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초분광영상 기반 탁수 모니터링에서의 탁도-SS 관계식 적용성 검토

Review of applicability of Turbidity-SS relationship in hyperspectral imaging-based turbid water monitoring

  • 김종민 (명지대학교 토목환경공학과) ;
  • 김광수 (명지대학교 토목환경공학과) ;
  • 권시윤 (오스틴대학교 토목건축환경공학부) ;
  • 김영도 (명지대학교 토목환경공학과)
  • Kim, Jongmin (Department of Civil and Environmental Engineering, Myongji University) ;
  • Kim, Gwang Soo (Department of Civil and Environmental Engineering, Myongji University) ;
  • Kwon, Siyoon (Center for Water and Environment, Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin) ;
  • Kim, Young Do (Department of Civil and Environmental Engineering, Myongji University)
  • 투고 : 2023.11.15
  • 심사 : 2023.11.29
  • 발행 : 2023.12.31

초록

우리나라의 강우 특성은 여름철 홍수기에 집중되어있다. 특히 이상강우 및 기상이변에 의한 집중강우의 증가 추세로 다량의 탁수가 댐 내에 유입될 시 전도현상으로 인해 탁수 장기화 현상이 발생하게 된다. 이러한 문제를 해결하기 위한 탁수 예측을 통한 선제적 조치 방안 또는 댐 운영방안 마련에 많은 연구가 진행되고 있다. 탁수 예측을 위해서는 상류 유입부의 탁수 자료를 필요로 하지만 현재 시·공간적인 데이터 해상도는 부족한 실정이다. 시간적 해상도 개선을 위해서는 탁도-SS 관계식에 대한 개발을 필요로 하며 공간적 해상도 개선을 위해 다항목수질측정기(YSI), 레이저부유사측정기(Laser In-Situ Scattering and Transmissometry, LISST), 초분광 센서 등의 센서 기반 측정을 통해 선, 면 단위 데이터 측정을 통해 탁수에 대한 공간적 해상도를 개선할 수 있다. 또한 LISST-200X의 경우 입경 크기 등에 대한 자료 수집이 가능함에 따라 분율(Clay : Silt : Sand)에 대한 탁도-SS 관계식에 활용될 수 있다. 또한 최근 원격탐사 방안 중 다른 탑재체에 비해 공간해상도 및 시간해상도가 높은 UAV와 분광·방사 해상도가 높은 초분광 센서를 활용 시 탁수 발생에 대한 공간적인 분포를 제시할 수 있다. 따라서, 본 연구에서는 LISST-200X 및 YSI-EXO를 활용하여 실험실 분석을 통해 분율(Clay : Silt : Sand)에 따라 탁도-SS 관계식을 산정하였으며 UAV (Matrice 600), 초분광센서(microHSI 410 SHARK)를 포함한 센서 기반 현장 측정을 통해 탁도와 부유사 농도, 측정된 부유사농도 기반 탁도-SS 관계식을 이용하여 산정한 탁도에 대하여 공간적 분포를 제시하였다. 이를 통해 탁도-SS 관계식에 대한 적용성 검토 및 탁수 발생 현황에 대하여 파악하고자 하였다.

Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.

키워드

과제정보

본 연구는 환경부 수생태계 건강성 확보 기술개발사업의 지원(2021003030002)에 의해 수행되었으며, 이와 같은 지원에 감사드립니다.

