Spatial-temporal migration dynamics of submarine dunes in St. Lawrence River

The seabed of the St. Lawrence River in Quebec City is a high-energy fluvial sedimentary environment with a mean annual discharge of 12,600 m
³
/s, the second largest in North America [1]. Significant changes can be observed in the seabed over short time scales, i.e, daily to weekly. These bathymetric changes on the bottom of St. Lawrence River and estuary represent a constant risk for the navigation, considering that surveys cannot be undertaken between November and April. Prediction models are necessary to anticipate the risks and the critical changes in the seabed. The development of a prediction model of dunes migration is the focus of this research. To better understand the dunes migration in the seabed, it is necessary to estimate thee quality of the acquired data in the context of the dunes. Many research works developed the error budget to bathymetric data, such as [2], [3] and [4]. The Combined Standard Measurement Uncertainty (CSMU) model presented in this paper considers the uncertainties associated with the observations made by the bathymetric system as well as the geometric uncertainty as developed by [5] for Mobile LiDAR Systems.