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This article introduces a practical method to investigate thermal pollution in coastal water from satellite data. The intensity and distribution areas of thermal pollution by the heated effluent discharge from the nuclear power plant on Daya Bay, southern China were investigated by using Landsat-5 Thematic Mapper (TM) thermal band data from 1994 to 2001. A local algorithm was developed, based on sea-truth data of water surface temperature measured when the satellite passed over the study area. The local algorithm was then applied to estimate water temperature from TM data. It shows that the remote sensing technique provides an effective means to quantitatively monitor the intensity of thermal pollution and to retrieve a very detailed distribution pattern of thermal pollution in coastal waters. The remotely-sensed results of the thermal pollution can be used for environmental management of coastal waters.

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Seasonal and intraseasonal variability of surface chlorophyll a concentration in the South China Sea is explored using the NASA standard Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) monthly and 8-day level-3 products from 1997 to 2007. The link between the seasonal and intraseasonal variability of the chlorophyll and physical forcing is revealed. Continuous wavelet transform indicates that chlorophyll in the South China Sea presents pronounced seasonal, as well as intraseasonal, variability. Chlorophyll a variability shows significant correlation with wind speed in all five sub-regions, while significant correlation with sea surface temperature only appears in the northern Sea. Intraseasonal variability of chlorophyll appears mainly in the winter, with spectral peaks around 32-64 days. It shows high commonalities for some periods in the intraseasonal cycle between chlorophyll a and sea surface temperature, wind stress curl or wind speed using cross wavelet transform.

, are used in an exponential regression model to estimate the TSM concentrations, the mean relative errors between the estimated and measured TSM are 27.2% and 23.3%, respectively for and , and the root mean square errors of estimation are 12.6 mg/L and 5.9 mg/L, respectively. This band-subtraction of two neighboring bands shows better performance than several popular single-band and band-combination models. This good performance may be mainly attributed to the band-subtraction of the two neighboring bands which improves the sensitivity of reflectance to suspended sediments by reducing the background impacts from water surface reflection and path radiance at the specific wavelengths. These methods and findings with the high spatial and high spectral resolution data may be used for the remote sensing of turbid estuary waters although further validation work with a wider range of TSM concentration may be necessary.

JONSSON, L.; CHEN, C, and SHI, P. 2005, A model of the 3D circulation, salinity distribution, and transport pattern in the pearl river estuary, China, Journal of Coastal Research, 21(5), 896-908, West Palm Beach (Florida), ISSN 0749-0208,The three-dimensional circulation, salinity distrihution, and overall transport pattern were simulated in the Pearl River Estuary, China, using a modified version of the Princeton Ocean Model (POM), The circulation in the estuary is mainly driven by tide, wind, and river runoff in a complex manner, where the relative importance of the different forcing factors varies over the year. Field data on currents from several locations in the estuary taken at different elevations through the water column were employed to validate the model together with measurements of the salinity distribution in the surface layer. Also, satellite images were utilized to qualitatively confirm the simulated overall transport pattern. Comparisons between measurements and calculations showed that the POM yielded satisfactory predictions without any particular calibration. However, for some events the coastal current outside the estuary induced by the large-scale circulation in the South China Sea affected the flow in the estuary, making it necessary to employ a more sophisticated boundary condition on the ocean side than what was initially implemented. The longterm objective of the numerical modeling of the flow and material transport in the Pearl River Estuary is to utilize the validated model for forecasting the circulation and water quality in the estuary in a comprehensive system where in-situ measurements and remote sensing are the other main components.