Environmental Engineering Research

Korean Society of Environmental Engineers (대한환경공학회)
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Analysis of optimum grid determination of water quality model with 3-D hydrodynamic model using environmental fluid dynamics code (EFDC)

  • Yin, Zhenhao (Analytical and Testing Center, Yanbian University) ;
  • Seo, Dongil (Department of Environmental Engineering, Chungnam National University)
  • Received : 2015.11.24
  • Accepted : 2016.02.28
  • Published : 2016.06.30
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Abstract

This study analyzes guidelines to select optimum number of grids to represent behavior of a given water system appropriately. The EFDC model was chosen as a 3-D hydrodynamic and water quality model and salt was chosen as a surrogate variable of pollutant. The model is applied to an artificial canal that receives salt water from coastal area and fresh water from a river from respective gate according to previously developed gate operation rule. Grids are subdivided in vertical and horizontal (longitudinal) directions, respectively until no significant changes are found in salinity concentrations. The optimum grid size was determined by comparing errors in average salt concentrations between a test grid systems against the most complicated grid system. MSE (mean squared error) and MAE (mean absolute error) are used to compare errors. The CFL (Courant-Friedrichs-Lewy) number was used to determine the optimum number of grid systems for the study site though it can be used when explicit numerical method is applied only. This study suggests errors seem acceptable when both MSE and MAE are less than unity approximately.

