DOI QR코드

DOI QR Code

QUAL2Kw 모형을 이용한 자동보정 방법 비교분석과 섬강의 수질관리 대안 평가

Comparative analysis of auto-calibration methods using QUAL2Kw and assessment on the water quality management alternatives for Sum River

  • 조재현 (가톨릭관동대학교 보건환경학과)
  • Cho, Jae Heon (Department of Health and Environment, Catholic Kwandong University)
  • 투고 : 2016.09.20
  • 심사 : 2016.10.20
  • 발행 : 2016.10.31

초록

본 연구에서는 GA와 QUAL2K를 통합한 QUAL2Kw 모형을 이용해서 수질모형 매개변수의 자동 보정 방법을 비교 분석하였다. 발전 속도가 빠른 원주시의 배출 오염부하의 영향을 크게 받는 섬강에 QUAL2Kw 모형을 적용하였고, 전 구간 단일 매개변수를 적용하는 방법과 구간별 매개변수를 적용하는 두가지 방법으로 자동보정 방법을 비교 분석하였다. CV(RMSE)의 오차와 GA의 적합도 분석결과 구간별 매개변수 방법이 단일 매개변수 방법보다 정밀도가 다소 높은 것으로 나타났으므로 본 연구에서는 구간별 매개변수 방법으로 계산한 자동보정 결과를 채택하였다. 검보정된 QUAL2Kw 모형을 섬강 수질관리를 위한 세가지 시나리오에 대해 적용해서 수질 개선 효과를 분석하였다. 원주하수처리장 방류수질을 개선하는 시나리오 1에서는 중권역 대표지점인 섬강 4-1지점의 BOD와 TP 농도가 각각 17.7%, 29.1% 감소되었고, 원주천 유입직후 섬강에서는 BOD와 TP 농도가 각각 50.4%, 40.5% 감소하여 섬강 수질 개선효과가 크다. 원주취수장을 폐쇄하고 섬강 이외의 수계에서 원주 일대에 광역상수도를 공급하는 시나리오 2에서는 섬강 중하류부의 유량이 증가함에 따라 섬강 본류의 수질이 소폭 개선된다. 원주천 합류 직후 섬강에서 BOD가 0.18mg/L, TP가 0.0063mg/L 감소하였다. 시나리오 3에서는 시나리오 1과 시나리오 2의 대안을 동시에 계획하는 것으로서 시나리오 1보다 섬강 수질이 소폭 더 개선된다. 시나리오별 수질 예측결과 원주하수처리장의 방류수질을 개선하는 것이 섬강 수질개선에 가장 효과적인 것으로 나타났다. 특히 원주천 합류직후 섬강 수질이 크게 개선된다. 원주취수장을 폐쇄하고 타 수계에서 광역상수도를 통해 원주 지역에 상수도를 공급하는 방안도 섬강 수질을 소폭 개선할 수 있다.

In this study, auto-calibration method for water quality model was compared and analyzed using QUAL2Kw, which can estimate the optimum parameters through the integration of genetic algorithm and QUAL2K. The QUAL2Kw was applied to the Sum River which is greatly affected by the pollution loads of Wonju city. Two auto-calibration methods were examined: single parameter application for the whole river reach and separate parameter application for each reach of multiple reaches. The analysis about CV(RMSE) and fitness of the GA show that the separate parameter auto-calibration method is better than the single parameter method in the degree of precision. Thus the separate parameter auto-calibration method is applied to the water quality modelling of this study. The calibrated QUAL2Kw was used for the three scenarios for the water quality management of the Sum River, and the water quality impact on the river was analyzed. In scenario 1, which improve the effluent water quality of Wonju WWTP, BOD and TP concentrations of the Sum River 4-1 station which is representative one of Mid-Watershed, are decreased 17.7% and 29.1%, respectively. And immediately after joining the Wonjucheon, BOD and TP concentrations are decreased 50.4% and 40.5%, respectively. In scenario 2, Wonju water supply intake is closed and multi-regional water supply, which come from other watershed except the Sum River, is provided. The Sum River water quality in scenario 2 is slightly improved as the flow of the river is increased. Immediately after joining the Wonjucheon, BOD and TP concentrations are decreased 0.18mg/L and 0.0063mg/L, respectively. In scenario 3, the water quality management alternatives of scenario 1 and 2 are planned simultaneously, the Sum River water quality is slightly more improved than scenario 1. Water quality prediction of the three scenarios indicates that effluent water quality improvement of Wonju WWTP is the most efficient alternative in water quality management of the Sum River. Particularly the Sum River water quality immediately after joining the Wonjucheon is greatly improved. When Wonju water supply intake is closed and multi-regional water supply is provided, the Sum River water quality is slightly improved.

