Lukas Mueller, Megan Iun, Asal Montakhab and Bruce MacVicar

University of Waterloo, Waterloo, Canada

In rivers it is difficult to quantify bedform dynamics during storm events. Direct observation of sediment pathways would provide insight into the mechanisms that underly bedform formation and destruction. In the current study, our objective was to visualize these processes in a meandering pool-riffle system with partial bed cover. We used a physical 1:45 scaled model of Toronto’s Wilket Creek to simulate storm events during which riffles formed as connective bedforms between alternate point bars. Sediment export was weighed and sieved to create a grain size distribution, while the bed’s topography was quantified using Structure-from-Motion techniques. Sediment pathways were observed using a novel technique, where regions of interest were filmed under ultra-violet light, illuminating painted tracers for which the pathways were extracted using Lagrangian tracking software. Results show that the area of active transport is limited to a narrow portion of the channel width, laterally increasing with flood stage. At low flow, transport is routed along the toe of point bars, while no particles travel into the region of the pool where the bed is uncovered. Riffles are rarely observed at these stages. As the flow increases, the lateral extent of active transport expands to include the higher parts of the bars, while connective riffles grow in areal extent and height. These results indicate that sediment-routing is a dominant mechanism behind the formation and maintenance of riffles in meandering rivers. Future work to quantify these processes will increase the effectiveness and longevity of river remediation design.

Victoria Barlow¹, Peter Ashmore¹ and Bruce MacVicar²

¹University of Western Ontario, London, Ontario, Canada

²University of Waterloo, Waterloo, Ontario, Canada

Urbanization disrupts the natural stability of river systems. Increased runoff volumes and peak flows due to the expansion of impervious surfaces cause changes to channel morphology, such as channel widening. Understanding and predicting historical changes is important for understanding channel response and risks of future flooding and erosion. Highland Creek, located in Toronto, Ontario, provides an example of an extremely well documented river that has experienced massive land cover changes due to urbanization over the past 6-7 decades. A longitudinal study of channel change was completed based on aerial imagery interpretations over multiple epochs beginning in a pre-urban to fully urban state of the watershed. These observational results were compared with the results of the predictive GIS-based Stream Power Index for Networks (SPIN) tool. SPIN was designed to spatially predict stream power and changes in stream power along a river network in response to land-use change such as urbanization. River channel response is physically controlled by changes to stream power so mapping stream power changes can form the basis for predicting morphologic changes which may be spatially and temporally variable as land-use changes. In addition to the original output of the SPIN tool, empirical and rational width equations were included that use stream power to predict width changes along the channel as a function of land-use change. Predictions show that as urban land cover expands throughout the watershed, stream power and width values will increase. This result is also reflected in the observed analysis; however, widths remain constant in reaches that have been heavily engineered. Overall, the predictive methods were relatively accurate in estimating the trend of morphologic change over time and locating vulnerable areas of change along a river system. The method has great potential for application in the management of future channels within urbanizing environments.

Karl Grambow and Bahram Gharabaghi

University of Guelph, Guelph, ON, Canada

Ice cover formation and ice thickness in Canadian rivers and other cold climates can be dangerous. When ice cover breaks in the spring it can be challenging to predict the timing and potential flooding severity. Determining the timing of a breakup event is critical for planning and mitigating flooding and subsequent damages. The goal of this study was to find an accurate way to predict a river’s ice breakup event to give early warning and improve policies around such events. Current ice thickness modelling for river ice cover was improved, then the stability of the ice cover was determined to predict break up timing. Hydrometric monitoring was performed for both the Thames River and the Humber River in Ontario, Canada, alongside the compilation of a large dataset for different size rivers from the Canadian River Ice Database. A large variety of Canada’s rivers were included, such as the Slave, Saskatchewan, Saugeen, and Grand Rivers. By combining the traditional ice thickness estimation technique of Cumulative Degree-Days of Freezing, hydraulic flow properties of a river, and the Generalize Method of Data Handling machine learning, a new, more accurate formula for ice thickness estimation was developed. This new method was used in conjunction with an ice stability index to forecast the timing of the ice breakup and jamming events for rivers of varying sizes. Along with ice breakup forecasting, drone photogrammetry was employed to accurately construct 3D models of the ice cover and ice-jam events. This research contributes to the application of new machine learning and remote sensing techniques in river ice analysis, along with providing more information for flood risk mitigation and policy creation for ice covered rivers in a variety rivers and watersheds.

