Environmental Modeling & Assessment

, Volume 16, Issue 2, pp 183–204 | Cite as

A Review of Public Domain Water Quality Models for Simulating Dissolved Oxygen in Rivers and Streams

  • Prakash R. Kannel
  • Sushil R. Kanel
  • Seockheon Lee
  • Young-Soo Lee
  • Thian Y. Gan
Article

Abstract

The review discusses six major public domain water quality models currently available for rivers and streams. These major models, which differ greatly in terms of processes they represent, data inputs requirements, assumptions, modeling capability, their strengths and weaknesses, could yield useful results if appropriately selected for the desired purposes. The public domain models, which are most suitable for simulating dissolved oxygen along rivers and streams, chosen in this review are simulation catchment (SIMCAT), temporal overall model for catchments (TOMCAT), QUAL2Kw, QUAL2EU, water quality analysis simulation program (WASP7), and quality simulation along rivers (QUASAR). Each of these models is described based on a consistent set of criteria-conceptualization, processes, input data, model capability, limitations, model strengths, and its application. The results revealed that SIMCAT and TOMCAT are over-simplistic but useful to quickly assess impact of point sources. The QUAL2Kw has provision for conversion of algal death to carbonaceous biochemical oxygen demand (CBOD) and thus more appropriate than QUAL2EU, where macrophytes play an important interaction. The extensive requirement of data in WASP7 and QUASAR is difficult to justify the time and costs required to set up these complex models. Thus, a single model could not serve all wide range of functionalities required. The choice of a model depends upon availability of time, financial cost and a specific application. This review may help to choose appropriate model for a particular water quality problem.

