Volcaniclastic rocks

Several landcover classifications based on Landsat images from 1966 to 2018

Since the report of the RNA aptamer for theophylline, theophylline has become a key molecule in chemical biology for designing RNA switches and riboswitches. In addition, theophylline is an important drug for treating airway diseases including asthma. The classic RNA aptamer with excellent selectivity for theophylline has been used to design biosensors, although DNA aptamers are more desirable for stability and cost considerations. In this work, we selected DNA aptamers for theophylline, and all the top sequences shared the same binding motifs. Binding was confirmed using isothermal titration calorimetry and a nuclease digestion assay, showing a dissociation constant (Kd) around 0.5 μM theophylline. The Theo2201 aptamer can be truncated down to 23-mer while still has a Kd of 9.8 μM. The selectivity for theophylline over caffeine is around 250,000-fold based on a strand-displacement assay, which was more than 20-fold higher compared to the classic RNA aptamer. For other tested analogs, ...

A DNA Aptamer for Theophylline with Ultrahigh Selectivity Reminiscent of the Classic RNA Aptamer

This dataset provides two 30-m resolution time series products of annual land cover classifications over the Arctic Boreal Vulnerability Experiment (ABoVE) core domain for each year of the period 1984-2014. The data are the annual dominant plant functional type in a given 30-m pixel derived from Landsat surface reflectance, landcover training data mapped across the ABoVE domain (using Random Forests modeling, with clustering and interpretation of field photography) and very high resolution imagery to assign land cover classifications. One product has a 15-class land cover classification that breaks out forest and shrub types into several additional classes; the other product provides a simplified, 10-class approach. Classification accuracy assessment results are provided per year. Assessments were based on a probability-based random sample of reference data that supported statistically robust estimation of areas and uncertainties in mapped areas.

This data was collected to understand annual land cover classifications over the Arctic Boreal Vulnerability Experiment (ABoVE) core domain for each year of the period 1984-2014.

This dataset is a synthesis of field plot characterization data, derived above-ground and below-ground combusted carbon, and acquired Fire Weather Index (FWI) System components for burned boreal forest sites across Alaska, USA, the Northwest Territories, and Saskatchewan, Canada from 1983-2016. Unburned plot data are also included. Compiled plot-level characterization data include stand age, disturbance history, tree density, and tree biophysical measurements for calculation of the above-ground (ag) and below-ground (bg) biomass/carbon pools, pre-fire and residual post-fire soil organic layer (SOL) depths and estimates of combustion of tree structural classes. The measured slope and aspect for each site and an assigned moisture class based on topography are also provided. Data from 1019 burned and 152 unburned sites are included. From the estimates of combusted ag and bg carbon pools and SOL losses, the total carbon combusted, the proportion of pre-fire carbon combusted, and the propor ...

1. Description of methods used for collection/generation of data: A. Soil Landscapes of Canada (SLC) Data Version 2.2 (Centre for Land and Biological Resources Research, Agriculture and Agri-Food Canada, 1996): This dataset was published in Dec 1996 by Agriculture and Agri-Food Canada based on soil survey mapping done over the years and updated regularly. The data has a resolution of 1:1 million and covers entire Canada. The dataset is structured as below: a. It divides whole of Canada into several ecodistricts which have been made available as a polygon shapefile where each polygon corresponds to an ecodistrict. b. Each polygon is further divided into a number of soil texture components. c. The percentage area covered by the components in an ecodistrict are given in tables but their locations are not known i.e. there is no shapefile defining coverage of each component inside of each ecodistrict. d. Each of these components have been allocated a soil type: CL - clay loam, KCL ...

Data was collected using autonomous recording units (ARU), and in-person point count surveys, during the 2018 field season. Variables such as: dominant vegetation cover, area of peatland, elevation, Natural Subregion classification, distance to closest road, ambient noise, wind speed, date and time of year, were collected along with the point counts and recorded files. Spectrograms were used to analyze recorded files since each bird species have unique songs and calls. Once files were processed a list of bird species present at each site was used for statistical analysis. This data collection method will also be repeated for the 2019 field season.

Data was collected from three rivers in the Greater Toronto Area of Southern Ontario: Ganatsekiagon Creek (City of Pickering), Wilket Creek (City of Toronto), and Morningside Creek (City of Toronto). The grain size distribution at each site was calculated using a Wolman Pebble count with a 200-stone sample size. Bedload transport was monitored over three years using Radio Frequency Identification (RFID) tracer stones, and periodic topographic surveys were conducted. A total of 300 tracers in 3 size classes were seeded in each site in August 2015. Tracer positions were recorded after each major rainfall event during the active field season each year, resulting in a total of 10, 12, and 13 recoveries in Ganatsekiagon Creek, Wilket Creek, and Morningside Creek, respectively. With each recovery, the travel distance of each tracer since its last known position is calculated. Detailed topographic surveys of the channel bed were conducted in the summers of 2016 and 2018 using a total station. ...

Shapefile detailing classified prairie watersheds (n = 4175) according to physiographic characteristics. These characteristics were assembled from a variety of sources, including remote sensed data and government databases. Variables included climatic (annual precipitation, potential evapotranspiration), physical (slope, elevation), surficial geology, wetland (density, size distribution), and land cover/use data. Watersheds were classified using a hierarchical clustering on principal components analysis. As a result, seven distinct classes of watersheds were identified. The dataset defines two classifications schemes: (1) Integrated Watershed Classification, and (2) Land Cover Watershed Classification. The schemes differ as the latter was performed without climatic variables. As such, the land cover approach is suited for applications where local climate is forced using other data sources (e.g., hydrological modelling). The integrated classification is suited for general applications. ...

Wolfe, J., Whitfield, C. J., Shook, K. R., Spence, C. (2019). Canadian Prairie Watershed Classification [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/101.0197

Canadian Prairie Watershed Classification

Prairies watershed classification geography

MESH 1.4 CLASS 3.6

Model name: Coupled hydrology land-surface model (MESH), using the Canadian Land Surface Scheme (CLASS) Model version number: MESH (1.4) using CLASS (3.6) Model source/webpage: https://wiki.usask.ca/pages/viewpage.action?pageId=220332269 Model output pre-processing script: TBA. Scripts will be shared on github. Model output post-processing script: TBA. Scripts will be shared on github. Model setup: Physically based with no calibration. Time step: Hourly Initial condition: Physically based, set based on the understanding of the hydrological system Boundary condition: Physically based, set based on the understanding of the hydrological system

surface radiative and turbulent fluxes snow energetics snow hydrology alpine hydrology glacier energetics and hydrology diagnostic variables MESH CLASS Canadian Rockies

Snow and ice processes in high mountain environments are controlled by precipitation, blowing snow redistribution, sublimation, and the exchange of radiative and turbulent fluxes. Snow interception in forests is important in many alpine regions. The current dataset is the collection of simulated data at different alpine and glacierized research sites in the Canadian Rockies (e.g. alpine ridges, glacier, alpine forests and clear cuts, and montane sites). The coupled hydrology land-surface model (MESH), using the Canadian Land Surface Scheme (CLASS), is run using a physically based modeling approach based on the understanding of the hydrological system. For the different sites, the model was run in single column mode and forced by 30-min meteorological observations collected as part of the Canadian Rockies Hydrological Observatory. The forcing data of shortwave and longwave irradiance were adjusted to slopes; meanwhile, air temperature, humidity, pressure and precipitation were adjusted ...

Land surface schemes can be applied to simulate evapotranspiration. This dataset contains the driving meteorological data, and various diagnostic data, from one of the Boreal Ecosystem Research and Monitoring Sites in central Saskatchewan, known as the Old Jack Pine site. In Nazarbakhsh et al. (2019, Hydrological Processes, https://doi.org/10.1002/hyp.13674) we used these data to drive two Canadian land surface schemes (CLASS and CLASS–CTEM). We used half–hourly values of shortwave radiation, longwave radiation, precipitation, air temperature, specific humidity, wind speed, and atmospheric pressure to drive the models. Flux tower estimates of evapotranspiration, with energy balance closure applied, were used to assess the performance of the models on daily and monthly timescales for years 2000 to 2010. We also used soil moisture (measured with Campbell Scientific CS615 probes, which measure liquid water content only) and soil temperature observations for years 2000 to 2010 to assess th ...

boreal forest BERMS Old Jack Pine site evapotranspiration land surface schemes CLASS CLASS-CTEM

Global climate change has had a significant effect on the permafrost landscape in Northern cold regions. Due to natural processes such as precipitation change and rising temperatures, in addition to anthropogenic intervention, we notice a steadily increasing, and systemic pattern of permafrost thaw. The fieldwork took place in the Sahtu region of the Northwest Territories, specifically within the Bogg Creek Watershed, located 30 kilometers South of the Town of Norman Wells. Our work seeks to use two geophysical methods, electrical resistivity tomography (ERT) and electromagnetic induction (EMI) to estimate the permafrost table depth in areas with local landscape features such as lakes and clear cuts. The purpose of this research is also to benchmark a non-ground coupled system (EMI) against the more classical ground-coupled methods (ERT). The ERT system we used is the Syscal Junior 48, and the EMI system was the Geonics Inc EM-31 and EM-34. The field mission lasted four days, and we co ...

MESH model is used for calibration/ validation of the streamflow. MESH is a physics-based, land-surface hydro- logical modelling system developed by Environment and Climate Change Canada. MESH performs both water and energy balances and is best suited to cold-region, large-scale catchments due to its ability to simulate snow processes, such as snow accumulation, redistribution, and melt. MESH is used to simulate important hydrological processes (like runoff generation, evapotranspiration, and soil moisture). SED model is a physically based watershed sediment transport model which is developed based on empirical equations and the sediment mass balance equation (for overland and instream flow). It includes different sediment classes and is suitable for large scale cold regions catchments. The model simulates hourly sediment load and concentration. The following input data were used for hydrological modelling: - Meteorological data: For model calibration and validation, seven forcin ...

Most of the data are available free for analysis in the Fraser Basin. The analysis procedure is applied on different data types, including point (e.g., streamflow records), vector (e.g., river network), and raster images (e.g., DEM) as inputs for the setup of the MESH model in the Fraser Basin. Different processing steps can be applied over input datasets, such as clipping, merging, filtering, mosaicking. The input data are as follows: 1) Basin, subbasin, subsubbasin boundary shapefiles 2) River networks 3) Streamflow records 4) Digital Elevation Model (DEM) 5) Land Cover Classes 6) Meteorological forcing 7) Soil Dataset

Data collected for this project include a series of surface and subsurface variables characterizing the thermal and mass balance of observation points and the study basin as a whole. This includes both continuous (30 minute intervals) and discrete data sets collected between 2017-07-10 and 2019-09-10. Each data set was stratified across a series of land cover classes designated within the study basin: open water, mineral-cored uplands, riparian, ice-rich permafrost, and thermokarst features. Surface variables measured continuously include stream discharge, albedo, air temperature, relative humidity, net radiation, and rain. Surface variables measured discretely include snow depth, snow density, vegetation height, and vegetation density. Subsurface variables measured continuously include soil temperature, volumetric moisture content, and water table depth. Subsurface variables measured discretely include evapotranspiration rates, groundwater pressure head, and near surface soil thermal ...

Investigation of alpine land cover classes and their influence on basin water balance in the Mackenzie Mountains, Northwest Territories

The Parsivel is an optical disdrometer that measures the velocity and size of falling hydrometeors with the goal of classifying hydrometeor type and retrieve precipitation Particle Size Distribution (PSD). We use an OTT Parsivel² laser-optical disdrometer that functions with two sensor heads facing each other. One head is a transmitter that emits radiation (at 650 nm wavelength at the red band) in a horizontal plane and the other head is a receiver that senses how much of that radiation is received. The instrument measures the size of the hydrometeor by measuring the length of radiation that is blocked by the particle diameter. The velocity of the hydrometeor is estimated based on the time that a particular hydrometeor is blocking the radiation between the transmitter and receiver. The OTT Parsivel² retrieves particle velocity and size every minute, with a range in velocity from 0.2 to 20 m/s and a range in particle diameter from 0.2 to 25 mm (OTT Hydromet GmbH, 2018). OTT Hydromet Gm ...

intensity of precipitation mm/h 1 min Parsivel precipitation since start mm 1 min Parsivel weather code SYNOP WaWa 1 min Parsivel weather code METAR/SPECI 1 min Parsivel weather code NWS 1 min Parsivel radar reflectivity dBz 1 min Parsivel (simulated by Parsivel software) MOR Visibility m 1 min Parsivel signal amplitude of laserband 1 min Parsivel number of detected particles 1 min Parsivel temperature in sensor °C 1 min Parsivel heating current A 1 min Parsivel sensor voltage V 1 min Parsivel kinetic energy J/(m2h) 1 min Parsivel snow intensity mm/h 1 min Parsivel size and speed spectrum number of particles per class 1 min Parsivel (spectrum for 32 classes of particle size and 32 classes of speed)

173 pesticide concentrations ug/L Spring/Summer Ca, CO3, Cl, F, Fe, Mg, Mn mg/L Spring/Summer conductivity us/cm Spring/Summer pH mg/L Spring/Summer nitrate dissolved mg/L Spring/Summer phosphorus – ortho & total mg/L Spring/Summer hardness, alkalinity mg/L Spring/Summer total dissolved solids mg/L Spring/Summer total nitrogen mg/L Spring/Summer ammonia-N mg/L Spring/Summer total organic carbon mg/L Spring/Summer wetland class classification Spring/Summer wetland vegetation percent Spring/Summer cyanobacteria bloom yes/no Spring/Summer Wetland area m2 Spring/Summer aquatic invertebrates abundance Spring/Summer waterfowl abundance Spring/Summer pesticide toxicity ug/L Collected from literature

permanence class Category Annual cover class Category Annual pH dimensionless Spring/summer YSI sonde conductivity us/cm Spring/summer YSI sonde alkalinity mg/L CaCO3 Spring/summer YSI sonde total nitrogen mg/L Spring/summer SmartChem analyzer 170 nitrate mg/L Spring/summer SmartChem analyzer 170 ammonia-N mg/L Spring/summer SmartChem analyzer 170 total phosphorus mg/L Spring/summer SmartChem analyzer 170 total dissolved phosphorus mg/L Spring/summer SmartChem analyzer 170 soluble reactive phosphorus mg/L Spring/summer SmartChem analyzer 170 sulfate mg/L Spring/summer SmartChem analyzer 170 Chlorophyll a ug/L Spring/summer Spectrometer

A high resolution, enhanced version of Environment and Climate Change Canada’s MESH (Modélisation Environnementale Communautaire - Surface Hydrology) land surface hydrological model was set up at a spatial resolution of approximately 4 km by 4 km to correspond to the resolution of dynamically downscaled Weather Research Forecast (WRF) atmospheric model outputs for current and future climates in the region. This convection-permitting WRF product used ERA-Interim reanalysis product boundary conditions over 2000 - 2015 to produce realistic, high resolution weather simulations. The pseudo global warming (PGW) approach to dynamical downscaling of future warming projection under RCP8.5 (2086 - 2100), used WRF bounded by ERA-Interim outputs that were perturbed by the mean outcomes of an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model projections. Available land surface data consist of digital elevation models (DEMs), i.e. the hydrologically conditioned HydroSh ...

The MESH version r1589_RTE_ts450s was used. This version of MESH has a hybrid functionality which allows users to define different grid specifications for routing scheme and land surface scheme. Here, in our model, routing scheme has a cell resolution of 0.0083 degree and land surface scheme has a resolution of 0.09 degree. The model includes 13 Ground Response Unit (GRU) classes. The Digital Elevation Models (DEM) was downloaded from USGS HydroSHEDS database with 30 arc-second resolution. Soil data was obtained from Global Soil Dataset for Earth System Models (Shangguan et al. 2014) (http://globalchange.bnu.edu.cn/research/soilw) and the landcover data was obtained from Climate Change Initiative (CCI) Land Cover 2015. The forcing data was extracted from the Global Environmental Multiscale atmospheric model and the Canadian Precipitation Analysis (GEM-CaPA) which a high-resolution gridded database.

Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snow ...

To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Snow pillow data (Government of BC - https://aqrt.nrs.gov.bc.ca/Data/) Manual Snow Course Stations (Government of BC - http://www.env.gov.bc.ca/wsd/data_searches/snow/asws/data/allmss_archive.csv) Climate Normals (ECCC - https://climate.weather.gc.ca/climate_normals/index_e.html)

Model calibration and validation are critical in hydrological model robustness assessment. Unfortunately, the commonly-used split-sample test (SST) framework for data splitting requires modelers to make subjective decisions without clear guidelines. This large-sample SST assessment study empirically assesses how different data splitting methods influence post-validation model testing period performance, thereby identifying optimal data splitting methods under different conditions. This study investigates the performance of two lumped conceptual hydrological models calibrated and tested in 463 catchments across the United States using 50 different data splitting schemes. These schemes are established regarding the data availability, length and data recentness of the continuous calibration sub-periods (CSPs). A full-period CSP is also included in the experiment, which skips model validation. The assessment approach is novel in multiple ways including how model building decisions are fram ...

The dataset is comprised of inputs to and outputs from the Cold Regions Hydrological Model (CRHM) when it was run as a virtual model of two classes of Canadian Prairie watersheds, as defined by Wolfe et al. (2019). These classes are Pothole Till and High Elevation Grasslands. These watersheds represented typified prairie watersheds based on physiogeography and coherent response to environmental change.Model parameters were informed by the results of Wolfe et al. (2019). The .prj files necessary to run the virtual models are included in the dataset. Climate forcing data are from the Adjusted and Homogenized Canadian Climate Dataset from a cohort of stations contained within each watershed class and cover a period from 1960-2006. There are a series of climate sensitivity scenarios that include applying a delta method to the original climate data (i.e., 1°C increments of warming, and -20%, +10%, +20% and +30% of precipitation). The .prj and .obs files for the baseline and each sensi ...

The dataset is comprised of inputs to and outputs from the Cold Regions Hydrological Model (CRHM) when it was run as a virtual model of the High Elevation Grasslands class, as defined by Wolfe et al. (2019). These watersheds represented typified prairie watersheds based on physiogeography and coherent response to environmental change. Model parameters were informed by the results of Wolfe et al. (2019). The .prj files necessary to run the virtual models are included in the dataset. Climate forcing data are from the Adjusted and Homogenized Canadian Climate Dataset from a cohort of stations contained within each watershed class and cover a period from 1960-2006. There are a series of climate sensitivity scenarios that include applying a delta method to the original climate data (i.e., 1°C increments of warming, and -20%, +10%, +20% and +30% of precipitation). Model output includes hourly catchment outflow, rainfall, snowfall, snow sublimation and snow water equivalent for the baseline a ...

He, Z., Spence, C., Shook, K., Whitfield, C., Pomeroy, J., Wolfe, J. (2021). Virtual Watershed Model Simulations for Typified Prairie Watersheds in High Elevation Grasslands [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/102.0517 Spence, C., He, Z., Shook, K. R., Mekonnen, B. A., Pomeroy, J. W., Whitfield, C. J., and Wolfe, J. D.: Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification–based virtual modelling approach, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2021-186, in review, 2021.

The dataset is comprised of inputs to and outputs from the Cold Regions Hydrological Model (CRHM) when it was run as a virtual model of the seven prairie basin classes, as defined by He et al. (2023). These watersheds represented typified prairie watersheds based on physiogeography and coherent response to environmental change. Model parameters were informed by the results of He et al. (2023). The .prj files necessary to run the virtual models are included in the dataset. Climate forcing data are from the Adjusted and Homogenized Canadian Climate Dataset from a cohort of stations contained within each watershed class and cover a period from 1960-2006. There are a series of climate sensitivity scenarios that include applying a delta method to the original climate data (i.e., 1°C increments of warming, and -20%, +10%, +20% and +30% of precipitation). Model output includes hourly catchment outflow, and depression water storage in the HRUs for the baseline and each scenario. There are also ...

He, Z., Shook, K., Spence, C., Pomeroy, J., Whitfield, C. (2023). Virtual Watershed Model Simulations for Typified Prairie Watersheds in Seven Basin Classes. Federated Research Data Repository. https://doi.org/10.20383/103.0815

Virtual Watershed Model Simulations for Typified Prairie Watersheds in Seven Basin Classes

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AAL-ML-1 Inductively coupled plasma-optical emission spectrometry (ICP-OES) (Thermo Scientific iCAP 6300) Water quality (either major cationic elements (Al, Ca, Fe, K, Mg, Mn, Na, P, S, and Si) or trace metals (As, Cr, Cu, Ni, Pb, Sr, Zn), other trace metals upon request (B, Ag, Cd, Co, Hg, Mo, Se Tl)) per sample $65 $75 $101 AAL-ML-2 Gallery™ Discrete Analyzer (Thermo Scientific) Water quality (nutrients) per sample $30 $35 $47 AAL-ML-3a Capillary Ion Chromatograph system (Dionex ICS-5000 with auto sampler) Water quality (inorganic anions (e.g., nitrate, sulfate, chloride, bromide), organic acids (e.g., acetate, butyrate, succinate)) per sample (for 7 inorganic anions only) $40 $46 $62 AAL-ML-3b " " " " per sample (for 7 inorganic ions plus organic acids) $50 $58 $78 AAL-ML-4 Total Organic C, Total N Analyzer (Shimadzu TOC-LCPH/CPN with auto injector) Water quality (organic and inorganic carbon and total nitrogen) per sample $40 $46 $62 AAL-ML-5 Gas Chromatograph (Shimadzu) G ...

SWSL-DS-1 Drone: DJI M600 Pro^^Sensors:^Riegl Mini Vux-1^Sony RGB^^Sensor Description:^Lidar Mapping unit with Integrated Sony 24mp camera^^Capabilities:^Class 1 laser product capable of producing 100,000 shots per second in a 360 degree field of view. IMU data is 200 hz. Data is post processed in Applanix and Riegl softwares. Products include .las files that are elevation colored, Intensity scale or RGB colorized. ^^Wavelength:^905nm, ^380nm-740nm per day $1,000 $1,200 $1,400 SWSL-DS-2 Drone: DJI M600 Pro^^Sensors:^Corning Hyperspectral Camera^^Sensor Description:^Push-broom Line Imaging Spectrometer^^Capabilities:^Produces continuous imaging of narrow spectral bands over a spectral range^^Wavelength:^400nm-1000nm per day $800 $960 $1,120 SWSL-DS-3 Drone: DJI Mavic 2 Pro^^Sensors:^RGB camera^^Sensor Description:^Hasselblad 20mp camera^^Capabilities:^Still imagery and video files are created using the 20MP camera. Products are jpeg and MP3 files^^Wavelength:^400nm-700nm per day $200 ...

UTABFWU-ML-1 Culturing:^Labconco Logic Class 2 Type A2 Biosafety Cabinet Work station provides personnel, product and environmental protection from hazardous particulates such as agents that require Biosafety Level 1 or 2. per day $30 $35 $42 UTABFWU-ML-2 Culturing:^Millipore Synergy UV Water Purification System Water purification system providing ultrapure water for laboratory needs (e.g., buffers and bacterial media preparation). per day $10 $12 $14 UTABFWU-ML-3 Culturing:^Powers Scientific Light & Temperature Control Growth Chamber Temperature-controlled unit allowing the use of large-volume flasks. Ability to control light intensity and light cycles. per day $30 $35 $42 UTABFWU-ML-4 Culturing:^Thermo Revco Elite Plus -86°C Freezer Ultra-Low Freezer allowing for the safe storage and preservation of biological samples. per day $20 $23 $28 UTABFWU-ML-5 Culturing:^VWR ADV Model 5000 Shaker Shaker allowing the use of large-volume flasks. per day $5 $6 $7 UTABFWU-ML-6 Lyophilization:^Lab ...

Phycological Community Analysis Portable AlgaeTorch (bbe Moldaenke)per day Handheld operational unit used for the quantification of cyanobacteria and total chlorophyll. University of Toronto 1 Phycological Community Analysis Portable PhycoLabAnalyser (bbe Moldaenke) Quick, simple chlorophyll measurement with algal class differentiation. It also provides phycocyanin measurements – an indicator for cyanotoxins as well as flavours and odorous substances. University of Toronto 1 Phycological Community Analysis Portable FluoroProbe III (bbe Moldaenke) Used for creating depth profiles of different phycological divisions. Individual profiles during the measurements are taken for green algae, blue-green algae/cyanobacteria, diatoms/dinoflagellates and cryptophytes (others can be added, e.g. Planktothrix rubescens). University of Toronto 1 Phycological Community Analysis Portable PHYTO-PAM-II^(Walz) Facilitates measurements of mixed algae populations for composition analysis and differences in ...

