Rivers continuously transport terrestrial organic carbon matter to the estuary and the ocean, and they play a critical role in productivity and biodiversity in the marine ecosystem as well as the global carbon cycle. The amount of terrestrial organic carbon transporting from the rivers to ocean is an essential piece of information, not only for the marine ecosystem management but also the carbon budget within catchment. However, this phenomenon is still not well understood. Most large rivers in Korea have a well-established national monitoring system of the river flow and the TOC (Total Organic Carbon) concentration from the mountain to the river mouth, which are fundamental for estimating the amount of the TOC flux. We estimated the flux of the total terrestrial organic carbon of five large rivers which flow out to the Yellow Sea, using the data of the national monitoring system (the monthly mean TOC concentration and the monthly runoff of river flow). We quantified the annual TOC flux of the five rivers, showing their results in the following order: the Han River (18.0×109 gC yr-1)>>Geum River (5.9×109 gC yr-1)>Yeongsan River (2.6×109 gC yr-1)>Sumjin River (2.0×109 gC yr-1)>>Tamjin River (0.2×109 gC yr-1). The amount of the Han River, which is the highest in the Korean rivers, corresponds to be 4% of the annual total TOC flux of in the Yellow River, and moreover, to be 0.6% of Yangtze River.

하도내에서 발생하는 유출량 및 TOC 자료는 비선형성이 강한 자료임에 따라 홍수에 대한 재난대응과 수질의 상시감시를 위해서는 자료의 특성 분석과 예측에 관한 연구는 필수라 할 수 있다. 따라서 본 연구에서 유출량 및 TOC, TOC부하량 자료에 대한 웨이블렛 변환에 의해 최종분해된 최종파형분해단계의 근사성분과 상세성분을 이용하여 예측모형을 개발하였다. 그 결과 기존 인공신경망 모형에서 관찰되었던 시계반대 방향으로 전이되는 지속현상의 극복 가능성을 보여주