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Modeling of Nitrogen Retention in Amite River

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Abstract

This paper presents an efficient and effective modeling approach to estimation of nitrogen retention in streams and rivers. The approach involves an extension of a newly developed longitudinal solute transport model, variable residence time (VART), by incorporating a first-order nitrogen reaction term. Parameters involved in the VART model are estimated using monthly mean flow and water quality data obtained through both field measurements and watershed modeling using the Hydrologic Simulation Program Fortran model. It is found that there is a strong correlation between nitrate-nitrogen removal rate and water temperature. In addition, low nitrate-nitrogen concentrations commonly occur when total organic carbon (TOC) and dissolved oxygen (DO) are also low, and high nitrogen concentrations correspond to high DO and TOC, indicating that denitrification is the primary biogeochemical process controlling nitrogen removal in natural rivers. The new approach is demonstrated through the computation of nitrogen removal in the Amite River, LA, USA. Functional relationships between the nitrate-nitrogen removal rate and water temperature are established for the Amite River. Monthly mean nitrate-nitrogen concentrations along the river are computed using the extended VART model, and computed nitrogen concentrations fit observed ones very well. The estimated annual nitrate-nitrogen removal in the Amite River is 27.4 tons or 15.5% of total nitrate-nitrogen transported annually through the Amite River.

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References

  • Alexander, R. B., Smith, R. A., & Schwarz, G. E. (2000). Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico. Nature, 403, 758–761.

    Article  CAS  Google Scholar 

  • Basnyat, P., Teeter, L., Flynn, K. M., & Lockaby, B. G. (1999). Relationship between landscape characteristics and nonpoint source pollution inputs to coastal estuaries. Environmental Management, 23, 539–549.

    Article  Google Scholar 

  • Bicknell, B. R., Imhoff, J. C., Kittle, J. L., Jr., Donigan, A. S., Jr., & Johanson, R. C. (1997). Hydrological simulation program Fortran: User’s manual for version 11. US Environmental Protection Agency, EPA/600/R-97/080 (p. 755). Athens: National Exposure Research Laboratory.

    Google Scholar 

  • Chapra, S. C. (1997). Surface water-quality modeling. New York: McGraw-Hill. 426 pp.

    Google Scholar 

  • DeAngelis, D. L., Loreau, M., Neergaard, D., Mulholland, P. J., & Marzolf, E. R. (1995). Modelling nutrient–periphyton dynamics in streams: The importance of transient storage zones. Ecological Modeling, 80, 149–160.

    Article  Google Scholar 

  • Deng, Z. Q., Bengtsson, L., & Singh, V. P. (2006). Parameter estimation for fractional dispersion model for rivers. Environmental Fluid Mechanics, 6(5), 451–475.

    Article  Google Scholar 

  • Deng, Z. Q., & Jung, H. S. (2009a). Scaling dispersion model for pollutant transport in rivers. Environmental Modelling & Software, 24(5), 627–663.

    Article  Google Scholar 

  • Deng, Z. Q., & Jung, H. S. (2009b). Variable residence time based model for solute transport in streams. Water Resources Research, 45, W03415. doi:10.1029/2008WR007000.

    Article  Google Scholar 

  • Deng, Z. Q., Singh, V. P., & Bengtsson, L. (2004). Numerical solution of fractional advection–dispersion equation. Journal of Hydraulic Engineering ASCE, 130(5), 422–431.

    Article  Google Scholar 

  • Dent, C. L., & Henry, J. C. (1999). Modelling nutrient–periphyton dynamics in streams with surface–subsurface exchange. Ecological Modelling, 122, 97–116.

    Article  CAS  Google Scholar 

  • Dingman, S. L. (1994). Physical hydrology. Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Donigian, A. S., Davis, H. H. (1978). User’s manual for agricultural runoff management (ARM) model. US Environmental Protection Agency, EPA/622/3-78-080.

  • Goolsby, D. A., Battaglin, W. A. (1995). Effects of episodic events on the transport of nutrients to the Gulf of Mexico. In: Proceedings of First Gulf of Mexico Hypoxia Management Conference, Dec. 5–6, Kenner, LA, USA.

  • Justic, D., Rabalais, N. N., & Turner, R. (1994). River borne nutrients, hypoxia and coastal ecosystem evolution: Biological responses to long-term changes in nutrient loads carried by the Po and the Mississippi Rivers. In K. R. Dyer & R. J. Orth (Eds.), Changes in fluxes in estuaries: Implications from science to management (pp. 161–167). Fredensborg: ECSA22/ERF Symposium Olsen & Olsen.

    Google Scholar 

  • Lane, R. R., Mashriqui, H. S., Kemp, G. P., Day, J. W., Day, J. N., & Hamilton, A. (2003). Potential nitrate removal from a river diversion into a Mississippi delta forested wetland. Ecological Engineering, 20(3), 237–249.