UTHAAL-DS-1 Phycological Community Analysis:^AlgaeTorch (bbe Moldaenke) Portable^Description:^Handheld operational unit used for the quantification of cyanobacteria and total chlorophyll. per day $200 $230 $280 UTHAAL-DS-2 "" per week $1,000 $1,150 $1,400 UTHAAL-DS-3 Phycological Community Analysis:^PhycoLabAnalyser (bbe Moldaenke) Portable^Description:^Quick, simple chlorophyll measurement with algal class differentiation. It also provides phycocyanin measurements – an indicator for cyanotoxins as well as flavours and odorous substances. per day $300 $345 $420 UTHAAL-DS-4 "" per week $1,800 $2,070 $2,520 UTHAAL-DS-5 Phycological Community Analysis:^FluoroProbe III (bbe Moldaenke) Portable^Description:^Used for creating depth profiles of different phycological divisions. Individual profiles during the measurements are taken for green algae, blue-green algae/cyanobacteria, diatoms/dinoflagellates and cryptophytes (others can be added, e.g. Planktothrix rubescens). per day $300 $345 ...

UTHAAL-ML-1 Flow Cytometry:^CytoFLEX Flow Cytometer (Beckman Coulter) Cell analysis system used for the qualitative and quantitative measurement of biological and physical properties of cells and other particles. Application flexibility, including an optional 96-well Plate Loader, 13 bandpass filters, and two lasers (Blue and Red). per hour $100 $115 $140 UTHAAL-ML-2 Flow Cytometry:^PhytoCyt flow cytometer (Turner Designs) Portable Cell analysis system used for many applications (e.g., cell counting, viability assays, physiological characterization, etc.). The optical filters and lasers have been optimized to detect the endogenous fluorophores common to phytoplankton, including phycoerythrin, chlorophyll and phycocyanins. One of the detectors has been optimized for green fluorescence detection, which allows labelling with exogenous reagents. per day $200 $230 $280 UTHAAL-ML-3 "" "" per week $1,200 $1,380 $1,680 UTHAAL-ML-4 Microscopy:^IX73 Inverted LED Fluorescence Microscope (Olympus) ...

^A Ten sample minimum. ^B Samples must be freeze-dried and homogenized. ^C For samples submitted ‘ready-to-analyze’, please contact us for advice regarding sample preparation and submission. ^D Please specify target analytes. ^E For add-on with other analytes only. ^F For samples submitted ‘ready-to-analyze’ (i.e., pre-weighed in tin capsules) ^G A $5 discount will apply to samples received ‘ready-to-analyze’ ^H Per class of co-extractable routine analytes (please see: https://www.trentu.ca/wqc/facilities-services/services) ^I Solid samples include biota, sediments, soils, etc. All prices are subject to change Services subject to availability.

The Bridge to Land Water Sky is Canada's only Indigenous-led Living Lab, inspiring a more resilient agriculture industry and the next wave of farmers. As the only Indigenous-led Living Lab in Canada, the Bridge to Land Water Sky will focus on identifying barriers Indigenous people face when entering the Agricultural Industry and will celebrate Indigenous knowledge as a key factor in building a more innovative and climate-resilient agricultural industry with global impacts. Goals: 1. Improve land management strategies for the mitigation of greenhouse gas emissions and improve carbon sequestration. We will test beneficial practices for revitalization and improvement of our land and soils. 2. Increase food security and sovereignty in Indigenous and non-Indigenous communities to benefit local food production and medicinal and traditional plants for Indigenous communities. 3. Protect biodiversity and water to support healthy ecosystems, people, and environmental co-benefits, including ...

Special Issue of Hydrology and Earth System Sciences (HESS) Understanding and predicting Earth system and hydrological change in cold regions (edited by S. Carey, C. DeBeer, J. Hanesiak, Y. Li, J. Pomeroy, B. Schaefli, M. Weiler, and H. Wheater): https://hess.copernicus.org/articles/special_issue919.html Short description: CCRN observes, diagnoses, and predicts environmental change in the Saskatchewan and Mackenzie River Basins. To integrate existing and new sources of data with improved predictive and observational tools to understand, diagnose and predict interactions amongst the cryospheric, ecological, hydrological, and climatic components of the changing Earth system at multiple scales, with a geographic focus on Western Canada’s rapidly changing cold interior. The cold interior of Western Canada east of the Continental Divide has one of the world's most extreme and variable climates and is experiencing rapid environmental change. In a region which includes a multiplicity o ...

Core Modelling and Forecasting is a GWF core team which performs world-class, leading-edge water science for cold regions to address the needs of the Canadian economy in adapting to change and managing risks associated with the uncertain water futures and extreme events brought about by climate change. Its research is delivered under eight themes: 1. Spatial Meteorological Forcing Data (https://gwf.usask.ca/core-modelling/research-themes/spatial-meteorological-forcing-data.php); 2. Geospatial Intelligence (https://gwf.usask.ca/core-modelling/research-themes/geospatial-intelligence.php); 3. Current Generation Hydrological Modelling (https://gwf.usask.ca/core-modelling/research-themes/current-generation-modelling.php); 4. Next Generation Hydrological Modelling (https://gwf.usask.ca/core-modelling/research-themes/next-generation-hydrological-modelling.php); 5. Water Resources Management (https://gwf.usask.ca/core-modelling/research-themes/water-resources-management.php); 6. Water Quality ...

Since the report of the RNA aptamer for theophylline, theophylline has become a key molecule in chemical biology for designing RNA switches and riboswitches. In addition, theophylline is an important drug for treating airway diseases including asthma. The classic RNA aptamer with excellent selectivity for theophylline has been used to design biosensors, although DNA aptamers are more desirable for stability and cost considerations. In this work, we selected DNA aptamers for theophylline, and all the top sequences shared the same binding motifs. Binding was confirmed using isothermal titration calorimetry and a nuclease digestion assay, showing a dissociation constant (Kd) around 0.5 μM theophylline. The Theo2201 aptamer can be truncated down to 23-mer while still has a Kd of 9.8 μM. The selectivity for theophylline over caffeine is around 250,000-fold based on a strand-displacement assay, which was more than 20-fold higher compared to the classic RNA aptamer. For other tested analogs, ...

A DNA Aptamer for Theophylline with Ultrahigh Selectivity Reminiscent of the Classic RNA Aptamer

A LiDAR-based decision-tree classification of open water surfaces in an Arctic delta

Seasonal temperature trend and ice phenology in Great Slave lake (GSL), are strongly influenced by warmer inflow from Slave river. The Slave river flows to GSL through Slave river delta (SRD), bringing a rise in temperature that triggers the ice break-up process of the lake. Slave river discharge is subject to multiple stressors including climate warming and upstream water activities, which in turn, directly affects the GSL break-up process. Consequently, monitoring the break-up process at SRD, where the river connects to the lake, serves as an indicator to better understand the cascading effects on GSL ice break-up. This research aims to develop random forest (RF) models to monitor the SRD ice break-up processes, using a combination of satellite images with optical sensors at high spatial resolution, including Landsat-5, Landsat-8, Sentinel-2a, and Sentinel-2b. The RF models were trained using manually selected training pixels to classify ice, open water, and cloud within the SRD. The ...

A Machine Learning Approach to Classify Open Water and Ice Cover on Slave River Delta

Evolutionary coupling is a well investigated phenomenon in software maintenance research and practice. Association rules and two related measures, support and confidence, have been used to identify evolutionary coupling among program entities. However, these measures only emphasize the co-change (i.e., changing together) frequency of entities and cannot determine whether the entities co-evolved by experiencing related changes. Consequently, the approach reports false positives and fails to detect evolutionary coupling among infrequently co-changed entities. We propose a new measure, identifier correspondence (id-correspondence), that quantifies the extent to which changes that occurred to the co-changed entities are related based on identifier similarity. Identifiers are the names given to different program entities such as variables, methods, classes, packages, interfaces, structures, unions etc. We use Dice-Sørensen co-efficient for measuring lexical similarity between the identifier ...

A devastating, flood-producing rainstorm occurred over southern Alberta, Canada, from 19 to 22 June 2013. The long-lived, heavy rainfall event was a result of complex interplays between topographic, synoptic, and convective processes that rendered an accurate simulation of this event a challenging task. In this study, the Weather Research and Forecasting (WRF) Model was used to simulate this event and was validated against several observation datasets. Both the timing and location of the model precipitation agree closely with the observations, indicating that the WRF Model is capable of reproducing this type of severe event. Sensitivity tests with different microphysics schemes were conducted and evaluated using equitable threat and bias frequency scores. The WRF double-moment 6-class microphysics scheme (WDM6) generally performed better when compared with other schemes. The application of a conventional convective/stratiform separation algorithm shows that convective activity was domi ...

A Spatiotemporal Surface Water Classification in the Mackenzie Delta and Tuktoyaktuk Peninsula

Urbanization significantly alters natural hydrological processes, leading to increased flood risks in urban areas. The potential damages caused by flooding in urban areas are widely recognized, making it crucial for urban residents to be well-informed about flood risks to mitigate potential losses. Flood maps serve as essential tools in this regard, providing valuable information that aids in effective planning, risk assessment, and decision-making. Despite floods being the most common natural disasters in Canada, many Canadians still lack access to high-quality, up-to-date flood maps. The occurrence of recent major flood events across the country has sparked renewed interest among government officials and stakeholders in launching new flood mapping initiatives. These projects are critical for enhancing flood risk management across communities. Traditional flood hazard mapping methods, based on deterministic approaches, often fail to account for the complexities and uncertainties inher ...

Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO2) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce (Picea mariana)-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parame ...

A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)

The freeze-thaw cycle associated with climatic seasonality is a common phenomenon in cold regions affecting a wide range of subsurface processes. Due to the complex and highly nonlinear nature of the associated hydrologic processes, transient freeze-thaw dynamics are conventionally quantified in a numerical way. Here we present a hybrid analytical-numerical scheme for solving one-dimensional soil (or porous media) temperature profiles when the soil profile is subjected to unidirectional freezing (or thawing) conditions. This scheme divides the partially-frozen soil into multi-layers, each with constant thermal parameters and fixed-temperature boundaries. Temperature profiles within each layer were obtained by solving multiple moving-boundary problems. The proposed hybrid analytical-numerical scheme was tested into a freezing test of silty clay in a permafrost region on the Qinghai-Tibetan Plateau, and its solution was in good agreement with the finite element numerical solution. Result ...

Land surface models (LSMs) are used to simulate water and energy fluxes between the land surface and atmosphere. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological Weighing Lysimeters (GWLs) are instruments that can provide field-scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire - Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land ...

Chasmer, L., Hopkinson, C., Veness, T., Quinton, W., & Baltzer, J. (2014). A decision-tree classification for low-lying complex land cover types within the zone of discontinuous permafrost. Remote Sensing of Environment, 143, 73-84. https://doi.org/10.1016/j.rse.2013.12.016

A decision-tree classification for low-lying complex land cover types within the zone of discontinuous permafrost

The freeze-thaw cycle associated with climatic seasonality is a common phenomenon in cold regions affecting a wide range of subsurface processes. Due to the complex and highly nonlinear nature of the associated hydrologic processes, transient freeze-thaw dynamics are conventionally quantified in a numerical way. Here we present a hybrid analytical-numerical scheme for solving one-dimensional soil (or porous media) temperature profiles when the soil profile is subjected to unidirectional freezing (or thawing) conditions. This scheme divides the partially-frozen soil into multi-layers, each with constant thermal parameters and fixed-temperature boundaries. Temperature profiles within each layer were obtained by solving multiple moving-boundary problems. The proposed hybrid analytical-numerical scheme was tested into a freezing test of silty clay in a permafrost region on the Qinghai-Tibetan Plateau, and its solution was in good agreement with the finite element numerical solution. Result ...

A code clone is a pair of code fragments, within or between software systems that are similar. Since code clones often negatively impact the maintainability of a software system, several code clone detection techniques and tools have been proposed and studied over the last decade. However, the clone detection tools are not always perfect and their clone detection reports often contain a number of false positives or irrelevant clones from specific project management or user perspective. To detect all possible similar source code patterns in general, the clone detection tools work on the syntax level while lacking user-specific preferences. This often means the clones must be manually inspected before analysis in order to remove those false positives from consideration. This manual clone validation effort is very time-consuming and often error-prone, in particular for large-scale clone detection. In this paper, we propose a machine learning approach for automating the validation process. ...

Study region The Peace-Athabasca Delta, a Ramsar Wetland of International Importance in northeastern Alberta, is protected within Wood Buffalo National Park and contributes to its UNESCO World Heritage status yet is threatened by climate change and upstream energy projects. Study focus Recent drawdown of the delta’s abundant shallow lakes and rivers has deteriorated vital habitat for wildlife and impaired navigation routes. Here, we report continuous measurements at ~50 lakes during open-water seasons of 2018 and 2019 to improve understanding of hydrological processes causing lake-level variation. New hydrological insights for the region Analyses reveal four patterns of lake-level variation attributable to influential hydrological processes, which provide the basis for a new lake classification scheme: 1) ‘Drawdown’ (≥15 cm decline) by evaporation and/or outflow after ice-jam floods, 2) ‘Stable’ lake levels (<15 cm change) sustained by rainfall, 3) ‘Gradual Rise’ by inundation from t ...

Neary, L. K., Remmer, C. R., Krist, J., Wolfe, B. B., and Hall, R. I.: A new lake classification scheme for the Peace-Athabasca Delta (Canada) characterizes hydrological processes that cause lake-level variation, Journal of Hydrology: Regional Studies (Special Issue: Water and Environmental Management in Oil Sands Regions), 38, 100948. https://doi.org/10.1016/j.ejrh.2021.100948, 2021

A new lake classification scheme for the Peace-Athabasca Delta (Canada) characterizes hydrological processes that cause lake-level variation

This paper presents a novel data fusion technique for improving the snow cover monitoring for a mesoscale Alpine region, in particular in those areas where two information sources disagree. The presented methodological innovation consists in the integration of remote-sensing data products and the numerical simulation results by means of a machine learning classifier (support vector machine), capable to extract information from their quality measures. This differs from the existing approaches where remote sensing is only used for model tuning or data assimilation. The technique has been tested to generate a time series of about 1300 snow maps for the period between October 2012 and July 2016. The results show an average agreement between the fused product and the reference ground data of 96%, compared to 90% of the moderate-resolution imaging spectroradiometer (MODIS) data product and 92% of the numerical model simulation. Moreover, one of the most important results is observed from the ...

Mountain water resources are of particular importance for downstream populations but are threatened by decreasing water storage in snowpack and glaciers. Groundwater contribution to mountain streamflow, once assumed to be relatively small, is now understood to represent an important water source to streams. This review presents an overview of research on groundwater in high mountain environments (As classified by Meybeck et al. (2001) as very high, high, and mid-altitude mountains). Coarse geomorphic units, like talus, alluvium, and moraines, are important stores and conduits for high mountain groundwater. Bedrock aquifers contribute to catchment streamflow through shallow, weathered bedrock but also to higher order streams and central valley aquifers through deep fracture flow and mountain-block recharge. Tracer and water balance studies have shown that groundwater contributes substantially to streamflow in many high mountain catchments, particularly during low-flow periods. The perce ...

Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and ...

Classification and clustering approaches provide a means to group watersheds according to similar attributes, functions, or behaviours, and can aid in managing natural resources. Although they are widely used, approaches based on hydrological response parameters restrict analyses to regions where well-developed hydrological records exist, and overlook factors contributing to other management concerns, including biogeochemistry and ecology. In the Canadian Prairie, hydrometric gauging is sparse and often seasonal. Moreover, large areas are endorheic and the landscape is highly modified by human activity, complicating classification based solely on hydrological parameters. We compiled climate, geological, topographical, and land-cover data from the Prairie and conducted a classification of watersheds using a hierarchical clustering of principal components. Seven classes were identified based on the clustering of watersheds, including those distinguishing southern Manitoba, the pothole re ...

Wolfe, J. D., Shook, K. R., Spence, C., & Whitfield, C. J. (2019). A watershed classification approach that looks beyond hydrology: application to a semi-arid, agricultural region in Canada. Hydrology & Earth System Sciences, 23(9), 3945-3967. https://doi.org/10.5194/hess-23-3945-2019.

Watershed classification can identify regions expected to respond similarly to disturbance. Methods should extend beyond hydrology to include other environmental questions, such as ecology and water quality. We developed a classification for the Canadian Prairie and identified seven classes defined by watershed characteristics, including elevation, climate, wetland density, and surficial geology. Results provide a basis for evaluating watershed response to land management and climate condition.

A watershed classification approach that looks beyond hydrology: application to a semi-arid, agricultural region in Canada

Advances in Permafrost Modelling: Enhancing MESH/CLASS to represent Permafrost Dynamics

Agriculture is a cornerstone of global food production, accounting for a substantial portion of water withdrawals worldwide. As the world’s population grows, so does the demand for water in agriculture, leading to alterations in regional water–energy balances. We present an approach to identify the influence of agriculture on the water–energy balance using empirical data. We explore the departure from the Budyko curve for catchments with agricultural expansion and their associations with changes in the water–energy balance using a causal discovery algorithm. Analyzing data from 1,342 catchments across three Köppen-Geiger climate classes—temperate, snowy, and others—from 1980 to 2014, we show that temperate and snowy catchments, which account for over 90% of stations, exhibit distinct patterns. Cropland percentage (CL%) emerges as the dominant factor, explaining 47 and 37% of the variance in deviations from the Budyko curve in temperate and snowy catchments, respectively. In temperate c ...

Alpine regions receive large volumes of precipitation and are important to local and regional water balances, particularly during baseflow periods of winter cold and summer drought when the larger basin area is frozen and/or water limited. Alpine headwaters in western Canada are expected to warm and receive more precipitation during the coming decades, with implications for groundwater recharge and streamflow generation within these systems and the regional river networks to which they contribute. Throughout the North, thawing peat plateaus and other ice-rich permafrost features are resulting in an increased extent of thermokarst and wetland land cover. This transition places infrastructure and water resources at risk as the structural integrity and reliable flow paths previously maintained by the frozen soils become compromised. Alpine systems are particularly susceptible to hydrological change due to the amplification of climate warming with both latitude and elevation. The inherent ...

Object-oriented programming has had a significant impact on software development because it provides programmers with a clear structure of a large system. It encapsulates data and operations into objects, groups objects into classes and dynamically binds operations to program code. With the emergence of multi-core processors, application developers have to explore concurrent programming to take full advantage of multi-core technology. However, when it comes to concurrent programming, object-oriented programming remains elusive as a useful programming tool. Most object-oriented programming languages do have some extensions for concurrency, but concurrency is implemented independently of objects: for example, concurrency in Java is managed separately with the Thread object. We employ a programming model called Lime that combines action systems tightly with object-oriented programming and implements concurrency by extending classes with actions and guarded methods. This provides programme ...

In recent years, Deep Learning (DL) models have widely been applied to develop safety and security critical systems. The recent evolvement of Deep Neural Networks (DNNs) is the key reason behind the unprecedented achievements in image classification, object detection, medical image analysis, speech recog nition, and autonomous driving. However, DL models often remain a black box for their practitioners due to the lack of interpretability and explainability. DL practitioners generally use standard metrics such as Precision, Recall, and F1 score to evaluate the performance of DL models on the test dataset. However, as high-quality test data is not frequently accessed, the expected level of accuracy of these standard metrics on test datasets cannot justify the trustworthiness of testing adequacy, generality and robustness of DL models. The way we ensure the quality of DL models is still in its infancy; hence, a scalable DL model testing frame work is highly demanded in the context of soft ...

Changes in the water cycle influence the energy balance of the Earth. The water cycle is represented using the water balance equation, in which Evapotranspiration (ET) is a vital parameter. One of the main drivers of the change in ET within a specific area is the change in land cover. This study focuses on estimating ET across the Upper Gundar River Basin located in the state of Tamil Nadu, India. Notable features of this landscape include agriculture throughout the year supported using an extensive network of tanks and borewells, and the presence of Prosopis juliflora, a widely prevalent invasive species known to consume groundwater and moisture. Due to the lack of spatial variability in point ET measurements, ET models using remote sensing imagery as the main forcing data have been widely used to assess the spatial variability and temporal variability based on the principle of surface energy balance. These models are collectively referred to as Surface Energy Balance (SEB) models. Th ...

Weather and climate are major factors influencing worldwide wildfire activity. This study assesses surface and atmospheric conditions associated with the 2014 extreme wildfires in the Northwest Territories (NWT) of Canada. Hot and dry conditions led to the NWT experiencing the most severe wildfire season in its recorded history. The season included a record number of cloud-to-ground lightning flashes and set a record for area burned. Lightning was the dominant ignition source and accounted for about 95% of the wildfires. Prolonged periods of smoke led to dramatic reductions in visibility, frequent road closures, and reduced air quality resulting in numerous health alerts. Temporal and spatial patterns of lightning characteristics in 2014, derived from Canadian Lightning Detection Network data, were different from those in other years with, for example, far more positive flashes from 0600 to 1200 utc (midnight to 6:00 am local time). The highest fraction of positive cloud-to-ground flas ...

Yirdaw S.Z., K. R. Snelgrove, F. R. Seglenieks, C. O. Agboma and E.D. Soulis. (2009). An assessment of the WATCLASS hydrological model result of the Mackenzie River basin using the GRACE satellite total water storage measurement. Hydrological Processes pp3391-3400

An assessment of the WATCLASS hydrological model result of the Mackenzie River basin using the GRACE satellite total water storage measurement

Eddy covariance (EC) is one of the most effective ways to directly observe evaporation from a lake surface. However, the deployment of EC systems on lakes is costly and technically challenging which engenders a need for accurate modelling of evaporation from reservoirs for effective management. This study aims to 1) refactor the Canadian Small Lakes Model (CSLM) into modern high-level programming languages in open-source repositories and 2) evaluate evaporation estimates from the CSLM using nine years of EC observations of a pit-lake in Northern Alberta. The CSLM is a 1-D physical lake model simulating a mixing layer and arbitrary thick skin layer which interfaces with the atmosphere and includes a module for ice dynamics. It was developed to interface with the Canadian Global Coupled models as part of the surface classification scheme, and thus utilizes widely accessible forcing data. In this study the CSLM evaporation estimates are also compared to a commonly used bulk transfer metho ...

An ever-growing Canadian urban population could be severely impacted by increase in temperature. Canada’s mean temperature is projected to increase by 6-8°C towards the end of the 21st century. The consequence of rising temperatures is an increased likelihood of extreme temperature events like heatwaves and wildfires. The thesis aims to assess changes in extreme temperature in large Canadian urban areas. The research will help in developing mitigation measures like urban planning, which help cope with changing temperature extremes. Predicting urban temperature change will require rigorous assessment of climate models, to account for the uncertainty in projecting temperature in large urban agglomerates. CMIP6 ensemble of models, provide an opportunity for assessment of urban-based projections. The models however, would need to be of fine resolution to fully capture its variability since urban temperature is heavily influenced by local urban features that contribute to Urban heat island ...

Wastewater treatment plants (WWTPs) are traditionally designed to target the removal of contaminants such as total suspended solids, phosphorous, biological oxygen demand, and ammonia. Recent changes to the Federal Wastewater Systems Effluent Regulations (WSER) in Canada require all WWTPs to be operating with secondary treatment or equivalent by 2021. Upgrades being implemented at WWTPs across the country will improve the quality of final effluent discharged into the receiving waters. However, over the past several years, contaminants of emerging concern such as pharmaceuticals, personal care products, and endocrine disrupting compounds have become widely prevalent in wastewater. These compounds are not monitored or targets for removal in Canada causing them to be routinely discharged into surface waters. The Grand River watershed is the largest watershed in southern Ontario and receives effluent discharge from 30 WWTPs. Several studies have been conducted in the Grand River to asse ...

