Field investigation was carried out during 4 to 15 April 2001 around the Changjiang River Estuary. The similar distribution of sea surface nutrients and suspended sediment （SS） concentration is attributed to the phy...Field investigation was carried out during 4 to 15 April 2001 around the Changjiang River Estuary. The similar distribution of sea surface nutrients and suspended sediment （SS） concentration is attributed to the physical mixing of Changjiang diluted water （CDW） with the Taiwan Warm Current （TWC）. On the basis of the observed positive relationship between total phosphorus （TP） and SS concentration, the sea surface TP is inversed from satellite SS data. SS is believed to be an ideal eutrophic state assessing index substitution for TP, the eutrophication classification critical value of SS adopted in this research was based on the linear model： CTP =0. 000 6Css_ ＋0. 016 3, r^2 =0.564 5, n =32. Although lack of in-situ chromophoric dissolved organic matter （CDOM） measurement, a good relationship was observed between the in-situ DIN （dissolved inorganic nitrogen） concentration with near real time SeaWiFS absorption coefficient of CDOM （ACD） data： cDIN= 1. 406 5AACB_ - 0. 035 9, r^2 = 0. 741 5, n = 16. This empirical regression algorithm was also utilized for inversing the DIN concentration from SeaWiFS ACD data, and for establishing the eutrophication classification critical value of satellite ACD data. The established remote eutrophication classification sys- tem was later used for seawater eutrophic state assessment. The evaluation suggested that the Zhoushan Fishing Ground especially the western border is affected seriously with the nutrient input. The nutrient is mainly from the terrestrial source transported by the Changjiang River runoff. The seawater quality classification precision was assessed by in-situ data, which suggested the seawater quality distribution is similar to the two classification systems, and the remote classification error is below 25%.展开更多
基金This study was supported by the Zhejiang Province Natural Science Foundation under contract No.Y506205the"863"Hi-Tech Research and Development Program of China under contract No 2003AA131160+1 种基金the United Technical Program of Changjiang Delta under contract No.2004E60054the Vital Technical of Zhejiang Province under contract No.2004C13027
文摘Field investigation was carried out during 4 to 15 April 2001 around the Changjiang River Estuary. The similar distribution of sea surface nutrients and suspended sediment （SS） concentration is attributed to the physical mixing of Changjiang diluted water （CDW） with the Taiwan Warm Current （TWC）. On the basis of the observed positive relationship between total phosphorus （TP） and SS concentration, the sea surface TP is inversed from satellite SS data. SS is believed to be an ideal eutrophic state assessing index substitution for TP, the eutrophication classification critical value of SS adopted in this research was based on the linear model： CTP =0. 000 6Css_ ＋0. 016 3, r^2 =0.564 5, n =32. Although lack of in-situ chromophoric dissolved organic matter （CDOM） measurement, a good relationship was observed between the in-situ DIN （dissolved inorganic nitrogen） concentration with near real time SeaWiFS absorption coefficient of CDOM （ACD） data： cDIN= 1. 406 5AACB_ - 0. 035 9, r^2 = 0. 741 5, n = 16. This empirical regression algorithm was also utilized for inversing the DIN concentration from SeaWiFS ACD data, and for establishing the eutrophication classification critical value of satellite ACD data. The established remote eutrophication classification sys- tem was later used for seawater eutrophic state assessment. The evaluation suggested that the Zhoushan Fishing Ground especially the western border is affected seriously with the nutrient input. The nutrient is mainly from the terrestrial source transported by the Changjiang River runoff. The seawater quality classification precision was assessed by in-situ data, which suggested the seawater quality distribution is similar to the two classification systems, and the remote classification error is below 25%.
