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Abstract Inland waters emit significant amounts of carbon dioxide (CO₂) to the atmosphere; however, the global magnitude and source distribution of inland water CO₂emissions remain uncertain. These fluxes have previously been “statistically upscaled” by independently estimating dissolved CO₂concentrations and gas exchange velocities to calculate fluxes. This scaling, while robust and defensible, has known limitations in representing carbon source limitations and spatial variability. Here, we develop and calibrate a CO₂transport model for the continental United States, simulating carbon transport and transformation in >22 million hydraulically connected rivers, lakes, and reservoirs. We estimate 25% lower CO₂fluxes compared to upscaling estimates forced by the same observational calibration data. While precise CO₂source distribution estimates are limited by the resolution of model parameterizations, our model suggests that stream corridor CO₂production dominates over groundwater inputs at the continental scale. Our results further suggest that the lack of observational networks for groundwater CO₂and scalable metabolic models of aquatic CO₂production remain the most salient barriers to further coupling of our model with other Earth system components. 

Here we observe and predict the location of beaded stream catchments throughout the pan-Arctic domain by combining the location of known beaded streams with recent advances in computer vision and high-resolution (3 meter (m)) satellite imagery. Specifically, we use the location of known existing beaded streams to classify potential river catchments as beaded or non-beaded, then download high resolution imagery across those regions, and use the latest You-Only-Look-Once (YOLO) object detection algorithm to identify beaded streams throughout the pan-Arctic, estimating 138,500 ± 43,700 beaded catchments globally, occurring in an estimated one third of all pan-Arctic catchments. In the largest dataset of beaded streams to date (Arp et al., 2015), only 375 catchments that contain beaded streams were identified, thus our estimate significantly expands our current understanding of the location and prevalence of Arctic beaded streams. Data is accessible through the alternate identifier link on Zenodo: https://doi.org/10.5281/zenodo.7223256 

Abstract Arctic rivers drain ~15% of the global land surface and significantly influence local communities and economies, freshwater and marine ecosystems, and global climate. However, trusted and public knowledge of pan-Arctic rivers is inadequate, especially for small rivers and across Eurasia, inhibiting understanding of the Arctic response to climate change. Here, we calculate daily streamflow in 486,493 pan-Arctic river reaches from 1984-2018 by assimilating 9.18 million river discharge estimates made from 155,710 satellite images into hydrologic model simulations. We reveal larger and more heterogenous total water export (3-17% greater) and water export acceleration (factor of 1.2-3.3 larger) than previously reported, with substantial differences across basins, ecoregions, stream orders, human regulation, and permafrost regimes. We also find significant changes in the spring freshet and summer stream intermittency. Ultimately, our results represent an updated, publicly available, and more accurate daily understanding of Arctic rivers uniquely enabled by recent advances in hydrologic modeling and remote sensing. 

The magnitude of stream and river carbon dioxide (CO 2 ) emission is affected by seasonal changes in watershed biogeochemistry and hydrology. Global estimates of this flux are, however, uncertain, relying on calculated values for CO 2 and lacking spatial accuracy or seasonal variations critical for understanding macroecosystem controls of the flux. Here, we compiled 5,910 direct measurements of fluvial CO 2 partial pressure and modeled them against watershed properties to resolve reach-scale monthly variations of the flux. The direct measurements were then combined with seasonally resolved gas transfer velocity and river surface area estimates from a recent global hydrography dataset to constrain the flux at the monthly scale. Globally, fluvial CO 2 emission varies between 112 and 209 Tg of carbon per month. The monthly flux varies much more in Arctic and northern temperate rivers than in tropical and southern temperate rivers (coefficient of variation: 46 to 95 vs. 6 to 12%). Annual fluvial CO 2 emission to terrestrial gross primary production (GPP) ratio is highly variable across regions, ranging from negligible (<0.2%) to 18%. Nonlinear regressions suggest a saturating increase in GPP and a nonsaturating, steeper increase in fluvial CO 2 emission with discharge across regions, which leads to higher percentages of GPP being shunted into rivers for evasion in wetter regions. This highlights the importance of hydrology, in particular water throughput, in routing terrestrial carbon to the atmosphere via the global drainage networks. Our results suggest the need to account for the differential hydrological responses of terrestrial–atmospheric vs. fluvial–atmospheric carbon exchanges in plumbing the terrestrial carbon budget. 

Remote sensing of river discharge (RSQ) is a burgeoning field rife with innovation. This innovation has resulted in a highly non-cohesive subfield of hydrology advancing at a rapid pace, and as a result misconceptions, mis-citations, and confusion are apparent among authors, readers, editors, and reviewers. While the intellectually diverse subfield of RSQ practitioners can parse this confusion, the broader hydrology community views RSQ as a monolith and such confusion can be damaging. RSQ has not been comprehensively summarized over the past decade, and we believe that a summary of the recent literature has a potential to provide clarity to practitioners and general hydrologists alike. Therefore, we here summarize a broad swath of the literature, and find after our reading that the most appropriate way to summarize this literature is first by application area (into methods appropriate for gauged, semi-gauged, regionally gauged, politically ungauged, and totally ungauged basins) and next by methodology. We do not find categorizing by sensor useful, and everything from un-crewed aerial vehicles (UAVs) to satellites are considered here. Perhaps the most cogent theme to emerge from our reading is the need for context. All RSQ is employed in the service of furthering hydrologic understanding, and we argue that nearly all RSQ is useful in this pursuit provided it is properly contextualized. We argue that if authors place each new work into the correct application context, much confusion can be avoided, and we suggest a framework for such context here. Specifically, we define which RSQ techniques are and are not appropriate for ungauged basins, and further define what it means to be ‘ungauged’ in the context of RSQ. We also include political and economic realities of RSQ, as the objective of the field is sometimes to provide data purposefully cloistered by specific political decisions. This framing can enable RSQ to respond to hydrology at large with confidence and cohesion even in the face of methodological and application diversity evident within the literature. Finally, we embrace the intellectual diversity of RSQ and suggest the field is best served by a continuation of methodological proliferation rather than by a move toward orthodoxy and standardization.