Analysis of carbon and water cycle variability in Canadian watersheds using coupled MESH-CLASSIC model. Assessing the impact of climate change on the McKenzie Creek in the Great Lakes region

Recent advances in the Mod´elisation Environmentale Communautaire Surface and Hydrology system (MESH) allows for vector-based routing to better represent the reality of the catchment structure and water processes within the catchment. MESH has also been coupled with the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) allows for the simulation of carbon, water, and energy cycles at a catchment scale. In this study, the MESH-CLASSIC model was tested in three catchments across Canada, the Groundhog River catchment (a Boreal Forest catchment in northern Ontario), the Big Creek catchment (a managed agricultural catchment in southern Ontario), and the White Gull Creek catchment (a boreal forest and wetland in northern Saskatchewan). The vector-based MESH-CLASSIC model simulations were performed for historic and future climate change scenarios, RCP 4.5 and 8.5. Model biases in simulating hydrological processes such as stream flow, evapotranspiration, snow mass, and soil ...

Daniel Mutton, M. Altaf Arain, Bruce Davidson, Daniel Princz (2022). Analysis of coupled MESH-CLASSIC model performance in Canadian watersheds . Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.

Research uses coupled MESH-CLASSIC model to predict future carbon, water, and energy cycle in three watersheds across Canada

Analysis of coupled MESH-CLASSIC model performance in Canadian watersheds

Biomaterials used in biomedical implants, diagnostic devices, and in-situ sensors, all face the issue of biofouling. Surface modification of biomaterial surfaces with antifouling polymers can prevent non-specific adsorption of proteins and other bio-foulants onto these surfaces. Although there are many antifouling polymers to chose from, getting the polymers onto different materials is challenging as the surface modification process is dependent on the substrate’s surface chemistry. This limits the kinds of materials that are able to be modified, especially in devices made with several materials that must be modified as a single unit. Therefore, the goal of this research is to develop an effective antifouling surface modification that is compatible with different types and classes of biomaterials. A three-step modification approach was taken to form dense antifouling polymer brushes. The surfaces were first activated using oxygen plasma to increase the density of surface hydroxyl group ...

Ice jam formation is a key concern for many rivers in cold regions. Ice jams can lead to destructive floods during the ice season and create major disturbances in the aquatic environment. In the past years, numerous approaches, including numerical, empirical and data-driven models, have been applied to understand and potentially help reduce the detrimental impacts of ice-jam formation and flooding on riverine communities. Although these approaches are capable of solving many ice-related problems, they still have some limitations. Recent advancements in machine learning offers many methodological opportunities to deal with a plethora of data. This study explores the use of modelling output (e.g. hydrological and hydraulic model results and global circulation model (GCM) output) in various machine learning algorithms to predict river-ice hydraulic processes, such as ice-jam formation and mid-winter breakup along the Saint John River, which is a transboundary and transborder river in Nort ...

Synthetic aperture radar (SAR) is a widely used tool for Earth observation activities. It is particularly effective during times of persistent cloud cover, low light conditions, or where in situ measurements are challenging. The intensity measured by a polarimetric SAR has proven effective for characterizing Arctic tundra landscapes due to the unique backscattering signatures associated with different cover types. However, recently, there has been increased interest in exploiting novel interferometric SAR (InSAR) techniques that rely on both the amplitude and absolute phase of a pair of acquisitions to produce coherence measurements, although the simultaneous use of both intensity and interferometric coherence in Arctic tundra image classification has not been widely tested. In this study, a time series of dual-polarimetric (VV, VH) Sentinel-1 SAR/InSAR data collected over one growing season, in addition to a digital elevation model (DEM), was used to characterize an Arctic tundra stud ...

Causes of software architectural change are clas- sified as perfective, preventive, corrective, and adaptive. Change classification is used to promote common approaches for address- ing similar changes, produce appropriate design documentation for a release, construct a developer’s profile, form a balanced team, support code review, etc. However, automated architectural change classification techniques are in their infancy, perhaps due to the lack of a benchmark dataset and the need for extensive human involvement. To address these shortcomings, we present a benchmark dataset and a text classifier for determining the architectural change rationale from commit descriptions. First, we explored source code properties for change classification independent of project activity descriptions and found poor outcomes. Next, through extensive analysis, we identified the challenges of classifying architectural change from text and pro- posed a new classifier that uses concept tokens derived from t ...

In Canada's Arctic tundra region, permafrost is continuous, and the landscape is rich in patterned features. Polygonal terrain, which includes both high- and low-centered features and their wet trenches below, is considered to be high-latitude wetlands in the continuous permafrost region. These prominent hydrological features retain and transport water within widespread ice-wedge networks and govern many ecosystem dynamics. Due to the meter-scale spatial gradients of these processes, mapping of polygonal wetland networks necessitates high-resolution imagery. To date, most studies have used optical imagery for this task; however, these sensors are affected by cloud cover and polar darkness, limiting image availability and repeatability. Thus, our overall objective was to evaluate high-resolution hybrid compact polarimetric (HCP) imagery from the recently launched Radarsat Constellation Mission (RCM), in fusion with ArcticDEM topographic data, for Arctic landscape mapping with a focus on ...

In recent decades, there has been a surge in the availability of precipitation datasets, each leveraging diverse data sources and sophisticated algorithms. However, the density of the gauged station network presents a substantial challenge in thoroughly assessing these datasets, particularly in regions with sparse coverage. This study seeks to quantify the observational uncertainty of precipitation across North America by introducing a novel framework. The framework is designed to detect potential outliers, categorize datasets based on their level of agreement, and operate at both monthly and daily time steps. Eleven datasets spanning from 2002 to 2017 are investigated: ANUSPLIN, CaPA, CHIRPS, CMORPH, DAYMET, ERA5, GSMaP, IMERG, MSWEP, PERSIANN and PRISM. Analyses at the grid-cell scale revealed that on average and across the entire domain, excluding outlier datasets reduced observational uncertainty by ~17% for the monthly time step and ~39% for the daily time step. Aggregating result ...

The seasonal temperature trends and ice phenology in the Great Slave Lake (GSL) are significantly influenced by inflow from the Slave River. The river undergoes a sequence of mechanical break-ups all the way to the GSL, initiating the GSL break-up process. Additionally, upstream water management practices impact the discharge of the Slave River and, consequently, the ice break-up of the GSL. Therefore, monitoring the break-up process at the Slave River Delta (SRD), where the river meets the lake, is crucial for understanding the cascading effects of upstream activities on GSL ice break-up. This research aimed to use Random Forest (RF) models to monitor the ice break-up processes at the SRD using a combination of satellite images with relatively high spatial resolution, including Landsat-5, Landsat-8, Sentinel-2a, and Sentinel-2b. The RF models were trained using selected training pixels to classify ice, open water, and cloud. The onset of break-up was determined by data-driven thresho ...

Significant challenges from changes in climate and land use face sustainable water use in the Canadian Prairies ecozone. The region has experienced significant warming since the mid-20th century, and continued warming of an additional 2 ∘C by 2050 is expected. This paper aims to enhance understanding of climate controls on Prairie basin hydrology through numerical model experiments. It approaches this by developing a basin-classification-based virtual modelling framework for a portion of the Prairie region and applying the modelling framework to investigate the hydrological sensitivity of one Prairie basin class (High Elevation Grasslands) to changes in climate. High Elevation Grasslands dominate much of central and southern Alberta and parts of south-western Saskatchewan, with outliers in eastern Saskatchewan and western Manitoba. The experiments revealed that High Elevation Grassland snowpacks are highly sensitive to changes in climate but that this varies geographically. Spring maxi ...

Spence, C., He, Z., Shook, K. R., Mekonnen, B. A., Pomeroy, J. W., Whitfield, C. J., & Wolfe, J. D. (2022). Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach. Hydrology and Earth System Sciences. 26, 1801-1819. https://doi.org/10.5194/hess-26-1801-2022

Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach

Wetland drainage has been pervasive in the North American Prairie Pothole Region. There is strong evidence that this drainage increases the hydrological connectivity of previously isolated wetlands and, in turn, runoff response to snowmelt and rainfall. It can be hard to disentangle the role of climate from the influence of wetland drainage in observed records. In this study, a basin-classification-based virtual modelling approach is described that can isolate these effects on runoff regimes. The basin class which was examined, entitled Pothole Till, extends throughout much of Canada's portion of the Prairie Pothole Region. Three knowledge gaps were addressed. First, it was determined that the spatial pattern in which wetlands are drained has little influence on how much the runoff regime was altered. Second, no threshold could be identified below which wetland drainage has no effect on the runoff regime, with drainage thresholds as low as 10 % in the area being evaluated. Third, wette ...

Assessing runoff sensitivity of North American Prairie Pothole Region basins to wetland drainage using a basin classification-based virtual modelling approach

The importance of trees in non-forest landscapes has been the focus of only a few studies. However, these trees provide many important ecosystem services. In this study, we mapped and quantified these trees using Sentinel-2 (S2) and very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed a Random Forest (RF) classification to map the spatial distribution of native trees in different scenarios. The optimal model showed an overall accuracy and kappa of 0.99 and 0.98, respectively. We mapped 40,500 km2 of tree cover, including native tree cover (approximately 29,565 km2 ≈10.5%), excluding plantations, regional and provincial parks, and water bodies in the Canadian prairie region of Saskatchewan. According to our results, the highest numbers of native trees were found in the eastern and northwestern parts of the study area – cluster “BLK_1” and the “Black” soil zone, with total cover of 5,388 and 13,233 km2, respectively. The lowest numbers of native t ...

Climate change presents unique challenges for grape growers across the world. In Ontario, three distinct viticultural regions are experiencing climatic shifts towards warmer growing seasons. According to historical records collected from Environment and Climate Change Canada, Lake Erie North Shore has transitioned from an intermediate-to-warm growing season classification, the Niagara Peninsula from the lower to upper limits of the intermediate zone, and Prince Edward County from cool to intermediate, when analyzing their average growing season temperatures. Terroir is directly related to vine water status, an indicator of grapevine stress. Biophysical responses controlled by air temperature and precipitation include fluctuations in vapour pressure deficits, evapotranspiration, and water-use-efficiency rates, as well as soil water content levels. By conducting an extensive literature review, the development of a conceptual model addresses how variations in climatic controls, under the ...

Lakes are regarded as sentinels of change, where shifts in environmental conditions significantly affect lake phenology. A significant consequence of the change is the perceived increase in the frequency, magnitude, and severity of algal blooms in lakes globally. Algal blooms/increased productivity in lakes pose significant ecological, economic and health risks, impacting fisheries, tourism, and freshwater access. The impacts of external nutrient loading from anthropogenic sources are well documented; however, blooms have been observed to occur in even remote lakes. Climate change is a hypothesized driver of these recent algal bloom trends, such as increasing global air temperatures, water temperatures, lake ice loss, precipitation intensity, and drought. Past research on the impact of climatic drivers on algal biomass dynamics has often been limited to lab, mesocosm, or short termed observations, due to limited in situ data. New remote sensing data products make use of historic multis ...

Global gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent r ...

The topic of satellite remote sensing of lake ice has gained considerable attention in recent years. Optical satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) allow for the monitoring of lake ice cover (an Essential Climate Variable or ECV), and dates associated with ice phenology (freeze-up, break-up, and ice cover duration) over large areas in an era where ground-based observational networks have nearly vanished in many northern countries. Ice phenology dates as well as dates of maximum and minimum ice cover extent (for lakes that do not form a complete ice cover in winter or do not totally lose their ice cover in summer) are useful for assessing long-term trends and variability in climate, particularly due to their sensitivity to changes in near-surface air temperature. Existing knowledge-driven (threshold-based) retrieval algorithms for lake ice cover mapping that use top-of-atmosphere (TOA) reflectance products do not perform well under lower solar illu ...

Wu, Y., Duguay, C. R., & Xu, L. (2021). Assessment of machine learning classifiers for global lake ice cover mapping from MODIS TOA reflectance data. Remote Sensing of Environment, 253, 112206. https://doi.org/10.1016/j.rse.2020.112206 .

Assessment of machine learning classifiers for global lake ice cover mapping from MODIS TOA reflectance data

Yirdaw, S.Z., Snelgrove, K.R., Seglenieks, F.R., Agboma, C.O. and Soulis, E.D. (2009). Assessment of the WATCLASS Hydrological Model Result of the Mackenzie River Basin Using the GRACE Satellite Total Water Storage Measurement. Hydrologic Processes, https://doi.org/10.1002/hyp.7450.

Assessment of the WATCLASS Hydrological Model Result of the Mackenzie River Basin Using the GRACE Satellite Total Water Storage Measurement

Assessment of the WATCLASS hydrological model result of the MacKenzie River Basin using the result of the GRACE satellite total water storage measurement

When a programmer makes changes to a target program entity (files, classes, methods), it is important to identify which other entities might also get impacted. These entities constitute the impact set for the target entity. Association rules have been widely used for discovering the impact sets. However, such rules only depend on the previous co-change history of the program entities ignoring the fact that similar entities might often need to be updated together consistently even if they did not co-change before. Considering this fact, we investigate whether cloning relationships among program entities can be associated with association rules to help us better identify the impact sets. In our research, we particularly investigate whether the impact set detection capability of a clone detector can be utilized to enhance the capability of the state-of-the-art association rule mining technique, Tarmaq, in discovering impact sets. We use the well known clone detector called NiCad in our in ...

Repeatable methods capable of quantifying Arctic surface water extent at high resolutions are important, but still require development. Here, we present a study using very-high resolution (VHR) X-band Synthetic Aperture Radar (SAR) imagery from Capella Space for fine-scale semantic segmentation of Arctic surface water features. Our study proposes a modified U-Net encoder-decoder model for this task, optimized using the Nadam algorithm. Otsu thresholding was leveraged to rapidly generate 512 × 512-pixel patches for the U-Net, resulting in an efficient and automated training pipeline. Within this study, we also quantitatively compared the deep learning (DL) U-Net to a shallow machine learning (ML) algorithm, XGBoost (XGB), and evaluated the Capella Space imagery against spatially and temporally coincident Sentinel-1 C-band. Performance evaluations showed the U-Net outperforms XGB measured under several statistical metrics, reaching an Intersection over Union (IoU) of 0.955. An explainabi ...

Simulation-optimization techniques in support of groundwater management are computationally expensive. To tackle such computational burden, a variety of surrogate modeling-frameworks have been proposed, where a cheaper-to-run model referred to as a surrogate is used in lieu of a computationally intensive model. These frameworks are generally based on what referred herein to as ‘global surrogate modelling’ where a single surrogate approximates the underlying response surface of a model. Such classic frameworks, however, are sub-optimal when the response surface is complex and/or high-dimensional. This paper proposes a novel ‘local surrogate modelling’ framework that simultaneously builds and evolves multiple local surrogates, guided by an automatic clustering method. Unlike traditional clustering methods that select the number of clusters a priori, the proposed automatic clustering method concurrently determines the optimum number of clusters and the clustering scheme itself. To serve a ...

Release notes are admitted as an essential technical document in software maintenance. They summarize the main changes, e.g. bug fixes and new features, that have happened in the software since the previous release. Manually producing release notes is a time-consuming and challenging task. For that reason, sometimes developers neglect to write release notes. For example, we collect data from GitHub with over 1900 releases, and among them, 37% of the release notes are empty. To mitigate this problem, we propose an automatic release notes generation approach by applying the text summarization techniques, i.e. TextRank. To improve the keyword extraction method of traditional TextRank, we integrate the GloVe word embedding technique with TextRank. After generating release notes automatically, we apply machine learning algorithms to classify the release note contents (or sentences). We classify the contents into six categories, e.g. bug fixes and performance improvements, to represent the r ...

Automatically generating release notes with content classification models

Beaver (Castor canadensis and Castor fiber) are regarded widely as ecosystem engineers and the dams they create are well-known for their ability to drastically alter the hydrology of rivers. As a result, beaver are increasingly being included in green infrastructure practices to combat the effects of climate change and enhance ecosystem resilience. Both drought and flood mitigation capabilities have been observed in watersheds with beaver dam structures; however, how dams possess contrasting mitigation abilities is not fully understood since most studies neglect to acknowledge variation in beaver dam structures. In this study, an extensive cross-site survey of the physical and hydrologic properties of beaver dams was conducted in the Canadian Rocky Mountains in Alberta. This research aimed to improve the understanding of the hydrology of beaver dams by categorizing dams using their intrinsic properties and landscape settings to identify fundamental patterns that may be applicable acros ...

In Arctic-boreal regions, climate change induced permafrost thaw causes complex interactions between topography, microbiology, hydrology and vegetation distribution that impact the emission rate of radiatively important gasses like methane (CH4). Vegetation distribution, for example, can be used as a proxy for permafrost thaw and the greenhouse gas emissions associated with each stage. To scale emissions up from the site level, more accurate remotely sensed data is needed to produce the necessary vegetation cover maps. Analyses of data collected from unpiloted aerial systems (UAS) have proven effective at classifying vegetation distribution into land cover classes that often include multiple species. However, focusing classification at the level of species functional group (SFG) could further improve scaling efforts by representing vegetation distribution, and thus permafrost thaw impacts and gas emissions, more accurately. High resolution, UAS-derived, hyperspectral imagery was collec ...

Beyond what the eye can see: using high-resolution UAS-derived hyperspectral imagery to classify boreal peatland vegetation

Satellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the field, it is almost impossible to reorganize backscattering responses at pixel scales. Considering the influence of soil storage on watershed streamflow, we thus suggested watershed-scale hydrological validation. In addition, to overcome the limitations of backscattering models that are widely used for C-band Synthetic Aperture Radar (SAR) soil moisture but applied to bare soils only, in this study, RADARSAT-2 soil moisture was stochastically retrieved to correct vegetation effects arising from agricultural lands. Roughness-corrected soil moisture retrievals were assessed at various spatial scales over the Brightwater Creek basin (land cover: crop lands, gross drainage area: 1540 km2) in Sask ...

Increased loading of nitrogen and phosphorus from agricultural and urban intensification has led to severe degradation of inland and coastal waters. Lakes, reservoirs, wetlands, and streams retain and transform these nutrients, thus regulating their delivery to downstream waters. While the processes controlling nitrogen and phosphorus removal from the water column are relatively well-known, there is a lack of quantitative understanding of how these processes manifest across spatial scales. This thesis explores the relationship between hydrologic and biogeochemical controls on nutrient processing in a lentic water body (lakes, reservoirs, and wetlands). Here, our work revolves around three research questions: 1) What are the emergent patterns between nutrient processing rates and residence times in lentic systems? 2) What are the underlying mechanisms contributing to the observed patterns? 3) What is the relative magnitude of nutrient retention as a function of wetland size? These ques ...

Flow management has the potential to significantly affect ecosystem condition. Shallow lakes in arid regions are especially susceptible to flow management changes, which can have important implications for the formation of cyanobacterial blooms. Here, we reveal water quality shifts associated with changing source water inflow management. Using in situ monitoring data, we studied a seven-year time span during which inflows to a shallow, eutrophic drinking water reservoir transitioned from primarily natural landscape runoff (2014–2015) to managed flows from a larger upstream reservoir (Lake Diefenbaker; 2016–2020) and identified significant changes in cyanobacteria (as phycocyanin) using generalized additive models to classify cyanobacterial bloom formation. We then connected changes in water source with shifts in chemistry and the occurrence of cyanobacterial blooms using principal components analysis. Phycocyanin was greater in years with managed reservoir inflow from a mesotrophic ups ...

The Global Water Futures program (GWF) was granted $77.8 million by the Canada First Research Excellence Fund to conduct research on the forecasting and management of water futures in Canada as part of an effort to combat projected risks associated with global climate change. The production of scientific knowledge is a clear objective of the GWF program, and the evaluation and enumeration of research outcomes is a key metric. The goal of this work is to create a comprehensive bibliographic analysis of research outputs across the full extent of the GWF program including metadata such as the title, author, publication date and geographic locations of the works. Processes to incorporate quality control, classification and validation were documented to ensure these outputs are effectively managed, monitored and evaluated. Links to the resources are also made available to ensure they are easily accessible to a wide range of audiences. Enhanced accessibility is key in sharing critical climat ...

The design and maintenance of APIs (Application Programming Interfaces) are complex tasks due to the constantly changing requirements of their users. Despite the efforts of their designers, APIs may suffer from a number of issues (such as incomplete or erroneous documentation, poor performance, and backward incompatibility). To maintain a healthy client base, API designers must learn these issues to fix them. Question answering sites, such as Stack Overflow (SO), have become a popular place for discussing API issues. These posts about API issues are invaluable to API designers, not only because they can help to learn more about the problem but also because they can facilitate learning the requirements of API users. However, the unstructured nature of posts and the abundance of non-issue posts make the task of detecting SO posts concerning API issues difficult and challenging. In this paper, we first develop a supervised learning approach using a Conditional Random Field (CRF), a statis ...

Ahasanuzzaman, M., Asaduzzaman, M., Roy, C. K., & Schneider, K. A. (2020). CAPS: a supervised technique for classifying Stack Overflow posts concerning API issues. Empirical Software Engineering, 25(2), 1493-1532. https://doi.org/10.1007/s10664-019-09743-4

CAPS: a supervised technique for classifying Stack Overflow posts concerning API issues

Permafrost thaw/degradation in the Northern Hemisphere due to global warming is projected to accelerate in coming decades. Assessment of this trend requires improved understanding of the evolution and dynamics of permafrost areas. Land surface models (LSMs) are well-suited for this due to their physical basis and large-scale applicability. However, LSM application is challenging because (a) LSMs demand extensive and accurate meteorological forcing data, which are not readily available for historic conditions and only available with significant biases for future climate, (b) LSMs possess a large number of model parameters, and (c) observations of thermal/hydraulic regimes to constrain those parameters are severely limited. This study addresses these challenges by applying the MESH-CLASS modeling framework (Modélisation Environmenntale communautaire—Surface et Hydrology embedding the Canadian Land Surface Scheme) to three regions within the Mackenzie River Basin, Canada, under various me ...

Permafrost plays an important role in the hydrology of arctic/subarctic regions. However, permafrost thaw/degradation has been observed over recent decades in the Northern Hemisphere and is projected to accelerate. Hence, understanding the evolution of permafrost areas is urgently needed. Land surface models (LSMs) are well-suited for predicting permafrost dynamics due to their physical basis and large-scale applicability. However, LSM application is challenging because of the large number of model parameters and the complex memory of state variables. Significant interactions among the underlying processes and the paucity of observations of thermal/hydraulic regimes add further difficulty. This study addresses the challenges of LSM application by evaluating the uncertainty due to meteorological forcing, assessing the sensitivity of simulated permafrost dynamics to LSM parameters, and highlighting issues of parameter identifiability. Modelling experiments are implemented using the MESH- ...

Human-induced disturbances of terrestrial and aquatic ecosystems continue at alarming rates. With the advent of both raw sensor and analysis-ready datasets, the need to monitor ecosystem disturbances is now more imperative than ever; yet the task is becoming increasingly complex with increasing sources and varieties of earth observation data. In this research, computer vision methods and tools are interrogated to understand their capability for comparing spatial patterns. A critical survey of literature provides evidence that computer vision methods are relatively robust to scale and highlights issues involved in parameterization of computer vision models for characterizing significant pattern information in a geographic context. Utilizing two widely used pattern indices to compare spatial patterns in simulated and real-world datasets revealed their potential to detect subtle changes in spatial patterns which would not otherwise be feasible using traditional pixel-level techniques. A t ...

Projections of change in high-flow extremes with global warming vary widely among, and within, large midlatitude river basins. The spatial variability of these changes is attributable to multiple causes. One possible and little-studied cause of changes in high-flow extremes is a change in the synchrony of mainstem and tributary streamflow during high-flow extremes at the mainstem-tributary confluence. We examined reconstructed and simulated naturalized daily streamflow at confluences on the Columbia River in western North America, quantifying changes in synchrony in future streamflow projections and estimating the impact of these changes on high-flow extremes. In the Columbia River basin, projected flow regimes across colder tributaries initially diverge with warming as they respond to climate change at different rates, leading to a general decrease in synchrony, and lower high-flow extremes, relative to a scenario with no changes in synchrony. Where future warming is sufficiently larg ...