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References

  1. Canale RP, Seo D. Performance, reliability and uncertainty of total phosphorus models for lakes 2. Stochastic analyses. Water Res. 1996;30:95-102. https://doi.org/10.1016/0043-1354(95)00115-2
  2. Chapra SC. Surface water-quality modeling. New York: McGraw-Hill; 1997.
  3. Kim SJ, Seo D, Ahn KH. Estimation of Proper EFDC Parameters to Improve the Reproductability of Thermal Stratification in Korea Reservoir (in Korean). J. Korean. Water Resour. Assoc. 2011;44:741-752. https://doi.org/10.3741/JKWRA.2011.44.9.741
  4. Seo D, Kim MA, Ahn JH. Prediction of Chlorophyll-a changes due to weir constructions in the Nakdong River using EFDC-WASP modelling. Environ. Eng. Res. 2012;17:95-102. https://doi.org/10.4491/eer.2012.17.2.095
  5. Hamrick JM. A Three-Dimensional Environmental Fluid Dynamics Computer Code; Theoretical and Computational Aspects The College of William and Mary, Virginia Institute of Marine Science Special Report. Rep. Va. Inst. Mar. Sci. 1992.
  6. Wool TA, Ambrose RB, Martin JL, Comer EA. The Water Quality Analysis Simulation Program, WASP6. Part A: Model Documentation. Athens: Center for Exposure Assessment Modelling. US EPA. 2001.
  7. Wool TA, Davie SR, Rodriguez HN. Development of three-dimensional hydrodynamic and water quality models to support total maximum daily load decision process for the Neuse River Estuary, North Carolina. J. Water Resour. Plann. Manage. 2003;129:295-306. https://doi.org/10.1061/(ASCE)0733-9496(2003)129:4(295)
  8. Jeon JH, Chung SW. A Sensitivity Analysis on Numerical Grid Size of a Three-Dimensional Hydrodynamic and Water Quality Model (EFDC) for the Saemangeum Reservoir (in Korean). J. Korean Soc. Water Environ. 2012;28:26-37.
  9. Kim SJ, Seo D, Ahn KH. Estimation of Proper EFDC Parameters to Improve the Reproductability of Thermal Stratification in Korea Reservoir (in Korean). J. Korea. Water Resour. Assoc. 2011;44:741-752. https://doi.org/10.3741/JKWRA.2011.44.9.741
  10. Miyakoda K, Strickler RF, Nappo CJ, Baker PL, Hembree GD. The Effect of horizontal Grid Resolution in an Atmospheric Circulation Model. J. Atmos. Sci. 1971;28:481-499. https://doi.org/10.1175/1520-0469(1971)028<0481:TEOHGR>2.0.CO;2
  11. Molnar DK, Julien PY. Grid-Size Effects on Surface Runoff Modeling. J. Hydrol. Eng. 2000;5:8-16. https://doi.org/10.1061/(ASCE)1084-0699(2000)5:1(8)
  12. Pathapati SS, Sansalone JJ. CFD Modeling of a Storm-Water Hydrodynamic Separator. Environ. Eng. Res. 2009;135:191-202. https://doi.org/10.1061/(ASCE)0733-9372(2009)135:4(191)
  13. Rengstorfa AM, Mohnb C, Brownc C, Wiszd MS, Grehan AJ. Predicting the distribution of deep-sea vulnerable marine ecosystems using high-resolution data: Considerations and novel approaches. Deep Sea Research Part I: Oceanographic Research Papers. 2014;93:72-82. https://doi.org/10.1016/j.dsr.2014.07.007
  14. Seo D, Sigdel R, Kwon KH, Lee YS. 3-D Hydrodynamic Modelling of Yongdam Lake, Korea using EFDC. Desalin. Water Treat. 2010;19:42-48. https://doi.org/10.5004/dwt.2010.1894
  15. Chang CL, Chao YC. Effects of spatial data resolution on runoff predictions by the BASINS model. Int. J. Environ. Sci. Technol. 2014;11:1563-1570. https://doi.org/10.1007/s13762-013-0342-9
  16. Eguen M, Aguilar C, Herrero J, Millares A, Polo MJ. On the influence of cell size in physically-based distributed hydrological modelling to assess extreme values in water resource planning. Nat. Hazard. Earth. Sys. 2012;12:1573-1582. https://doi.org/10.5194/nhess-12-1573-2012
  17. Vieux BE, Needham S. Nonpoint-Pollution Model Sensitivity to Grid-Cell Size. J. Water Resour. Plann. Manage. 1993;119:141-157. https://doi.org/10.1061/(ASCE)0733-9496(1993)119:2(141)
  18. K-Water. Gyung-In Canal Project (Navigation Part), Environmental Impact Assessment Report II (in Korean). K-Water, Korea Water Resour. Corporation; 2009.
  19. Seo D, Kim MA. Application of EFDC and WASP7 in Series for Water Quality Modelling of the Yongdam Lake, Korea. J. Korea. Water Resour. Assoc. 2011;44:439-447. https://doi.org/10.3741/JKWRA.2011.44.6.439
  20. Aquaveo. SMS 12.1 - The Complete Surface-water Solution [Internet]. Aquaveo. Available from: http://www.aquaveo.com/software/sms-surface-water-modeling-system-introduction.
  21. Jung ST, Noh JW, Huh YT. Analysis of Saltwater Intrusion Using 2-D & 3-D Numerical Model in the Seomjin River Estuary. The Annual Conference of Korea Water Resources Association; 21 May 2009. p. 785-790.
  22. Noh JW, Lee JY, Shin JK. Analysis of Saltwater Intrusion by Flushing Discharge in the Seomjin River Estuary (in Korean). J. Environ. Impact. Assess. 2011;20:325-335.
  23. Hamrick JM. User's manual for the environmental fluid dynamics computer code, Special report in applied marine science and ocean engineering. College of William and Mary, Virginia Institute of Marine Science. 1996. p. 336.
  24. US Army Corps of Engineers. HEC-RAS River Analysis System, Hydraulic Reference Manual, Version 4.1. Hydraulic Engineering Center; 2011.
  25. Courant R, Friedrichs K, Lewy H. On the partial difference equations of mathematical physics. IBM. J. Res. Dev. 1967;11: 215-234. https://doi.org/10.1147/rd.112.0215
  26. Wikipedia. Courant-Friedrichs-Lewy condition [Internet]. Wikipedia. Available from: https://en.wikipedia.org/wiki/Courant%E2%80%93Friedrichs-%E2%80%93Lewy_condition.
  27. Hamrick JM. Linking Hydrodynamic and Biogeochemical Transport Models for Estuarine and Coastal Waters. Estuarine and Coastal modelling. In: The 3rd International Conference of American Society of Civil Engineers; 1994; New York. p. 591-608.
  28. Johnson BH, Kim KW, Health RE, Hsieh BB, Butler HL. Validation of Three Dimensional Hydrodynamic Model of Chesapeake Bay. J. Hydraulic. Engineering. 1993;119:2-20. https://doi.org/10.1061/(ASCE)0733-9429(1993)119:1(2)
  29. Kim JK, Kwak GI, Jeong JH, Three-Dimensional Mixing Characteristics in Seomjin River Estuary. J. Korean Soc. Mar. Environ. Eng. 2008;11:164-174.
  30. Seo D, Yu H. Error Analysis of a Steady State Water Quality Model, QUAL2E using a Combination of EFDC-hydro and WASP7.2. In IWA World Water Congress and Exhibition; 2008; Vienna.
  31. Seo D, Kwon KH, Park BJ, Sigdel R. Water Quality Modeling of Yongdam Lake Using EFDC 3-D Hydrodynamics Model and WASP7.3 Water Quality Model. In WCWF; 2009; Incheon.
  32. Seo D, Seo MJ, Goo MS, Yoo JK. Serial Use of Hydrodynamic and Water Quality Model of the Geum River using EFDC-Hydro and WASP7.2. J. Korean Soc. Water Waste. Water. 2009;23:15-22.

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