Camille Chouinard, Guilherme Corrêa and Lisa Whitwell

Niagara College, Niagara-on-the-Lake, Canada

The Amaolo Nature Sanctuary, a former agricultural land within the jurisdiction of the City of Hamilton, was donated to Hamilton Naturalists’ Club (HNC) in 2010. A stream, belonging to the Fairchild Creek sub-watershed, flows across the property. By the 1940s, the stream was channelized for agricultural purposes and later, two other streams were excavated. Soil was placed on the stream banks, creating artificial mounds across the floodplain. Combined with steep banks, the connectivity of the floodplain was negatively impacted. HNC intends to restore the floodplain and requested a study conducted by Niagara College Ecosystem Restoration graduate students, aiming to map existing terrain, and provide a restoration concept, list of permits, and a high-level cost estimate. This summary focuses only on the hydrology, mapping, and restoration design aspects.

A hydrological study, detailing the characteristics of the watershed that drains to the stream and local rainfall indices, made it possible to predict average and peak flows on a long-term basis. Flow measurements were documented and found to be consistent with averages for March 2021 and 2022. However, peak flows can be much higher than measured flow. Site mapping was based on Geographic Information System (GIS) data from Natural Resources Canada’s CanElevation Series High Resolution Digital Elevation Model (HRDEM). The HRDEM Digital Terrain Model (DTM) was utilized in QGIS to determine the existing topography. A single stream was proposed with natural meander bends as in Figure 1 [see Pdf of abstracts and/or poster]. Three ponds were recommended as well as a marsh area to enhance habitat and biodiversity on the site. Cross-sections were imported into AutoCAD and the new stream given gentler bank slopes. Soil volume to be excavated and filled was balanced so that no excess soil would need to be transported off-site, saving costs.

David Nguyen, Lillian Collis, Chelsea Vance and Andrew Binns

University of Guelph, Guelph, Canada

Understanding the sediment dynamics and evolving morphology of a river can be challenging due to the complexities, heterogeneities, and interconnected relationships between components of the river system. Quantifying the rate and magnitude at which rivers change geometry can yield insights to how sediments are eroded and transported. Manually measuring these changes can be a labour-intensive and time-consuming tasks, while more advanced techologies such as aerial surveillance and LiDAR can be prohibitively expensive. In recent years, drone technology has become increasingly affordable and offers a quick and easy method to obtain aerial data on river geometries. In this research, a small, inexpensive, and accessible drone is used to capture aerial photos and videos at select river sites to study their morphological changes over time. The footage is used with photogrammetry techniques to create digital elevation models that can be easily compared with each collected dataset to identify locations of rapid change and quantify the magnitude of change.

The research is being conducted in the Credit River watershed, where land uses are rapidly changing with new developments and expanding infrastructure to support a growing population. These changes to land use can impact flow characteristics of the Credit River and its tributaries, which in turn can impact the morphological development and sediment transport regimes. By studying both in-river sediment transport processes and channel morphology from an aerial view, a more comprehensive understanding of the current state of the river channel and how it is evolving can be obtained. Results thus far show that some locations already have notable changes occurring to the channel geometry and highlights how the easy-to-use drone-based photogrammetry method can have wide applications.

Karine Smith¹, Jackie Cockburn¹ and Paul Villard²

¹University of Guelph, Guelph, Ontario, Canada

²GEO Morphix Ltd., Campbellville, Canada

Understanding fluvial processes impacted by ice is essential to supporting channel design and stream corridor work in cold region rivers. Challenges with winter fieldwork limit field studies of fluvial processes in ice-covered riffle-pool sequences. In this study, field and modelling approaches were used to investigate the impacts of ice cover on velocity and shear stress in a small, shallow riffle-pool sequence in Southern Ontario, Canada. Changes in flow direction, maximum velocity depth and magnitude were evaluated and shown to vary between smooth and rough cross-sections. Shear stress under ice was influenced by maximum velocity depth and magnitude within the riffle and pool. Fieldwork and modelling both demonstrated changes in shear stress distribution throughout the riffle-pool. Cross sections with higher roughness demonstrated increases in shear stress under ice, while cross-sections with lower roughness exhibited overall decreases in shear stress. Modelling paired with field data provided detailed shear stress magnitude and distribution estimates under ice.