The microbiome has been described as an additional host “organ” with well-established beneficial roles. In addition to aiding in digestion of food and uptake of nutrients, microbiota in guts of vertebrates are responsible for regulating several beneficial functions, including stimulating immune responses and maintaining homeostasis. However, effects of exposures to chemicals on both structure and function of the gut microbiome of fishes are understudied. The overall purpose of research reported in this thesis was to characterize the effects of polycyclic aromatic hydrocarbons (PAHs) on the gut microbiomes of freshwater fishes, using both laboratory- and field-based assessments. PAHs have a number of well-characterized deleterious impacts in fish and are known modulators of the aryl hydrocarbon receptor, a receptor that has a bidirectional relationship with the microbiome. As such, this chemical class was selected to investigate targeted effects on the microbiome. The objectives of this ...

The microbiome has been described as an additional host “organ” with well-established beneficial roles. In addition to aiding in digestion of food and uptake of nutrients, microbiota in guts of vertebrates are responsible for regulating several beneficial functions, including stimulating immune responses and maintaining homeostasis. However, effects of exposures to chemicals on both structure and function of the gut microbiome of fishes are understudied. The overall purpose of research reported in this thesis was to characterize the effects of polycyclic aromatic hydrocarbons (PAHs) on the gut microbiomes of freshwater fishes, using both laboratory- and field-based assessments. PAHs have a number of well-characterized deleterious impacts in fish and are known modulators of the aryl hydrocarbon receptor, a receptor that has a bidirectional relationship with the microbiome. As such, this chemical class was selected to investigate targeted effects on the microbiome. The objectives of this ...

Kershaw, G. G. L. (2020). Characterizing alpine basin land cover classes and their influence on water storage and routing in the Mackenzie Mountains, Kaska & Shúhtaot'ine shared territory. University of Guelph GEG Brown Bag Speakers Series. Guelph, ON, Canada.

Characterizing alpine basin land cover classes and their influence on water storage and routing in the Mackenzie Mountains, Kaska & Shúhtaot'ine shared territory

Vegetation growth and productivity in Canada's boreal are governed by a characteristically short growing season, which is largely driven by the Freeze/Thaw(F/T) cycles that constrain the supply of water and nutrients through seasonally frozen soils. Since much of the vegetation in the Canadian boreal consists of evergreen species which do not experience large seasonal cycles in photosynthetic biomass, monitoring this growing season through the use of visible and near-infrared wavelengths via spectral indices such as the Normalized Difference Vegetation Index (NDVI) has proven difficult. To adequately capture growing season constraints in these northern environments, microwave remote sensing offers potential. L-band passive microwave observations are sensitive to near-surface soil moisture conditions and can monitor F/T states effectively due to the high contrast in permittivity between frozen and thawed soils. We characterize F/T information using products from both the Soil Moisture O ...

Plant diversity varies immensely over large-scale gradients in temperature, precipitation, and seasonality at global and regional scales. This relationship may be driven in part by climatic variation in the relative importance of abiotic and biotic interactions to the diversity and composition of plant communities. In particular, biotic interactions may become stronger and more host specific with increasing precipitation and temperature, resulting in greater plant species richness in wetter and warmer environments. This hypothesis predicts that the many defensive compounds found in plants’ metabolomes should increase in richness and decrease in interspecific similarity with precipitation, temperature, and plant diversity. To test this prediction, we compared patterns of chemical and morphological trait diversity of 140 woody plant species among seven temperate forests in North America representing 16.2°C variation in mean annual temperature (MAT), 2,115 mm variation in mean annual prec ...

Qu, Y., Scott, K.A. (2024) Classification of Ice and Water In a Regulated River Using Convolutional Neural Networks, Geoinformatics 2024

Classification of Ice and Water In a Regulated River Using Convolutional Neural Networks

Tang, W., and Carey, S.K. 2022.?Classifying Annual Daily Hydrographs in Western North America using t-Distributed Stochastic Neighbor Embedding (t-SNE). Hydrological Processes. https://doi.org/10.1002/hyp.14473.

Classifying Annual Daily Hydrographs in Western North America using t-Distributed Stochastic Neighbor Embedding (t-SNE

Classifying terrain in a muskeg-wetland regime for application to a GRU type distributed hydrologic model

A code clone is a pair of similar code fragments, within or between software systems. To detect each possible clone pair from a software system while handling the complex code structures, the clone detection tools undergo a lot of generalization of the original source codes. The generalization often results in returning code fragments that are only coincidentally similar and not considered clones by users, and hence requires manual validation of the reported possible clones by users which is often both time-consuming and challenging. In this paper, we propose a machine learning based tool 'CloneCognition' (Open Source Codes: https://github.com/pseudoPixels/CloneCognition ; Video Demonstration: https://www.youtube.com/watch?v=KYQjmdr8rsw) to automate the laborious manual validation process. The tool runs on top of any code clone detection tools to facilitate the clone validation process. The tool shows promising clone classification performance with an accuracy of up to 87.4%. The tool ...

Per- and poly-fluoroalkyl substances (PFASs) are a diverse group of over 12,000 synthetic, amphiphilic compounds known for a resistance to degradation that has led to some compounds having a widespread, global presence. Despite not being considered acutely potent compared to other environmental pollutants, PFASs can undergo extensive biomagnification and bioaccumulation in aquatic environments. This results in both humans and wildlife being chronically exposed to PFASs and resulting in some PFASs also being ubiquitous in blood and tissues, with associated toxic effects. While specific substances of concern have been phased-out or banned, other PFASs that are emerging as alternative substances are still produced and are being released into the environment. These “replacement” PFASs are emerging as potential contaminants of concern but remain under-studied and un-tested with relatively unknown toxicity profiles. Therefore, this dissertation aimed to (1) provide an assessment of two such ...

Bellisario, L., L.D. Boudreau, D.L. Verseghy, W.R. Rouse, and P.D. Blanken, (1999). Comparing the performance of the Canadian Land Surface Scheme (CLASS) for two subarctic terrain types. Atmos-Ocean, 38, 181-204.

Comparing the performance of the Canadian Land Surface Scheme (CLASS) for two subarctic terrain types

Kamali M., K. Ponnambalam and E.D. Soulis. (2007). Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization. Hydrology and Earth System Sciences - Discussions pp2307-2321

Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization

Invited Talk to Class at Western University Feb 14th, 1:30 - 3:00 PM

Mutton, D., Arain, M. A. Coupled MESH-CLASSIC model for catchment-scale water and carbon cycle studies. Global Water Futures 4th Annual Science Meeting. University of Saskatoon, Saskatoon, Saskatchewan, Canada , May 17-19, 2021.

Coupled MESH-CLASSIC model for catchment-scale water and carbon cycle studies

The North American beaver (Castor canadensis) is regarded widely as an ecosystem engineer and the dams they create are well known for their ability to drastically alter the hydrology of river basins. As a result, beavers are increasingly being included in green infrastructure practices to combat the effects of climate change and enhance ecosystem resilience. Both drought and flood mitigation capabilities have been observed in watersheds with beaver dam structures; however, how dams can possess such contrasting mitigation abilities is not fully understood as most studies neglect to acknowledge the incredible variation in beaver dam structures. In this study, an extensive cross-site survey of dam properties and water flow through dams in the Canadian Rocky Mountains in Alberta was conducted. The dam flow type classification from Woo and Waddington (1990) was evaluated in this new context and adapted to include two new flow types not found in the original study. The survey revealed signif ...

Optimizing microbial metabolism and improving wastewater treatment efficiency require a deep understanding of carbon utilization and advanced microbial monitoring tools. While mixotrophic bacteria offer promising applications in bioplastic production, challenges persist in understanding their metabolic preferences under varying substrate conditions. Similarly, the ability to accurately detect bacteria is essential for preventing sludge bulking and ensuring operational efficiency. This dissertation addresses these challenges by investigating the carbon preferences of a mixotrophic bacterium for enhanced biopolymer synthesis and developing artificial intelligence (AI)-based image processing tools for microbial detection and segmentation in wastewater treatment. Specifically, the metabolic mechanisms and bacteria substrate preferences were explored under different organic (acetate, butyrate) and gaseous (H₂, CO₂, O₂) concentrations, revealing a predominant reliance on organic carbon durin ...

In municipal wastewater treatment, effective secondary clarification relies on the balance between floc-forming bacteria and filamentous bacteria. Consequently, comprehensive and real-time monitoring of this balance will enable reliable operation of biological wastewater treatment. This research presents an artificial intelligence (AI)-based approach for the classification of filamentous and floc-forming bacteria in microscopic images using deep learning. To provide ground truth labeling, an automated rule-based segmentation algorithm was developed using color and morphology criteria along with supplementary filtration steps to enhance the precision of filamentous and floc-forming bacteria identification. The segmentation algorithm demonstrated reliable detection and categorization of bacteria across varying background intensities and effectively recognized intricate microbial configurations. Subsequently, the supervised deep learning model was trained on the segmented images and const ...

Various functional DNA molecules have been used for the detection of environmental contaminants in water, but their practical applications have been limited. To address this gap, this review highlights the efforts to develop field-deployable water quality biosensors. The biosensor devices include microfluidic, lateral flow and paper-based devices, and other novel ideas such as the conversion of glucometers for the detection of environmental analytes. In addition, we also review DNA-functionalized hydrogels and their use in diffusive gradients in thin films (DGT) devices. We classify the sensors into one-step and two-step assays and discuss their practical implications. While the review is focused on works reported in the last five years, some classic early works are cited as well. Overall, most of the existing work only tested spiked water samples. Future work needs to shift to real environmental samples and the comparison of DNA-based sensors to standard analytical methods.

The Köppen-Geiger (KG) climate classification has been widely used to determine the climate at global and regional scales using precipitation and temperature data. KG maps are typically developed using a single product; however, uncertainties in KG climate types resulting from different precipitation and temperature datasets have not been explored in detail. Here, we assess seven global datasets to show uncertainties in KG classification from 1980 to 2017. Using a pairwise comparison at global and zonal scales, we quantify the similarity among the seven KG maps. Gauge- and reanalysis-based KG maps have a notable difference. Spatially, the highest and lowest similarity is observed for the North and South Temperate zones, respectively. Notably, 17% of grids among the seven maps show variations even in the major KG climate types, while 35% of grids are described by more than one KG climate subtype. Strong uncertainty is observed in south Asia, central and south Africa, western America, an ...

Detailed investigation of discrepancies in Köppen-Geiger climate classification using seven global gridded products

If two or more program entities (such as files, classes, methods) co-change (i.e., change together) frequently during software evolution, then it is likely that these two entities are coupled (i.e., the entities are related). Such a coupling is termed as evolutionary coupling in the literature. The concept of traditional evolutionary coupling restricts us to assume coupling among only those entities that changed together in the past. The entities that did not co-change in the past might also have coupling. However, such couplings can not be retrieved using the current concept of detecting evolutionary coupling in the literature. In this paper, we investigate whether we can detect such couplings by applying transitive rules on the evolutionary couplings detected using the traditional mechanism. We call these couplings that we detect using our proposed mechanism as transitive evolutionary couplings. According to our research on thousands of revisions of four subject systems, transitive e ...

Snow interception in cold regions needleleaf forest canopies is a crucial process that controls local snow accumulation and redistribution over >20% of the Earth's land surface. Various ground-based methods exist to measure intercepted snow load, however all are based on single-tree measurements and are difficult to implement. No research has focussed on detecting large areal intercepted snow loads and no studies have assessed the use of satellite observations. In this study, four remote sensing indices (NDSI, NDVI, albedo, and land surface temperature (LST)) were retrieved from Landsat images to study their sensitivity to canopy intercepted snow and the possibility of using them to detect the presence of intercepted snow. The results indicate that presence of intercepted snow on canopy increased NDSI and albedo, but decreased NDVI. Intercepted snow presence also decreased the areal variability of NDSI and NDVI while increasing that of albedo. For these three indices, the differences b ...

Vernal pools are small, temporary, forested wetlands of ecological importance with a high sensitivity to changing climate and land-use patterns. These ecosystems are under considerable development pressure in southeastern Georgian Bay, where mapping techniques are required to inform wise land-use decisions. Our mapping approach combines common machine learning techniques [random forest, support vector machines (SVMs)] with object-based image analysis. Using multispectral image segmentation on high-resolution orthoimagery, we first created objects and assigned classes based on field collected data. We then supplied machine learning algorithms with data from freely available sources (Ontario orthoimagery and Sentinel 2) and tested accuracy on a reserved dataset. We achieved producer’s accuracies of 85 and 79% and user’s accuracies of 78 and 84% for random forest and SVMs models, respectively. Difficulty differentiating between small, dark shadows and small, obscured pools accounted for m ...

There are many real-world hydrological problems on the Canadian Prairies for which existing tools are poorly suited, due to the region’s complex cold-region hydrology and its equally complex hydrography, which is dominated by depressions, poorly defined and results in dynamic drainage basin contributing areas to streamflow. The complexities of the problems are compounded by changes in hydrology due to climate change, and by changes in depressional storage capacities due to wetland drainage. Although some hydrological models (CRHM, MESH) are able to simulate Prairie hydrology, including the effects of changes in climate, they do not have the ability to simulate detailed local-scale hydraulics. Conversely, hydraulic models which can simulate these small-scale features do not have the ability to simulate prairie hydrological processes. The Prairie Hydrology Design and Analysis Product (PHyDAP) deploys the research results of the GWF Prairie Water Project to produce a tool useful for solvi ...

Preferential flowpaths transport phosphorus (P) to agricultural tile drains. However, if and to what extent this may vary with soil texture, moisture conditions, and P placement is poorly understood. This study investigated (a) interactions between soil texture, antecedent moisture conditions, and the relative contributions of matrix and preferential flow and (b) associated P distributions through the soil profile when fertilizers were applied to the surface or subsurface. Brilliant blue dye was used to stain subsurface flowpaths in clay and silt loam plots during simulated rainfall events under wet and dry conditions. Fertilizer P was applied to the surface or via subsurface placement to plots of different soil texture and moisture condition. Photographs of dye stains were analysed to classify the flow patterns as matrix dominated or macropore dominated, and soils within plots were analysed for their water-extractable P (WEP) content. Preferential flow occurred under all soil texture ...

In addition to aiding in digestion of food and uptake of nutrients, microbiota in guts of vertebrates are responsible for regulating several beneficial functions, including development of an organism and maintaining homeostasis. However, little is known about effects of exposures to chemicals on structure and function of gut microbiota of fishes. To assess effects of exposure to polycyclic aromatic hydrocarbons (PAHs) on gut microbiota, male and female fathead minnows (Pimephales promelas) were exposed to environmentally-relevant concentrations of the legacy PAH benzo[a]pyrene (BaP) in water. Measured concentrations of BaP ranged from 2.3 × 10−3 to 1.3 μg L−1. The community of microbiota in the gut were assessed by use of 16S rRNA metagenetics. Exposure to environmentally-relevant aqueous concentrations of BaP did not alter expression levels of mRNA for cyp1a1, a “classic” biomarker of exposure to BaP, but resulted in shifts in relative compositions of gut microbiota in females rather ...

Hobbi, S., Papalexiou, S.M., Rupa, C., Tang, G., Clark, M.P., Markonis, I., 2021. Discrepancies in Köppen-Geiger Climate Classification Using Ten Global Gridded Products. AGU Fall Meeting 2021, AGU.?

Discrepancies in Köppen-Geiger Climate Classification Using Ten Global Gridded Products

Holmes Jason , Discrete-time Markov chain modelling of the Ontario air quality health index & image classification of Diatom genera using decision tree-based classifiers, 2021

Discrete-time Markov chain modelling of the Ontario air quality health index & image classification of Diatom genera using decision tree-based classifiers

Differential impacts of policies or changes in environmental conditions on people is a growing area of interest to decision-makers, yet remains an often neglected area of study for the environmental valuation literature. Using data from a large national survey of over 24,000 people conducted in Canada, this paper implements a latent class Kuhn-Tucker recreation demand model to assess differences in preferences and values for nature-based activities. Preferences are disaggregated by self-reported Indigeneity, immigration status, and gender. We find that Indigenous people receive 63% greater benefits from participating in nature-based activities compared to non-Indigenous people living in Canada. Immigrants have the lowest participation in, and benefits associated with, nature-based activities. Similarly, women receive 21% lesser benefits associated with nature-based activities when compared to men. These results demonstrate that Indigenous peoples may be more vulnerable to adverse impac ...

Kershaw, G.G.L. (2019). Distinguishing alpine valley landcover classes based on surface and subsurface hydrology. Cold Regions Research Centre Days. Waterloo, ON, Canada. (Oral) Conference Presentation

Distinguishing alpine valley landcover classes based on surface and subsurface hydrology

Phytoplankton monitoring is essential for better understanding and mitigation of phytoplankton bloom formation. We present a microfluidic cytometer with two imaging modalities for onsite detection and identification of phytoplankton: a lensless imaging mode for morphological features, and a fluorescence imaging mode for autofluorescence signal of phytoplankton. Both imaging modes are integrated in a microfluidic device with a field of view (FoV) of 3.7 mm × 2.4 mm and a depth of field (DoF) of 0.8 mm. The particles in the water flow channel can be detected and classified with automated image processing algorithms and machine learning models using their morphology and fluorescence features. The performance of the device was demonstrated by measuring Chlamydomonas, Euglena, and non-fluorescent beads in both separate and mixed flow samples. The recall rates for Chlamydomonas and Euglena ware 93.6% and 94.4%. The dual-modality imaging approach enabled observing both morphology and fluoresc ...

Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning

Tile-drainage area has expanded across the Canadian Lake Erie watershed in recent decades, and effects on phosphorus (P) loading are unclear. Eleven years (2010 to 2021) of daily P, total suspended solids (TSS), discharge, and climatological data were aggregated from three Canadian tributaries that form a gradient of tiled areas: East Sydenham River (ESR, 60% tile), Thames River (TR, 48% tile), and Grand River (GR, 23% tile). Instead of using traditional seasons (winter, spring, summer, fall), we classified seasons by air temperature to highlight hydrological periods of importance for P loss through tile drains. Seasons included frozen (<?3.2 °C), thawing (?3.2 – 6.7 °C), bare (6.7 – 15.9 °C), and growing (>15.9 °C). Nonparametric comparisons revealed that during every season, the ESR and TR had significantly higher soluble reactive P (SRP) and total P (TP) concentrations than the GR. For %SRP, the ESR was significantly higher than the other rivers during every season, while for TSS, t ...

Large-scale pre-trained transformer models such as BERT have become ubiquitous in Natural Language Processing (NLP) research and applications. They bring significant improvements to both academia benchmarking tasks and industry applications: the average score on the General Language Understanding Evaluation benchmark (GLUE) has increased from 74 to 90+; commercial search engines such as Google and Microsoft Bing are also applying BERT-like models to search. Despite their exciting power, these increasingly large transformer-based models are notorious for having billions of parameters and being slow in both training and inference, making deployment difficult when inference time and resources are limited. Therefore, model efficiency has become a more important and urgent problem in the transformer era. In this thesis, we propose and innovate methods for efficient NLP models. We choose to specifically focus on inference efficiency: pre-trained models are almost always publicly available, a ...

Climate change, water stress, and rapid population growth have increased the need to manage water resources through innovative sustainable technologies. Decentralized systems such as membrane treatment trains have become increasingly important to provide high volumes of potable water to millions of people. Pressure-driven membrane systems have dominated separation processes due to their low cost, small footprint, ease of operation, and high permeate quality. Conventionally, pressure-driven membranes are classified into microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). MF and UF membranes operate under low pressure (< 7 bar, <~100 psi). They can separate a variety of large particles such as bacteria, natural organic matter, suspended solids, and colloids. In contrast, NF and RO membranes are more energy-intense due to operating at high pressures (7 – 80 bar, ~100 – 1200 psi) and can remove small molecules such as ions, pharmaceuticals, and heavy ...

Wet terrestrial ecosystems play a vital role in the Arctic, linking various hydro-ecological and permafrost processes. However, climate warming is altering these ecosystems, impacting their functional properties and spatial extents. Despite their importance, current maps are often limited by thematic detail, spatial resolution, or coverage. To better assess ecosystem status, vulnerability, and changes, more comprehensive datasets are needed. This Ph.D. addressed this research gap by studying several emerging Earth observation (EO), remote sensing (RS), and machine learning (ML) techniques for enhanced wet terrestrial ecosystem mapping and monitoring across the Arctic at various spatial scales, from local to regional. Each chapter examined new spaceborne synthetic aperture radar (SAR) datasets, given SAR's sensitivity to moisture and inundation. The initial chapters focused on high and very-high resolution (VHR) SAR imagery. First, the recently launched Radarsat Constellation Mission (R ...

Aim High-throughput pipelines supported by eDNA metabarcoding have been applied in various freshwater ecosystems. Both eDNA in ethanol (EtOH) samples (ES-eDNA) and in water samples (WS-eDNA) can provide comprehensive classification lists with good taxonomic resolution and coverage for determining freshwater biodiversity and biomonitoring. But, the advantages of ES-eDNA metabarcoding over WS-eDNA metabarcoding remain unclear for routine assessments of diversity of benthic macroinvertebrates in streams. Location Qiantang River Basin, China. Methods Here, we compared ES-eDNA and WS-eDNA metabarcoding to evaluate the performance of two eDNA workflows in determining biodiversity and recovery of damaged macroinvertebrate communities. All eDNA samples from the environment and bulk specimen of macroinvertebrates were processed into available molecular operational taxonomic units (MOTUs) and identified to the level of genus. Results WS-eDNA detected more exact sequence variants (ESVs) (for ...

Accurate estimation of precipitation fields remains a grand challenge in cold regions hydrology due to the sparseness of precipitation gauges and lack of quantitative precipitation estimation from ground based weather radars. It is even more challenging in cold regions mountains due to blockage of ground based weather radars, and the complexity of modelling precipitation. Satellite remote sensing provides an alternative to precipitation monitoring in complex terrain when retrieval algorithms are able to represent a range of hydrometeor types. The Global Precipitation Measurement (GPM) satellite constellation has been successfully monitoring liquid precipitation since early 2014 through the Integrated Multi-SatellitE Retrievals for GPM (IMERG) algorithm. IMERG uses a constellation of satellites with passive microwave and infrared sensors to estimate precipitation, which is intercalibrated using GPM’s core platform Dual-frequency Precipitation Radar (DPR). The DPR sensor has been working ...

Rising human populations and ever-increasing demand for potable water result in increased municipal wastewater production. The collection, treatment, and management of municipal wastewaters include energy-intensive processes leading to the generation and emission of greenhouse, potentially toxic, and odorous gases. The main goal of this thesis was to advance knowledge of greenhouse gas (including carbon dioxide, CO2; methane, CH4; and nitrous oxide, N2O) and smelly compound (including ammonia, NH3; and hydrogen sulphide, H2S) emissions from typical municipal wastewater treatment plants (MWTPs) to accurately describe their emission rate estimates (EREs) using operating parameters. This research included laboratory and field assessments of greenhouse gas (GHG) and odour emissions in conjunction with monitored operating parameters. Laboratory-scale reactors simulating open-to-air treatment processes including primary and secondary clarifiers and anaerobic, anoxic, and aerobic reactors, we ...

Phosphorus (P) loss in agricultural discharge has typically been associated with surface runoff; however, tile drains have been identified as a key P pathway due to preferential transport. Identifying when and where these pathways are active may establish high-risk periods and regions that are vulnerable for P loss. A synthesis of high-frequency, runoff data from eight cropped fields across the Great Lakes region of North America over a 3-yr period showed that both surface and tile flow occurred year-round, although tile flow occurred more frequently. The relative timing of surface and tile flow activation was classified into four response types to infer runoff-generation processes. Response types were found to vary with season and soil texture. In most events across all sites, tile responses preceded surface flow, whereas the occurrence of surface flow prior to tile flow was uncommon. The simultaneous activation of pathways, indicating rapid connectivity through the vadose zone, was s ...

