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Humans have drastically disrupted the global sediment cycle. Suspended sediment flux and concentration are key controls over both river morphology and river ecosystems. Our ability to understand sediment dynamics within river corridors is limited by observations. Here, we present RivSed, a database of satellite observations of suspended sediment concentration (SSC) from 1984 to 2018 across 460 large (>60 m wide) US rivers that provides a new, spatially explicit view of river sediment. We found that 32% of US rivers have a declining temporal trend in sediment concentration, with a mean reduction of 40% since 1984, whereas only 2% have an increasing trend. Most rivers (52%) show decreasing sediment concentration longitudinally moving downstream, typically due to a few large dams rather than the accumulated effect of many small dams. Comparing our observations with modeled ‘pre-dam’ longitudinal SSC, most rivers (53%) show different patterns. However, contemporary longitudinal patterns in concentration are remarkably stable from year to year since 1984, with more stability in large, highly managed rivers with less cropland. RivSed has broad applications for river geomorphology and ecology and highlights anthropogenic effects on river corridors across the US.

Accurately estimating stream discharge is crucial for many ecological, biogeochemical, and hydrologic analyses. As of September 2022, The National Ecological Observatory Network (NEON) provided up to 5 years of continuous discharge estimates at 28 streams across the United States. NEON created rating curves at each site in a Bayesian framework, parameterized using hydraulic controls and manual measurements of discharge. Here we evaluate the reliability of these discharge estimates with three approaches. We (1) compared predicted to observed discharge, (2) compared predicted to observed stage, and (3) calculated the proportion of discharge estimates extrapolated beyond field measurements. We considered 1,523 site-months of continuous streamflow predictions published by NEON. Of these, 39% met our highest quality criteria, 11% fell into an intermediate classification, and 50% of site-months were classified as unreliable. We provided diagnostic metrics and categorical evaluations of continuous discharge and stage estimates by month for each site, enabling users to rapidly query for suitable NEON data.

Rivers are among the most imperiled ecosystems globally, yet we do not have broad‐scale understanding of their changing ecology because most are rarely sampled. Water color, as perceived by the human eye, is an integrative measure of water quality directly observed by satellites. We examined patterns in river color between 1984 and 2018 by building a remote sensing database of surface reflectance, RiverSR, extracted from 234,727 Landsat images covering 108,000 kilometers of rivers > 60 m wide in the contiguous USA. We found 1) broad regional patterns in river color, with 56% of observations dominantly yellow and 38% dominantly green; 2) river color has three distinct seasonal patterns that were synchronous with flow regimes; 3) one third of rivers had significant color shifts over the last 35 years. RiverSR provides the first map of river color and new insights into macrosystems ecology of rivers.

The rivers of Appalachia (United States) are among the most biologically diverse freshwater ecosystems in the temperate zone and are home to numerous endemic aquatic organisms. Throughout the Central Appalachian ecoregion, extensive surface coal mines generate alkaline mine drainage that raises the pH, salinity, and trace element concentrations in downstream waters. Previous regional assessments have found significant declines in stream macroinvertebrate and fish communities after draining these mined areas. Here, we expand these assessments with a more comprehensive evaluation across a broad range of organisms (bacteria, algae, macroinvertebrates, all eukaryotes, and fish) using high‐throughput amplicon sequencing of environmental DNA (eDNA). We collected water samples from 93 streams in Central Appalachia (West Virginia, United States) spanning a gradient of mountaintop coal mining intensity and legacy to assess how this land use alters downstream water chemistry and affects aquatic biodiversity. For each group of organisms, we identified the sensitive and tolerant taxa along the gradient and calculated stream specific conductivity thresholds in which large synchronous declines in diversity were observed. Streams below mining operations had steep declines in diversity (−18 to −41%) and substantial shifts in community composition that were consistent across multiple taxonomic groups. Overall, large synchronous declines in bacterial, algal, and macroinvertebrate communities occurred even at low levels of mining impact at stream specific conductivity thresholds of 150–200 µS/cm that are substantially below the current U.S. Environmental Protection Agency aquatic life benchmark of 300 µS/cm for Central Appalachian streams. We show that extensive coal surface mining activities led to the extirpation of 40% of biodiversity from impacted rivers throughout the region and that current water quality criteria are likely not protective for many groups of aquatic organisms.