• Title/Summary/Keyword: 조위 예측

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Prediction of Salinity Changes for Seawater Inflow and Rainfall Runoff in Yongwon Channel (해수유입과 강우유출 영향에 따른 용원수로의 염분도 변화 예측)

  • Choo, Min Ho;Kim, Young Do;Jeong, Weon Mu
    • Journal of Korea Water Resources Association
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    • v.47 no.3
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    • pp.297-306
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    • 2014
  • In this study, EFDC (Environmental Fluid Dynamics Code) model was used to simulate the salinity distribution for sea water inflow and rainfall runoff. The flowrate was given to the boundary conditions, which can be calculated by areal-specific flowrate method from the measured flowrate of the representative outfall. The boundary condition of the water elevation can be obtained from the hourly tidal elevation. The flowrate from the outfall can be calculated using the condition of the 245 mm raifall. The simulation results showed that at Sites 1~2 and the Mangsan island (Site 4) the salinity becomes 0 ppt after the rainfall. However, the salinity is 30 ppt when there is no rainfall. Time series of the salinity changes were compared with the measured data from January 1 to December 31, 2010 at the four sites (Site 2~5) of Yongwon channel. Lower salinities are shown at the inner sites of Yongwon channel (Site 1~4) and the sites of Songjeong river (Site 7~8). The intensive investigation near the Mangsan island showed that the changes of salinity were 21.9~28.8 ppt after the rainfall of 17 mm and those of the salinity were 2.33~8.05 ppt after the cumulative rainfall of 160.5 mm. This means that the sea water circulation is blocked in Yongwon channel, and the salinity becomes lower rapidly after the heavy rain.

Simulation Approach for the Tracing the Marine Pollution Using Multi-Remote Sensing Data (다중 원격탐사 자료를 활용한 해양 오염 추적 모의 실험 방안에 대한 연구)

  • Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.249-261
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    • 2020
  • Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.