Daniel Wu (2019). Evaluating impacts of thinning in a temperate pine forest using CLASS-CTEM Model (B.Sc. thesis). McMaster University, Hamilton, Canada. Thesis

Evaluating impacts of thinning in a temperate pine forest using CLASS-CTEM Model (B.Sc. thesis

High-latitude ecosystems have experienced substantial warming over the past 40 years, which is expected to continue into the foreseeable future. Consequently, an increase in vegetation growth has occurred throughout the circumpolar North as documented through remote sensing and plot-level studies. A major component of this change is shrub expansion (shrubbing) in arctic and subarctic ecotones. However, these changes are highly variable depending on plant species, topographic position, hydrology, soils and other ecosystem properties. Changes in shrub and other vegetation properties are critical to document due to their first-order control on water, energy and carbon balances. This study uses a combination of multi-temporal LiDAR (Light Detection and Ranging) and field surveys to measure temporal changes in shrub vegetation cover over the Wolf Creek Research Basin (WCRB), a 180 km2 long-term watershed research facility located ~15 km south of Whitehorse, Yukon Territory. This work focuse ...

As wetlands around the world are being lost, policies are implemented to help protect further destruction and loss of valuable services that wetlands provide. In Alberta, wetland policy has been put in place with the goals of protecting the most valuable wetlands and replacing necessary loss of wetlands to maintain functional value. To help the policy meet its objectives, the Alberta Wetland Rapid Evaluation Tool-Actual (ABWRET-A) was developed and implemented in Alberta’s settled area in 2015 as a standardized way to give a value score via functional assessment to any wetland in the province, with the hopes that the most valuable wetlands will be conserved. These assessment tools are in constant need of review and improvement to make sure they are helping meet policy goals. I assess biases made in the selection for ABWRET-A calibration wetlands and determine how these biases affect ABWRET-A scoring to determine if subsequent scores provided by this tool are over or under estimating we ...

Supercells are the most violent thunderstorm, which can produce strong tornadoes, large hail, damaging winds, and flash flooding. From June to August, the Canadian Prairies (i.e., a major agricultural region of Canada) are greatly affected by various supercells, including low-precipitation (LP), high-precipitation (HP), and classic supercells. Despite the enormous socioeconomic impact of supercell thunderstorms over the Canadian Prairies, it remains poorly understood which environmental conditions are favorable for the development and maintenance of supercells. Therefore, this work aims to study the dynamical and thermodynamical characteristics of the environment during different supercells by examining severe weather parameters derived from soundings. Specifically, this study analyzed 23 LP, 15 HP, and 16 classic-type supercells that occurred over the Canadian Prairies and compared their dynamical and thermodynamical characteristics with their US Great Plains counterparts. Preliminar ...

BACOLI is a Fortran software package for solving one-dimensional parabolic partial differential equations (PDEs) with separated boundary conditions by B-spline adaptive collocation methods. A distinguishing feature of BACOLI is its ability to estimate and control error and correspondingly adapt meshes in both space and time. Many models of scientific interest, however, can be formulated as multiscale parabolic PDE systems, that is, models that couple a system of parabolic PDEs describing dynamics on a global scale with a system of ordinary differential equations describing dynamics on a local scale. This article describes the Fortran software eBACOLI, the extension of BACOLI to solve such multiscale models. The performance of the extended software is demonstrated to be statistically equivalent to the original for purely parabolic PDE systems. Results from eBACOLI are given for various multiscale models from the extended problem class considered.

Linking software features to code components is commonly performed during software development and maintenance, including to implement a feature, document code, design test cases, trace requirements, track changes, and support inspection of safety–critical software by government and other third parties. However, manually mapping features to code is error-prone and time consuming, even for developers familiar with a system. To overcome these challenges several studies proposed automated techniques to reduce human intervention when linking features to code components. Nonetheless, three challenges remain: (i) accuracy, (ii) cost, and (iii) explainability. Linking of irrelevant code snippets causes an extra burden of analyses. If the approach lacks explainability, then a tool is less useful for many crucial systems such as safety–critical software. Moreover, heavyweight techniques such as those that require generating execution traces of every scenario or require training deep-learning mo ...

Testing software is considered to be one of the most crucial phases in software development life cycle. Software bug fixing requires a significant amount of time and effort. A rich body of recent research explored ways to predict bugs in software artifacts using machine learning based techniques. For a reliable and trustworthy prediction, it is crucial to also consider the explainability aspects of such machine learning models. In this paper, we show how the feature transformation techniques can significantly improve the prediction accuracy and build confidence in building bug prediction models. We propose a novel approach for improved bug prediction that first extracts the features, then finds a weighted transformation of these features using a genetic algorithm that best separates bugs from non-bugs when plotted in a low-dimensional space, and finally, trains the machine learning model using the transformed dataset. In our experiment with real-life bug datasets, the random forest and ...

Testing and debugging software to fix bugs is considered one of the most important stages of the software life cycle. Many studies have investigated ways to predict bugs in software artifacts using machine learning techniques. It is important to consider the explanatory aspects of such models for reliable prediction. In this paper, we show how feature transformation can significantly improve prediction accuracy and provide insight into the inner workings of bug prediction models. We propose a new approach for bug prediction that first extracts the features, then finds a weighted transformation of these features using a genetic algorithm that best separates bugs from non-bugs when plotted in a low-dimensional space, and finally, trains predictive models using the transformed dataset. In our experiment using the proposed feature transformation, the traditional machine learning and deep learning classifiers achieved an average improvement of 4.25% and 9.6% in recall values for bug classif ...

Sakib Mostafa, Shamse Tasnim Cynthia, Banani Roy, Debajyoti Mondal (2024) Feature transformation for improved software bug detection and commit classification, Journal of Systems and Software, Volume 219, 2025, 112205, ISSN 0164-1212

Feature transformation for improved software bug detection and commit classification

Cowichan Lake lamprey (Entosphenus macrostomus) is a threatened species resident to Mesachie Lake, Cowichan Lake, and adjoining Bear Lake and their major tributaries in British Columbia. Decreases in trapping success have created concerns that the population is declining. Some potential threats include water use, climate change, and management actions. Owing to the absence of long-term data on population trends, little information is available to estimate habitat quality and factors that influence it. We sought to fill this gap by examining associations between habitat area and variables representing suspected key drivers of habitat availability. Critical habitat areas were imaged using an unmanned aerial vehicle over a period of three years at three sites at Cowichan Lake and a subsequent habitat area was classified. Meteorological and anthropogenic controls on habitat area were investigated through automatic relevance detection regression models. The major driver of habitat area duri ...

In this paper, we develop a radar snow water equivalent (SWE) retrieval algorithm based on a parameterized forward model of bicontinuous dense media radiative transfer (Bic-DMRT). The algorithm is based on retrieving the absorption loss of the snowpack which is directly proportional to the SWE. In the algorithm, Bic-DMRT is first applied to generate a lookup table (LUT) of snowpack backscattering at X- and Ku-band. Regression training is applied to the LUT to transform the dual-frequency backscatter into functions of two parameters: the scattering albedo at X-band and SWE. The background scattering is subtracted from the SnowSAR data to give the volume scattering of snow. Classification of SnowSAR data is applied to provide a priori information. Based on the obtained volume scattering and the priori information, a cost function is established to find SWE. Performance of the retrieval algorithm was tested using three sets of airborne SnowSAR data acquired over mixed areas in Finland and ...

Flow management has the potential to significantly affect ecosystem condition. Shallow lakes in arid regions are especially susceptible to flow management changes, which can have important implications for the formation of cyanobacterial blooms. Here, we reveal water quality shifts associated with changing source water inflow management. Using in situ monitoring data, we studied a seven-year time span during which inflows to a shallow, eutrophic drinking water reservoir transitioned from primarily natural landscape runoff (2014–2015) to managed flows from a larger upstream reservoir (Lake Diefenbaker; 2016–2020) and identified significant changes in cyanobacteria (as phycocyanin) using generalized additive models to classify cyanobacterial bloom formation. We then connected changes in water source with shifts in chemistry and the occurrence of cyanobacterial blooms using principal components analysis. Phycocyanin was greater in years with managed reservoir inflow from a mesotrophic ups ...

Smart packaging of fresh produce is an emerging technology toward reduction of waste and preservation of consumer health and safety. Smart packaging systems also help to prolong the shelf life of perishable foods during transport and mass storage, which are difficult to regulate otherwise. The use of these ever-progressing technologies in the packaging of fruits has the potential to result in many positive consequences, including improved fruit quality, reduced waste, and associated improved public health. In this review, we examine the role of smart packaging in fruit packaging, current-state-of-the-art, challenges, and prospects. First, we discuss the motivation behind fruit quality monitoring and maintenance, followed by the background on the development process of fruits, factors used in determining fruit quality, and the classification of smart packaging technologies. Then, we discuss conventional freshness sensors for packaged fruits including direct and indirect freshness indica ...

DNA aptamers for small molecules hold transformative promise in biosensing, diagnostics, and therapeutics, yet their in vitro evolution has been hampered by incomplete knowledge of the parameters that drive efficient enrichment. In recent years, the development of library-immobilization based method, so called capture-SELEX, has generated over 100 high-quality DNA aptamers for various types of small molecules. Importantly, capture-SELEX allows systematic investigation of fundamental problems in the selection of aptamers. This thesis studies the capture-SELEX platform by dissecting thermodynamic, kinetic, and methodological variables to accelerate the discovery of high-affinity DNA aptamers. Using adenosine/ATP as targets for selection has repeatedly produced the same guanine-rich aptamer motif that was first reported by the Szostak group in 1995. This aptamer has been considered as the adenosine/ATP aptamer by the field. First, by gradually increasing the selection stringency on classi ...

Fluvial systems in southern Ontario are regularly affected by widespread early-spring flood events primarily caused by rain-on-snow events. Recent studies have shown an increase in winter floods in this region due to increasing winter temperature and precipitation. Streamflow simulations are associated with uncertainties mainly due to the different scenarios of greenhouse gas emissions, global climate models (GCMs) or the choice of the hydrological model. The internal variability of climate, defined as the chaotic variability of atmospheric circulation due to natural internal processes within the climate system, is also a source of uncertainties to consider. Uncertainties of internal variability can be assessed using hydrological models fed by downscaled data of a global climate model large ensemble (GCM-LE), but GCM outputs have too coarse of a scale to be used in hydrological modeling. The Canadian Regional Climate Model Large Ensemble (CRCM5-LE), a 50-member ensemble downscaled from ...

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conv ...

Aquatic environments with high levels of dissolved ferrous iron and low levels of sulfate serve as an important systems for exploring biogeochemical processes relevant to the early Earth. Boreal Shield lakes, which number in the tens of millions globally, commonly develop seasonally anoxic waters that become iron rich and sulfate poor, yet the iron–sulfur microbiology of these systems has been poorly examined. Here we use genome-resolved metagenomics and enrichment cultivation to explore the metabolic diversity and ecology of anoxygenic photosynthesis and iron/sulfur cycling in the anoxic water columns of three Boreal Shield lakes. We recovered four high-completeness and low-contamination draft genome bins assigned to the class Chlorobia (formerly phylum Chlorobi) from environmental metagenome data and enriched two novel sulfide-oxidizing species, also from the Chlorobia. The sequenced genomes of both enriched species, including the novel “Candidatus Chlorobium canadense”, encoded the ...

Changes in the frequency and intensity of extreme precipitation resulting from climate change are responsible for natural disasters such as severe floods and have been a major study focus during the last decades. Previous studies have mainly focused on the trends of annual maxima precipitation at global and regional scales. However, little is known about how extreme precipitation trends change among different climate types. This study offers a global analysis of extreme precipitation changes in terms of climate type by using over 8500 gauge-based records. We focus on the period 1964 to 2013 when global warming was accelerating. A climate type is assigned to each station based on the Köppen Geiger (KG) climate classification, resulting in 30 KG climate subtypes. Mann-Kendall test and Sen’s slope estimator are applied to each time series, measuring the magnitude and significance of trends. The heaviness of the tail for each station is assessed based on the shape parameter of the Generali ...

Hobbi, S., Nerantzaki, S., Papalexiou, S.M., Rajulapati, C.R., 2022. Global analysis of extreme precipitation changes in the Koumlppen-Geiger climate classification. EGU22, Copernicus Meetings. https://doi.org/10.5194/egusphere-egu22-10335?

Global analysis of extreme precipitation changes in the Koumlppen-Geiger climate classification

Climate change is contributing to extreme climate events such as prolonged heat waves, hurricanes, and flooding. Climate classification schemes have become critical tools in investigating these events. One of the most widely used schemes is the Köppen-Geiger (KG) classification, which groups the world’s climate types using multiple variables based on precipitation and temperature data. Studies that apply the KG classification have a variety of purposes, including to present the geographical distribution of climate types, to measure shifts among climate types, to study changes in extreme events at regional scales, and to present future projections of climate types. However, several aspects of KG classification have not been thoroughly investigated in the literature: First, few studies have explored the differences among climate types at the global scale derived from multiple sources of precipitation and temperature data; second, little research has looked at changes in extreme precipita ...

Global characteristics of extreme precipitation and variation of climate types from Köppen-Geiger classification using different datasets

A graphical analysis method is applied over the province of Alberta, Canada using publicly available water level data from standard monitoring wells to evaluate and categorize aquifer recovery. Agriculture in the province relies heavily upon surface water for irrigation, which is increasingly unreliable due to climate change and increasing climate variability. Due to an expected future reliance on groundwater, it is necessary to better understand groundwater flow and aquifer characteristics across Alberta to prevent over-allocation of groundwater resources. Water level data from provincial monitoring well hydrographs are examined and graphically analyzed to broadly characterize recovery in agriculturally significant regions of the province of Alberta, Canada. Through this analysis, the presence of a recharge boundary within a recovery curve can be ascertained. Of the 292 monitoring wells originally screened, recovery curve analysis is conducted on 49 monitoring wells. Using graphical a ...

New members of a software team can struggle to locate user requirements if proper software engineering principles are not practiced. Reading through code, finding relevant methods, classes and files take a significant portion of software development time. Many times developers have to fix issues in code written by others. Having a good tool support for this code browsing activity can reduce human effort and increase overall developers' productivity. To help program comprehension activities, building an abstract code summary of a software system from the call graph is an active research area. A call graph is a visual representation of caller-callee relationships between different methods of a software project. Call graphs can be difficult to comprehend for a larger code-base. The motivation is to extract the essence from the call graph by finding execution scenarios from a call graph and then cluster them together by concentrating the information in the code-base. Later, different techn ...

Permafrost thaw has been observed in recent decades in the Northern Hemisphere and is expected to accelerate with continued global warming. Predicting the future of permafrost requires proper representation of the interrelated surface/subsurface thermal and hydrologic regimes. Land surface models (LSMs) are well suited for such predictions, as they couple heat and water interactions across soil-vegetation-atmosphere interfaces and can be applied over large scales. LSMs, however, are challenged by the long-term thermal and hydraulic memories of permafrost and the paucity of historical records to represent permafrost dynamics under transient climate conditions. In this study, we aim to understand better how LSMs function under different spin-up states, which facilitates addressing the challenge of model initialization by characterizing the impact of initial climate conditions and initial soil frozen and liquid water contents on the simulation length required to reach equilibrium. Further ...

Evolutionary coupling is a well investigated phenomenon in software maintenance research and practice. Association rules and two related measures, support and confidence, have been used to identify evolutionary coupling among program entities. However, these measures only emphasize the co-change (i.e., changing together) frequency of entities and cannot determine whether the entities co-evolved by experiencing related changes. Consequently, the approach reports false positives and fails to detect evolutionary coupling among infrequently co-changed entities. We propose a new measure, identifier correspondence (id-correspondence), that quantifies the extent to which changes that occurred to the co-changed entities are related based on identifier similarity. Identifiers are the names given to different program entities such as variables, methods, classes, packages, interfaces, structures, unions etc. We use Dice-Sørensen co-efficient for measuring lexical similarity between the identifier ...

Merchant, M., Obadia, M., Mahdianpari, M., Bourgeau-Chavez, L., Brisco, B., DeVries, B., Berg, A.A. (2023) Ice-wedge polygon classification with deep learning: evaluation of hybrid compact polarimetric RADARSAT constellation mission and arcticDEM.

Ice-wedge polygon classification with deep learning: evaluation of hybrid compact polarimetric RADARSAT constellation mission and arcticDEM

Phragmites australis (Cav.) Trin. ex Steudel subspecies australis is one of the worst plant invaders in wetlands of North America. Remote sensing is the most cost-effective method to track its spread given its widespread distribution and rapid colonization rate. We hypothesize that the morphological and/or physiological features associated with different phenological states of Phragmites can influence their reflectance signal and thus affect mapping accuracies. We tested this hypothesis by comparing classification accuracies of cloud-free images acquired by Landsat 7, Landsat 8, and Sentinel 2 at roughly monthly intervals over a calendar year for two wetlands in southern Ontario. We used the Support Vector Machines classification and employed field observations and image acquired from unmanned aerial vehicle (8 cm) to perform accuracy assessments. The highest Phragmites producer’s, user’s, and overall accuracy (96.00, 91.11, and 88.56% respectively) were provided by images acquired in ...

Streamflow in Western North America (WNA) has been experiencing pronounced changes in terms of volume and timing over the past century, primarily driven by natural climate variability and human-induced climate changes. This thesis advances on previous work by revealing the most recent streamflow changes in WNA using a comprehensive suite of classical hydrometric methods along with novel Deep Learning (DL) based approaches for change detection and classifica- tion. More than 500 natural streams were included in the analysis across western Canada and the United States. Trend analyses based on the Mann-Kendall test were conducted on a wide selection of classic hydrometric indicators to represent varying aspects of streamflow over 43 years from 1979 to 2021. A general geograph- ical divide at approximately 46◦N degrees latitude indicates that total streamflow is increasing to the north while declining to the south. Declining late summer flows (July–September) were also widespread across th ...

Umair, M., Melton, J.R., Roy, A., et al. (2023) Implementation of plant hydraulics in the Canadian land surface scheme including biogeochemical cycles (CLASSIC).

Implementation of plant hydraulics in the Canadian land surface scheme including biogeochemical cycles (CLASSIC)

Fassnacht, S.R. and E.D. Soulis, (2002). Implications during transitional periods of improvements to the snow processes in the land surface scheme – hydrological model WATCLASS. Atmosphere-Ocean, 40, 389-403.

Implications during transitional periods of improvements to the snow processes in the land surface scheme – hydrological model WATCLASS

The collection efficiency of a typical precipitation gauge-shield configuration decreases with increasing wind speed, with a high scatter for a given wind speed. The high scatter in the collection efficiency for a given wind speed arises in part from the variability in the characteristics of falling snow and atmospheric turbulence. This study uses weighing gauge data collected at the Marshall Field Site near Boulder, Colorado, during the WMO Solid Precipitation Intercomparison Experiment (SPICE). Particle diameter and fall speed data from a laser disdrometer were used to show that the scatter in the collection efficiency can be reduced by considering the fall speed of solid precipitation particles. The collection efficiency was divided into two classes depending on the measured mean-event particle fall speed during precipitation events. Slower-falling particles were associated with a lower collection efficiency. A new transfer function (i.e., the relationship between collection efficie ...

Conventional assessment and evaluation of sediment quality are based on laboratory-based ecotoxicological and chemical measurements with lack of concern for ecological relevance. Microbiotas in sediment are responsive to pollutants and can be used as alternative ecological indicators of sediment pollutants; however, the linkage between the microbial ecology and ecotoxicological endpoints in response to sediment contamination has been poorly evaluated. Here, in situ microbiotas from the Three Gorges Reservoir (TGR) area of the Yangtze River were characterized by DNA metabarcoding approaches, and then, changes of in situ microbiotas were compared with the ecotoxicological endpoint, aryl hydrocarbon receptor (AhR) mediated activity, and level of polycyclic aromatic hydrocarbons (PAHs) in sediments. PAHs and organic pollutant mixtures mediating AhR activity had different effects on the structures of microbiotas. Specifically, Shannon indices of protistan communities were negatively correla ...

With the increasing availability of SAR imagery in recent years, more research is being conducted using deep learning (DL) for the classification of ice and open water; however, ice and open water classification using conventional DL methods such as convolutional neural networks (CNNs) is not yet accurate enough to replace manual analysis for operational ice chart mapping. Understanding the uncertainties associated with CNN model predictions can help to quantify errors and, therefore, guide efforts on potential enhancements using more–advanced DL models and/or synergistic approaches. This paper evaluates an approach for estimating the aleatoric uncertainty [a measure used to identify the noise inherent in data] of CNN probabilities to map ice and open water with a custom loss function applied to RADARSAT–2 HH and HV observations. The images were acquired during the 2014 ice season of Lake Erie and Lake Ontario, two of the five Laurentian Great Lakes of North America. Operational image ...

Abstract: Herbicides and safeners have been formulated together to help protect crop plants from the injurious effects of herbicides while maintaining the ability of the herbicides to selectively remove targeted weeds. These groups of compounds became important as agriculture increased to sustain the world's ever-increasing population. Selected emerging safeners (SESs), Mefenpyr di-ethyl (MEF) and Cyprosulfamide (CPS) and their co-herbicides (Fenoxaprop-p-ethyl (FEN) and Isoxaflutole (ISO)) used during pre- and post-emergence of cereals and grains were used for this study. The mobility of safeners varied in the environment in relation to their chemical properties, such as octanol-water solubility partition coefficient. Herbicides and safeners have been found in the aquatic environment because they could dissipate from the point of application through leaching, surface runoff, and volatilization. The sorption of safeners such as CPS to soil was found to be governed by soil pH. Hence, th ...

Infrared (IR) is an important data source for satellite quantitative precipitation estimation, and has been widely applied in the fields of meteorology, hydrology, and agriculture. In the past decades, a series of IR retrieval algorithms have been developed to support the production of IR-based and IR-microwave merged precipitation products. Recently, deep learning techniques such as the convolutional neural network (CNN) show great potential in obtaining IR precipitation estimates with higher accuracy than traditional retrieval algorithms. In this study, we present an upgraded version of IR Precipitation Estimation using CNN (IPEC), i.e., IPEC version 2 (IPEC-V2), with a new end-to-end manner. IPEC-V2 is used to generate a precipitation dataset based on IR data from China’s Fengyun (FY) geostationary satellites (FY-2F, 2G, and 4A). To overcome the difficulty of model training in regions with sparse observations, IPEC-V2 models are firstly pre-trained over the data-rich Continental US ...

We advance methodologies for monitoring ground surface freeze/thaw (F/T) detection, integrating laboratory pedology, field observations, and satellite remote sensing (RS) to enhance terrestrial cryosphere monitoring. The thesis addresses critical gaps stemming from reliance on static, intrinsic thresholds for F/T classification, advocating for and developing more accurate, scalable, and context-adaptive methods through a multiscale approach. Beginning with detailed characterization of soil moisture sensors in frozen, thawed, and transitional states in the laboratory, Chapter 2 introduces permittivity-based soil freezing characteristic curves (SFCCs) in agricultural fields. This approach improves the accuracy of F/T detection and deepens our understanding of the dynamics involved, serving as a tool for monitoring water resources in cold climate agriculture. The analysis in Chapter 3 reveals that the scale and location of soil moisture measurements can significantly influence the shape o ...

During the past few decades, contamination of sediments by persistent toxic substances (PTSs) has been observed in estuarine and coastal areas on the west coast of South Korea. The contaminants are suspected to cause toxicities in aquatic biota, but little is known about their ecological effects, particularly on benthic microbial communities. In this study, an eDNA-based assessment was applied along with classic assessments of exposure, such as chemistry and in vitro bioassays, to evaluate condition of benthic bacterial communities subjected to PTSs. Two strategies were adopted for the study. One was to conduct a comprehensive assessment in space (by comparing seawater and freshwater sites at five coastal regions) and in time (by following change over a 5-y period). Although we found that bacterial composition varied among and within years, some phyla, such as Proteobacteria (28.7%), Actinobacteria (13.1%), Firmicutes (12.7%), and Chloroflexi (12.5%) were consistently dominated across ...

Talus and moraine serve as vital groundwater reservoirs, with their associated capability to modulate the baseflow of major rivers that originate in headwater environments. Recent field-based studies conducted in the Canadian Rocky Mountains have identified a nonlinear storage-discharge relationship expressed by these surficial alpine aquifers and the importance of their spatial positioning and extent in headwater environments. However, few studies have tried to upscale our current small-scale understanding of these surficial units, to better understand how their storage-discharge dynamics influence basin-scale (i.e. 10^3-10^4 km^2) hydrology. This study aimed to develop a means to integrate several representative features associated with alpine aquifers into a basin-scale hydrological model to potentially improve its capability to estimate and predict the baseflow of mountain rivers. Specifically, this study developed a simple object-oriented image classification workflow to map the s ...

