Rating Curve Estimation of Surface Water Quality Data Using LOADEST

Abstract

Measurement of the nutrient concentrations in the stream is usually done on weekly, biweekly or monthly basis due to limited resources. There is need to estimate concentration and loads during the period when no data is available. The objectives of this study were to test the performance of a suite of regression models in predicting continuous water quality loading data and to determine systematic biases in the prediction. This study used the LOADEST model which includes several predefined regression models that specify the model form and complexity. Water quality data primarily nitrogen and phosphorus from five monitoring stations in the Neuse River Basin in North Carolina, USA were used in the development and analyses of rating curves. We found that LOADEST performed generally well in predicting loads and observation trends with general tendency/bias towards overestimation. Estimated Total Nitrogen (TN) varied from observation (“true” load) by -1% to 9%, but for the Total Phosphorus (TP) it ranged from -2% to 27%. Statistical evaluation using R2, Nash-Sutcliff Efficiency (NSE) and Partial Load Factor (PLF) showed a strong correlation in prediction.

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B. Jha and M. Jha, "Rating Curve Estimation of Surface Water Quality Data Using LOADEST," Journal of Environmental Protection, Vol. 4 No. 8, 2013, pp. 849-856. doi: 10.4236/jep.2013.48099.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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[16] USGS LOADEST, “Load Estimator (LOADEST): A Fortran Program for Estimating Constituent Loads in Streams and Rivers. Techniques and Models Book 4,” Chapter 5, US Geological Survey, Reston, 2004.
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[26] USGS, “Statistical Methods in Water Resources,” In: D. R. Helsel and R. M. Hirsch, Eds., Techniques of Water-Resources Investigations, US Geological Survey, 2002, p. 522. http://water.usgs.gov/pubs/twri/twri4a3
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[28] S. D. Preston, V. J. Bierman Jr. and S. E. Sillman, “An Evaluation of Methods for the Estimation of Tributary Mass Loads,” Water Resources Research, Vol. 25, No. 6, 1989, pp. 1379-1389. doi:10.1029/WR025i006p01379
[29] A. Ullrich and M. Volk, “Influence of Different Nitrate-N Monitoring Strategies on Load Estimation as a Base for Model Calibration and Evaluation,” Environmental Monitoring and Assessment, Vol. 171, No. 1-4, 2010, pp. 513-527. doi:10.1007/s10661-009-1296-8
[30] M. K. Jha, K. E. Schilling, P. W. Gassman and C. F. Wolter, “Targeting Land-Use Change for Nitrate-Nitrogen Load Reductions in an Agricultural Watershed,” Journal of Soil and Water Conservation, Vol. 65, No. 6, 2010, pp. 342-352. doi:10.2489/jswc.65.6.342
[31] M. K. Jha, C. F. Wolter, P. W. Gassman and K. E. Schilling, “Assessment of TMDL Implementation Strategies for Nitrate Impairment of the Raccoon River, Iowa,” Journal of Environmental Quality, Vol. 39, No. 4, 2010, pp. 1317-1327. doi:10.2134/jeq2009.0392
[32] M. K. Jha, J. G. Arnold and P. W. Gassman, “Water Quality Modeling for the Raccoon River Watershed Using SWAT,” Transactions of the ASABE, Vol. 50, No. 2, 2007, pp. 479-493.
[33] I. G. Littlewood, C. D. Watts and J. M. Custance, “Systematic Application of United Kingdom River Flow and Quality Databases for Estimating Annual River Mass Loads (1975-1994),” Science of the Total Environment, Vol. 210-211, 1998, pp. 21-40. doi:10.1016/S0048-9697(98)00042-4
[34] K. E. Schilling and Y. K. Zhang, “Baseflow Contribution to Nitrate-Nitrogen Export from a Large Agricultural Watershed USA,” Journal of Hydrology, Vol. 295, No. 1-4, 2004, pp. 305-316. doi:10.1016/j.jhydrol.2004.03.010
[35] Y. Guo, M. Markus and M. Demissie, “Uncertainty of Nitrate-N Load Computations for Agricultural Watersheds,” Water Resources Research, Vol. 38, No. 10, 2002, p. 1185. doi:10.1029/2001WR001149
