Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of longitudinal / transverse dispersion coefficients and prediction of concentration at river confluence in two-dimensional solute transport analysis

2차원 혼합 해석시 합류부에서 종/횡분산계수 산정 및 농도예측 기여도 평가

  • Baek, Kyong Oh (Hankyong National University, Department of Civil and Environmental Engineering) ;
  • Lee, Dong Yeol (Hankyong National University, Department of Civil and Environmental Engineering) ;
  • Seo, Il Won (Seoul National University, Department of Civil and Environmental Engineering)
  • 백경오 (국립한경대학교 건설환경공학부) ;
  • 이동열 (국립한경대학교 건설환경공학부) ;
  • 서일원 (서울대학교 건설환경공학부)
  • Received : 2020.12.29
  • Accepted : 2021.03.05
  • Published : 2021.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

Mixing characteristics of the longitudinal/transverse directions is inevitably different in rivers with a large aspect ratio. Particularly complex mixing behavior occurs in the area of the confluence where tributaries and main streams of different concentrations meet, and it is necessary to accurately implement such mixing characteristics by assigning appropriate values of longitudinal and transverse dispersion coefficients. In this study, the mixing behavior according to the different values in the longitudinal/transverse dispersion coefficient was analyzed by using the two-dimensional model (RAMS) at the confluence where three rivers (the Nakdong River, the Geumho River, and the Jincheon Creek) meet. Firstly the longitudinal and transverse dispersion coefficients were calibrated and validated based on the electrical conductivity (EC) acquired from field measurements. Through the calibration and validation, it was shown that the longitudinal dispersion coefficient was about 25 times larger than the transverse dispersion coefficient in this area. Then assuming that a hazardous substance (phenol) was introduced into the upper boundaries of the Geumho River and the Jincheon Creek due to an accidental spill, the concentration of phenol arrived at the water intake facilities was calculated by using the calibrated numerical model. As a result, characteristics such as time and peak concentration of hazardous substances reaching the water intake facilities were very different according to the ratio of the longitudinal/transverse dispersion coefficient values. In fact, this is an example that the selection of the dispersion coefficients can affect decision-making such as stopping water intake during an appropriate time at the facilities, when if phenol is introduced into a river. In the end, when using a two-dimensional mixing model in a river, it was confirmed that the provision of an appropriate value of the longitudinal/transverse dispersion coefficient was an important factor.

평면 2차원 혼합 해석시 연안이나 호소의 경우 수평방향 분산이 균일하다고 볼 수 있지만, 종/횡의 비율이 세장(細長)한 하천의 경우 종/횡 방향의 혼합 특성은 상이할 수 밖에 없다. 특히 농도가 서로 다른 지류와 본류가 만나는 합류부 일대는 복잡한 혼합 양상이 발생하므로, 수치모형을 활용할 경우 종분산과 횡분산계수를 분리하여 각각 적절한 값을 부여함으로써 재현성을 높일 수 있다. 본 연구에서는 기저농도가 서로 다른 세 하천(낙동강, 금호강, 진천천)이 만나는 낙동강 강정고령보 ~ 달성보 일대를 대상 구간으로 삼아, 2차원 하천해석 소프트웨어인 RAMS를 활용하여 종/횡분산계수 값의 차이에 따른 2차원적 혼합특성을 분석해 보았다. 이를 위해 먼저 실측을 통해 취득한 전기전도도(EC) 자료를 기반으로 종분산 및 횡분산계수를 각각 검/보정하였다. 검보정 결과 이 구간에서는 종분산계수가 횡분산계수에 비해 약 25배 크다는 것을 확인하였다. 다음으로 금호강 및 진천천 상류단에 수질사고로 유해물질(페놀)이 유입되었을 경우를 가정하여 매개변수(분산계수)가 검/보정된 모형(종/횡분산계수를 25배 비율로 부여)으로 하류 양수장(우암/월성 양수장)에 도달하는 유해물질의 농도를 예측해 보았다. 또한 분산계수가 검보정되지 않은 모형(종/횡분산계수를 동일한 값으로 부여)으로 유해물질의 양수장 도달 농도를 계산하였다. 그 결과 종/횡분산계수값의 비율에 따라 유해물질이 양수장에 도달하는 시간, 도달된 물질의 첨두농도 등이 매우 다르게 나타났다. 이는 실제로 페놀이 유입된다면 취/양수장 등에서 적정시간 취수중단 등의 조치를 취해야 하는데, 해석모형의 분산계수가 의사결정에 큰 영향을 미칠 수 있음을 보여준 사례라 할 수 있다. 향후 수질사고 예측/대응 시스템을 구축하는 경우, 계산엔진으로 활용되는 모형의 분산계수 결정에 유의해야 함을 환기시킨다.

Keywords

Acknowledgement

본 연구는 환경부 화학사고 대응 환경기술개발사업(2018001960001)의 연구비 지원에 의하여 연구되었으며 이에 감사드립니다. 본 연구는 서울대학교 공학연구원 및 건설환경종합연구소의 지원 아래 수행되었습니다.