Integration of surrogate optimization and pca for calibration of hydrologic models, a WATCLASS case study

Groundwater vulnerability assessments, often presented in the form of a thematic map, provide a measure of the relative susceptibility of a groundwater system to contamination introduced at or near the ground surface. However, most groundwater vulnerability assessments rely on deterministic, point estimates based on averaged input parameters, and result in a single output value without any indication of the uncertainty or variation around this value. To facilitate the most effective application and interpretation of groundwater vulnerability assessments, a method for incorporating the uncertainty associated with the natural variation of input parameters into groundwater vulnerability assessments was developed and demonstrated in south-central Saskatchewan. A comprehensive literature review and synthesis, including a review of the conceptual basis of intrinsic groundwater vulnerability assessment methods, a critical evaluation of common and representative methods, and a review of the cu ...

Groundwater vulnerability assessments, often presented in the form of a thematic map, provide a measure of the relative susceptibility of a groundwater system to contamination introduced at or near the ground surface. However, most groundwater vulnerability assessments rely on deterministic, point estimates based on averaged input parameters, and result in a single output value without any indication of the uncertainty or variation around this value. To facilitate the most effective application and interpretation of groundwater vulnerability assessments, a method for incorporating the uncertainty associated with the natural variation of input parameters into groundwater vulnerability assessments was developed and demonstrated in south-central Saskatchewan. A comprehensive literature review and synthesis, including a review of the conceptual basis of intrinsic groundwater vulnerability assessment methods, a critical evaluation of common and representative methods, and a review of the cu ...

Despite the high historical losses attributed to flood events, Canadian flood mitigation efforts have been hindered by a dearth of current, accessible flood extent/risk models and maps. Such resources often entail large datasets and high computational requirements. This study presents a novel, computationally efficient flood inundation modeling framework (“InundatEd”) using the height above nearest drainage (HAND)-based solution for Manning's equation, implemented in a big-data discrete global grid system (DGGS)-based architecture with a web-GIS (Geographic Information Systems) platform. Specifically, this study aimed to develop, present, and validate InundatEd through binary classification comparisons to recently observed flood events. The framework is divided into multiple swappable modules including GIS pre-processing; regional regression; inundation models; and web-GIS visualization. Extent testing and processing speed results indicate the value of a DGGS-based architecture alongsi ...

While designing a software system, minimizing coupling among program entities (such as files, classes, methods) is always desirable. If a software entity is coupled with many other entities, this might be an indication of poor software design because changing that entity will likely have ripple change effects on the other coupled entities. Evolutionary coupling, also known as change coupling, is a well investigated way of identifying coupling among program entities. Existing studies have investigated whether file level or class level evolutionary couplings are related with software bug-proneness. While these existing studies have mixed findings regarding the relationship between bug-proneness and evolutionary coupling, none of these studies investigated whether method level (i.e., function level for procedural languages) evolutionary coupling is correlated with bug-proneness. Investigation considering a finer granularity (i.e., such as method level granularity) can help us pinpoint whi ...

Assessment of remote sensing derived freeze/thaw products from L-band radiometry requires ground validation. There is growing interest in utilizing soil moisture networks to meet this validation requirement, although it remains unclear whether the current configuration of these networks is appropriate. To address this issue, a small-scale L-band radiometry study was conducted from November 2014 to April 2015 to capture F/T events. Soil moisture probes measuring soil temperature and real dielectric permittivity were installed within a surface-based L-band radiometer footprint vertically at the surface and horizontally at 2.5, 5 and 10 cm depths. A binary freeze/thaw product was derived using radiometer brightness temperatures and compared to the binary F/T classification using soil temperature, real dielectric permittivity and air temperature measurements. The results of the study found that shallow probe depths (vertical and 2.5 cm) resulted in an improvement in the radiometer F/T prod ...

The large stocks of soil organic carbon (SOC) in soils and deposits of the northern permafrost region are sensitive to global warming and permafrost thawing. The potential release of this carbon (C) as greenhouse gases to the atmosphere does not only depend on the total quantity of soil organic matter (SOM) affected by warming and thawing, but it also depends on its lability (i.e., the rate at which it will decay). In this study we develop a simple and robust classification scheme of SOM lability for the main types of soils and deposits in the northern permafrost region. The classification is based on widely available soil geochemical parameters and landscape unit classes, which makes it useful for upscaling to the entire northern permafrost region. We have analyzed the relationship between C content and C-CO2 production rates of soil samples in two different types of laboratory incubation experiments. In one experiment, ca. 240 soil samples from four study areas were incubated using t ...

Peter Kuhry, Jiří Bárta, Daan Blok, Bo Elberling, Samuel Faucherre, Gustaf Hugelius,, Christian J. Jørgensen,a, Andreas Richter, Hana Šantrůčková, and Niels Weiss (2020). Lability classification of soil organic matter in the northern permafrost region. Biogeosciences, 17, 361-379. https://doi.org/10.5194/bg-17-361-2020

Lability classification of soil organic matter in the northern permafrost region

Harmful Algal Bloom (HABs) reports have increased globally, where climate change is considered a primary driver. While the role of temperature and precipitation on bloom formation is well understood on HAB formation, lake ice remains understudied. Reduced ice duration periods may alter algal growth, extent, duration and timing due to earlier light penetration, shifts in mixing, and changes to thermal regimes. Northern lakes are at an elevated risk due to the greater rate of air temperature change at high latitudes. To determine the importance of lake ice in the prediction of HABs, an observational time series (2002-2019) was analyzed utilizing new remote sensing data products provided by the ESA CCI Lakes+ project to determine the potential link between lake ice (lake ice on-off DOY and lake ice duration), lake surface water temperature (LSWT; mean/max, peak LSWT DOY, LSWT anomaly days) and algal biomass parameters (mean and max chlorophyll-a (chl-a, a proxy of algal biomass), high chl ...

Changes to ice cover on lakes throughout the northern landscape has been established as an indicator of climate change and variability, expected to have implications for both human and environmental systems. Monitoring lake ice cover is also required to enable more reliable weather forecasting across lake-rich northern latitudes. Currently, the Canadian Ice Service (CIS) monitors lakes using synthetic aperture radar (SAR) and optical imagery through visual interpretation, with total lake ice cover reported weekly as a fraction out of ten. An automated method of classification would allow for more detailed records to be delivered operationally. In this research, we present an automatic ice-mapping approach which integrates unsupervised segmentation from the Iterative Region Growing using Semantics (IRGS) algorithm with supervised random forest (RF) labeling. IRGS first locally segments homogeneous regions in an image, then merges similar regions into classes across the entire scene. Rec ...

Hoekstra, M., Jiang, M., Clausi, D. A., & Duguay, C. (2020). Lake Ice-Water Classification of RADARSAT-2 Images by Integrating IRGS Segmentation with Pixel-Based Random Forest Labeling. Remote Sensing, 12(9), 1425. https://doi.org/10.3390/rs12091425

Lake Ice-Water Classification of RADARSAT-2 Images by Integrating IRGS Segmentation with Pixel-Based Random Forest Labeling

In this study we assess the total storage, landscape distribution, and vertical partitioning of soil organic carbon (SOC) stocks on the Brøgger Peninsula, Svalbard. This type of high Arctic area is underrepresented in SOC databases for the northern permafrost region. Physico-chemical, elemental, and radiocarbon (14C) dating analyses were carried out on thirty-two soil profiles. Results were upscaled using both a land cover classification (LCC) and a landform classification (LFC). Both LCC and LFC approaches provide weighted mean SOC 0–100 cm estimates for the study area of 1.0 ± 0.3 kg C m−2 (95% confidence interval) and indicate that about 68 percent of the total SOC storage occurs in the upper 30 cm of the soil, and about 10 percent occurs in the surface organic layer. Furthermore, LCC and LFC upscaling approaches provide similar spatial SOC allocation estimates and emphasize the dominant role of “vegetated area” (4.2 ± 1.6 kg C m−2) and “solifluction slopes” (6.7 ± 3.6 kg C m−2) in ...

Warming has led to widespread impacts on the landscape in northern ecosystems. Areas underlain by discontinuous permafrost are as highly susceptible to significant change as a result of permafrost thaw leading to ground subsidence. The Baker Creek watershed is a typical Taiga Shield landscape on permafrost, just north of Yellowknife in the Northwest Territories. In this region, bedrock outcrops are interspersed with lakes, wetlands, soil-filled lowlands, and forests. Permafrost is discontinuous across the landscape – while bedrock and the terrain beneath lakes and streams are permafrost-free, permafrost can be found in forested parts of the landscape, usually associated with peatlands and glaciolacustrine sediments. Across this landscape, we took intensive ground-based measurements characterizing land cover types by their depth of organic soil and frost table. Using archival aerial photographs and recent satellite imagery, we assessed changes in land cover between 1972 and 2017. Stro ...

Continental high latitudes have been warming at higher rates than the global average, causing substantial permafrost thaw with widespread effects on soils, vegetation, streamflow seasonality and land subsidence. Complex feedbacks are controlled by precipitation changes and soil hydraulic and thermal properties, amongst many factors. The Mackenzie River Basin (MRB) is the largest drainage basin in Canada (1.8x106 km2), underlain by permafrost of various classes for most of its extent (70–80% by area). Changes to the MRB affect atmospheric feedback, inflows to the Arctic Ocean, and local environments and communities. This study aims to parameterize a land surface hydrology model (MESH) for the MRB to simulate the coevolution of hydrology and permafrost dynamics, and hence enable the investigation of future change impacts. MESH, designed to simulate cold region processes, couples energy and water exchanges and requires a deep soil profile and long spin-up periods to initialize the permafr ...

Monitoring river ice is crucial for planning safe navigation routes, with ice–water classification being one of the most important tasks in ice mapping. While high-resolutions satellite imagery, such as synthetic aperture radar (SAR), is well-suited to this task, manual interpretation of these data is challenging due to the large data volume. Machine learning approaches are suitable methods to overcome this; however, training the models might not be time-effective when the desired result is a narrow structure, such as a river, within a large image. To address this issue, we proposed a model incorporating a graph neural network (GNN), called learnable weights graph convolution network (LWGCN). Focusing on the winters of 2017–2021 with emphasis on the Beauharnois Canal and Lake St Lawrence regions of the Saint Lawrence River. The model first converts the SAR image into graph-structured data using simple linear iterative clustering (SLIC) to segment the SAR image, then connecting the cent ...

Learnable Weight Graph Neural Network for River Ice Classification

Deep neural networks are prevalent in supervised learning for large amounts of tasks such as image classification, machine translation and even scientific discovery. Their success is often at the sacrifice of interpretability and generalizability. The increasing complexity of models and involvement of the pre-training process make the inexplicability more imminent. The outstanding performance when labeled data are abundant while prone to overfit when labeled data are limited demonstrates the difficulty of deep neural networks' generalizability to different datasets. This thesis aims to improve interpretability and generalizability by restricting representations. We choose to approach interpretability by focusing on attribution analysis to understand which features contribute to prediction on BERT, and to approach generalizability by focusing on effective methods in a low-data regime. We consider two strategies of restricting representations: (1) adding bottleneck, and (2) introducing c ...

Climate-driven permafrost degradation and an intensification of the hydrological cycle are rapidly altering the intricate ecohydrological processes of Arctic wetlands, threatening their long-term carbon sequestration capabilities. Addressing this concern through effective management holds immense potential for climate regulation, mitigation, and adaptation efforts. As such, there is growing need for timely spatial inventory data identifying Arctic wetlands with sufficient accuracy, resolution, and detail. Wetland mapping at large scales necessitates the processing of large volumes of Earth observation (EO) data, a challenge known as “Big Data”. Consequently, in this study, we present a cloud-based methodology exploiting the remarkable collection of EO data and computational power of Google Earth Engine (GEE) to map Arctic wetlands at 10 m spatial resolution. Our workflow evaluated temporally aggregated optical and radar satellite imagery and novel hydro-physiographic layers as inputs i ...

The shoreline of Western Lake Ontario (WLO) comprises ecologically important wetlands and habitats for aquatic life. It is also borders to the Greater Toronto Area (GTA), one of Canada's largest and most densely populated regions. The WLO receives urban stormwater runoff and effluent from treatment plants that deliver nutrients and sediments to the nearshore zone. The WLO is also threatened by invasive species, including dreissenid mussels that are modifying biogeochemical nutrient cycling in the lake. Therefore, the potential re-eutrophication of Lake Ontario remains a major binational concern. In this study, we focus on reconstructing the eutrophication trajectory in WLO to provide essential knowledge to inform mitigation climate-adaptive strategies to protect the lake. We are using chlorophyll-a (Chl-a) concentration data obtained from remote sensing measurements as an indicator of phytoplankton biomass. One particular challenge in the nearshore waters of WLO is the presence of Clad ...

Background and Aims: Stand-replacing crown fires are the most prevalent type of fire regime in boreal forests in North America. However, a substantial proportion of low-severity fires are found within fire perimeters. Here, we aimed to investigate the effects of low-severity fires on the reproductive potential and seedling recruitment in boreal forest stands in between stand-replacing fire events. Methods: We recorded site and tree characteristics from 149 trees within 12 sites dominated by mature black spruce [Picea mariana (Mill.) B.S.P.] trees in the Northwest Territories, Canada. The presence of fire-scarred trees supported classification of sites as unburned or affected by low-severity fires in recent history. We used non-parametric tests to evaluate differences in site conditions between unburned and low-severity sites. We used linear and additive statistical models to evaluate differences in tree age, size and reproductive traits among unburned trees and trees from low-severity ...

This study developed an integrated biogeochemical and hydrological modelling system by incorporating the latest versions of the nitrogen coupled Canadian Land Surface Scheme-Canadian Terrestrial Ecosystem Model (CLASS-CTEM) into the Modelisation Environmentale Communautaire (MEC) Surface and Hydrology system (MESH), hereafter referred to as MESH-CTEM. The newly developed MESH-CTEM modelling system allows simulations of energy, water, carbon and nitrogen fluxes and their feedbacks on vegetation growth and exploration of impacts of future climatic changes on catchment-scale processes. Performance of the MESH-CTEM system was tested at the Big Creek watershed within Norfolk county, Ontario, Canada, which is a 573 km2 crop-dominated catchment with areas of broadleaf and needleleaf forests, using observed eddy covariance flux, meteorological and hydrological datasets from October 2004 to December 2017 at a grid resolution of 0.02o latitude × 0.02o longitude. MESH-CTEM showed a significant in ...

Land-atmosphere interactions are commonly quantified using eddy-covariance (EC) equipment. This technique provides fluxes which are attributed to an area-averaged two-dimensional flux footprint. Although source flux heterogeneity is present within these footprints, current EC footprint models are unable to distinguish the variable flux contributions (although they are incorporated into the bulk EC flux). A disaggregation method would increase the value of EC data by allowing users to isolate individual fluxes from features within the flux footprint; furthermore, this may extend the useability of the EC method to more complex terrain of mixed land classifications. It remains unexplored how high-resolution surface energy balance (SEB) models can be used to disaggregate these EC footprints. This thesis presents a SEB workflow using Unoccupied Aerial Vehicles (UAVs) to generate high-resolution patterns of evapotranspiration (ET) to disaggregate EC footprints in a novel disaggregated flux f ...

Organic chemical pollutants are delivered to riverine habitats via basin land use and hydrology interactions. Aquatic organisms eventually absorb these substances, where they might have negative consequences. However, our capacity to reliably predict potential future changes in pollutant concentrations is now constrained by information gaps relating to the links between hydrological, chemical, and biological processes. In the South Saskatchewan River, Canada, in the years 2020 and 2021, concentrations of three pesticide classes (organochlorines, organophosphates, and herbicides) in the water, sediments, and fish were examined. Organochlorine pesticides have been prohibited in Canada since the 1970s; however, methoxychlor and lindane were occasionally found in samples of sediment and fish that may have been contaminated in the past. Organophosphate pesticides, with the exception of malathion and parathion, were close to detection limit in both sampling years in all matrices, while neoni ...

Organic chemical pollutants are delivered to riverine habitats via basin land use and hydrology interactions. Aquatic organisms eventually absorb these substances, where they might have negative consequences. However, our capacity to reliably predict potential future changes in pollutant concentrations is now constrained by information gaps relating to the links between hydrological, chemical, and biological processes. In the South Saskatchewan River, Canada, in the years 2020 and 2021, concentrations of three pesticide classes (organochlorines, organophosphates, and herbicides) in the water, sediments, and fish were examined. Organochlorine pesticides have been prohibited in Canada since the 1970s; however, methoxychlor and lindane were occasionally found in samples of sediment and fish that may have been contaminated in the past. Organophosphate pesticides, with the exception of malathion and parathion, were close to detection limit in both sampling years in all matrices, while neoni ...

Modeling of extreme events is important in many scientific fields, including environmental and civil engineering, and impacts and risk assessments. Among available methods, statistical models that allow estimating extremes’ frequency and intensity are regularly used in procedures to anticipate potential changes in extreme events. Extreme value theory provides a theoretical basis for statistical estimation of extreme events using frequency analysis. The challenge in modeling is knowing when to use the block maxima method or the peaks-over-threshold (POT) method. Each has its drawbacks. POT describes the main characteristics of the observed extreme series; the threshold selection is always challenging and might affect the accuracy of the simulated results and the credibility of changes in extreme values. To encompass this challenge, mixture models offer more flexibility to represent samples with nonhomogeneous data. This study presents the gamma generalized Pareto (GGP) mixture model for ...

The effects of wetland management of drainage and restoration on the hydrology of small basins over the Canadian Prairies, were investigated using a virtual basin modelling approach created through the Cold Regions Hydrological Modelling platform (CRHM) for seven biophysical basin classes that typify the region. The model included wind redistribution of snow, energy balance snowmelt, infiltration to frozen soils, Penman-Monteith actual evapotranspiration, soil and ground water dynamics and fill and spill of internally drained surface depressions that often form wetlands. Wetland loss induced by agricultural drainage was represented by scenarios that progressively reduced the depression area and storage capacity by increments of 10%, and ongoing wetland restoration policies were represented by expanding the existing depressions to historical sizes. Model simulations showed that, on average, both annual total streamflow and maximum daily streamflow had the largest sensitivities to wetlan ...

He, Z., Shook, K., Spence, C., Pomeroy, J.W., Whitfield, C. (2022) Modeling the Streamflow Sensitivity to Wetland Drainage and Restoration Over the Canadian Prairies Using a Basin Classification Approach. American Geophysical Union (AGU) Fall Meeting, Chicago, USA, December 12 to December 16, 2022. https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1072974

This study investigated the effects of wetland loss caused by agricultural activities on basin streamflow in the Canadian Prairies. At the same time, we studied the extent to which wetland restoration policy could influence streamflow in the Prairies. To do that, we divided the entire Canadian Prairies into seven basin types based on a set of biophysical factors delineating land cover, soil, and topography. Responses of hydrological processes to wetland changes in the classified basins were physically represented in the Cold Regions Hydrological Modelling platform (CRHM). The results quantified the sensitivities of annual total streamflow and peak daily streamflow to per 10% loss or expansion in the wetlands. It is found that restoring wetland closer to the basin outlet is more effective in reducing the volume of peak streamflow. Our results could be used to inform agricultural practices and wetland management policies in the Canadian Prairies where a number of waterfowl and other gras ...

Modeling the Streamflow Sensitivity to Wetland Drainage and Restoration Over the Canadian Prairies Using a Basin Classification Approach

The Upper Columbia and Okanagan River basins are important mountain headwaters to provide biodiversity and ecosystem services and to supply water for hydropower dams and reservoir operations in British Colombia, Canada, and the northwest United States. However, the impact of forest disturbance by forest harvesting, disease, and wildfire and then recovery, and deglaciation on the basin hydrology has not been thoroughly studied. The impact of largescale forest disturbances in the basin on the magnitude of recent flooding has not been fully investigated. This study aims to develop a methodology to simulate forest disturbance and regrowth in a hydrological land surface model and then use the model to investigate the impact of forest disturbance on the basin hydrology. An enhanced version of MESH (Modélisation Environnementale communautaire - Surface Hydrology) that incorporated mountain hydrology and vector base routing was setup over a total of 2177 model sub-basins; 1822 for the Upper Co ...

This study evaluated the effects of climate perturbations on snowmelt, soil moisture, and streamflow generation in small Canadian Prairies basins using a modelling approach based on classification of basin biophysical characteristics. Seven basin classes that encompass the entirety of the Prairies Ecozone in Canada were determined by cluster analysis of these characteristics. Individual semi-distributed virtual basin (VB) models representing these classes were parameterized in the Cold Regions Hydrological Model (CRHM) platform, which includes modules for snowmelt and sublimation, soil freezing and thawing, actual evapotranspiration (ET), soil moisture dynamics, groundwater recharge, and depressional storage dynamics including fill and spill runoff generation and variable connected areas. Precipitation (P) and temperature (T) perturbation scenarios covering the range of climate model predictions for the 21st century were used to evaluate climate sensitivity of hydrological processes in ...

He, Z., Shook, K., Spence, C., Pomeroy, J. W., and Whitfield, C. (2023) Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach, Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023

Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach

The Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) is a flexible modelling framework reproducing the behaviour of 47 established hydrological models. This toolbox can be used to calibrate and run models in a user-friendly and consistent way and is designed to facilitate the sharing of model code for reproducibility and to support intercomparison between hydrological models. Additionally, it allows users to create or modify models using components of existing ones. We present a new MARRMoT release (v2.1) designed for improved speed and ease of use. While improved computational efficiency was the main driver for this redevelopment, MARRMoT v2.1 also succeeds in drastically reducing the verbosity and repetitiveness of the code, which improves readability and facilitates debugging. The process to create new models or modify existing ones within the toolbox is also simplified in this version, making MARRMoT v2.1 accessible for researchers and practitioners at all levels of e ...

We report on the characteristics of precipitation associated with three types of landfalling atmospheric rivers (ARs) over western North America in the winter season from 1980 to 2004. The ARs are classified according to three landfalling regions as southern, middle and northern types. Two main centers of precipitation are associated with the contributions by the ARs: one over Baja California linked to the southern type of the ARs, and the other over Washington State correlated with the northern and middle types of the ARs. ARs are seen to play a dominant role in the occurrences of extreme precipitation events, with a proportionately greater impact on more extreme events. Moisture flux convergence makes the dominant contribution to precipitation when ARs and extreme precipitation occur simultaneously in the studied areas. Moisture flux convergence in these cases is, in turn, dominated by the mean and transient moisture transported by the transient wind, with greater contribution from t ...

River ice monitoring is important for hydrological research and water resource management of the Tibetan Plateau but limited by the serious shortage of field observations, and remote sensing can be used as an effective supplementary means for monitoring river ice. However, remote sensing high-altitude river ice is scarce and a basin-scale understanding of river ice is lacking on the Tibetan Plateau. To ascertain the spatial and temporal distribution characteristics of high-altitude river ice at the basin scale, we selected the Babao River basin as the study area, which is a typical river basin located in the northeastern Tibetan Plateau. Utilizing 447 available Landsat images during the river ice period from 1999 to 2018 and the classical normalized difference snow index (NDSI) algorithm, we monitored the river ice in a long time series at the Babao River basin. The average Khat of accuracy validation reached 0.973. The average area of river ice in the river ice period of this basin sh ...

Lake Erie’s commercial and recreational walleye fishery is the largest of the Great Lakes, requiring effective management to maintain a sustainable and complex fishery. Lake Erie’s walleye fishery is composed of multiple spawning populations, which presents a management challenge. The movement patterns and recruitment of distinct walleye populations that make up the fishery must be considered by managers to avoid overexploitation and to maintain population diversity. The Grand River walleye population in Lake Erie’s eastern basin is considered a priority for rehabilitation due to blocked access to spawning habitat by a low-head dam and degraded habitat quality. The objectives of this study were to: i) investigate movement patterns of spawning walleye in the Grand River using acoustic telemetry; and, ii) investigate movement and habitat use of young-of-the-year (YOY) walleye in relation to the Dunnville Dam and surrounding habitat segments using stable isotope analysis. Between 2015 and ...

