Enhanced Estimation of Terrestrial Loadings for TMDLs: Normalization Approach
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 3
Abstract
The effective implementation of total maximum daily loads (TMDLs) usually requires that relationships between terrestrial contaminant loadings and instream concentrations be estimated using deterministic fate and transport (DFT) models. The limitations of using conventional DFT models are that model predictions do not converge to observations as source loadings approach their calibrated values, and model-prediction errors are not explicitly included in the model output. A normalization approach is proposed that yields an accurate convergence to observations and can explicitly account for prediction errors. The proposed approach is demonstrated using field data collected at the Little River Experimental Watershed in Georgia, where source-load reductions are related to the confidence of compliance with a water-quality standard.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
Professor George Vellidis of the University of Georgia generously allowed us to use the FC data collected under his supervision. Tom Jobes of the Saint John’s Water Management District, Fla., patiently provided advice on using HSPF, and Kate Flynn of USGS provided advice on using HSPEXP. Gary Feyereisen of USDA ARS in University Park, Pa., provided essential insight into previous studies of the Little River Experimental Watershed.
References
Benham, B. L., et al. (2006). “Modeling bacteria fate and transport in watersheds to support TMDLs.” Transactions of the American Society of Agricultural and Biological Engineers, 49(4), 987–1002.
Benjamin, J. R., and Cornell, C. A. (1970). Probability, statistics, and decision for civil engineers, McGraw-Hill, New York.
Bicknell, B. R., Imhoff, J. C., Kittle, J. L., Jr., and Donigian, A. S., Jr. (2001). “Hydrological simulation program—Fortran (HSPF): Users manual for release 12.” Technical Rep. Prepared for National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Athens, Ga.
Borah, D. K., and Bera, M. (2003). “Watershed-scale hydrologic and nonpoint-source pollution models: Review of mathematical bases.” Transactions of the American Society of Agricultural Engineers, 46(6), 1553–1566.
Borsuk, M. E., Snow, C., and Reckhow, K. (2002). “Predicting the frequency of water quality standard violations: A Probabilistic approach for TMDL development.” Environ. Sci. Technol., 36(10), 2109–2115.
Bosch, D. D., and Sheridan, J. M. (2007). “Stream discharge database, Little River Experimental Watershed, Georgia, United States.” Water Resour. Res., 43, W09473.
Dilks, D., and Freedman, P. (2004). “Improved consideration of the margin of safety in total maximum daily load development.” J. Environ. Eng., 130(6), 690–694.
Eadie, W., Drijard, D., James, F., Roos, M., and Sadoulet, B. (1971). Statistical methods in experimental physics, North-Holland, Amsterdam.
Feyereisen, G., Strickland, T., Bosch, D., and Sullivan, D. (2007). “Evaluation of SWAT manual calibration and input parameter sensitivity in the Little River Watershed.” Transactions of the American Society of Agricultural and Biological Engineers, 50(3), 843–855.
Gassman, P. W., Reyes, M. R., Green, C. H., and Arnold, J. G. (2007). “The soil and water assessment tool: Historical development, applications, and future research directions.” Transactions of the American Society of Agricultural and Biological Engineers, 50(4), 1211–1250.
Georgia Department of Natural Resources. (2002). “Total maximum daily loads (TMDLs) for fecal coliform in 303(d) listed streams in the Oconee River Basin.” Environmental Protection Division, Atlanta, Ga.
Haas, C., and Heller, B. (1988). “Test of the validity of the Poisson assumption for analysis of most-probable-number results.” Appl. Environ. Microbiol., 54(12), 2996–3002.
Hahn, G., and Meeker, W. (1991). Statistical intervals: A guide for practitioners, Wiley, New York.
Hantush, M. M., and Kalin, L. (2008). “Stochastic residual-error analysis for estimating hydro-logic model predictive uncertainty.” J. Hydrol. Eng., 13(7), 585–596.
Hellweger, F., and Masopust, P. (2008). “Investigating the fate and transport of escherichia coli in the Charles River, Boston, using high-resolution observation and modeling.” J. Am. Water Resour. Assoc., 44(2), 509–522.
