Abstract As high-latitudes warm, permafrost thaws, and the hydrological cycle accelerates, ground-based monitoring of riverine organic matter may be supplemented by satellite remote sensing during ice-free conditions. Recent programs, namely the Arctic Great Rivers Observatory, have established methodologically consistent sampling across the hydrograph, and shared the resulting data publicly. However, these efforts are limited by frequency, funding, and length of record. Satellite remote sensing can be used to estimate chromophoric dissolved organic matter (CDOM) as a riverine constituent that influences optical properties in surface waters. In this study, daily CDOM absorption was first estimated using discharge-constituent regression-based models for 2000–2013. We then regressed these discharge-based CDOM estimates against Landsat TM and ETM+ surface reflectance data from Google Earth Engine for the six largest rivers draining the pan-Arctic watershed (the Kolyma, Lena, Mackenzie, Ob', Yenisey, and Yukon rivers). These CDOM results were converted to dissolved organic carbon (DOC), using the strong relationship (R2 = 0.88) between direct measurements of the two constituents. Using river-specific remote sensing models, R2 could be as high as 0.84. Grouping all rivers into a single “universal” regression reduced R2 and increased root mean square errors, such as in the Yenisey River where R2 dropped by 0.63, and RMSE rose by 1.1 m−1. Seasonally varying discharge drove much of the variation in satellite-derived CDOM and DOC, corroborating recent studies. Satellite imagery can increase the frequency of monitoring observations, particularly during summer and fall when riverine CDOM absorption may be most sensitive to thawing permafrost.

中文翻译：

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使用 Landsat TM 和 ETM+ 数据量化无冰条件下北极主要河流的 CDOM 和 DOC

摘要 随着高纬度地区变暖、多年冻土融化和水文循环加速，无冰条件下卫星遥感可以补充对河流有机物的地面监测。最近的项目，即北极大河流观测站，已经在整个水文过程线中建立了方法上一致的采样，并公开分享了所得数据。然而，这些努力受到频率、资金和记录长度的限制。卫星遥感可用于估计发色溶解有机物 (CDOM) 作为影响地表水光学特性的河流成分。在这项研究中，首次使用基于排放成分回归的模型估算了 2000 年至 2013 年的每日 CDOM 吸收量。然后，我们将这些基于排放的 CDOM 估计值与来自 Google Earth Engine 的 Landsat TM 和 ETM+ 表面反射数据进行回归，这些数据来自泛北极流域的六大河流（科雷马河、勒拿河、麦肯齐河、奥布河、叶尼塞河和育空河）。这些 CDOM 结果被转换为溶解有机碳 (DOC)，使用两种成分的直接测量之间的强关系 (R2 = 0.88)。使用特定河流的遥感模型，R2 可能高达 0.84。将所有河流分组为一个单一的“通用”回归降低了 R2 并增加了均方根误差，例如在叶尼塞河中，R2 下降了 0.63，RMSE 上升了 1.1 m-1。季节性变化的排放驱动了卫星衍生的 CDOM 和 DOC 的大部分变化，这证实了最近的研究。