Significance: Stream/river carbon dioxide (CO ₂ ) emission has significant spatial and seasonal variations critical for understanding its macroecosystem controls and plumbing of the terrestrial carbon budget. We relied on direct fluvial CO ₂ partial pressure measurements and seasonally varying gas transfer velocity and river network surface area estimates to resolve reach-level seasonal variations of the flux at the global scale. The percentage of terrestrial primary production (GPP) shunted into rivers that ultimately contributes to CO ₂ evasion increases with discharge across regions, due to a stronger response in fluvial CO ₂ evasion to discharge than GPP. This highlights the importance of hydrology, in particular water throughput, in terrestrial–fluvial carbon transfers and the need to account for this effect in plumbing the terrestrial carbon budget.

Satellite estimates of inland water quality have the potential to vastly expand our ability to observe and monitor the dynamics of large water bodies. For almost 50 years, we have been able to remotely sense key water quality constituents like total suspended sediment, dissolved organic carbon, chlorophyll a, and Secchi disk depth. Nonetheless, remote sensing of water quality is poorly integrated into inland water sciences, in part due to a lack of publicly available training data and a perception that remote estimates are unreliable. Remote sensing models of water quality can be improved by training and validation on larger data sets of coincident field and satellite observations, here called matchups. To facilitate model development and deeper integration of remote sensing into inland water science, we have built AquaSat, the largest such matchup data set ever assembled. AquaSat contains more than 600,000 matchups, covering 1984–2019, of ground‐based total suspended sediment, dissolved organic carbon, chlorophyll a, and SDDSecchi disk depth measurements paired with spectral reflectance from Landsat 5, 7, and 8 collected within ±1 day of each other. To build AquaSat, we developed open source tools in R and Python and applied them to existing public data sets covering the contiguous United States, including the Water Quality Portal, LAGOS‐NE, and the Landsat archive. In addition to publishing the data set, we are also publishing our full code architecture to facilitate expanding and improving AquaSat. We anticipate that this work will help make remote sensing of inland water accessible to more hydrologists, ecologists, and limnologists while facilitating novel data‐driven approaches to monitoring and understanding critical water resources at large spatiotemporal scales.

The highest concentration of the world’s lakes are found in Arctic-boreal regions [C. Verpoorter, T. Kutser, D. A. Seekell, L. J. Tranvik, Geophys. Res. Lett. 41, 6396–6402 (2014)], and consequently are undergoing the most rapid warming [J. E. Overland et al., Arctic Report Card (2018)]. However, the ecological response of Arctic-boreal lakes to warming remains highly uncertain. Historical trends in lake color from remote sensing observations can provide insights into changing lake ecology, yet have not been examined at the pan-Arctic scale. Here, we analyze time series of 30-m Landsat growing season composites to quantify trends in lake greenness for >4 × 10⁵ waterbodies in boreal and Arctic western North America. We find lake greenness declined overall by 15% from the first to the last decade of analysis within the 6.3 × 10⁶-km² study region but with significant spatial variability. Greening declines were more likely to be found in areas also undergoing increases in air temperature and precipitation. These findings support the hypothesis that warming has increased connectivity between lakes and the land surface [A. Bring et al., J. Geophys. Res. Biogeosciences 121, 621–649 (2016)], with implications for lake carbon cycling and energy budgets. Our study provides spatially explicit information linking climate to pan-Arctic lake color changes, a finding that will help target future ecological monitoring in remote yet rapidly changing regions. Significance Arctic and boreal regions are undergoing dramatic warming and also possess the world’s highest concentration of lakes. However, ecological changes in lakes are poorly understood. We present a continental-scale trend analysis of satellite lake color in the green wavelengths, which shows declining greenness from 1984 to 2019 in Arctic-boreal lakes across western North America. Annual 30-m Landsat composites indicate lake greenness has decreased by 15%. Our findings show a relationship between lake color, rising air temperatures, and increasing precipitation, supporting the theory that warming may be increasing connectivity between lakes and surrounding landscapes. Overall, our results bring a powerful set of observations in support of the hypothesis that lakes are sentinels for global change in rapidly warming Arctic-boreal ecosystems.