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Abstract 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. 

Abstract Global change may contribute to ecological changes in high-elevation lakes and reservoirs, but a lack of data makes it difficult to evaluate spatiotemporal patterns. Remote sensing imagery can provide more complete records to evaluate whether consistent changes across a broad geographic region are occurring. We used Landsat surface reflectance data to evaluate spatial patterns of contemporary lake color (2010–2020) in 940 lakes in the U.S. Rocky Mountains, a historically understudied area for lake water quality. Intuitively, we found that most of the lakes in the region are blue (66%) and were found in steep-sided watersheds (>22.5°) or alternatively were relatively deep (>4.5 m) with mean annual air temperature (MAAT) <4.5°C. Most green/brown lakes were found in relatively shallow sloped watersheds with MAAT ⩾4.5°C. We extended the analysis of contemporary lake color to evaluate changes in color from 1984 to 2020 for a subset of lakes with the most complete time series ( n = 527). We found limited evidence of lakes shifting from blue to green states, but rather, 55% of the lakes had no trend in lake color. Surprisingly, where lake color was changing, 32% of lakes were trending toward bluer wavelengths, and only 13% shifted toward greener wavelengths. Lakes and reservoirs with the most substantial shifts toward blue wavelengths tended to be in urbanized, human population centers at relatively lower elevations. In contrast, lakes that shifted to greener wavelengths did not relate clearly to any lake or landscape features that we evaluated, though declining winter precipitation and warming summer and fall temperatures may play a role in some systems. Collectively, these results suggest that the interactions between local landscape factors and broader climatic changes can result in heterogeneous, context-dependent changes in lake color. 

Abstract 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.