A 3D numerical modeling of the links between hydrodynamics, dissolved oxygen, and water temperature of a northern rural-urban shallow lake with two distinct basins

A 3D hydrodynamic model (EFDC) was applied to simulate dissolved oxygen (DO) and temperature (T) (two crucial parameters impacting water quality) throughout Lake St. Charles, a rural-urban shallow lake located North of Quebec City, Canada. Model outputs of T and DO corroborate observations at five monitoring stations within the lake. Simulated results indicated annual cycles of turnovers and stratifications and different behaviors for the deep and shallow basins. For the simulated years, the deep basin was stratified in summer and winter, while the shallow basin was mostly mixed throughout the year. The lake heat budget indicates that during summer with a long retention time, the thermal structure of the lake is principally controlled by net radiation, latent, and sensible heat fluxes. For the rest of the year, the inflow (from the main tributary, the Des Hurons River) and outflow are the main drivers of the lake's thermal structure.

JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments

We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot. The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360 ^° RGB video at 15 fps, 3D point clouds from two 16 planar rays Velodyne LiDARs, line 3D point clouds from two Sick Lidars, audio signal, RGB-D video at 30 fps, 360 ^° spherical image from a fisheye camera and encoder values from the robot's wheels. Our dataset incorporates data from traditionally underrepresented scenes such as indoor environments and pedestrian areas, all from the ego-perspective of the robot, both stationary and navigating. The dataset has been annotated with over 2.4 million bounding boxes spread over five individual cameras and 1.8 million associated 3D cuboids around all people in the scenes totaling over 3500 time consistent trajectories. Together with our dataset and the annotations, we launch a benchmark and metrics for 2D and 3D person detection and tracking. With this dataset, which we plan on extending with further types of annotation in the future, we hope to provide a new source of data and a test-bench for research in the areas of egocentric robot vision, autonomous navigation, and all perceptual tasks around social robotics in human environments.

The impacts of changing climate and streamflow on nutrient speciation in a large Prairie reservoir

Climate mediated warming water temperature, drought and extreme flooding are projected to shift the phenology of nutrients in receiving lakes and reservoirs further intensifying eutrophication and algal blooms, especially in temperate reservoirs. An emerging issue in reservoir management is the prediction of climate change impacts, a necessity for sound decision making and sustainable management. Lake Diefenbaker is a large multipurpose reservoir in the Canadian Prairies. In this study, the impact of climate change on nutrient speciation in Lake Diefenbaker is examined using loosely linked SpAtially Referenced Regression On Watershed attributes (SPARROW) and CE-QUAL-W2 models. Two climate mediated scenarios, RCP 8.5 representing the most extreme climate change, and climate induced streamflow were modelled. Nutrient levels are anticipated to double under the climate change and streamflow scenarios. Winter and spring were identified as hot moments for nitrogen pollution with a plausible saturation of nitrous oxides in the future. Of concern is a plausible recycling of nitrate through dissimilatory nitrate reduction to ammonium. Summer and fall on the other hand represent the period for phosphorus enrichment and internal loading with a probable succession of cyanobacteria in the summer.

Impacts of Varying Dam Outflow Elevations on Water Temperature, Dissolved Oxygen, and Nutrient Distributions in a Large Prairie Reservoir

Dam operations are known to have significant impacts on reservoir hydrodynamics and solute transport processes. The Gardiner Dam, one of the structures that forms the Lake Diefenbaker reservoir located in the Canadian Prairies, is managed for hydropower generation and agricultural irrigation and is known to have widely altering temperature regimes and nutrient circulations. This study applies the hydrodynamic and nutrient CE-QUAL-W2 model to explore how various withdrawal depths (5, 15, 25, 35, 45, and 55 m) influence the concentrations and distribution of nutrients, temperature, and dissolved oxygen (DO) within the Lake Diefenbaker reservoir. As expected, the highest dissolved nutrient (phosphate, P O 4 3 - - P and nitrate, N O 3 - - N ) concentrations were associated with hypoxic depth horizons in both studied years. During summer high flow period spillway operations impact the distribution of nutrients, water temperatures, and DO as increased epilimnion flow velocities route the incoming water through the surface of the reservoir and reduce mixing and surface warming. This reduces reservoir concentrations but can lead to increased outflow nitrogen (N) and phosphorus (P) concentrations. Lower withdrawal elevations pull warmer surface water deeper within the reservoir and decrease reservoir DO during summer stratification. During fall turnover low outflow elevations increase water column mixing and draws warmer water deeper, leading to slightly higher temperatures and nutrient concentrations than shallow withdrawal elevations. The 15 m depth (540 m above sea level) outflow generally provided the best compromise for overall reservoir and outflow nutrient reduction.

Sedimentation and erosion in Lake Diefenbaker, Canada: solutions for shoreline retreat monitoring

This study looks into sedimentation and erosion rates in Lake Diefenbaker, a prairie reservoir, in Saskatchewan, Canada, which has been in operation since 1968. First, we looked at the historical data in all different formats over the last 70 years, which includes data from more than 20 years before the formation of the lake. The field observations indicate high rates of shoreline erosion, especially in the upstream portion as a potential region for shoreline retreat. Because of the great importance of this waterbody to the province, monitoring sedimentation and erosion rates is necessary for maintaining the quality of water especially after severe floods which are more common due to climate change effects. Second, we used Google Maps Elevation API, a new tool from Google that provides elevation data for cross sections drawn between two points, by drawing 24 cross sections in the upstream area extending 250 m from each bank. This feature from Google can be used as an easy and fast monitoring tool, is free of charge, and provides excellent control capabilities for monitoring changes in cross-sectional profiles.

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m³/s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

Classification of English vowels using speech evoked potentials

The objective of this study is to investigate whether Speech Evoked Potentials (SpEPs), which are auditory brainstem responses to speech stimuli, contain information that can be used to distinguish different speech stimuli. Previous studies on brainstem SpEPs show that they contain valuable information about auditory neural processing. As such, SpEPs may be useful for the diagnosis of central auditory processing disorders and language disability, particularly in children. In this work, we examine the spectral amplitude information of both the Envelope Following Response, which is dominated by spectral components at the fundamental (F0) and its harmonics, and Frequency Following Response, which is dominated by spectral components in the region of the first formant (F1), of SpEPs in response to the five English language vowels (\a\,\e\,\ae\,\i\,\u\). Using spectral amplitude features, a classification accuracy of 78.3% is obtained with a linear discriminant analysis classifier. Classification of SpEPs demonstrates that brainstem neural responses in the region of F0 and F1 contain valuable information for discriminating vowels. This result provides an insight into human auditory processing of speech, and may help develop improved methods for objectively assessing central hearing impairment.