Jean Morin

Spectral gradients of downwelling light in a fluvial lake (Lake Saint-Pierre, St-Lawrence River)

Large fluvial lakes are understudied with respect to their underwaterlight climates. Fluvial lakes pose unique challenges for photobiologistsinterested in the interactions amongst light climate, nutrients and microbialcommunity structure and biodiversity. This is because fluvial lakes are typifiedby highly dynamic flow regimes often incorporating different inflows anddischarges each characterized by their own unique physico-chemical composition.These compositional characteristics include the concentrations of chromophoricdissolved organic matter (CDOM), suspended solids, and pigments such aschlorophyll. Together these factors contribute to the distribution andcomposition of the water masses that make up fluvial lakes. These water masses,in turn, flow over lakebeds that are typically complex in their morphometry andfeature extensive macrophyte beds, further enhancing the habitat heterogeneityof these ecosystems. We here report on the spectral attenuation of ultravioletradiation (UVR = 280–400 nm) and photosyntheticallyactive radiation (PAR = 400–700 nm) in the three mainwater masses of Lake Saint-Pierre and evaluate the relative contribution ofCDOM, and particulate organic material to UVR attenuation. We demonstrate thatUVR penetrates 18 to 30% of the water column (1% penetration depth) in the LakeSaint-Pierre ecosystem, and show how the underwater spectral UVR varies withinthe three water masses.

Temporal and spatial variability of tidal‐fluvial dynamics in the St. Lawrence fluvial estuary: An application of nonstationary tidal harmonic analysis

Predicting tides in upstream reaches of rivers is a challenge, because tides are highly nonlinear and nonstationary, and accurate short-time predictions of river flow are hard to obtain. In the St. Lawrence fluvial estuary, tide forecasts are produced using a one-dimensional model (ONE-D), forced downstream with harmonic constituents, and upstream with daily discharges using 30 day flow forecasts from Lake Ontario and the Ottawa River. Although this operational forecast system serves its purpose of predicting water levels, information about nonstationary tidal-fluvial processes that can be gained from it is limited, particularly the temporal changes in mean water level and tidal properties (i.e., constituent amplitudes and phases), which are function of river flow and ocean tidal range. In this paper, a harmonic model adapted to nonstationary tides, NS_TIDE, was applied to the St. Lawrence fluvial estuary, where the time-varying external forcing is directly built into the tidal basis functions. Model coefficients from 13 analysis stations were spatially interpolated to allow tide predictions at arbitrary locations as well as to provide insights into the spatiotemporal evolution of tides. Model hindcasts showed substantial improvements compared to classical harmonic analyses at upstream stations. The model was further validated by comparison with ONE-D predictions at a total of 32 stations. The slightly lower accuracy obtained with NS_TIDE is compensated by model simplicity, efficiency, and capacity to represent stage and tidal variations in a very compact way and thus represents a new means for understanding tidal rivers.

Emergence of New Explanatory Variables for 2D Habitat Modelling in Large Rivers: The St. Lawrence Experience

The St. Lawrence River is one of the most important large rivers in North America. This 600-km long watercourse is characterized by a high degree of physical heterogeneity, including fast moving narrow reaches separated by fluvial lakes reaching 10 km in width. The mean annual discharge from the outflow of Lake Ontario is 7500 m3/s and has been managed for hydropower and transportation since the 1960s. With the management plan currently under review an effort is being made to include criteria that take into account the impacts of regulation on the biotic components of the river ecosystem. High resolution 2D spatial modelling of river habitats and floodplains is a powerful tool to make quantitative impact assessments of the biota. Physical variables commonly used in habitat models include depth, velocity and substrate size. In addition, other abiotic variables such as wind-generated wave stress, light penetration, water temperature, sedimentation of fine particles, specific discharge and bottom slope, that define the local ’hydroperiod’ have been suggested. Our proposed approach integrates abiotic data obtained from numerical models, field measurements and biological information to overcome problems inherent in temporally and spatially heterogeneous river systems. This approach was tested with a habitat model applied to submerged aquatic vegetation, various categories of wetlands, benthic organisms and various life stages of a number offish species. Logistic regression is the statistical model currently used to synthesize the relationships between abiotic and biotic factors. The short-term objective of this modelling exercise in the St. Lawrence River is to understand the underlying links between fluvial physics and biota. A longer-term objective is to provide a real-time analysis of key variables and to quantify the links between trophic levels.

Freshwater wetlands: fertile grounds for the invasive Phragmites australis in a climate change context.

Climate change will likely affect flooding regimes, which have a large influence on the functioning of freshwater riparian wetlands. Low water levels predicted for several fluvial systems make wetlands especially vulnerable to the spread of invaders, such as the common reed (Phragmites australis), one of the most invasive species in North America. We developed a model to map the distribution of potential germination grounds of the common reed in freshwater wetlands of the St. Lawrence River (Québec, Canada) under current climate conditions and used this model to predict their future distribution under two climate change scenarios simulated for 2050. We gathered historical and recent (remote sensing) data on the distribution of common reed stands for model calibration and validation purposes, then determined the parameters controlling the species establishment by seed. A two-dimensional model and the identified parameters were used to simulate the current (2010) and future (2050) distribution of germination grounds. Common reed stands are not widespread along the St. Lawrence River (212 ha), but our model suggests that current climate conditions are already conducive to considerable further expansion (>16,000 ha). Climate change may also exacerbate the expansion, particularly if river water levels drop, which will expose large bare areas propitious to seed germination. This phenomenon may be particularly important in one sector of the river, where existing common reed stands could increase their areas by a factor of 100, potentially creating the most extensive reedbed complex in North America. After colonizing salt and brackishwater marshes, the common reed could considerably expand into the freshwater marshes of North America which cover several million hectares. The effects of common reed expansion on biodiversity are difficult to predict, but likely to be highly deleterious given the competitiveness of the invader and the biological richness of freshwater wetlands.