Keywords

Water quality models Dissolved oxygen SIMCAT TOMCAT QUAL2Kw QUAL2EU WASP7 QUASAR 

References

  1. 1.
    Agoshkov, V. I. (2002) Mathematical Models of Life Support Systems. In V. I. Agoshkov (Ed.), Knowledge for Sustainable Development, An Insight into the Encyclopaedia of Life Support Systems (pp 335-281) Vol. 1 UNESCO/EOLSS.Google Scholar
  2. 2.
    USEPA (2009) Water quality models and tools. In United States Environmental Protection Agency (USEPA) [online] http://www.epa.gov/waterscience/models/ accessed 25 November 2009
  3. 3.
    Chapra, S. C. (1997) Surface water- quality modeling. McGraw-Hill International Edition p 844.Google Scholar
  4. 4.
    Cox, B. A. (2003). A review of currently available in-stream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers. The Science of the Total Environment, 314, 335–377.CrossRefGoogle Scholar
  5. 5.
    Reckhow, K. H. (1994). Water-quality simulation modeling and uncertainty analysis for risk assessment and decision-making. Ecological Modelling, 72(1–2), 1–20.CrossRefGoogle Scholar
  6. 6.
    Warn, A. E. (1987). SIMCAT—a catchment simulation model for planning investment for river quality (pp. 211–218). Oxford: IAWPRC, Pergamon.Google Scholar
  7. 7.
    Crabtree, B., Seward, A. J., & Thompson, L. (2006). A case study of regional catchment water quality modelling to identify pollution control requirements. Water Science and Technology, 53(10), 47–54.CrossRefGoogle Scholar
  8. 8.
    Elmore, H. L., & Hayes, T. W. (1960). Solubility of atmospheric oxygen in water, Twenty-ninth progress report of the committee on sanitary engineering research. Journal of the Sanitary Engineering Division, ASCE, 86(SA4), 41–53.Google Scholar
  9. 9.
    Crabtree, B., Hickman, M., & Martin, D. (1999). Integrated water quality and environmental cost-benefit modelling for the management of the River Tame. Water Science and Technology, 39(4), 213–220.CrossRefGoogle Scholar
  10. 10.
    Bowden, K., & Brown, S. R. (1984). Relating effluent control parameters to river quality objectives using a generalized catchment simulation model. Water Science and Technology, 16(5–7), 197–206.Google Scholar
  11. 11.
    Keller, V. (2005). Risk assessment of “down-the-drain” chemicals: Search for a suitable model. The Science of the Total Environment, 360(1–3), 305–318.Google Scholar
  12. 12.
    Kinniburgh, J. H., Tinsley, M. R., & Bennett, J. (1997). Orthophosphate concentrations in the River Thames. Journal of the Chartered Institution of Water and Environmental Management, 11(3), 178–185.CrossRefGoogle Scholar
  13. 13.
    Brown, L. C. & Barnwell, T. O. (1987) The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: documentation and user manual (p 204). Env. Res. Lab. USEPA, EPA/600/3-87/007, Athens, GA.Google Scholar
  14. 14.
    Rauch, W., Henze, M., Koncsos, L., Reichert, P., Shanahan, P., Somlyody, L., et al. (1998). River water quality modelling: I. State of the art. Water Science and Technology, 38(11), 237–244.CrossRefGoogle Scholar
  15. 15.
    Streeter, W. H. & Phelps, E. B. (1925) A study of the pollution and natural purification of the Ohio River. Public Health Service: Washington DC, USA Public Health Bulletin 146.Google Scholar
  16. 16.
    Orlob, G. T. e. (1982) In Mathematical modelling of water quality: Streams, Lakes and Reservoirs (p 542) 1982; Wiley, Chichester.Google Scholar
  17. 17.
    Walton, R., & Webb, M. (1994). Qual2e simulations of pulse loads. Journal of Environmental Engineering-Asce, 120(5), 1017–1031.CrossRefGoogle Scholar
  18. 18.
    USEPA (1995) QUAL2E Windows interface user's guide. United States Environmental Protection Agency, EPA/823/B/95/003 p 66.Google Scholar
  19. 19.
    Ambrose, R. B., Wool, T. A., Connolly, J. P., & Shanz, R. W. (1987). WASP5, a hydrodynamic and water quality model. Athens: U.S. Environ. Protection Agency. EPA/600/3-87/039.Google Scholar
  20. 20.
    Park, S. S., & Uchrin, C. G. (1997). A stoichiometric model for water quality interactions in macrophyte dominated water bodies. Ecological Modelling, 96(1–3), 165–174.CrossRefGoogle Scholar
  21. 21.
    Park, S. S., & Lee, Y. S. (2002). A water quality modeling study of the Nakdong River, Korea. Ecological Modelling, 152(1), 65–75.CrossRefGoogle Scholar
  22. 22.
    Barnwell, T. O., Brown, L. C., & Whittemore, R. C. (2004). Importance of field data in stream water quality modeling using QUAL2E-UNCAS. Journal of Environmental Engineering-Asce, 130(6), 643–647.CrossRefGoogle Scholar
  23. 23.
    Cubillo, F., Rodriguez, B., & Barnwell, T. O. (1992). A system for control of river water-quality for the community of Madrid using Qual2e. Water Science and Technology, 26(7–8), 1867–1873.Google Scholar
  24. 24.
    Ning, S. K., Chang, N. B., Yang, L., Chen, H. W., & Hsu, H. Y. (2001). Assessing pollution prevention program by QUAL2E simulation analysis for the Kao-Ping River Basin, Taiwan. Journal of Environmental Management, 61(1), 61–76.CrossRefGoogle Scholar
  25. 25.
    Chaudhury, R. R., Sobrinho, J. A. H., Wright, R. M., & Sreenivas, M. (1998). Dissolved oxygen modeling of the Blackstone River (Northeastern United States). Water Research, 32(8), 2400–2412.CrossRefGoogle Scholar
  26. 26.
    Pelletier, G. J., & Chapra, S. C. (2005). QUAL2Kw theory and documentation (version 5.1), a modeling framework for simulating river and stream water quality. Washington: Department of ecology.Google Scholar
  27. 27.