    Article  Google Scholar 

  • Mishra, P. K., & Deng, Z. Q. (2009). Sediment TMDL development for the Amite River. Water Resources Management, 23(5), 839–852.

    Article  Google Scholar 

  • Mulholland, P. J., Helton, A. M., Poole, G. C., Hall, R. O., Hamilton, S. K., Peterson, B. J., et al. (2008). Stream denitrification across biomes and its response to anthropogenic nitrate loading. Nature, 452, 202–205.

    Article  CAS  Google Scholar 

  • Nordin, C. F., Sabol, G. V. (1974). Empirical data on longitudinal dispersion in rivers. Water Resources Investigations 20-74, US Geological Survey.

  • Peterson, B. J., Wollheim, W. M., Mulholland, P. J., Webster, J. R., Meyer, J. L., Tank, J. L., et al. (2001). Control of nitrogen export from watersheds by headwater streams. Science, 292, 86–90.

    Article  CAS  Google Scholar 

  • US EPA (Environmental Protection Agency) (2000). BASINS technical note 6: Estimating hydrology and hydraulic parameters for HSPF (EPA 823-R-00-012).

  • US EPA (Environmental Protection Agency) (2001). Better Assessment Science Integrating Point and Nonpoint Sources, BASINS (version 3.0.), EPA 823-B-01-001.

  • Rabalais, N. N., Turner, R. E., & Scavia, D. (2002). Beyond science into policy: Gulf of Mexico hypoxia and the Mississippi River. BioSciene, 52(2), 129–142.

    Article  Google Scholar 

  • Seitzinger, S. P., Styles, R. V., Boyer, E. W., Alexander, R. B., Billen, G., Howarth, R. W., et al. (2002). Nitrogen retention in rivers: Model development and application to watersheds in the northeastern USA. Biogeochemistry, 57(58), 199–237.

    Article  Google Scholar 

  • Sheibley, R. W., Jackman, A. P., Duff, J. H., & Triska, F. J. (2003). Numerical modeling of coupled nitrification–denitrification in sediment perfusion cores from the hyporheic zone of the Shingobee River, MN. Advances in Water Resources, 26, 977–987.

    Article  CAS  Google Scholar 

  • Stream Solute Workshop. (1990). Concepts and methods for assessing solute dynamics in stream ecosystems. Journal of the North American Benthological Society, 9(2), 95–119.

    Article  Google Scholar 

  • Tang, Z., Engel, B. A., Pijanowski, B. C., & Lim, K. J. (2005). Forecasting land use change and its environmental impact at a watershed scale. Journal of Environmental Management, 76, 35–45.

    Article  CAS  Google Scholar 

  • Thomas, S. A., Valett, H. M., Webster, J. R., & Mulholland, P. J. (2003). A regression approach to estimating reactive solute uptake in advective and transient storage zones of stream ecosystems. Advances in Water Resources, 26, 965–976.

    Article  CAS  Google Scholar 

  • Turner, R. E., & Rabalais, N. N. (1991). Changes in Mississippi River water quality this century. Implications for coastal food webs. Bioscience, 41, 140–147.

    Article  Google Scholar 

  • Webster, J. R., Mulholland, P. J., Tank, J. L., Valett, H. M., Dodds, W. K., Peterson, B. J., Bowden, W. B., Dahm, C. N., Findlay, S., Gregory, S. V., Grimm, N. B., Hamilton, S. K., Johnson, S. L., Marti, E., McDowell, W. H., Meyer, J. L., Morrall, D. D., Thomas, S. A., & Wollheim, W. M. (2003). Factors affecting ammonium uptake in streams – an inter-biome perspective. Freshwater Biology, 48, 1329–1352.

    Article  CAS  Google Scholar 

  • Whittemoore, R. C., & Beebe, J. (2000). EPA’s basins model: Good science or serendipitous modeling. Journal of the American Water Resources Association, 36, 493–499.

    Article  Google Scholar 

  • Xu, Y. J. (2006). Organic nitrogen retention in the Atchafalaya River Swamp. Hydrobiologia, 560, 133–143.

    Article  CAS  Google Scholar 

Download references

Acknowledgment

Support for this research by the USGS and Louisiana Water Resources Research Institute and LaSPACE is gratefully acknowledged.

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  1. Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803-6405, USA

    Hoon-Shin Jung & Zhi-Qiang Deng

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  1. Hoon-Shin Jung
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  2. Zhi-Qiang Deng
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Correspondence to Zhi-Qiang Deng.

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Jung, HS., Deng, ZQ. Modeling of Nitrogen Retention in Amite River. Water Air Soil Pollut 215, 411–425 (2011). https://doi.org/10.1007/s11270-010-0487-9

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  • DOI: https://doi.org/10.1007/s11270-010-0487-9

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