한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제57권7호
  • /
  • Pages.461-470
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  • 2024
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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직독식 센서 측정 항목을 활용한 낙동강 유역의 총인(T-P) 예측 연구

Prediction of Total Phosphorus (T-P) in the Nakdong River basin utilizing In-Situ Sensor-Derived water quality parameters

  • 강유민 (명지대학교 토목환경공학과) ;
  • 남수한 (명지대학교 토목환경공학과) ;
  • 김영도 (명지대학교 토목환경공학과)
  • Kang, YuMin (Department of Civil & Engineering, MyongJi University) ;
  • Nam, SuHan (Department of Civil & Engineering, MyongJi University) ;
  • Kim, YoungDo (Department of Civil & Engineering, MyongJi University)
  • 투고 : 2024.02.21
  • 심사 : 2024.06.21
  • 발행 : 2024.07.31
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초록

본 연구는 다양한 인간의 활동으로 인해 공공수역에 영양물질이 유입됨에 따라 발생하는 부영양화를 초기에 대응하기 위해 T-P (Total Phosphorus) 예측을 진행하였다. 기존의 T-P 모니터링 시스템은 인력 및 시간이 많이 소요되는 단점이 존재해 직독식 센서를 활용한 측정이 국내외를 막론하고 많이 시도되고 있는 추세이다. 따라서 직독식 센서를 통해 얻을 수 있는 수질항목을 활용하여 T-P 예측을 진행하였으며, 두 단계로 나누어 진행하였다. T-P 예측에 있어 Turbidity (Tur)의 중요성에 대해 살펴보았으며, 자동수질분석기 분석항목을 추가한 분석을 통해 직독식 센서 측정 항목만으로 T-P 예측이 가능한지 살펴보았다. 본 연구의 연구 대상 지점인 낙동강 유역 내 T-P 현황을 살펴본 결과, T-P 농도가 상류 지역 대비 중·하류 지역에 높게 나타났다. Pearson 상관분석을 통해 지점별로 T-P와 상관성이 높은 수질항목을 파악하였으며, 이를 활용하여 다중선형회귀분석을 진행하여 T-P를 예측하였다. Tur의 유무에 따른 분석을 진행하였으며, 자동수질분석기 분석항목이 포함된 분석을 통해 직독식 센서 측정 항목과의 성능을 비교하였다. 결과적으로 Tur 활용의 중요성을 확인하였으며, 이는 부영양화 개선 대책 수립을 위한 보조 자료로 활용할 수 있을 것으로 판단된다.

This study aimed to predict total phosphorus (T-P) to address early eutrophication caused by nutrient influx from various human activities. Traditional T-P monitoring systems are labor-intensive and time-consuming, leading to a global trend of using direct reading sensors. Therefore, this study utilized water quality parameters obtained from direct reading sensors in a two-stage T-P prediction process. The importance of turbidity (Tur) in T-P prediction was examined, and an analysis was conducted to determine if T-P prediction is possible using only direct reading sensor parameters by adding automatic water quality analyzer parameters. The study found that T-P concentrations were higher in the mid-lower reaches of the Nakdong River basin compared to the upper reaches. Pearson correlation analysis identified water quality parameters highly correlated with T-P at each site, which were then used in multiple linear regression analysis to predict T-P. The analysis was conducted with and without the inclusion of Tur, and the performance of models incorporating automatic water quality analyzer parameters was compared with those using only direct reading sensor parameters. The results confirmed the significance of Tur in T-P prediction, suggesting that it can be used as a foundational element in the development of measures to prevent eutrophication.

키워드

과제정보

본 연구는 환경부 수생태계 건강성 확보 기술개발사업의 지원(2021003030005)에 의해 수행되었으며, 이와 같은 지원에 감사드립니다.