    Chapra, S. C., & Pelletier, G. J. (2003). QUAL2K: A modeling framework for simulating river and stream water quality (beta version): documentation and users manual. Civil and Environmental Engineering Department. Medford: Tufts University.Google Scholar
  28. 28.
    Pelletier, G. J., Chapra, S. C., & Tao, H. (2006). QUAL2Kw—a framework for modeling water quality in streams and rivers using a genetic algorithm for calibration. Environmental Modelling and Software, 21(3), 419–425.CrossRefGoogle Scholar
  29. 29.
    Kannel, P. R., Lee, S., Lee, Y. S., Kanel, S. R., & Pelletier, G. J. (2007). Application of automated QUAL2Kw for water quality modeling and management in the Bagmati River, Nepal. Ecological Modelling, 202(3–4), 503–517.CrossRefGoogle Scholar
  30. 30.
    Cristea, N. & Pelletier, G. (2005) Wenatchee River temperature Total Maximum Daily Load study. In Washington State Department of Ecology, Olympia, WA.Google Scholar
  31. 31.
    Turner, D. F., Pelletier, G. J., & Kasper, B. (2009). Dissolved oxygen and pH modeling of a periphyton dominated, nutrient enriched river. Journal of Environmental Engineering, 135(8), 645–652.CrossRefGoogle Scholar
  32. 32.
    Ambrose, R. B., & Wool, T. A. (2009). WASP7 stream transport model theory and user’s guide. Athens: U.S. Environmental Protection Agency. EPA/600/R-09/100.Google Scholar
  33. 33.
    Wool, T. A., Ambrose, R. B., Martin, J. L., & Comer, E. A. (2001). Water quality analysis simulation program (WASP) Version 6.0: User’s Manual. Athens: U.S. Environmental Protection Agency.Google Scholar
  34. 34.
    Ditoro, D. M., Fitzpatrick, J. J., & Thomann, R. V. (1983). Documentation for water analysis simulation program (WASP) and model verification program (MVP). Westwood: Hydroscience. USEPA Contract No. 68-01-3872.Google Scholar
  35. 35.
    Ambrose, R. B., Wool, T. A., & Connolly, J. P. (1988). WASP, version 4, a hydrodynamic and water quality model—model theory, user's manual, and programmer's guide. Athens: U.S. Environmental Protection Agency.Google Scholar
  36. 36.
    Ambrose, R. B., Martin, J. L., & TA, Wool. (2006). WASP7 benthic algae—model theory and user's guide. Washington: U.S. Environmental Protection Agency. EPA/600/R-06/106 (NTIS PB2007-100139).Google Scholar
  37. 37.
    Nikolaidis, N. P., Karageorgis, A. P., Kapsimalis, V., Marconis, G., Drakopoulou, P., Kontoyiannis, H., et al. (2006). Circulation and nutrient modeling of Thermaikos Gulf, Greece. Journal of Marine Systems, 60(1–2), 51–62.CrossRefGoogle Scholar
  38. 38.
    Ambrose, R. B., Wool, T. A., & Martin, J. L. (1993). The water quality simulation program (WASP), version 5, Part A, Model documentation. Athens: Environmental Research Lab, U. E. P. A.Google Scholar
  39. 39.
    Rygwelski, K. R., Richardson, W. L., & Endicott, D. D. (1999). A screening-level model evaluation of atrazine in the Lake Michigan basin. Journal of Great Lakes Research, 25(1), 94–106.CrossRefGoogle Scholar
  40. 40.
    Stansbury, J., & Admiraal, D. M. (2004). Modeling to evaluate macrophyte induced impacts to dissolved oxygen in a tailwater reservoir. Journal of the American Water Resources Association, 40(6), 1483–1497.CrossRefGoogle Scholar
  41. 41.
    Whitehead, P., Beck, B., & Oconnell, E. (1981). A systems-model of streamflow and water-quality in the Bedford Ouse river system. 2. Water-Quality Modeling. Water Research, 15(10), 1157–1171.CrossRefGoogle Scholar
  42. 42.
    Whitehead, P. G., Caddy, D. E., & Templeman, R. F. (1984). An online monitoring, data management and forecasting system for the Bedford Ouse River Basin. Water Science and Technology, 16(5–7), 295–314.Google Scholar
  43. 43.
    Whitehead, P., & Young, P. (1979). Water-quality in river systems—Monte-Carlo analysis. Water Resources Research, 15(2), 451–459.CrossRefGoogle Scholar
  44. 44.
    Ferrier, R. C., Whitehead, P. G., Sefton, C., Edwards, A. C., & Pugh, K. (1995). Modeling impacts of land-use change and climate-change on nitrate-nitrogen in the River Don, North-East Scotland. Water Research, 29(8), 1950–1956.CrossRefGoogle Scholar
  45. 45.
    Whitehead, P. G., Williams, R. J., & Lewis, D. R. (1997). Quality simulation along river systems (QUASAR): Model theory and development. The Science of the Total Environment, 194, 447–456.CrossRefGoogle Scholar
  46. 46.
    Whitehead, P. G., Mccartney, M. P., Williams, R. J., Ishemo, C. A. L., & Thomas, R. (1995). A method to simulate the impact of acid-mine drainage on River systems. Journal of the Chartered Institution of Water and Environmental Management, 9(2), 119–131.Google Scholar
  47. 47.
    Whitehead, P. G. & Williams, R. J. (1982) In A dynamic nitrate balance model for Fiver basins, IAHS Exeter Conference Proceedings IAHS Publication.Google Scholar
  48. 48.
    Lewis, D. R., Williams, R. J., & Whitehead, P. G. (1997). Quality simulation along rivers (QUASAR): An application to the Yorkshire Ouse. The Science of the Total Environment, 194, 399–418.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Prakash R. Kannel
    • 1
    • 2
  • Sushil R. Kanel
    • 3
  • Seockheon Lee
    • 4
  • Young-Soo Lee
    • 5
  • Thian Y. Gan
    • 1
  1. 1.Department of Civil and Environmental EngineeringUniversity of AlbertaEdmontonCanada
  2. 2.Department of Irrigation, Ministry of IrrigationKathmanduNepal
  3. 3.Pegasus Technical Services, Inc.CincinnatiUSA
  4. 4.Water Environment & Remediation Research CentreKorea Institute of Science and TechnologySeoulSouth Korea
  5. 5.Department of Environmental EngineeringKwangwoon UniversitySeoulSouth Korea

Personalised recommendations