References

  1. Ahmadi, M., Jaafarzadeh, N., Rahmat, Z.G., Babaei, A.A., Alavi, N., Baboli, Z., and Niri, M.V. (2017). "Kinetic studies on the removal of phenol by MBBR from saline wastewater." Journal of Environmental Health Science & Engineering, Vol. 15, No. 22. doi: 10.1186/s40201-017-0284-0
  2. Baek, K.O. (2018). "Flowchart on choosing optimal method of observing transverse dispersion coefficient for solute transport in open channel flow." Sustainability, Vol. 10, 1332. doi: 10.3390/su10051332
  3. Baek, K.O., and Seo, I.W. (2010). "Routing procedures for observed dispersion coefficients in two-dimensional river mixing." Advances in Water Resources, Vol. 33, pp. 1551-1559. https://doi.org/10.1016/j.advwatres.2010.09.005
  4. Baek, K.O., and Seo, I.W. (2016). "On the methods for determining the transverse dispersion coefficient in river mixing." Advances in Water Resources, Vol. 90, pp. 1-9. https://doi.org/10.1016/j.advwatres.2016.01.009
  5. Baek, K.O., and Seo, I.W. (2017). "Estimation of transverse dispersion coefficient for two-dimensional models of mixing in natural streams." Journal of Hydro-environment Research, Vol. 15, pp. 67-74. https://doi.org/10.1016/j.jher.2017.01.003
  6. Elder, J.W. (1959). "The dispersion of marked fluid in turbulent shear flow." Journal of Fluid Mechanics, Vol. 5, pp. 544-560. https://doi.org/10.1017/S0022112059000374
  7. Fischer, H.B., List, E.J., Koh, R.C.Y., Imberger, J., and Brooks, N.H. (1979). Mixing in inland and coastal waters. Academic press, New York, U.S.
  8. Han, E.J., Kim, Y.D., Baek, K.O., and Seo, I.W. (2019). "Relation between transverse dispersion and diffusion at meandering channel in two-dimensional mixing based on tracer tests." Environmental Earth Sciences, Vol. 78, No. 24. doi: 10.1007/s12665-019-8710-5.
  9. Jung, S.H., Seo, I.W., Kim, Y.D., and Park, I. (2019). "Feasibility of velocity-based method for transverse mixing coefficients in river mixing analysis." Journal of Hydraulic Engineering, ASCE, Vol. 145, No. 11, 04019040. https://doi.org/10.1061/(asce)hy.1943-7900.0001638
  10. Ministry of Environment (ME) (2020). Enforcement decree of the framework act on environmental policy. President Executive Directive, No. 30674.
  11. Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., and Veith T.L. (2007). "Model evaluation guidelines for systematic quantification of accuracy in watershed simulation." Transaction of the ASABE, Vol. 50, No. 3, pp. 885-900. https://doi.org/10.13031/2013.23153
  12. National Institute of Environmental Research (NIER) (2015). Development and application of validation technique for advection-diffusion of dissolved pollutants using tracer experiments (II).
  13. Piasecki, M., and Katopodes, N.D. (1999). "Identification of stream dispersion coefficients by adjoint sensitivity method." Journal of Hydraulic Engineering, ASCE, Vol. 125, No. 7, pp. 714-724. https://doi.org/10.1061/(ASCE)0733-9429(1999)125:7(714)
  14. Rutherford, J.C. (1994). River mixing, Wiley, UK.
  15. Seo, I. W. Baek, K.O., and Jeon, T.M. (2006). "Analysis of transverse mixing in natural streams under slug tests." Journal of Hydraulic Research, Vol. 44, No. 3, pp. 350-362. https://doi.org/10.1080/00221686.2006.9521687
  16. Seo, I.W., Baek, K.O., Jeon, T.M., and Jin J.H. (2003). "Tracer tests on transverse mixing in meandering streams." Journal of the Korean Water Resources Association, Vol. 36, No. 4, pp. 673-689. https://doi.org/10.3741/JKWRA.2003.36.4.673
  17. Seo, I.W., Choi, H.J., Kim, Y.D., and Han, E.J. (2016). "Analysis of two-dimensional mixing in natural streams based on transient tracer tests." Journal of Hydraulic Engineering, Vol. 142, No. 8, 04016020. https://doi.org/10.1061/(asce)hy.1943-7900.0001118
  18. Seo, I.W., Kim, J.S., and Jung, S.H. (2016). "Numerical simulation of two-dimensional pollutant mixing in rivers using RAMS." Procedia Engineering, Vol. 154, pp. 544-549. https://doi.org/10.1016/j.proeng.2016.07.550
  19. Seo, I.W., Lee, M.E., and Baek, K.O. (2008). "2D modeling of heterogeneous dispersion in meandering channels." Journal of Hydraulic Engineering, Vol. 134, No. 2, pp. 196-204. https://doi.org/10.1061/(asce)0733-9429(2008)134:2(196)