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Sediment Mobilization from Streambank Failures: Model Development and Climate Impact StudiesStryker, Jody Juniper 01 January 2017 (has links)
This research incorporates streambank erosion and failure processes into a distributed watershed model and evaluates the impacts of climate change on the processes driving streambank sediment mobilization at a watershed scale. Excess sediment and nutrient loading are major water quality concerns for streams and receiving waters. Previous work has established that in addition to surface and road erosion, streambank erosion and failure are primary mechanisms that mobilize sediment and nutrients from the landscape. This mechanism and other hydrological processes driving sediment and nutrient transport are likely to be highly influenced by anticipated changes in climate, particularly extreme precipitation and flow events. This research has two primary goals: to develop a physics-based watershed model with more inclusive representation of sediment by including simulation of streambank erosion and geotechnical failure; and to investigate the impacts of climate change on unstable streams and suspended sediment mobilization by overland erosion, erosion of roads, and the erosion as well as failure of streambanks. This advances mechanistic simulation of suspended sediment mobilization and transport from watersheds, which is particularly valuable for investigating the impacts of climate and land use changes, as well as extreme events.
Model development involved coupling two existing physics-based models: the Bank Stability and Toe Erosion Model (BSTEM) and the Distributed Hydrology Soil Vegetation Model (DHSVM). This approach simulates streambank erosion and failure in a spatially explicit environment. The coupled model is applied to the Mad River watershed in central Vermont as a test case. I then use the calibrated Mad River model to predict the response in watershed sediment loading to future climate scenarios that specifically represent local temperature and precipitation trends for the northeastern US, particularly changing trends in the frequency and magnitude of extreme precipitation.
Overall the streambank erosion and failure processes are captured in the coupled model approach. Although the presented calibration of the model underestimates suspended sediment concentrations resulting from relatively small storm/flow events, it still improves prediction of cumulative loads and in some cases suspended sediment concentrations during elevated flow events in comparison to model results without including BSTEM. Increases in temperature affect the timing and magnitude of snow melt and spring flows, as well as associated sediment mobilization, in the watershed. Increases in annual precipitation and in extreme precipitation events produce increases in annual as well as peak discharge and sediment loads in the watershed.
This research adds to the body of evidence indicating that streambank erosion and failure can be a major source of suspended sediment, and thereby a major source of phosphorus as well. It also shows that local climate trends in the Northeast are likely to result in higher peak discharges and sediment yields from meso-scale, high-gradient watersheds that encompass headwater forested streams and agricultural floodplains. One limitation was that we could not drive the model with meteorological data that represented changes in both temperature and precipitation, highlighting the need for improved climate predictions. This coupled model approach could be parameterized for alternative watersheds and be re-applied to answer various questions related to erosion processes and sediment transport in a watershed. These findings have important implications for resource allocation and targeted watershed management strategies.
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Analysis of Monthly Suspended Sediment Load in Rivers and Streams Using Linear Regression and Similar Precipitation DataEchiejile, Faith 18 August 2021 (has links)
No description available.
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Analysis of Suspended Sediment Loads in Streams and Rivers using Linear Regression and Pearson CorrelationSakwe, Chantal Wase January 2015 (has links)
No description available.
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