fall_Meeting_El_Paso

7. Figure 1 . Study Watershed Locations (Map courtesy of F.T. Heitmuller, Geographer, U.S. Geological Survey, Texas Water Science Center, 8027 Exchange Dr. Austin, TX., used with permission). 2005_ASCE_Fall_Meeting_El_Paso

8. Introduction • Basin physical characteristics are used in a variety of hydrologic models. Examples: • Qp=cIA • Tc=kLnSm(typical structure of timing model) • Regionalized regression equations to estimate unit hydrograph parameters (Qp,Tp) from watershed physical characteristics for practical application in Texas. 2005_ASCE_Fall_Meeting_El_Paso

9. Methods • Automated: • Various computed values from digital elevation models using GIS scripts. • Manual • Various computed values from topographic maps (paper-based) using navigation dividers, scales, grid sheets, and mechanical planimeters. 2005_ASCE_Fall_Meeting_El_Paso

10. Automated Methods • Over 20 characteristics (Brown and others, 2000). • Comparable characteristics are: • Total Drainage Area (TDA) • Basin Perimeter (BP) • Minimum/Maximum Elevation (MNELEV;MXELEV) • Basin Relief (BR) • Main Channel Length (MCL) • Main channel slope (85/10) (MCS) • Main channel slope (Asquith and Slade, 1997) (MCS2) 2005_ASCE_Fall_Meeting_El_Paso

11. Manual Methods • Fewer Characteristics • Comparable characteristics are: • Total Drainage Area (TDA_M) • Basin Perimeter (BP_M) • Minimum/Maximum Elevation (MNELEV_M;MXELEV_M) • Basin Relief (BR_M) • Main Channel Length (MCL_M) • Main channel slope (85/10) (MCS_M) • Main channel slope (Asquith and Slade, 1997) (MCS2_M) 2005_ASCE_Fall_Meeting_El_Paso

12. Watershed Delineation • Automated • 8-cell pour point model and flow accumulation up to watershed divide. • Manual • Steepest ascent along flowline up to watershed divide. • Mechanical planimetry to determine area. • Areas adjusted to agree with published areas from USGS small watershed studies. • Results vary by analyst. 2005_ASCE_Fall_Meeting_El_Paso

13. Watershed Delineation • Manual delineation and boundary file creation. 2005_ASCE_Fall_Meeting_El_Paso

14. Watershed Boundary Comparisons 2005_ASCE_Fall_Meeting_El_Paso

15. Figure 3. Log-log plot of TDA_M, MCL_M, and BP_M versus TDA, MCL, and BP. 2005_ASCE_Fall_Meeting_El_Paso

16. Figure 4. Log-log plot of BR_M, MCS_M, and MCS2_M, versus BR,MCS, and MCS2. 2005_ASCE_Fall_Meeting_El_Paso

17. Quantitative Comparison • Natural pairing for each watershed (manual vs. automated). • Paired two-sample t-test • Assumes differences are normally distributed. 2005_ASCE_Fall_Meeting_El_Paso

18. Figure 5. Frequency diagram (histogram) of differences between selected manual and automated characteristics. Manual characteristics are “uncorrected.” 2005_ASCE_Fall_Meeting_El_Paso

19. Hypothesis Testing 2005_ASCE_Fall_Meeting_El_Paso

20. Adjusted Values • Qualitative analysis: • Marker clouds are parallel to 1:1 line. • Multiplicative factor could be applied to correct for differences. • Used median uncorrected relative difference as correction for manual values. • Re-analyze 2005_ASCE_Fall_Meeting_El_Paso

21. 2005_ASCE_Fall_Meeting_El_Paso Figure 6. Frequency diagram (histogram) of differences between selected manual and automated characteristics. Manual characteristics are “corrected.”

22. Hypothesis Testing 2005_ASCE_Fall_Meeting_El_Paso

23. Illustrative Application • Purpose of the characteristic analysis is to estimate various parameters in hydrologic models. • The Kirpich (1940) formula is typical: • In this case time of concentration is related to main channel length and dimensionless slope. 2005_ASCE_Fall_Meeting_El_Paso

24. Figure 7. Plot of time of concentration using Kirpich equation using manually determined versus automatically determined characteristics. 2005_ASCE_Fall_Meeting_El_Paso

25. 2005_ASCE_Fall_Meeting_El_Paso

26. Figure 9. Model peak discharge versus observed peak discharge for 1300 storms. 2005_ASCE_Fall_Meeting_El_Paso

27. Conclusions • Manual and automated are qualitatively similar, but differences are statistically significant. • A multiplicative correction factor to each characteristic produces differences that are not significant. • Suggests that analysis differences are some systematic bias that scales with watershed size. 2005_ASCE_Fall_Meeting_El_Paso

28. Conclusions • Use of manual characteristics in a typical formula for hydrologic application produces timing estimates well within an order of magnitude of the estimates using automated analysis. • Differences in timing values for either method are not statistically significant if the characteristics are “corrected”. 2005_ASCE_Fall_Meeting_El_Paso

29. Conclusions • For small watersheds (20 sq.mi.), correction is probably unnecessary, and method choice is a matter of analyst preference. • For large and multiple watershed studies the speed of the automated methods, even considering the time required to assemble the digital elevation maps and schedule an analyst, greatly reduces overall effort required to generate these characteristics. 2005_ASCE_Fall_Meeting_El_Paso

30. References Asquith, W.H., Thomson, D.B., Cleveland, T.G., and X. Fang. 2004. “Synthesis of Rainfall and Runoff Data Used for Texas Department of Transportation Research Projects 0-4193 and 0-4194.” U.S. Geological Survey Open-File Report 2004-103, 50p. Asquith, W.H., and Slade, Raymond, Jr., 1997, Regional equations for estimation of peak-stream flow frequency for natural basins in Texas: U.S. Geological Survey Water-Resources Investigations Report 96-4307, 68p. Brown, J.R., Ulery, R.L., and Parcher, J.W. 2000. “Creating a standardized watersheds database for the Lower Rio Grande/Rio Bravo, Texas.” U.S. Geological Survey Open-File Report 2000-065, 13p. Kirpich, Z. P. 1940. “Time of concentration of small agricultural watersheds.” Civil Engineering, ASCE, Vol.10, No. 6, p. 362. 2005_ASCE_Fall_Meeting_El_Paso