Houck, O. (2002). The Clean Water Act TMDL Program: Law, policy, and implementation, 2nd Ed., Environmental Law Institute, Washington, D.C.
Isaaks, E., and Srivastava, R. (1989). An introduction to applied geostatistics, Oxford University Press, New York.
Labiosa, W. B., Leckie, J. O., Shachter, R. D., Freyberg, D., and Rytuba, J. J. (2005). “Incorporating uncertainty in watershed management decision-making: A mercury TMDL case.” Proc., Watershed Management Conf.: Managing Watersheds for Human and Natural Impacts, ASCE, Reston, Va.
Lilliefors, H. W. (1967). “On the Kolmogorov-Smirnov test for normality with mean and variance unknown.” J. Am. Stat. Assoc., 62, 399–402.
Lumb, A. M., McCammon, R. B., and Kittle, J. L. (1994). “Users manual for an expert system (HSPEXP) for calibration on the hydrological simulation program—Fortran.” Water-Resources Investigations Rep. No. 94-4168, United States Geological Survey, Reston, Va.
McBride, G. B. (2003). “Confidence of compliance: Parametric versus nonparametric approaches.” Water Res., 37, 3666–3671.
McBride, G. B., and Ellis, J. C. (2001). “Confidence of compliance: A Bayesian approach for percentile standards.” Water Res., 35, 1117–1124.
National Research Council. (2001). Assessing the TMDL approach to water-quality management, National Academy Press, Washington, D.C.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R., and King, K. W. (2002). “Soil and water assessment tool theoretical documentation, version 2000.” Technical Rep. No. 02-01, U.S. Department of Agriculture, Agriculture Research Service, Grassland, Soil, and Water Research Laboratory, Temple, Tex.
Novotny, V. (2004). “Simplified databased total maximum daily loads, or the world is log-normal.” J. Environ. Eng., 130(6), 674–683.
Parajuli, P. B., Mankin, K. R., and Barnes, P. L. (2007). “New methods in modeling sources specific bacteria at watershed scale using SWAT.” Proc., Watershed Management to Meet Water Quality Standards and TMDLS (Total Maximum Daily Load) Proc., Fourth Conf., American Society of Agricultural and Biological Engineers, St. Joseph, Mich.
Reckhow, K. (2003). “On the need for uncertainty assessment in TMDL modeling and implementation.” J. Water Resour. Plann. Manage., 129(4), 245–246.
Shapiro, S. and Wilk, M. (1965). “An analysis of variance test for normality (complete samples).” Biometrika, 52(3–4), 591–611.
Skahill, B. E. (2004). “Use of the Hydrological Simulation Program—FORTRAN (HSPF) model for watershed studies.” SMART Technical Notes Collection Rep. No. ERDC/TN SMART-04-1, U.S. Army Engineer Research and Development Center, Vicksburg, Miss.
U.S. EPA. (1983). “Results of the nationwide urban runoff program.” Final Rep., Water Planning Division, Washington, D.C.
U.S. EPA. (2004). “Overview of current total maximum daily load—TMDL—Program and regulations.” ⟨http://www.epa.gov/owow/tmdl/overviewfs.html⟩ (May 9, 2005).
U.S. EPA. (2008). “Causes of impairment for 303(d) listed waters.” ⟨www.iaspub.epa.gov/waters10/attains nation cy.control?p report type=T#causes303d⟩ (September 17, 2008).
Van Liew, M. W., Arnold, J. G., and Garbrecht, J. D. (2003). “Hydrologic simulation on agricultural watersheds: Choosing between two models.” Transactions of the American Society of Agricultural and Biological Engineers, 46(6), 1539–1551.
Vrugt, J. A., Gupta, H. V., Bouten, W., and Sorooshian, S. (2003). “A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters.” Water Resour. Res., 39(8), 1201.
Zhang, H., and Yu, S. (2004). “Applying the first-order error analysis in determining the margin of safety for total maximum daily load computations.” J. Environ. Eng., 130(6), 664–673.
Information & Authors
Information
Published In
Copyright
© 2010 ASCE.
History
Received: Jun 7, 2008
Accepted: Jun 29, 2009
Published online: Apr 15, 2010
Published in print: May 2010
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.