大亚湾溶解氧分布特征及环境影响因子研究

基于2004-2010年间大亚湾海域的环境监测数据,分析了溶解氧的水平分布特征、年际变化规律及主要环境影响因子。分析结果表明,表层溶解氧水平分布均匀,底层浓度梯度明显,城镇入海口和大亚湾核电站附近溶解氧含量较低;表层溶解氧逐年变化不大,底层的年际变化较为显著,大亚湾中央位置溶解氧的年际变化幅度较大;经与各环境因子进行相关性分析得知无机氮是影响溶解氧变化的主要环境因子,二者呈负相关。     

半分析模型在近岸及河口水体透明度反演应用研究

Secchi depth(SD, m) is a direct and intuitive measure of water's transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water's transparency in satellite images. Here an in-situ dataset(338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang(Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference(UPD) between estimated and measured SD is 23.3%(N=338, R~2=0.89), with about 60% of stations in the dataset having relative difference(RD)≤20%, over 80% of stations having RD≤40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7%(N=132,R~2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5.