Spatio-temporal changes in water temperature and discharge of the Arctic rivers are important variables to be observed not only for estimating runoff contributions from snow melt, rainfall, and thawing of permafrost over the continents but also for assessing their impacts on the Arctic sea-ice and marine ecosystem. Nevertheless, the number of ground water gauging stations and the frequency of in-situ measurements for temperature and discharge has been decreasing since the 20 Century due to the shrinkage of budgets for maintaining the in-situ stations. In this study, we explored the possibility to perform near-daily monitoring of river surface temperature (RST) and river channel width (RCW) from space using a Japanese satellite-borne optical sensor named SGLI which can observe radiances at the spectral bands from near-ultraviolet to thermal infrared regions at the same spatial resolution of 250-m on a global scale. River surface brightness temperature (RSBT) measured with SGLI TIR band was used as RST without atmospheric correction. RCW was derived as the widths of water pixels identified along river channels using SGLI reflectances at visible to shortwave infrared bands. Analysis results of two-year SGLI data acquired in 2018 and 2019 show that RSBT and RCW can be retrieved successfully from the SGLI observations on a daily basis after applying a spatio-temporal interpolation. The accuracies of the retrieved RSBT evaluated with in-situ water temperatures are about 2.57 K with the interpolation (and 1.84 K without the interpolation but with lower observation frequencies). Retrieved RCWs are correlated well with in-situ river water discharges indicating potentials to assess variations of not only snow melt water but also precipitation within the river basin. Thus, SGLI data can be used to reconstruct not only the river water temperature but also the river water discharges along the continental river channels for assessing heat flux flowing into the Arctic Ocean.

北极河流水温和流量的时空变化是重要的观察变量，不仅用于估计大陆上积雪融化、降雨和永久冻土融化的径流贡献，而且还用于评估它们对北极海冰的影响和海洋生态系统。然而，由于维持原位站的预算缩减，地下水测量站的数量和温度和流量原位测量的频率自 20 世纪以来一直在下降。在这项研究中，我们探索了使用名为 SGLI 的日本星载光学传感器从空间对河面温度 (RST) 和河道宽度 (RCW) 进行近乎日常监测的可能性，该传感器可以观察从近紫外到热光谱波段的辐射在全球范围内具有相同空间分辨率 250 米的红外区域。使用 SGLI TIR 波段测量的河面亮温 (RSBT) 作为 RST，未经大气校正。RCW 是作为使用 SGLI 反射率在可见光至短波红外波段沿河道识别的水像素的宽度得出的。对 2018 年和 2019 年获得的两年 SGLI 数据的分析结果表明，应用时空插值后，每天都可以从 SGLI 观测中成功检索 RSBT 和 RCW。用原位水温评估的反演 RSBT 的准确度约为 2.57 K（无插值时为 1.84 K，但观测频率较低）。检索到的 RCW 与原位河水排放密切相关，表明不仅可以评估融雪水的变化，还可以评估流域内降水的变化。因此，SGLI 数据不仅可用于重建河水温度，还可用于重建沿大陆河道排放的河水，以评估流入北冰洋的热通量。检索到的 RCW 与原位河水排放密切相关，表明不仅可以评估融雪水的变化，还可以评估流域内降水的变化。因此，SGLI 数据不仅可用于重建河水温度，还可用于重建沿大陆河道排放的河水，以评估流入北冰洋的热通量。检索到的 RCW 与原位河水排放密切相关，表明不仅可以评估融雪水的变化，还可以评估流域内降水的变化。因此，SGLI 数据不仅可用于重建河水温度，还可用于重建沿大陆河道排放的河水，以评估流入北冰洋的热通量。