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Abstract Stream geomorphic change is highly spatially variable but critical to landform evolution, human infrastructure, habitat, and watershed pollutant transport. However, measurements and process models of streambank erosion and floodplain deposition and resulting sediment fluxes are currently insufficient to predict these rates in all perennial streams over large regions. Here we measured long-term lateral streambank and vertical floodplain change and sediment fluxes using dendrogeomorphology in streams around the U.S. Mid-Atlantic, and then statistically modeled and extrapolated these rates to all 74 133 perennial, nontidal streams in the region using watershed- and reach-scale predictors. Measured long-term rates of streambank erosion and floodplain deposition were highly spatially variable across the landscape from the mountains to the coast. Random Forest regression identified that geomorphic change and resulting fluxes of sediment and nutrients, for both streambank and floodplain, were most influenced by urban and agricultural land use and the drainage area of the upstream watershed. Modeled rates for headwater streams were net erosional whereas downstream reaches were on average net depositional, leading to regional cumulative sediment loads from streambank erosion (−5.1 Tg yr −1 ) being nearly balanced by floodplain deposition (+5.3 Tg yr −1 ). Geomorphic changes in stream valleys had substantial influence on watershed sediment, phosphorus, carbon, and nitrogen budgets in comparison to existing predictions of upland erosion and delivery to streams and of downstream sediment loading. The unprecedented scale of these novel findings provides important insights into the balance of erosion and deposition in streams within disturbed landscapes and the importance of geomorphic change to stream water quality and carbon sequestration, and provides vital understanding for targeting management actions to restore watersheds.
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Evaluation of Human Impact on Sediment Dynamics in an Intensively Managed Agricultural Watershed Using Distributed Modeling
ABSTRACT By altering hydrological and geomorphological processes at watershed scales, humans have substantially influenced the movement of sediment on Earth's surface. Despite widespread recognition of human impacts on erosion and deposition, few studies have assessed the magnitude of change in watershed‐scale sediment fluxes before and after the implementation of industrial agriculture and how agricultural development has altered the spatial distribution of sediment fluxes throughout watersheds. This study uses a modeling approach to explore changes in sediment fluxes before and after agricultural development in the upper Sangamon River Basin—an agricultural watershed in the midwestern United States. Comparison of model predictions with river hydrological and sediment data and with information on soil erosion and floodplain sedimentation shows the model accurately captures contemporary fluxes of water and sediment. To assess human impact, native land‐cover conditions are used to estimate the magnitude and spatial distribution of sediment fluxes before the landscape was transformed by farming practices. Results suggest that sediment delivery from hillslopes to streams in this low relief watershed has increased 11‐fold and the sediment load in streams has increased eight‐fold since European settlement. Floodplain sedimentation has also increased dramatically, a finding consistent with recent estimates of post‐settlement alluvium accumulation rates. The proportion of sediment exported from the basin is now slightly greater than it was in the 1800s. Overall, the model results indicate that humans have greatly enhanced the movement and storage of sediment within the upper Sangamon River basin.
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- Award ID(s):
- 2012850
- PAR ID:
- 10596099
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- River Research and Applications
- Volume:
- 41
- Issue:
- 8
- ISSN:
- 1535-1459
- Format(s):
- Medium: X Size: p. 1616-1629
- Size(s):
- p. 1616-1629
- Sponsoring Org:
- National Science Foundation
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