From the River to the Sea: Modeling Coastal River, Wetland, and Shoreline Dynamics
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2017
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Complex feedbacks dominate landscape dynamics over large spatial scales (10s – 100s km) and over the long-term (10s – 100s yrs). These interactions and feedbacks are particularly strong at land-water boundaries, such as coastlines, marshes, and rivers. Water, although necessary for life and agriculture, threatens humans and infrastructure during natural disasters (e.g., floods, hurricanes) and through sea-level rise. The goal of this dissertation is to better understand landscape morphodynamics in these settings, and in some cases, to investigate how humans have influenced these landscapes (e.g., through climate or land-use change). In this work, I use innovative numerical models to study the larger-scale emergent interactions and most critical variables of these systems, allowing me to clarify the most important feedbacks and explore large space and time scales.
Chapter 1 focuses on understanding the shoreline dynamics of pocket (embayed) beaches, which are positioned between rocky headlands and adorn about half the world’s coastlines. Previous work suggested that seasonality or oscillations in climate indices control erosion and accretion along these shorelines; however, using the Coastline Evolution Model (CEM), I find that patterns of shoreline change can be found without systematic shifts in wave forcings. Using Principal Component Analysis (PCA), I identify two main modes of sediment transport dynamics: a shoreline rotation mode, which had been previously studied, and a shoreline “breathing” mode, which is newly discovered. Using wavelet analysis of the PCA mode time series, I find characteristic time scales of these modes, which emerge from internal system dynamics (rather than changes in the wave forcing; e.g., seasonality). To confirm the breathing mode’s existence, I retroactively identified this mode in observations of pocket beach shoreline change from different parts of the world. Characterization of these modes, as well as their timescales, better informs risk assessment and coastal management decisions along thinning shorelines, especially as climate change affects storminess and wave energy variations across the world.
Chapter 2 moves slightly inland to examine how coastal marshes, which provide numerous ecosystem services and are an important carbon sink, respond to climate change and anthropogenic influences. Specifically, I focus on how increasing concentrations of atmospheric CO2 affect marsh resilience to increased rates of sea-level rise relative to inorganic sediment availability and elevated nitrogen levels. Using a meta-analysis of the available literature for marsh plant biomass response to elevated levels of CO2 and nitrogen, I incorporated these effects into a coupled model of marsh vegetation and morphodynamics. Although nitrogen’s effect on biomass and marsh accretion rates is less clear, elevated CO2 causes a fertilization effect, increasing plant biomass, which enhances marsh accretion rates (through increased rates of both in- organic and organic sedimentation). Findings from the model experiments suggest that the CO2 fertilization effect significantly increases marsh resilience to sea-level rise; however, reduced inorganic sediment supply (e.g., through land-use change or damming) still remains a serious threat to marsh survival).
Almost half a billion people live on or near river deltas, which are flat, fertile landscapes that have long been ideal for human settlement, but are increasingly vulnerable to flooding. These landscapes are formed by the repeated stacking of sedimentary lobes, the location and size of which are formed by river channel avulsions, which occur when the river changes course relatively rapidly. Despite the importance of avulsions to delta morphodynamics, we do not fully understand their dynamics(specifically, avulsion location and timing). In order to investigate the relative influence of rivers and waves on delta morphology and avulsion processes, I develop the River Avulsion and Floodplain Evolution Model (RAFEM) and couple it to CEM to create a new morphodynamic river delta model.
In Chapter 3, I use the new coupled fluvial-coastal model to examine the upstream location of avulsions over a range of sea-level rise rates and wave energies. In model experiments, the longitudinal river profile adjusts as the river progrades, causing a preferential avulsion location where the river aggradation relative to the floodplain topography is most rapid. This avulsion length scale is a function of the amount of in-channel sedimentation required to trigger an avulsion, where a larger amount of aggradation required necessitates a greater amount of pre-avulsion progradation. If an avulsion is triggered once aggradation reaches half bankfull channel depth, the preferential length scale is around a backwater length, which scales well with laboratory and field observations.
In Chapter 4, I explore how a wide range sea-level rise rates and wave climates affect both delta morphology and avulsion dynamics with the coupled model. Surprisingly, I find that increasing sea-level rise rates do not always accelerate avulsions. In river-dominated deltas, avulsion time scales tend not to decrease, as upslope river mouth transgression counteracts base-level driven aggradation. I also find that both the sign and magnitude of the wave climate diffusivity affects both avulsion dynamics and large-scale delta morphology. My findings highlight not only important differences between river and wave-dominated deltas, but also prototypical deltas and those created in the lab. Because the wave climate, sea-level rise rate, and amount of in-channel aggradation required to trigger an avulsion all affect rates of autogenic variability operating within the delta, each of these forcings has important implication for avulsion dynamics and stratigraphic interpretation of paleo-deltaic deposits.
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Ratliff, Katherine Murray (2017). From the River to the Sea: Modeling Coastal River, Wetland, and Shoreline Dynamics. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/14458.
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