Unstructured triangular meshes are an efficient and effective landscape representation that are suitable for use in distributed hydrological and land surface models. Their variable spatial resolution provides similar spatial performance to high-resolution structured grids while using only a fraction of the number of elements. Many existing triangulation methods either sacrifice triangle quality to introduce variable resolution or maintain well-formed uniform meshes at the expense of variable triangle resolution. They are also generally constructed to only fulfil topographic constraints. However, distributed hydrological and land surface models require triangles of varying resolution to provide landscape representations that accurately represent the spatial heterogeneity of driving meteorology, physical parameters and process operation in the simulation domain. As such, mesh generators need to constrain the unstructured mesh to not only topography but to other important surface and sub- ...

Seasonal measurements of glacier mass balance provide insight into the relation between climate forcing and glacier change. To evaluate the feasibility of using remotely sensed methods to assess seasonal balance, we completed tandem airborne laser scanning (ALS) surveys and field-based glaciological measurements over a 4-year period for six alpine glaciers that lie in the Columbia and Rocky Mountains, near the headwaters of the Columbia River, British Columbia, Canada. We calculated annual geodetic balance using coregistered late summer digital elevation models (DEMs) and distributed estimates of density based on surface classification of ice, snow, and firn surfaces. Winter balance was derived using coregistered late summer and spring DEMs, as well as density measurements from regional snow survey observations and our glaciological measurements. Geodetic summer balance was calculated as the difference between winter and annual balance. Winter mass balance from our glaciological observ ...

Toxic metals and metalloids pollution is a major ecological and human health issue, yet classical detection methods are limited. Here we review surface-enhanced Raman spectroscopy-based sensors using nanomaterial-based substrates for metal detection, with emphasis on substrate composition, functionalization, and assembly; metal sensing strategies; and analytical performance. Substrates include nobel metals, semiconductors, and composites. Substrate assembly can be done in solution or on solid supports. Sensing strategies comprise direct sensing, reporter recognition, reporter migration, substrate aggregation, and substrate modification. In general, the physicochemical properties of the substrates determine sensor sensitivity through electromagnetic and chemical enhancements of Raman scattering, whereas substrate surface functionalization, or lack thereof, determines sensor selectivity and the sensing mechanism. The main elements analyzed are mercury, lead, copper, arsenic, and chromium ...

We merge classical extreme value methods to extract high (high temperatures (HT)) and low (low temperatures (LT)) temperatures and form time series having at least one extreme value per year. Observed daily maximum and minimum temperature records are used from 4,797 quality-controlled, global, surface stations over 1970–2019. We assess changes in the magnitude and frequency of extreme temperatures by introducing and applying novel methods that exploit the definition of stationarity. Analysis shows significant increasing (40.6% of the stations) and decreasing (41.1%) trends in the frequency of high and LT, respectively, and increasing trends in both high- and low-temperature values (35.6% and 49.7%). Globally, HT and LT frequencies are increasing and decreasing, respectively, by 0.9% and 1.1% per year, relative to the expected frequencies under the assumption of stationarity. The global mean annual HT and LT magnitudes are increasing by 0.004 and 0.016°C/year compared to the expected on ...

The Global Environmental Multiscale Model (GEM) is currently in operational use for data assimilation and forecasting at 25–15 km scales; regional 10 km scales over North America; and 2.5 km scales over Canada. To evaluate the GEM model for forecasting applications in Iran, global daily temperature and precipitation outputs of GEM at a 25 km scale were compared to data sets from hydrometeorological stations and the De Martonne climate classification method was used to demarcate climate zones for comparisons. GEM model outputs were compared to observations in each of these zones. The results show good agreement between GEM outputs and measured daily temperatures with Kling-Gupta efficiencies of 0.76 for the arid, 0.71 for the semiarid, and 0.78 for the humid regions. There is also an agreement between GEM outputs and measured annual precipitation with differences of 50% for the arid, 36% for the semiarid, and 15% for the humid region. There is a ~13% systematic difference between the el ...

Halogenated disinfection by-products (DBPs) are a diverse class of compounds formed during the treatment of drinking water through reactions between natural organic matter (NOM), inorganic precursors such as bromide, and applied disinfectants. Health Canada regulates a handful of DBPs, but there are over 700 unregulated DBPs that have been described and many of these are more toxic than the regulated DBPs. Here, a data-independent precursor isolation and characteristic fragment (DIPC-Frag) method operated on a Q ExactiveTM Hybrid Quadrupole-OrbitrapTM Mass Spectrometer equipped with a UHPLC system was adapted for the detection of brominated and iodinated DBPs (Br-DBPs and I-DBPs) in chlorinated water. Extraction and analytical conditions were optimized, chemometric strategies were applied, and a library of 553 Br-DBPs and 112 I-DBPs was established with structures predicted for the most abundant compounds. As the method exhibited good precision (~15% RSD), it was then used to study tre ...

Machine learning (ML) is increasingly considered the solution to environmental problems where only limited or no physico-chemical process understanding is available. But when there is a need to provide support for high-stake decisions, where the ability to explain possible solutions is key to their acceptability and legitimacy, ML can come short. Here, we develop a method, rooted in formal sensitivity analysis (SA), that can detect the primary controls on the outputs of ML models. Unlike many common methods for explainable artificial intelligence (XAI), this method can account for complex multi-variate distributional properties of the input-output data, commonly observed with environmental systems. We apply this approach to a suite of ML models that are developed to predict various water quality variables in a pilot-scale experimental pit lake. A critical finding is that subtle alterations in the design of an ML model (such as variations in random seed for initialization, functional cl ...

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian La ...

Permafrost is an important feature of cold-region hydrology, particularly in river basins such as the Mackenzie River basin (MRB), and it needs to be properly represented in hydrological and land surface models (H-LSMs) built into existing Earth system models (ESMs), especially under the unprecedented climate warming trends that have been observed. Higher rates of warming have been reported in high latitudes compared to the global average, resulting in permafrost thaw with wide-ranging implications for hydrology and feedbacks to climate. The current generation of H-LSMs is being improved to simulate permafrost dynamics by allowing deep soil profiles and incorporating organic soils explicitly. Deeper soil profiles have larger hydraulic and thermal memories that require more effort to initialize. This study aims to devise a robust, yet computationally efficient, initialization and parameterization approach applicable to regions where data are scarce and simulations typically require larg ...

Permafrost is an important feature of cold-region hydrology and needs to be properly represented in hydrological and land surface models (H-LSMs), especially under the observed and expected climate warming trends. This study aims to devise a robust, yet computationally efficient, initialization and parameterization approach for permafrost. We used permafrost observations from three sites along the Mackenzie River valley spanning different permafrost classes to test the validity of the approach.

Le réservoir de carbone de sol est un élément clé du cycle global du carbone et donc du système climatique. Les sols et le carbone organique qu'ils contiennent constituent le plus grand réservoir de carbone des écosystèmes terrestres. Ce réservoir est également responsable du stockage d'une grande quantité de carbone prélevé de l'atmosphère par les plantes par la photosynthèse. C'est pourquoi les sols sont considérés comme une stratégie de mitigation viable pour réduire la concentration atmosphérique de CO2 dûe aux émissions globales de CO2 d'origine fossile. Malgré son importance, des incertitudes subsistent quant à la taille du réservoir global de carbone organique de sol et à ses dynamiques. Les modèles de biosphère terrestre sont des outils essentiels pour quantifier et étudier la dynamique du carbone organique de sol. Ces modèles simulent les processus biophysiques et biogéochimiques au sein des écosystèmes et peuvent également simuler le comportement futur du réservoir de carbone ...

Gauthier, Charles (2023) Optimisation des paramètres de carbone de sol dans le modèle CLASSIC à l'aide d'optimisation bayésienne et d'observations, Umontreal Papyrus - Thèses et mémoires, https://hdl.handle.net/1866/31992

Optimisation des paramètres de carbone de sol dans le modèle CLASSIC à l'aide d'optimisation bayésienne et d'observations

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

Qu, B., Roy, A., Melton, J.R., Baltzer, J.L., Ryu, Y., Detto, M., Sonnentag, O. (2024) Optimizing maximum carboxylation rate for North America’s boreal forests in the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC) v.1.3, Geoscientific Model Development

Optimizing maximum carboxylation rate for North America’s boreal forests in the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC) v.1.3

Arctic soils store large amounts of organic carbon and other elements, such as amorphous silicon, silicon, calcium, iron, aluminum, and phosphorous. Global warming is projected to be most pronounced in the Arctic, leading to thawing permafrost which, in turn, changes the soil element availability. To project how biogeochemical cycling in Arctic ecosystems will be affected by climate change, there is a need for data on element availability. Here, we analyzed the amorphous silicon (ASi) content as a solid fraction of the soils as well as Mehlich III extractions for the bioavailability of silicon (Si), calcium (Ca), iron (Fe), phosphorus (P), and aluminum (Al) from 574 soil samples from the circumpolar Arctic region. We show large differences in the ASi fraction and in Si, Ca, Fe, Al, and P availability among different lithologies and Arctic regions. We summarize these data in pan-Arctic maps of the ASi fraction and available Si, Ca, Fe, P, and Al concentrations, focusing on the top 100?c ...

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant ...

Le changement climatique modifie rapidement la composition, la structure et le fonctionnement de la forêt boréale. Des simulations robustes de la productivité primaire brute (PPB) de la forêt boréale avec des modèles de biosphère terrestre (MBT) sont essentielles pour prédire la force des sources de puits de carbone dans les régions arctiques-boréales. Les mesures de covariance des turbulences fournissent des données précieuses pour l’analyse et l'affinement des MBT. Dans cette thèse, j'ai organisé un ensemble de données d'analyse de modèles pour les forêts boréales d'Amérique du Nord en compilant et harmonisant les données de flux de covariance des turbulences (les flux de dioxyde de carbone, d'eau et d'énergie) et les mesures environnementales (données météorologiques) sur huit peuplements forestiers matures (> 70 ans) représentatifs des différentes caractéristiques de peuplements, de climat et de conditions de pergélisol du biome boréal. L’ensemble de données a été utilisée dans une ...

Wildfire is the largest disturbance affecting peatlands, with northern peat reserves expected to become more vulnerable to wildfire as climate change enhances the length and severity of the fire season. Recent research suggests that high water table positions after wildfire are critical to limit atmospheric carbon losses and enable the re-establishment of keystone peatland mosses (i.e. Sphagnum). Post-fire recovery of the moss surface in Sphagnum-feathermoss peatlands, however, has been shown to be limited where moss type and burn severity interact to result in a water repellent surface. While in situ measurements of moss water repellency in peatlands have been shown to be greater for feathermoss in both a burned and unburned state in comparison to Sphagnum moss, it is difficult to separate the effect of water content from species. Consequently, we carried out a laboratory based drying experiment where we compared the water repellency of two dominant peatland moss species, Sphagnum and ...

The genus Pseudomonas includes genetically diverse groups of species that do not share a common evolutionary history. My research focused on analyzing the genome sequences of different Pseudomonas species to robustly elucidate their evolutionary relationships using multiple independent approaches, which include: (i) Construction of phylogenetic trees based on several large data sets of conserved proteins, and 16S rRNA gene sequences (ii) Determination of pairwise genomic similarities based on AAI and POCP matrices, (iii) Identification of molecular markers such as Conserved Signature Indels (CSIs) and Conserved Signature Proteins (CSPs), specific for different Pseudomonas species clades supported by other methods. Our Phylogenomic analyses revealed three major lineages/groups within Pseudomonas: Aeruginosa, Fluorescens, and Pertucinogena. While the Aeruginosa and Fluorescens lineages include multiple distinct clades, no molecular or biochemical traits were previously known to different ...

The availability and quality of quad-pol synthetic aperture radar (SAR) datasets has increased substantially since the early 2000s, allowing for polarimetrically complete investigations of freshwater ice. These investigations have lead to improved ice classification methods, new understanding of microwave-ice scattering processes, and the potential for new methods to extract ice observables. Such analyses are predicated on the decomposition of the target’s polarimetric properties along mathematical or physical lines. This paper comprehensively reviews the underlying theory and contemporary application of radar polarimetric decomposition as it applies to freshwater ice systems. Modelling and investigation of lake ice, river ice, and glacial systems are discussed. We conclude with recommendations for further research, discussing the value of further development of freshwater-ice models, their use in characterization of the scattering process, and the potential for new methods to extract ...

Conifer forests historically have been resilient to wildfires in part due to thick organic soil layers that regulate combustion and post-fire moisture and vegetation change. However, recent shifts in fire activity in western North America may be overwhelming these resilience mechanisms with potential impacts for energy and carbon exchange. Here, we quantify the long-term recovery of the organic soil layer and its carbon pools across 511 forested plots. Our plots span ~ 140,000 km2 across two ecozones of the Northwest Territories, Canada, and allowed us to investigate the impacts of time-after-fire, site moisture class, and dominant canopy type on soil organic layer thickness and associated carbon stocks. Despite thinner soil organic layers in xeric plots immediately after fire, these drier stands supported faster post-fire recovery of the soil organic layer than in mesic plots. Unlike xeric or mesic stands, post-fire soil carbon accumulation rates in hydric plots were negligible despit ...

Although there is increasing consensus that river restoration should focus on restoring processes rather than form, proven techniques to design and monitor projects for sediment transport processes are lacking. This study monitors bedload transport and channel morphology in a rural, an urban unrestored, and an urban restored reach. Objectives are to compare bedload transport regimes, assess the stability and self-maintenance of constructed riffle-pool sequences, and evaluate the impact of the project on coarse sediment continuity in the creek. Sediment tracking is done using radio frequency identification tracers and morphologic change is assessed from repeated cross-section surveys. Mean annual velocity is used to quantify the average downstream velocity of tracers, defined as the mean overall tracer travel length divided by the total study duration. The channel reconstruction slows down the downstream velocity of particles in the D75 and D90 size classes, but does not significantly c ...

Cyanobacteria, also known as blue-green algae for a long time, are the most ancient and problematic bloom-forming phylum on earth. An alert levels framework has been established by World Health Organization(WHO) to prevent the potential harmful cyanobacterial blooms. Normally, low cyanobacteria levels are found in surface water. 2000 cyanobacterial cells/mL and 100,000 cyanobacterial cells/mL are established for WHO Alert Level 1 and 2, respectively. However, eutrophication, climate change and other factors may promote the spread of cyanobacteria and increase the occurrence of harmful cyanobacterial blooms in water on a global scale. Hence, a rapid real time cyanobacteiral monitoring system is required to protect public health from the cyanotoxins produced by toxic cyanobacterial species. Current methods to control or prevent the development of harmful cyanobacterial blooms are either expensive, time consuming or not effective in the long term. The best method to control the blooms is t ...

In seasonally frozen environments, hydrological processes are highly dynamic during and following the melt period in the spring, and this is when most of the runoff and groundwater re- charge happens. This is also when evapotranspiration (ET) fluxes start to increase in response to higher solar radiation, and a resumption of photosynthesis in evergreen species. This thesis applies the Canadian Land Surface Scheme (CLASS) to three Boreal Ecosystem Research and Monitoring Sites (BERMS) in the boreal forest in Saskatchewan; Old Jack Pine, Old Black Spruce and Old Aspen. CLASS was used to simulate the energy and water balance of the vegetation, soil and snowpack at the three sites. Consistent with previous studies, it was shown that ET is overestimated in the model during the melt/thaw period. A series of numerical experiments were undertaken to investigate in detail the controls on simulated fluxes within the CLASS model and explore the model behaviour. The phenomenon of freezing point de ...

Major rivers that originate in mountainous areas provide the main water supply for more than one third of the world's population. These rivers typically exhibit a four-to-five-month high flow period driven by snowmelt and rain, followed by a seven-to-eight-month low flow period sustained by groundwater discharge from mountain headwaters. Recent small-scale and field-based studies have identified talus slopes, moraines, rock glaciers, and alpine meadows as the main landforms responsible for storing and discharging groundwater in these headwater environments and have further classified them as alpine aquifers. However, there has not been much progress upscaling our current small-scale understanding of alpine aquifers to the watershed-scale. This study aims to upscale our knowledge of alpine aquifers by developing a geospatial modelling approach that can 1) map the spatial extent and distribution of different aquifers that are common in alpine watersheds and 2) employ a numerical groundwa ...

The role of hummocky terrain in governing runoff routing and focussing groundwater recharge in the Northern Prairies of North America is widely recognised. However, most hydrological studies in the region have not effectively utilised information on the surficial geology and associated landforms in large-scale hydrological characterization. The present study uses an automated digital elevation model (DEM) analysis of a 6500-km2 area in the Northern Prairies to quantify hydrologically relevant terrain parameters for the common types of terrains in the prairies with different surficial deposits widespread in the prairies, namely, moraines and glaciolacustrine deposits. Runoff retention (and storage) capacity within depressions varies greatly between different surficial deposits and is comparable in magnitude with a typical amount of seasonal snowmelt runoff generation. The terrain constraint on potential runoff retention varies from a few millimetres in areas classified as moraine to ten ...

Identical or nearly similar code fragments in a software system's code-base are known as code clones. Code clones from the same clone class have a tendency of co-changing (changing together) consistently during evolution. Focusing on this co-change tendency, existing studies have investigated prediction and ranking co-change candidates of regular clones. However, a recent study shows that micro-clones which are smaller than the minimum size threshold of regular clones might also need to be co-changed consistently during evolution. Thus, identifying and ranking co-change candidates of micro-clones is also important. In this paper, we investigate factors that influenc the co-change tendency of the co-change candidates of a target micro-clone fragment. We mine fil level evolutionary coupling from thousands of revisions of our subject systems through mining association rules and analyze this coupling for the purpose of ranking. According to our finding on six open-source subject systems w ...

As a consequence of increasing temperatures, a rapid increase in shrub vegetation has occurred throughout the circumpolar North and is expected to continue. Rates of shrub expansion are highly variable, both at the regional scale and within local study areas. This study uses repeat airborne LiDAR and field surveys to measure changes in shrub vegetation cover along with landscape-scale variations in a well-studied subarctic headwater catchment in Yukon Territory, Canada. Airborne LiDAR surveys were conducted in August 2007 and 2018, whereas vegetation surveys were conducted in summer 2019. Machine learning classification algorithms were used to predict shrub presence/absence in 2018 based on rasterized LiDAR metrics, with the best-performing model applied to the 2007 LiDAR to create binary shrub cover layers to compare between survey years. Results show a 63.3% total increase in detectable shrub cover >= 0.45 m in height between 2007 and 2018, with an average yearly expansion of 5.8%. T ...

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain “non-standard” data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modelin ...

Developers often search for relevant code examples on the web for their programming tasks. Unfortunately, they face two major problems. First, the search is impaired due to a lexical gap between their query (task description) and the information associated with the solution. Second, the retrieved solution may not be comprehensive, i.e., the code segment might miss a succinct explanation. These problems make the developers browse dozens of documents in order to synthesize an appropriate solution. To address these two problems, we propose CROKAGE (Crowd Knowledge Answer Generator), a tool that takes the description of a programming task (the query) and provides a comprehensive solution for the task. Our solutions contain not only relevant code examples but also their succinct explanations. Our proposed approach expands the task description with relevant API classes from Stack Overflow Q&A threads and then mitigates the lexical gap problems. Furthermore, we perform natural language proces ...

Quantifying the behavior and performance of hydrologic models is an important aspect of understanding the underlying hydrologic systems. We argue that classical error measures do not offer a complete picture for building this understanding. This study demonstrates how the information theoretic measure known as transfer entropy can be used to quantify the active transfer of information between hydrologic processes at various timescales and facilitate further understanding of the behavior of these systems. To build a better understanding of the differences in dynamics, we compare model instances of the Structure for Unifying Multiple Modeling Alternatives (SUMMA), the Variable Infiltration Capacity (VIC) model, and the Precipitation Runoff Modeling System (PRMS) across a variety of hydrologic regimes in the Columbia River Basin in the Pacific Northwest of North America. Our results show differences in the runoff of the SUMMA instance compared to the other two models in several of our stu ...

Assessing extreme precipitation events is of high importance to hydrological risk assessment, decision making, and adaptation strategies. Global gridded precipitation products, constructed by combining various data sources such as precipitation gauge observations, atmospheric reanalyses and satellite estimates, can be used to estimate extreme precipitation events. Although these global precipitation products are widely used, there has been limited work to examine how well these products represent the magnitude and frequency of extreme precipitation. In this work, the five most widely used global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR and WFDEI) are compared to each other and to GHCN-daily surface observations. The spatial variability of extreme precipitation events and the discrepancy amongst datasets in predicting precipitation return levels (such as 100- and 1000-year) were evaluated for the time period 1979-2017. The behaviour of extremes, that is the frequency and ...

Software developers often look for solutions to their code-level problems by submitting questions to technical Q&A websites like Stack Overflow (SO). They usually include example code segments with questions to describe the programming issues. SO users prefer to reproduce the reported issues using the given code segments when they attempt to answer the questions. Unfortunately, such code segments could not always reproduce the issues due to several unmet challenges (e.g., external library not found) that might prevent questions from receiving prompt and appropriate solutions. A previous study produced a catalog of potential challenges that hinder the reproducibility of issues reported at SO questions. However, it is unknown how the practitioners (i.e., developers) perceive the challenge catalog. Understanding the developers' perspective is inevitable to introduce interactive tool support that promotes reproducibility. We thus attempt to understand developers' perspectives by surveying ...

Hydrological models, which have become increasingly complex in the last half century due to the advances in computing capabilities and data collection, have been extensively utilized to facilitate decision-making in water resources management. Such computer-based models generally contain considerable parameters that cannot be directly measured, and hence calibration and validation are required to ensure model transferability and robustness in model building (development). The most widely used method used for assessing model transferability in time is the split-sample test (SST) framework, which has even been a paradigm in the hydrological modeling community for decades. However, there is no clear guidance or empirical/numerical evidence that supports how a dataset should be split into the calibration and validation subsets. The SST decisions usually appear to be unclear and even subjective in literature. Even though past studies have spared tremendous efforts to investigate possible wa ...

Both climate and statistical models play an essential role in the process of demonstrating that the distribution of some atmospheric variable has changed over time and in establishing the most likely causes for the detected change. One statistical difficulty in the research field of detection and attribution resides in defining events that can be easily compared and accurately inferred from reasonable sample sizes. As many impacts studies focus on extreme events, the inference of small probabilities and the computation of their associated uncertainties quickly become challenging. In the particular context of event attribution, the authors address the question of how to compare records between the counterfactual “world as it might have been” without anthropogenic forcings and the factual “world that is.” Records are often the most important events in terms of impact and get much media attention. The authors will show how to efficiently estimate the ratio of two small probabilities of re ...

This book exposes practitioners and students to the theory and application of river and lake ice processes to gain a better understanding of these processes for modelling and forecasting. It focuses on the following processes of the surface water ice: freeze-up, ice cover thickening, ice cover breakup and ice jamming. The reader will receive a fundamental understanding of the physical processes of each component and how they are applied in monitoring and modelling ice covers during the winter season and forecasting ice floods. Exercises accompany each component to reinforce the theoretical principles learned. These exercises will also expose the reader to different tools to process data, such a space-borne remote sensing imagery for ice cover classification. A thread supporting numerical modelling of river ice and lake ice processes runs through the book.

The nc file contains two global Köppen-Geiger (KG) Climate Classification maps (resolution 0.5°). The robust maps are developed by using monthly temperature and precipitation data from UDEL, CRU, JRA55, NCEP/CFSR, MERRA2, ERA5, and WFDEI gridded products over the period 1980 to 2017. MasterMap 1 shows the most frequently observed climate types among all KG maps for each grid point, after directly merging the climate maps produced by the seven datasets. MasterMap 2 results from estimating the medians of precipitation and temperature among the seven datasets at each grid point.

