Ice jam floods are frequent occurrences throughout the Saint John River. Spring ice breakup, due to the freshet, are the most common and damaging. A coupled two-dimensional hydro and ice dynamics model was used to study the breakup and jamming processes on the 64 km reach of the Saint John River between Grand Falls and the Beechwood Generation Station. The model simulated the evolution of the 2012 ice breakup and jamming event, which caused record high flooding. The simulated results compared well with observed data and provided detailed information on the breakup processes. The study showed that both failure due to accumulation of ice at the cover leading edge and failure due to high rates of water level change from surges were important ice breakup processes. It was also found that one of the most significant factors in the flooding at Perth–Andover was the release of ice from above Grand Falls.
Many hydrologic studies that are the basis for water resources planning and management rely on streamflow information. Calibration and use of hydrologic models to extend flow series based on rainfall data, perform flood frequency analysis, or develop flood maps for land use planning and design of engineering works, such as channels, dams, bridges, and water intake, are examples of such studies. In most real-world engineering applications, errors in flow data are neglected or not adequately addressed. However, because flows are estimated based on the water level measurements by fitted rating curves, they can be subjected to significant uncertainties. How large these uncertainties are and how they can impact the results of such studies is a topic of interest for researchers, practitioners, and decision-makers of water resources. The quantitative assessment of these uncertainties is important to obtain a more realistic description of many water resources related studies. River restoration in many areas is limited by data availability and funding. A means to assess the uncertainty of flow data to be used in the design and analysis of river restoration projects that is cost effective and has minimal data requirements would greatly improve the reliability of river restoration design. This paper proposes an assessment of how uncertainties related to rating curves and frequency analysis may affect the results of flood mapping in a real-world application to a small watershed with limited data. A Bayesian approach was performed to obtain the posterior distributions for the model parameters and the HEC-RAS (Hydrologic Engineering Center-River Analysis System) hydraulic model was used to propagate the uncertainties in the water surface elevation profiles. The analysis was conducted using freely available data and open source software, greatly reducing traditional analysis costs. The results demonstrate that for the study case the uncertainty related to the frequency analysis study impacted the water profiles more significantly than the uncertainty associated with the rating curve.
Cross vane structures aim to reduce near-bank shear and increase center channel flow intensity to retain flood flow and maintain sediment transport capacity in stream channels. These in-stream structures have been widely applied for river management, but how they interact with the local ice regime is poorly understood. This paper presents a numerical model study of the interaction of cross vane structures with sediment and ice using a two-dimensional coupled river ice-sediment dynamic model. The model was used to simulate a variety of ice and flow conditions to show how cross vanes affect sediment and ice processes. The study showed the design of cross vane structures in cold region rivers should consider the ice effects, especially the increasing potential of ice jam formation and related bed change.
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