키워드

참고문헌

  1. Brown LC, Barnwell TO Jr. 1987. The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: Documentation and user manual. Environmental Research Laboratory. Office of Research and Development. U.S.EPA/600/3-87/007.
  2. Chapra SC, Pelletier GJ, Tao H. 2007. QUAL2K: a modeling framework for simulating river and stream water quality, version 2.07. Documentation and Users Manual. Medford, MA: Civil and Environmental Engineering Dept., Tufts University.
  3. Cho JH. 2011. Application of the QUAL2Kw model to a Polluted River for Automatic Calibration and Sensitivity Analysis of Genetic Algorithm Parameters. Journal of Environmental Impact Assessment. 20(3): 357-365. [Korean Literature]
  4. Cho JH, Ha SR. 2010. Parameter optimization of the QUAL2K model for a multiple-reach river using an influence coefficient algorithm. Science of the Total Environment. 408(8): 1985-1991. https://doi.org/10.1016/j.scitotenv.2010.01.025
  5. Cho JH, Seo HJ. 2007. Parameter optimization of SWMM for runoff quantity and quality calculation in a eutrophic lake watershed using a genetic algorithm. Water Science and Technology: Water Supply. 7(5-6): 35-41. https://doi.org/10.2166/ws.2007.114
  6. Cho JH, Sung KS, Ha SR. 2004. A river water quality management model for regional wastewater treatment cost using a genetic algorithm. Journal of Environmental Management. 73(3): 229-242. https://doi.org/10.1016/j.jenvman.2004.07.004
  7. Je CH, Kim KS. 2004. Web-based application for estimating water quality impacts due to environmental dredging. Environmental Geology. 46(2): 123-234.
  8. Kannel PR, Lee S, Lee YS, Kanel SR, Pelletier GJ. 2007. Application of automated QUAL2Kw for water quality modeling and management in the Bagmati River, Nepal. Ecological Modelling. 202: 185-190.
  9. Kim KS, Je CH. 2006. Development of a framework of automated water quality parameter optimization and its application. Environmental Geology. 49: 405-412. https://doi.org/10.1007/s00254-005-0085-0
  10. Little KW, Williams RE. 1992. Least-squares calibration of QUAL2E. Water Environment Research. 64(2): 179-185. https://doi.org/10.2175/WER.64.2.12
  11. Liu S, Butler D, Brazier R, Heathwaite L, Khu, ST. 2007. Using genetic algorithms to calibrate a water quality model. Science of the Total Environment. 374: 260-272. https://doi.org/10.1016/j.scitotenv.2006.12.042
  12. Pelletier GJ, Chapra SC. 2008. QUAL2Kw theory and documentation(version 5.1): A modeling framework for simulating river and stream water quality. Available from: http://www.ecy.wa.gov/programs/eap/models/.
  13. Rinaldi S, Romano P, Soncini-Sessa R. 1979. Parameter estimation of Streeter-phelps models. Journal of Environmental Engineering. 105(1): 75-88.
  14. Ryu JC, Kang HW, Choi JW, Kong DS, Gum DH, Jang CH, Lim KJ. 2012. Application of SWAT-CUP for Streamflow Autocalibration at Soyang-gang Dam Watershed. Journal of Korean Society on Water Environment. 28(3): 347-358. [Korean Literature]
  15. Son AL, Han KY, Park KO, Kim BH. 2011. Development of 1-Dimensional Water Quality Model Automatizing Calibration-Correction and Application in Nakdong River. Journal of Environmental Impact Assessment. 20(5): 765-777. [Korean Literature]
  16. Song KD, Paik DH, Lee YW. 2006. Development of Method for Deciding Automatically Parameters of Water Quality Simulation Models. Journal of Environmental Impact Assessment. 15(2): 101-109. [Korean Literature]
  17. Wood D, Houck MH, Bell JM. 1998. Automated calibration and use of stream quality simulation model. Journal of Environmental Engineering. 116(2): 236-248. https://doi.org/10.1061/(ASCE)0733-9372(1990)116:2(236)