참고문헌

  1. Ahn, J.M., Lee, I.J., Jung, K.Y., Kim, J.E., Lee, K.C., Cheon, S.U., and Lyu, S.W. (2016). "Characteristics of trend and pattern for water quality monitoring networks data using Seasonal-kendall, SOM and RDA on the Mulgeum in the Nakdong River." Journal of Environmental Science International, Vol. 25, No. 3, pp. 361-371. https://doi.org/10.5322/JESI.2016.25.3.361
  2. Baik, J.J., Park, J.M., and Choi, M.H. (2020). "Estimation and assessment of total phosphorus and trophic state index estimated from landsat 8 dataset on 2018 at Daecheong reservoir." Journal of Korean Society of Environmental Engineers, Vol. 42, No. 9, pp. 415-423. https://doi.org/10.4491/KSEE.2020.42.9.415
  3. Bong, T.H., and Kim, B.I. (2017). "Prediction of ultimate bearing capacity of soft soils reinforced by gravel compaction pile using multiple regression analysis and artificial neural network." Journal of the Korean Geotechnical Society, Vol. 33, No. 6, pp. 27-36. https://doi.org/10.7843/KGS.2017.33.6.27
  4. Choi, J.H., and Kim, Y.K. (2021). "Prediction of the Land price based on deep learning and residual kriging." Journal of the Korean Data Information Science Society, Vol. 32, No. 3, pp. 475-485.
  5. Han, S.H., Lee, E.H., and Kim, H.O. (2012), "Development of software sensor for total phosphorus and nitrogen in various waterbody" Journal of the Korean Society for Environmental Analysis, Vol. 15, No. 3, pp. 215-223.
  6. Jung, D.G., Kim, S.D., Kwon, S.Y., Lee, J.Y., Kim, Y.S., Lee, J.Y., Kim, J.K., Kim, S.W., Kong, S.H., and Jung, D.W. (2020). "Development of a portable total-phosphorus monitoring system for preventing eutrophication in Advance." Journal of Sensor Science and Technology, Vol. 29, No. 5, pp. 342-347.
  7. Jung, J.M., Park, S.H., Lee, Y.S., and Gim, J.H. (2019). "The development of infrared thermal imaging safety diagnosis system using pearson's correlation coefficient." Journal of the Korean Solar Energy Society, Vol. 39, No. 6, pp. 55-65. https://doi.org/10.7836/kses.2019.39.6.055
  8. Jung, S.Y., and Kim, I.K. (2017). "Analysis of water quality factor and correlation between water quality and Chl-a in middle and downstream weir section of Nakdong River." Journal of Korean Society of Environmental Engineers, Vol. 39, No. 2, pp. 89-96. https://doi.org/10.4491/KSEE.2017.39.2.89
  9. Kamari, M., Tarvainen, M., Kotamaki, N., and Tattari, S. (2020). "High-frequency measured turbidity as a surrogate for phosphorus in boreal zone rivers: appropriate options and critical situations." Environmental Monitoring and Assessment, Vol. 192, No. 366, pp. 1-20. https://doi.org/10.1007/s10661-019-7904-3
  10. Kim, H.K., Jeong, H.S., and Bae, S.J. (2015). "Deriving water quality criteria of total nitrogen for nutrient management in the stream." Journal of the Korean Society of Agricultural Engineers, Vol. 57, No. 3, pp. 121-127. https://doi.org/10.5389/KSAE.2015.57.3.121
  11. Kim, Y.L., Lee, K.H., and Park, S.H. (2023). "Application and evaluation of machine learning techniques for real-time short-term prediction of air pollutants." Journal of Korean Society for Atmospheric Environment, Vol. 39, No. 1, pp. 107-127. https://doi.org/10.5572/KOSAE.2023.39.1.107
  12. Lee, D.H., Kang, E.T., Joo, J.C., Go, H.W., Ahn, C.M., Bae, Y.H., and Song, K.D. (2022). "Water quality analysis and Chl-a prediction of 15 large-scale freshwater lakes in Korea by multivariate statistical analysis." Journal of Korean Society of Environmental Engineers, Vol. 44, No. 12, pp. 589-602. https://doi.org/10.4491/KSEE.2022.44.12.589
  13. Lee, S.I., Cho, D.H., and Lee, M.P. (2018). "Spatializing the pearson's correlation coefficient: An experimental comparison of three relevant techniques." Journal of the Korean Geographical Society, Vol. 53, No. 5, pp. 761-776.
  14. Lim, J.S., Kim, Y.W., Lee, J.H., Park, T.J., and Byun, I.G. (2015). "Evaluation of correlation between Chlorophyll-a and multiple parameters by multiple linear regression analysis." Journal of Korean Society of Environmental Engineers, Vol. 37, No. 5, pp. 253-261. https://doi.org/10.4491/KSEE.2015.37.5.253
  15. Valkama, P., and Ruth, O. (2017). "Impact of calculation method, sampling frequency and hysteresis on suspended solids and total phosphorus load estimations in cold climate." Hydrology Research, Vol. 48, No. 6, pp. 1594-1610. https://doi.org/10.2166/nh.2017.199
  16. Villa, A., Folster, J., and Kyllmar, K. (2019). "Determining suspended solids and total phosphorus from turbidity: Comparison of high-frequency sampling with conventional monitoring methods." Environmental Monitoring and Assessment, Vol. 191, No. 605, pp. 1-16. https://doi.org/10.1007/s10661-018-7122-4
  17. Zhang, Y., Li, M., Dong, J., Yang, H., van Zwieten, L., Lu, H., Alshameri, A., Zhan, Z., Chen, X., Jiang, X., Xu, W., Bao, Y., and Wang, H. (2021). "A critical review of methods for analyzing freshwater eutrophication." Water, Vol. 13, No. 225, pp. 1-20. https://doi.org/10.3390/w13020225