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.
Because of the high logistical and financial costs of direct measurements of riverine suspended sediment, remote sensing is increasingly used to supplement the direct‐observation record. The accuracy of this method is poorly constrained, and its potential as a tool for understanding river sediment transport is thus limited. We introduce and apply global‐scale methods for estimating depth‐integrated suspended‐sediment concentrations (SSCs) using Landsat 5 and 7 satellite imagery calibrated with 134,697 in situ SSC measurements. We account for river‐to‐river variability in the relationship between water optical properties and SSC by (a) categorizing rivers using unsupervised K‐means clustering and/or (b) correcting calibration estimates for individual rivers using local in situ measurements of SSC, suspended‐sediment grain size, and percent organic carbon (POC). In the absence of site‐specific in situ SSC measurements, clustering rivers reduces the average relative error of SSC estimates from 97% to 73%. We show that as few as five site‐specific in situ measurements combined with our algorithm further reduces average relative error to 49% and average relative at‐a‐station bias in SSC to 7%. Little additional improvement in accuracy or bias is gained by including measurements of percent sand or POC of the suspended sediment. Since only modest additional accuracy is gained after ~5–10 paired in situ SSC measurements and satellite observations, sampling campaigns should prioritize limited sampling at diverse locations rather than intensive sampling at a limited number of sites. In addition, we publish standalone calibrations for 151 rivers made solely with in situ SSC measurements local to those sites.
more » « less- NSF-PAR ID:
- 10446792
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Earth Surface
- Volume:
- 125
- Issue:
- 7
- ISSN:
- 2169-9003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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