참고문헌

  1. Chung, S.W., Jung, Y.R., Ko, I.H., and Kim, N.I. (2007). "Development and validation of a decision support system for the real-time monitoring and management of reservoir turbidity flows: A case study for Daecheong Dam." Journal of the Korea Water Resources Association, KWRA, Vol. 41, No. 3, pp. 293-303. https://doi.org/10.3741/JKWRA.2008.41.3.293
  2. Chung, S.W., Lee, H.S., and Jung, Y.R. (2008). "Turbidity modeling for a negative buoyant density flow in a reservoir with consideration of multiple particle sizes." Journal of Korean Society on Water Environment, Vol. 24, No. 3, pp. 365-377.
  3. Chung, S.W., Lee, J.H., Lee, H.S., and Maeng, S.J. (2011). "Uncertainty of discharge-SS relationship used for turbid flow modeling." Journal of Korea Water Resources Association, Vol. 44, No. 12, pp. 991-1000. https://doi.org/10.3741/JKWRA.2011.44.12.991
  4. Chung, S.W., and Oh, J.K. (2006). "River water temperature variations at upstream of Daecheong Lake during rainfall events and development of prediction models." Journal of the Korea Water Resources Association, KWRA, Vol. 39, No. 1, pp. 79-88. https://doi.org/10.3741/JKWRA.2006.39.1.079
  5. Corning (2017). Corning micro HSI 410 SHARK: Integrated, Coherent, Airborne Hyperspectral Imaging System, accessed 2 May 2020, <https://www.corning.com/microsites/coc/oem/documents/hyperspectral-imaging/Corning-MicroHSI-410-SHARK-Brochure.pdf>.
  6. Ehrbar, D., Schmocker, L., Vetsc, D.F., Boes, R.M., and Doering, M. (2017). "Measuring suspended sediments in periglacial reservoirs using water samples, laser in-situ scattering and transmissometry and acoustic Doppler current profiler." International Journal of River Basin Management, Vol. 15, No. 4, pp. 413-431. https://doi.org/10.1080/15715124.2017.1327866
  7. Fan, C.L. (2014). "Spectral analysis of water reflectance for hyperspectral remote sensing of water quality in estuarine water." Journal of Geoscience and Environment Protection, SciRes., No. 2, pp. 19-27.
  8. Gwon, Y.H., Kin, D.S., and You, H.J. (2020). "A standardized procedure on building spectral library for hazardous chemicals mixed in river flow using hyperspectral image." Journal of Korea Water Resour. Association, KWRA, Vol. 53, No. 10, pp. 845-859.
  9. Kim, B.C., and Jung, S.M. (2007). "Turbid storm runoffs in Lake Soyang and their environmental effect." Journal of the Korean Society of Environmental Engineering, KSEE, Vol. 29, No. 11, pp. 1185-1190.
  10. Kim, G.S., Choi, J.Y., Nam, S.H., Kim, Y.D., and Kwon, J.H., (2023). "A study on the development of a Blue-green algae cell count estimation formula in Nakdong River downstream using hyperspectral sensors." Journal of the Korea Water Resources Association, KWRA, Vol. 56, No. 6, pp. 373-380. https://doi.org/10.3741/JKWRA.2023.56.6.373
  11. Kim, T.W., Kim, Y.D., and Yi, Y.K. (2012). "A study on field experiment and numerical modeling for efficiency analysis of selective withdrawal in Imha reservoir." Journal of the Korean Society of Civil Engineers, Vol. B32, No. 2B, pp. 113-121.
  12. Kim, W.G., Jung, K.S., and Yi, Y.K. (2006). "The variation of water temperature and turbidity of stream flows entering Imha reservoir." Korean journal of limnology, Vol. 39, No. 1, pp. 13-20.
  13. Kisevic, M., Morovic, M., and Andricevic, R. (2016). "The use hyperspectral data for evaluation of water quality parametersin the river Sava" Fresenius Environmental Bulletin, Vol. 25, No. 11, pp. 4814-4822.
  14. Kwak, S.H., Lee, K.S., Cho, H.I., Seo, Y.J., and Lyu, S.W. (2017). "Field measurement of suspended material distribution at the river confluence." Journal of the Korean Society of Civil Engineers, KSCE, Vol. 37, No. 2, pp. 467-474. https://doi.org/10.12652/KSCE.2017.37.2.0467
  15. Kwon, S., Shin, J., Seo, I.W., Noh, H., Jung, S.H., and You, H. (2022). "Measurement of suspended sediment concentration in open channel flows based on hyperspectral imagery from UAVs." Advances in Water Resources, Vol. 159, 104076.
  16. Kwon, S.Y., Gwon, Y.H., Kin, D.S., Seo, I.W., and You, H.J. (2023). "Unsupervised classification of riverbed types for bathymetry mapping in shallow rivers using UAV-based hyperspectral imagery." Remote Sensing, Vol. 15, No. 11, 2803.
  17. Landers, M.N., and Sturm, T.W. (2013). "Hysteresis in suspended sediment to turbidity relations due to changing particle size distributions." Water Resources Research, Vol. 49, pp. 5487-5500. https://doi.org/10.1002/wrcr.20394
  18. Mikkelsen, O., and Pejrup, M. (2001). "The use of a LISST-100 laser particle sizer for in-situ estimates of floc size, density and settling velocity." An International Journal of Marine Geology, Vol. 20, pp. 187-195. https://doi.org/10.1007/s003670100064
  19. You, H.J. (2018). Development of riverine bathymetry survey technique using drone-based hyperspectral image. Ph.D Dissertation, Dankook University