Abstract Dissolved organic carbon, DOC, and the colored component of dissolved organic matter, CDOM, are key indicators of coastal water quality and biogeochemical state. Yet applications of space-based remote sensing to monitoring of CDOM variability across estuarine ecosystems and assessment of DOC exchanges along highly dynamic terrestrial-aquatic interfaces have been scarce, in part due to the coarse spatial resolution of most existing ocean color sensors and the seasonal and regional dependence of most existing algorithms. Here, we used a rich dataset of field observations to develop and validate new CDOM and DOC algorithms that are broadly applicable to different estuarine and coastal regions, over different seasons and a wide range of in-water conditions. Algorithms were applied to satellite imagery from MERIS-Envisat at a spatial resolution (300 m) that can resolve much of the spatial variability that characterizes estuaries and their margins. Multi-spectral remote sensing reflectance (Rrs) was used to retrieve CDOM absorption at various wavelengths and CDOM absorption spectral slope in the 275–295 nm spectral range (S275–295). DOC concentrations were obtained from a tight relationship between the DOC-specific CDOM absorption and S275–295, two optical quantities that depend only on the quality of CDOM and strongly covary across spatial and temporal scales. Algorithm evaluation using MERIS satellite data across different estuarine and coastal environments (i.e., the northern Gulf of Mexico, the Delaware Bay, the Chesapeake Bay estuary, and the Middle Atlantic Bight coastal waters) and across different seasons over multiple years resulted in relative errors (mean absolute percent difference; MAPD) of 29% (N = 17), 9.5% (N = 14), and 18% (N = 32), for aCDOM(300), S275–295, and DOC, respectively. These relative errors are comparable to those previously reported for satellite retrievals of CDOM and DOC products in less optically complex offshore waters. Application of these algorithms to multi-year MERIS satellite imagery over the Chesapeake Bay estuary allowed, for the first time, to capture the impact of tidal exchanges on carbon dynamics along wetland-estuary interfaces, and resolved spatial gradients, seasonal variability, and year-to-year changes in estuarine carbon amount and quality associated with marsh carbon export, riverine inputs, and extreme precipitation events.

中文翻译：

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北美河口及其边缘有色溶解有机质和溶解有机碳动态遥感反演

摘要 溶解有机碳 DOC 和溶解有机质的有色成分 CDOM 是沿海水质和生物地球化学状态的关键指标。然而，天基遥感在监测河口生态系统的 CDOM 变化和评估沿高度动态的陆水界面的 DOC 交换方面的应用一直很少，部分原因是大多数现有海洋颜色传感器的空间分辨率粗糙，以及季节性和大多数现有算法的区域依赖性。在这里，我们使用了丰富的现场观测数据集来开发和验证新的 CDOM 和 DOC 算法，这些算法广泛适用于不同的河口和沿海地区、不同季节和各种水下条件。算法以空间分辨率 (300 m) 应用于 MERIS-Envisat 的卫星图像，该图像可以解决表征河口及其边缘的大部分空间变异性。多光谱遥感反射率 (Rrs) 用于检索不同波长的 CDOM 吸收和 275-295 nm 光谱范围 (S275-295) 内的 CDOM 吸收光谱斜率。DOC 浓度是从 DOC 特定 CDOM 吸收和 S275-295 之间的紧密关系中获得的，这两个光学量仅取决于 CDOM 的质量并且在空间和时间尺度上有很强的共变。使用 MERIS 卫星数据在不同河口和沿海环境（即墨西哥湾北部、特拉华湾、切萨皮克湾河口、和中大西洋湾沿岸水域）和多年不同季节导致的相对误差（平均绝对百分比差异；MAPD）分别为 29% (N = 17)、9.5% (N = 14) 和 18% (N = 32)，分别为 aCDOM(300)、S275-295 和 DOC。这些相对误差与先前报告的在光学复杂度较低的近海水域中 CDOM 和 DOC 产品的卫星检索相当。将这些算法应用于切萨皮克湾河口的多年 MERIS 卫星图像，首次能够捕捉潮汐交换对湿地 - 河口界面碳动力学的影响，并解决空间梯度、季节变化和年-与沼泽碳输出、河流输入和极端降水事件相关的河口碳数量和质量的年度变化。