In companion paper 1, the SAtellite Water Cycle (SAWC) satellite data set integration approach was presented. SAWC accounts for (1) the closure of the water budget at the sub‐basin scale by (2) using upstream/downstream dependencies. Here, the SAWC database is used to reconstruct a missing water component. The total water storage change (dS) can be reconstructed prior to the Gravity Recovery and Climate Experiment (GRACE) period. In terms of seasonal and interannual variations, SAWC provides long‐term dS estimates that are highly consistent with the GRACE estimate (2002–2015). When compared to the extent of inundation, correlation of anomalies reaches 0.6 over sub‐basins presenting large floodplain. A strong relationship (correlation of 0.7) exists between the monthly dS and the El Niño index. The river discharge R can also be estimated using the SAWC approach during the GRACE period. A scheme was developed to estimate R continuously along the river through the indirect interpolation of discharge station measurements by using satellite estimates of dS, precipitation P, and evaporation E. These R estimates along the river were evaluated with 80 independent measurements and had a correlation of 0.86 and a Kling‐Gupta efficiency index of 0.71. A comprehensive monthly river discharge estimate was proposed for the first time across the Amazon basin over 13 years (2002–2015) at a 0.25° resolution. The SAWC framework is a pure observation tool for integrating a large range of satellite estimates, potentially facilitating the assimilation of such data into land surface models.

中文翻译：

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亚马逊水循环的相干卫星监测。第2部分：总蓄水量变化和河流流量估算

在配套文件1中，介绍了卫星水循环（SAWC）卫星数据集集成方法。SAWC解释了（1）使用上游/下游依存关系来关闭（2）子流域规模的水预算。在此，SAWC数据库用于重建缺失的水成分。总储水量变化（dS）可以在重力恢复和气候实验（GRACE）之前重建。就季节和年际变化而言，SAWC提供的长期dS估算值与GRACE估算值（2002-2015）高度一致。与淹没程度相比，与呈现大洪泛区的子流域相比，异常的相关性达到0.6。每月dS之间存在很强的关系（相关系数为0.7）和厄尔尼诺指数。在GRACE期间，也可以使用SAWC方法估算河流流量R。通过使用dS，降水P和蒸发E的卫星估计，通过间接插值排放站测量值，提出了沿河水连续估计R的方案。这些R沿河的估计值通过80次独立测量进行了评估，相关系数为0.86，克林古普塔效率指数为0.71。提出了以0.25°的分辨率在13年（2002-2015年）内整个亚马逊河流域的月度河水排放量的综合估算。SAWC框架是一个纯粹的观测工具，用于整合大范围的卫星估算值，从而有可能促进将此类数据同化到地表模型中。