Channel morphology in alluvial rivers results from the interactions among the flow of water and sediment, the grain size distribution of the material in transport, and the characteristics of the materials making up the channel boundary. Many modern river management problems depend upon the ability to predict channel behavior in response to changes in the delivery of sediment. Sediment budgets provide a framework for explicitly evaluating the links between sediment delivery to and export from a river, and changes in storage. In the work presented here I have developed sediment budgets at three different spatial and temporal scales in an effort to gain insight to channel response to a change in sediment supply. In Chapter 2, I present a bed load budget for the Snake River in Grand Teton National Park (GTNP), Wyoming. The analysis was designed to evaluate the effects of 50 years of flow regulation on net sediment flux and, thus, sediment storage for the Snake River below Jackson Lake Dam. In Chapter 3 I present a sediment mass balance constructed for a single flood on an aggrading 4-km reach of the middle Provo River, Utah. Sediment accumulation in the Provo River had driven significant point bar growth, and the sediment budget was designed to explicitly link patterns in sediment flux with morphologic change. In Chapter 4, I present the results from a physical experiment designed to further evaluate the effect of changing sediment supply on point bar morphology in a single meander bend. The experiment was conducted in a field-scale flume, the Outdoor StreamLab (OSL), at the University of Minnesota. In each of the cases I present here, the channel was subject to sediment accumulation due to either an increase in sediment supply (Provo River and OSL) or a decrease in transport capacity (Snake River). The analyses provide insight into processes governing channel response to changes in sediment supply and highlight the inherent challenges and uncertainties associated with sediment budgets, regardless of the scale of the analysis.

This dissertation presents the results of a multi-year interdisciplinary study of a dynamic coastal dune ecosystem restoration effort in Pacific Rim National Park Reserve in British Columbia, Canada. The research is the result of a collaboration with Parks Canada Agency (PCA) who, under the Species at Risk Act (SARA), are mandated to restore habitat for SARA listed species within the dune complex. In response, PCA committed to, and implemented, a dynamic dune ecosystem restoration program that involved widespread removal of invasive vegetation (Ammophila spp.), transplanting of native vegetation, introduction of an endangered species, and volunteer programs to prevent re-growth of Ammophila. A comprehensive monitoring program was developed with PCA and undertaken by the author and PCA collaborators from start of the project in Summer 2008 to Fall of 2012. This dissertation is the product of independent research by the author carried out under the supervision of the advisory committee and does not reproduce written materials prepared for, or by, PCA. The dissertation consists of three separate journal manuscripts (the first two published by completion of the dissertation) that stand alone as independent investigations but are structured here to provide a natural progression of research findings and allow for an overall synthesis of ideas and broader contributions of the research. The dune restoration program afforded an opportunity to review restoration trends and methods and implement a strategy and monitoring protocols based on leading edge science. Accordingly, the first manuscript, Chapter 2, summarises recent trends in coastal dune restoration, discusses relevant research surrounding beach-dune morphodynamics and coastal dune activity, and reviews preliminary data from the project. The study identifies usable control data for the project and builds the criteria for assessing the project as a whole. The second manuscript, Chapter 3, presents and analyses the core data obtained for the dissertation - 5 years of geomorphic monitoring from detailed land surveys with 3 years of analysis of beach-foredune-transgressive dune sediment budget responses derived from aerial LiDAR surveys. This chapter identifies several trends in the dune systems’ response to restoration that, with reference to the indicators developed in Chapter 2, suggest improved levels of dynamism in the landscape. Finally, Chapter 4 (manuscript 3), extends the findings of the restoration study and utilises the rich data set obtained from the restoration program to develop a dynamic mapping technique that better conveys the spatial-temporal morphodynamic behaviour of dune ecosystems. The study comments broadly on the potential to apply these data and techniques to the study of disturbance events in beach-dune systems. The dissertation is concluded (Chapter 5) with an overall summary of key research objectives and contributions, and presents recommendations for future research. / Graduate

Fluvial sediment transport is a process that has long been important in managing water resources. While we intuitively recognize that increased flow amounts to increased sediment discharge, there is still significant uncertainty in the details. Because sediment transport---and in the context of this dissertation, bed load transport---is a strongly nonlinear process that is usually modeled using empirical or semi-empirical equations, there exists a large amount of uncertainty around model parameters, predictions, and model suitability. The focus of this dissertation is to develop and demonstrate a series of physically- and statistically-based sediment transport models that build on the scientific knowledge of the physics of sediment transport while evaluating the phenomenon in an environment that leads us to robust estimates of parametric, predictive, and model selection uncertainty. The success of these models permits us to put theoretically and procedurally sound uncertainty estimates to a process that is widely acknowledged to be variable and uncertain but has, to date, not developed robust statistical tools to quantify this uncertainty. This dissertation comprises four individual papers that methodically develop and prove the concept of Bayesian statistical sediment transport models. A simple pedagogical model is developed using synthetic and laboratory flume data---this model is then compared to traditional statistical approaches that are more familiar to the discipline. A single-fraction sediment transport model is developed on the Snake River to develop a probabilistic sediment budget whose results are compared to a sediment budget developed through an ad hoc uncertainty analysis. Lastly, a multi-fraction sediment transport model is developed in which multiple fractions of laboratory flume experiments are modeled and the results are compared to the standard theory that has been already published. The results of these models demonstrate that a Bayesian approach to sediment transport has much to offer the discipline as it is able to 1) accurately provide estimates of model parameters, 2) quantify parametric uncertainty of the models, 3) provide a means to evaluate relative model fit between different deterministic equations, 4) provide predictive uncertainty of sediment transport, 5) propagate uncertainty from the root causes into secondary and tertiary dependent functions, and 6) provide a means by which testing of established theory can be performed.

Fluvial sediment transport is a process that has long been important in managing water resources. While we intuitively recognize that increased flow amounts to increased sediment discharge, there is still significant uncertainty in the details. Because sediment transport---and in the context of this dissertation, bed load transport---is a strongly nonlinear process that is usually modeled using empirical or semi-empirical equations, there exists a large amount of uncertainty around model parameters, predictions, and model suitability. The focus of this dissertation is to develop and demonstrate a series of physically- and statistically-based sediment transport models that build on the scientific knowledge of the physics of sediment transport while evaluating the phenomenon in an environment that leads us to robust estimates of parametric, predictive, and model selection uncertainty. The success of these models permits us to put theoretically and procedurally sound uncertainty estimates to a process that is widely acknowledged to be variable and uncertain but has, to date, not developed robust statistical tools to quantify this uncertainty. This dissertation comprises four individual papers that methodically develop and prove the concept of Bayesian statistical sediment transport models. A simple pedagogical model is developed using synthetic and laboratory flume data---this model is then compared to traditional statistical approaches that are more familiar to the discipline. A single-fraction sediment transport model is developed on the Snake River to develop a probabilistic sediment budget whose results are compared to a sediment budget developed through an ad hoc uncertainty analysis. Lastly, a multi-fraction sediment transport model is developed in which multiple fractions of laboratory flume experiments are modeled and the results are compared to the standard theory that has been already published. The results of these models demonstrate that a Bayesian approach to sediment transport has much to offer the discipline as it is able to 1) accurately provide estimates of model parameters, 2) quantify parametric uncertainty of the models, 3) provide a means to evaluate relative model fit between different deterministic equations, 4) provide predictive uncertainty of sediment transport, 5) propagate uncertainty from the root causes into secondary and tertiary dependent functions, and 6) provide a means by which testing of established theory can be performed.