[36] B.T. Aulenbach and R. P. Hooper, “The Composite Method: An Improved Method for Stream-Water Solute Load Estimation,” Hydrological Processes, Vol. 20, No. 14, 2006, pp. 3029-3047. doi:10.1002/hyp.6147
[37] F. Moatar and M. Meybeck, “Compared Performance of Different Algorithms for Estimating Annual Nutrient Loads Discharged by the Eutrophic River Loire,” Hydrological Processes, Vol. 19, No. 2, 2005, pp. 429-444. doi:10.1002/hyp.5541
[38] Z. Li, Y. K. Zhang, K. Schilling and M. Skopec, “Cokriging Estimation of Suspended Sediment Loads,” Journal of Hydrology, Vol. 327, No. 3-4, 2006, pp. 389-398. doi:10.1016/j.jhydrol.2005.11.028
[39] A. Zamyadi, J. Gallichand and M. Duchemin, “Comparison of Methods for Estimating Sediment and Nitrogen Loads from a Small Agricultural Watershed,” Canadian Society of Bioengineering, Vol. 49, 1-2, 2007, pp. 127-136.
[40] D. M. Robertson and E. D. Roerish, “Influence of Various Water Quality Sampling Strategies on Load Estimates for Small Streams,” Water Resources Research, Vol. 35, No. 12, 1999, pp. 3747-3759. doi:10.1029/1999WR900277
[41] T. A. Cohn, D. L. Caulder, E. J. Gilroy, L. D. Zynjuk and R. M. Summers, “The Validity of a Simple Statistical Model for Estimating Fluvial Constituent Loads: An Empirical Study Involving Nutrient Loads in Chesapeake Bay,” Water Resources Research, Vol. 28, No. 9, 1992, pp. 2353-2363. doi:10.1029/92WR01008
[42] USGS LOADEST, “Load Estimator (LOADEST): A Fortran Program for Estimating Constituent Loads in Streams and Rivers. Techniques and Models Book 4,” Chapter 5, US Geological Survey, Reston, 2004.
[43] D. A. Goolsby, W. A. Battaglin, B. T. Aulenbach and H. P. Hooper, “Nitrogen Flux and Sources in the Mississippi River Basin,” Science of the Total Environment, Vol. 248, No. 2-3, 2000, pp. 75-86. doi:10.1016/S0048-9697(99)00532-X
[44] D. A. Goolsby and W. A. Battaglin, “Long-Term Changes in Concentrations and Flux of Nitrogen in the Mississippi River Basin, USA,” Hydrological Processes, Vol. 15, No. 7, 2001, pp. 1209-1226. doi:10.1002/hyp.210
[45] R. P. Hooper, B. T. Aulenbach, and V. J. Kelly, “The National Stream Quality Accounting Network: A Flux-Based Approach to Monitoring the Water Quality of Large Rivers,” Hydrological Processes, Vol. 15, No. 7, 2001, pp. 1089-1106. doi:10.1002/hyp.205
[46] B. T. Aulenbach and R. P. Hooper, “The Composite Method: An Improved Method for Stream-Water Solute Load Estimation,” Hydrological Processes, Vol. 20, No. 14, 2006, pp. 3029-3047. doi:10.1002/hyp.6147
[47] T. R. Maret, D. E. MacCoy and D. M. Carlisle, “Long-Term Water Quality and Biological Responses to Multiple Best Management Practices in Rock Creek, Idaho,” Journal of the American Water Resources Association, Vol. 44, No. 5, 2008, pp. 1248-1269. doi:10.1111/j.1752-1688.2008.00221.x
[48] USGS, “USGS Open-File Report 2007-1080—Streamflow and Nutrient Fluxes of the Mississippi-Atchafalaya River Basin and Subbasins for the Period of Record through 2005, Methods Used to Estimate Nutrient Fluxes,” 2009. http://toxics.usgs.gov/pubs/of-2007-1080/methods.html
[49] USGS, “Application of Spatially Referenced Regression Modeling for the Evaluation of Total Nitrogen Loading in the Chesapeake Bay Watershed,” 2009. http://md.water.usgs.gov/publications/wrir-99-4054/html/index.htm
[50] C. G. Crawford, “Estimation of Suspended-Sediment Rating Curves and Mean Suspended Sediment Loads,” Journal of Hydrology, Vol. 129, No. 1-4, 1991, pp. 331-348. doi:10.1016/0022-1694(91)90057-O
[51] R. I. Ferguson, “River Loads Underestimated by Rating Curves,” Water Resources Research, Vol. 22, No. 1, 1986, pp. 74-76. doi:10.1029/WR022i001p00074
[52] USGS, “Statistical Methods in Water Resources,” In: D. R. Helsel and R. M. Hirsch, Eds., Techniques of Water-Resources Investigations, US Geological Survey, 2002, p. 522. http://water.usgs.gov/pubs/twri/twri4a3

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