A Robust Estimation Method for Correcting Dynamic Draft Error in PPK GPS Elevation Using ADCP Tilt Data

AbstractMeasuring temporal and spatial variations in water level with high resolution and accuracy can provide fundamental insights into the hydrodynamics of marine and riverine systems. Real-time kinematic global positioning systems (RTK GPS), and by extension postprocessed kinematic (PPK) positioning, have provided the opportunity to achieve this goal, by allowing fast and straightforward measurements with subdecimeter accuracy. However, boat-mounted GPS are subject to movements of the water surface (e.g., waves, long-period heaves) as well as to the effects of dynamic draft. The latter contaminate the records and need to be separated and removed from the data. A method is proposed to postcorrect the elevation data using tilt information measured by an attitude sensor—in this case, an acoustic Doppler current profiler (ADCP) equipped with internal pitch and roll sensors. The technique uses iteratively reweighted least squares (IRLS) regressions to determine the position of the center of rotation (COR) o...

Hydrodynamic Modeling of the St. Lawrence Fluvial Estuary. II: Reproduction of Spatial and Temporal Patterns.

This is the second part of an investigation aimed at documenting the tidal hydrodynamics of the St. Lawrence fluvial estuary (SLFE). In Part I, the calibration and validation of a high-resolution, two-dimensional (2D), time-dependent hydrodynamic model of the SLFE was presented. Herein, the process-based (structural) validation procedure used to quantitatively assess the ability of the model to reproduce spatial and temporal patterns observed in the field data is presented. Tidal and flow features were found to be reproduced satisfactorily in terms of their lateral and longitudinal variability at both the intratidal and fortnightly scales. These properties can be used to describe the real system dynamics, including flooding–drying processes, tidal propagation and modulation, and transient momentum balance, providing insights into the general physical processes of the SLFE and of large tidal rivers globally.

Hydrodynamic Modeling of the St. Lawrence Fluvial Estuary. I: Model Setup, Calibration, and Validation

In this study, a high-resolution, two-dimensional (2D), time-dependent hydrodynamic model of the St. Lawrence fluvial estuary was developed with the objective of documenting the tidal hydrodynamics of this complex yet poorly understood region. The hydrodynamic model solves the shallow-water equations over a finite-element–discretized domain, with an average spatial resolution of 50 m, and includes a drying–wetting component for the treatment of shallow intertidal areas. The numerical terrain model is composed of high-density topographic data and detailed friction fields associated with bottom substrate and macrophytes. Calibration and validation were carried out using recently acquired data for water level and velocity. Results show very good accuracy in water levels, with prediction skills higher than 0.99 at all stations (where a skill of 1 means perfect agreement between model and observations in terms of their relative average error) and root-mean-square errors (RMSEs) less than 5% of local tidal ranges downstream; at upstream stations where tidal ranges are significantly reduced, RMSEs were lower than 6 cm. Discharges were reproduced with similarly good accuracy, with errors lower than 6% of the maximum observed discharges at 11 of the 13 surveyed transects; the two remaining sections are subject to larger interpolation and bathymetric uncertainties. In this paper, critical aspects of model development are discussed, including the 2D approximation, temporal and spatial resolution, bathymetric uncertainty, error in the boundary conditions, and calibration under nonstationary conditions. This work is the first part of a two-part investigation serving as a methodological framework for model setup, calibration, and validation in large tidal rivers.

Reconstruction of Tidal Discharges in the St. Lawrence Fluvial Estuary: The Method of Cubature Revisited

Knowledge of tidal flows in rivers and estuaries is often scarce yet vital in determining flushing properties and sediment transport rates. While many rivers still remain ungauged, methodological difficulties often arise in gauged systems, resulting in short flow records compared to historical water level data. Notwithstanding, discharge reconstructions in estuaries are possible using indirect methods based on long‐term tidal data. In this paper, we revisit the method of cubature, integrating the continuity equation for discharges at different sections. The method consists in computing temporal changes in water volume from simultaneous tidal heights readings along the river and storage width estimations. These water balance estimates remain challenging to produce, because they require spatial interpolation of gappy tidal records and an accurate representation of inundated areas over time. Improvements on the method are made by using a 1D nonstationary tidal harmonic model that provides continuous tidal data along the estuary, with no temporal or spatial gaps. Secondly, a 2D finite element discretization is used to compute the time‐varying wetted surface area, relying on detailed topographic data over intertidal flats. The method is applied to the St. Lawrence fluvial estuary (SLFE) and validated against discharge data collected along 9 cross‐sections of the river, reaching relative RMSE below 4% of the diurnal tidal discharge range at downstream locations and below 9% upstream. One‐year reconstructions conducted in the SLFE also show the potential of the method to reproduce the tidal discharge variability along the tidal‐river continuum, for a wide range of temporal scales.