Robust Köppen-Geiger (KG) Climate Classification Maps

Aksamit, N. O., & Pomeroy, J. W. (2015). Saltating snow mechanics: Three species classification from high speed videography. Proceedings of the 72nd Eastern Snow Conference, 56-66. http://www.usask.ca/hydrology/papers/Aksamit_Pomeroy_2015.pdf

Saltating snow mechanics: Three species classification from high speed videography

We present a novel method for surface freeze/thaw (F/T) classification based on L-band brightness temperature (TB), as measured by the Soil Moisture Active Passive (SMAP) mission, combined with thermodynamic temperature estimates, whether in situ or derived from near real-time model output. Variations in the cryosphere have significant, lasting impacts on physical, biological, and social systems, and act as sensitive indicators of climate change. Remote sensing at microwave frequencies is uniquely suited for monitoring the cryosphere’s spatial and temporal dynamics. Indeed, SMAP was tasked with providing a daily classification of the surface F/T state as one of two primary mission goals. Although surface F/T events are extrinsically driven phenomena, most existing classification algorithms rely on intrinsic thresholds – those derived from single-variable observables – that may not accurately reflect in situ conditions. Meanwhile, soil physicists have long used a robust framework to stu ...

first_pagesettingsOrder Article Reprints Open AccessArticle Satellite-Observed Soil Moisture as an Indicator of Wildfire Risk by Jaison Thomas Ambadan,Matilda Oja,Ze’ev GedalofORCID andAaron A. Berg *ORCID Department of Geography, Environment and Geomatics, University of Guelph, Guelph, ON N1G 2W1, Canada * Author to whom correspondence should be addressed. Remote Sens. 2020, 12(10), 1543; https://doi.org/10.3390/rs12101543 Received: 20 February 2020 / Revised: 6 May 2020 / Accepted: 7 May 2020 / Published: 12 May 2020 (This article belongs to the Section Remote Sensing in Agriculture and Vegetation) Download Browse Figures Versions Notes Abstract Wildfires are a concerning issue in Canada due to their immediate impact on people’s lives, local economy, climate, and environment. Studies have shown that the number of wildfires and affected areas in Canada has increased during recent decades and is a result of a warming and drying climate. Therefore, identifying potential wildfire risk ar ...

Recent advancements in language models, particularly for high-resource languages, have not been paralleled in low-resource languages spoken across Africa. This thesis addresses this gap by scaling pre-training data and developing improved language models for African languages. We introduce Wura, a high-quality, document-level pre-training dataset encompassing 16 African languages along with four high-resource languages commonly spoken on the continent: Arabic, English, French, and Portuguese. Leveraging Wura, we pre-train new versions of the AfriBERTa (encoder-only) and AfriTeVa (encoder-decoder) model families. These new models demonstrate superior performance across a variety of natural language understanding and generation tasks compared to existing baselines. Notably, AfriTeVa V2 Large (1B) stands as the largest sequence-to-sequence model pre-trained for African languages to date. Our methodology includes a meticulous three-stage curation process for Wura --- auditing and filterin ...

Lake ice is a significant component of the cryosphere due to its large spatial coverage in high-latitude regions during the winter months. The Laurentian Great Lakes are the world’s largest supply of freshwater and their ice cover has a major impact on regional weather and climate, ship navigation, and public safety. Ice experts at the Canadian Ice Service (CIS) have been manually producing operational Great Lakes image analysis charts based on visual interpretation of the synthetic aperture radar (SAR) images. In that regard, we have investigated the performance of the semi-automated segmentation algorithm “glocal” Iterative Region Growing with Semantics (IRGS) for lake ice classification using dual polarized RADARSAT-2 imagery acquired over Lake Erie. Analysis of various case studies indicated that the “glocal” IRGS algorithm could provide a reliable ice-water classification using dual polarized images with a high overall accuracy of 90.4%. However, lake ice types that are based on s ...

Climate extremes such as heat waves and droughts are projected to occur more frequently with increasing temperature and an intensified hydrological cycle. It is important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to heat and drought stress as indicated by air temperature (Ta ) and evaporative fraction (EF). Using normalized daily carbon fluxes from the FLUXNET Network for 34 forest sites in North America, the seasonal pattern of sensitivities of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (RE) in response to Ta and EF anomalies were compared for different forest types. The results showed that warm temperatures in spring had a positive effect on NEP in conifer forests but a negative impact in deciduous forests. GEP in conifer forests increased with higher temperature anomalies in spring but decreased in summer. The drought- ...

Software architectural changes involve more than one module or component and are complex to analyze compared to local code changes. Development teams aiming to review architectural aspects (design) of a change commit consider many essential scenarios such as access rules and restrictions on usage of program entities across modules. Moreover, design review is essential when proper architectural formulations are paramount for developing and deploying a system. Untangling architectural changes, recovering semantic design, and producing design notes are the crucial tasks of the design review process. To support these tasks, we construct a lightweight tool [4] that can detect and decompose semantic slices of a commit containing architectural instances. A semantic slice consists of a description of relational information of involved modules, their classes, methods and connected modules in a change instance, which is easy to understand to a reviewer. We extract various directory and naming st ...

Software architectural changes involve more than one module or component and are complex to analyze compared to local code changes. Development teams aiming to review architectural aspects (design) of a change commit consider many essential scenarios such as access rules and restrictions on usage of program entities across modules. Moreover, design review is essential when proper architectural formulations are paramount for developing and deploying a system. Untangling architectural changes, recovering semantic design, and producing design notes are the crucial tasks of the design review process. To support these tasks, we construct a lightweight tool [4] that can detect and decompose semantic slices of a commit containing architectural instances. A semantic slice consists of a description of relational information of involved modules, their classes, methods and connected modules in a change instance, which is easy to understand to a reviewer. We extract various directory and naming st ...

Lake ice is a significant component of the cryosphere due to its large spatial coverage in high-latitude regions during the winter months. The Laurentian Great Lakes are the world’s largest supply of freshwater and their ice cover has a major impact on regional weather and climate, ship navigation, and public safety. Ice experts at the Canadian Ice Service (CIS) have been manually producing operational Great Lakes image analysis charts based on visual interpretation of the synthetic aperture radar (SAR) images. In that regard, we have investigated the performance of the semi-automated segmentation algorithm “glocal” Iterative Region Growing with Semantics (IRGS) for lake ice classification using dual polarized RADARSAT-2 imagery acquired over Lake Erie. Analysis of various case studies indicated that the “glocal” IRGS algorithm could provide a reliable ice-water classification using dual polarized images with a high overall accuracy of 90.4%. However, lake ice types that are based on s ...

Wang, J., Duguay, C. R., Clausi, D. A., Pinard, V., & Howell, S. E. (2018). Semi-automated classification of lake ice cover using dual polarization RADARSAT-2 imagery. Remote Sensing, 10(11), 1727. https://doi.org/10.3390/rs10111727

Semi-automated classification of lake ice cover using dual polarization RADARSAT-2 imagery

Simulating catchment response to climate and land use change using catchment classification and virtual basin modelling, paper

Qu, B., Roy A., Melton, J.R., et al. (2022) Simulating historical and future boreal forest net ecosystem production using CLASSIC. American Geophysical Meeting, Chicago, United States of America, (December 12-16). https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1171634

Simulating historical and future boreal forest net ecosystem production using CLASSIC

Permafrost thaw is causing a rapid evolution of the lowland discontinuous permafrost regions of the Taiga Plains in Northern Canada and elsewhere in the Northern Hemisphere. Notably, this thaw is changing the spatial distribution of the dominant hydrologic land cover types (permafrost plateaus, fens, and isolated bogs) in parts of the Northwest Territories (NWT), Canada. Here, we develop a multinomial time series land cover model (TSLCM) to simulate historical land cover transitions, model spatial patterns of transition, and predict the long term evolution of land cover in the areas surrounding the Scotty Creek Research Station (SCRS), NWT, and similar discontinuous permafrost landscapes. The machine learning-based TSLCM is informed by a set of observed spatio-temporal variables. The independent variables represent driving factors of change, and include the estimated summertime land surface temperature anomaly (LST), the distance and a custom cost distance to land cover interfaces, tim ...

Site-level simulations of water and carbon balances in North American boreal forests across permafrost-free and permafrost regions using CLASSIC

Snow is an essential component in hydrology systems, and more speci cally, monitoring variations in snow cover can provide valuable information about water supply, wildlife habitats, and climate changes. In recent years, the potential of wide band snow radar (e.g. 2-8 GHz) has been discovered with a series of campaigns in Operation IceBrdige (OIB). Due to data from OIB mainly focusing on sea ice, most of the algorithms were also developed for snow on sea ice. As a result, this thesis aimed to test the applicability of the interface-based pulse peakiness snow depth retrieval method to snow on land. In addition, due to the common usage of radar altimeter in sea ice classi cation, this thesis also explored the possibility of adapting some of the ideas in sea ice classi cation to develop another retrieval method. Both approaches were tested on the 6 major vegetation types (tree, tall shrub, riparian shrub, dwarf shrub, tussock, and lichen) in the study area. Snow depth derived from Airborn ...

Software is solely designed, implemented, tested, and inspected by expert people, unlike other engineering projects where they are mostly implemented by workers (non-experts) after designing by engineers. Researchers and practitioners have linked software bugs, security holes, problematic integration of changes, complex-to-understand codebase, unwarranted mental pressure, and so on in software development and maintenance to inconsistent and complex design and a lack of ways to easily understand what is going on and what to plan in a software system. The unavailability of proper information and insights needed by the development teams to make good decisions makes these challenges worse. Therefore, software design documents and other insightful information extraction are essential to reduce the above mentioned anomalies. Moreover, architectural design artifacts extraction is required to create the developer’s profile to be available to the market for many crucial scenarios. To that end, ...

The soil moisture active passive (SMAP) validation experiment in the boreal forest took place near Candle Lake, Saskatchewan within an area previously studied as a part of the experiments conducted at the Boreal Ecosystem Research and Monitoring Sites (BERMS). This study specifically focuses on the data collected within a single SMAP radiometer footprint, covering an area of approximately 30 × 30 km2 within a boreal forest environment. The land cover classes and soil types in the boreal forest area of the BERMS region are dominated by coniferous trees and soils represented by an often-thick, organic-rich layer of moss and leaf litter above a mineral soil layer. The completed field experiment focused on accurately representing both soils and vegetation of the region based on comprehensive sampling campaigns completed over two sampling periods between 16–30 June and 6–18 August 2022. Numerous datasets were collected from sampling campaigns and through the installation of in situ networks ...

The soil moisture active passive (SMAP) validation experiment in the boreal forest took place near Candle Lake, Saskatchewan within an area previously studied as a part of the experiments conducted at the Boreal Ecosystem Research and Monitoring Sites (BERMS). This study specifically focuses on the data collected within a single SMAP radiometer footprint, covering an area of approximately 30 × 30 km2 within a boreal forest environment. The land cover classes and soil types in the boreal forest area of the BERMS region are dominated by coniferous trees and soils represented by an often-thick, organic-rich layer of moss and leaf litter above a mineral soil layer. The completed field experiment focused on accurately representing both soils and vegetation of the region based on comprehensive sampling campaigns completed over two sampling periods between 16–30 June and 6–18 August 2022. Numerous datasets were collected from sampling campaigns and through the installation of in situ networks ...

The biogeochemical functioning of natural and engineered environments is closely linked to spatial and temporal variations in molecular oxygen (O2) concentrations. A luminescence-based, Multi-Fibre Optode (MuFO) microsensor technique was developed to measure O2 concentrations in fully and partially water-saturated systems. The technique relies on the conversion of high-resolution digital images of sensor-emitted light into O2 concentrations using the classical Stern-Volmer (SV) and Lehrer equations. The method was tested in two soil column experiments designed to simulate water table fluctuations (WT) and freeze-thaw cycles (FTC) under controlled conditions. The columns were filled with a homogenized mixture of peat (20 %) and sand (80 %). Depth distributions of O2 concentration were monitored without interruption for 20 (WT experiment) and 39 days (FTC experiment), while CO2 effluxes from the soils were measured periodically. Increases in CO2 emission accompanied both thawing (FTC exp ...

Drainage leads to trade-offs between crop production efficiency and wetland conservation, with complex impacts on ecosystem services. In North America’s Prairie Pothole Region, wetland drainage is widespread, often to increase the available land for cultivation, prevent crop loss due to flooding, and manage soil salinity. Wetlands are known for providing key ecosystem services such as improved water quality, flood mitigation, and carbon storage. There is limited research on how changes to soil hydrology and soil redistribution through wetland drainage can impact soil carbon storage and persistence in this region. This research evaluates factors that contribute to soil carbon storage in drained prairie pothole wetland based on 33 drained wetlands in Saskatchewan, Canada. These analyses showed regional differences in the response of soil carbon storage to drainage that are driven by environmental factors such as annual precipitation, temperature, and wetland permanence. We observed incre ...

Increased fire frequency, extent and severity are expected to strongly affect the structure and function of boreal forest ecosystems. In this study, we examined 213 plots in boreal forests dominated by black spruce (Picea mariana) or jack pine (Pinus banksiana) of the Northwest Territories, Canada, after an unprecedentedly large area burned in 2014. Large fire size is associated with high fire intensity and severity, which would manifest as areas with deep burning of the soil organic layer (SOL). Our primary objectives were to estimate burn depth in these fires and then to characterise landscapes vulnerable to deep burning throughout this region. Here we quantify burn depth in black spruce stands using the position of adventitious roots within the soil column, and in jack pine stands using measurements of burned and unburned SOL depths. Using these estimates, we then evaluate how burn depth and the proportion of SOL combusted varies among forest type, ecozone, plot-level moisture and s ...

Study region Italy. Study focus Knowing magnitude and frequency of extreme precipitation is necessary to reduce their impact on vulnerable areas. Here we investigate the performance of the Generalized Extreme Value () distribution, using a fine-resolution satellite-based gridded product, to analyze 13,247 daily rainfall annual maxima samples. A non-extreme value distribution with a power-type behavior, that is, the Burr Type XII (), is also evaluated and used to test the reliability of the in describing extreme rainfall. New hydrological insights for the region (1) in 44.9 % of the analyzed samples the predicts an upper rainfall limit; we deem this is an artifact due to sample variations; (2) we suggest the distribution, that is, the with shape parameters restricted only to positive values as a more consistent model complying with the nature of extreme precipitation; (3) , , and performed equally well in describing the observed annual precipitation, yet all distributions underes ...

In an effort to feed a growing world population, agriculture has rapidly intensified over the last six decades, relying heavily on agrochemicals (fertilizers, insecticides, fungicides, and herbicides) to increase and maintain desired crop yields. Despite environmental concerns in Canada’s agricultural regions, long-term patterns of changing crops and the associated trends in the proportion of cropland treated with agrochemicals are poorly documented. Using the Canadian Census of Agriculture, we compiled historical data over 35 years (eight census periods: 1981–2016) on agrochemical applications, measured as the proportion of cropland treated with pesticides and fertilizers and the associated crop classes, to identify and interpret spatial and temporal trends in Canada’s agricultural practices across 260 census units. Due to differences in agricultural practices, soil, and climatic conditions across the country, the Pacific (British Columbia), Prairie (Alberta, Saskatchewan, Manitoba), ...

Scientific workflows have emerged as well-established pillars of large-scale computational science and appeared as torchbearers to formalize and structure a massive amount of complex heterogeneous data and accelerate scientific progress. Scientists of diverse domains can analyze their data by constructing scientific workflows as a useful paradigm to manage complex scientific computations. A workflow can analyze terabyte-scale datasets, contain numerous individual tasks, and coordinate between heterogeneous tasks with the help of scientific workflow management systems (SWfMSs). However, even for expert users, workflow creation is a complex task due to the dramatic growth of tools and data heterogeneity. Scientists are now more willing to publicly share scientific datasets and analysis pipelines in the interest of open science. As sharing of research data and resources increases in scientific communities, scientists can reuse existing workflows shared in several workflow repositories. Un ...

Reading through code, finding relevant methods, classes and files takes a significant portion of software development time. Having good tool support for this code browsing activity can reduce human effort and increase overall developer productivity. To help with program comprehension activities, building an abstract code summary of a software system from its call graph is an active research area. A call graph is a visual representation of the caller-callee relationships between different methods of a software system. Call graphs can be difficult to comprehend for a large code-base. Previous work by Gharibi et al. on abstract code summarizing suggested using the Agglomerative Hierarchical Clustering (AHC) tree for understanding the codebase. Each node in the tree is associated with the top five method names. When we replicated the previous approach, we observed that the number of nodes in the AHC tree is burdensome for developers to explore. We also noticed only five method names for ea ...

Colloidally-stable zero valent iron nanoparticles (nZVI) were synthesized through a classical redox reaction of iron sulfate with minor modifications using cellulose nanocrystals (CNCs) as stabilizers. We obtained spherical nZVI particles with high surface roughness and a mean size of 130nm. Particles remain colloidally stable after more than two months. Cellulose nanocrystals play a dual role in nZVI stability: a foreign surface to encourage stable nucleation over fast aggregation and a stabilizer to prevent iron nanoparticles aggregating into fractal colloids. Our results highlight the impact of the presence of CNCs on the rates and mechanisms of nucleation, growth, aggregation, and aging of nZVI particles, indicating promise in controlling size and morphology of similarly redox-generated nanoparticles. Cellulose nanocrystal-stabilized nZVI nanoparticles demonstrate properties well-suited for enhanced soil and groundwater remediation. //Nanocomposites composed of carboxylated cellulo ...

Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, ...

Climate change is raising average temperatures, altering rain and snowfall patterns, thawing permafrost, increasing the frequency and intensity of extreme weather, and raising sea levels within Canada. This is leading to specific impacts for water resources, which affect water availability and quality. The nature and timing of water-related hazards such as floods and droughts are also exacerbated. Climate change, combined with human developments, have led to a range of impacts and risks that intersect with water systems, including damaged infrastructure, deteriorating water quality, and ecosystem impacts. These impacts and risks affect Canadians in a different ways depending on their geographic location, sector of interest, and time of year. Canadian organizations and institutions that manage water-related risks require easily accessible climate data necessary to understand these impacts and risks and prioritize adaptation efforts. The Canadian Centre for Climate Services (CCCS) offer ...

The Influence of Shade and Complex Topography on the Classification, Climate, and Energy Balance of a Sub-alpine Wetland

Snowmelt contributions to streamflow in mid-latitude mountain basins typically dominate other runoff sources on annual and seasonal timescales. Future increases in temperature and changes in precipitation will affect both snow accumulation and seasonal runoff timing and magnitude, but the underlying and fundamental roles of mountain basin geometry and hypsometry on snowmelt sensitivity have received little attention. To investigate the role of basin geometry in snowmelt sensitivity, a linear snow accumulation model and the Cold Regions Hydrological Modeling (CRHM) platform driven are used to estimate how hypsometry affects basin-wide snow volumes and snowmelt runoff. Area-elevation distributions for fifty basins in western Canada were extracted, normalized according to their elevation statistics, and classified into three clusters that represent top-heavy, middle, and bottom-heavy basins. Prescribed changes in air temperature alter both the snow accumulation gradient and the total snow ...

Quantifying water and energy fluxes are critical to understand how water is moved and stored on the landscape. These measurements are important for flood and drought forecasting, water resources management, and large-scale numerical weather prediction models. Moreover, land surface model’s (LSMs) which are hydrological tools used to predict and forecast water and energy fluxes, rely on these measurements to calibrate and validate their predictions. To evaluate hydrological fluxes and in turn water storage, representative observations are needed to capture the temporal and spatial dynamics of water on the landscape. However, hydrological fluxes are often difficult to measure and are limited to specific fluxes and spatial resolutions. Geological Weighing Lysimeters (GWL) are novel instruments that provide measurements of total integrated water storage at scales of 102 m2 and 106 m2 (field-scale). These tools use a saturated formations response to changes in mechanical loading, to estimat ...

Aufeis, also known as an icing or naled, is an accumulation of ice that forms primarily during winter when water is expelled onto frozen ground or ice surfaces and freezes in layers. Process-oriented aufeis research initially expanded in the 20th century, but recent interest in changing hydrological conditions in permafrost regions has rejuvenated this field. Despite its societal relevance, the controls on aufeis distribution and dynamics are not well defined and this impedes projections of variation in aufeis size and distribution expected to accompany climate change. This paper reviews the physical controls on aufeis development, current broad-scale aufeis distribution and anticipated change, and approaches to aufeis investigation. We propose an adjustment to terminology to better distinguish between the formation process and resulting ice bodies, a clarification of the aufeis classification approach based on source water, and a size threshold for broad-scale aufeis inventory to faci ...

Performance in simulating atmospheric rivers (ARs) over western North America based on AR frequency and landfall latitude is evaluated for 10 models from phase 5 of the Coupled Model Intercomparison Project among which the CanESM2 model performs well. ARs are classified into southern, northern, and middle types using self-organizing maps in the ERA-Interim reanalysis and CanESM2. The southern type is associated with the development and eastward movement of anomalous lower pressure over the subtropical eastern Pacific, while the northern type is linked with the eastward movement of anomalous cyclonic circulation stimulated by warm sea surface temperatures over the subtropical western Pacific. The middle type is connected with the negative phase of North Pacific Oscillation–west Pacific teleconnection pattern. CanESM2 is further used to investigate projected AR changes at the end of the twenty-first century under the representative concentration pathway 8.5 scenario. AR definitions usual ...

East of the Continental Divide in the cold interior of Western Canada, the Mackenzie and Nelson River basins have some of the world's most extreme and variable climates, and the warming climate is changing the landscape, vegetation, cryosphere, and hydrology. Available data consist of streamflow records from a large number (395) of natural (unmanaged) gauged basins, where flow may be perennial or temporary, collected either year-round or during only the warm season, for a different series of years between 1910 and 2012. An annual warm-season time window where observations were available across all stations was used to classify (1) streamflow regime and (2) seasonal trend patterns. Streamflow trends were compared to changes in satellite Normalized Difference Indices. Clustering using dynamic time warping, which overcomes differences in streamflow timing due to latitude or elevation, identified 12 regime types. Streamflow regime types exhibit a strong connection to location; there is a ...

Using only warm season streamflow records, regime and change classifications were produced for ~ 400 watersheds in the Nelson and Mackenzie River basins, and trends in water storage and vegetation were detected from satellite imagery. Three areas show consistent changes: north of 60° (increased streamflow and basin greenness), in the western Boreal Plains (decreased streamflow and basin greenness), and across the Prairies (three different patterns of increased streamflow and basin wetness).

Model calibration and validation are critical in hydrological model robustness assessment. Unfortunately, the commonly used split-sample test (SST) framework for data splitting requires modelers to make subjective decisions without clear guidelines. Unlike most SST studies that use two sub-periods (i.e., calibration and validation) to build models, this study incorporates an independent model testing period in addition to calibration and validation periods. Two hydrological models are calibrated and tested in 463 CAMELS catchments across the United States using 50 different data splitting schemes. These schemes are established regarding the data availability, length, and data recentness of the continuous calibration sub-periods (CSPs). A full-period CSP is also included in the experiment, which skips model validation entirely. The results are synthesized regarding the large sample of catchments and are comparatively assessed in multiple novel ways, including how model building decision ...

Model calibration and validation are critical in hydrological model robustness assessment. Unfortunately, the commonly used split-sample test (SST) framework for data splitting requires modelers to make subjective decisions without clear guidelines. This large-sample SST assessment study empirically assesses how different data splitting methods influence post-validation model testing period performance, thereby identifying optimal data splitting methods under different conditions. This study investigates the performance of two lumped conceptual hydrological models calibrated and tested in 463 catchments across the United States using 50 different data splitting schemes. These schemes are established regarding the data availability, length and data recentness of continuous calibration sub-periods (CSPs). A full-period CSP is also included in the experiment, which skips model validation. The assessment approach is novel in multiple ways including how model building decisions are framed a ...

Wildfires, which constitute the most extensive natural disturbance of the boreal biome, produce a broad range of ecological impacts to vegetation and soils that may influence post-fire vegetation assemblies and seedling recruitment. We inventoried post-fire understory vascular plant communities and tree seedling recruitment in the northwestern Canadian boreal forest and characterized the relative importance of fire effects and fire history, as well as non-fire drivers (i.e., the topoedaphic context and climate), to post-fire vegetation assemblies. Topoedaphic context, pre-fire forest structure and composition, and climate primarily controlled the understory plant communities and shifts in the ranked dominance of tree species (***8% and **13% of variance explained, respectively); however, fire and fire-affected soils were significant secondary drivers of post-fire vegetation. Wildfire had a significant indirect effect on understory vegetation communities through post-fire soil propertie ...

Existing software engineering tools have proved useful in automating some aspects of the code review process, from uncovering defects to refactoring code. However, given that software teams still spend large amounts of time performing code reviews despite the use of such tools, much more research remains to be carried out in this area. This dissertation present two major contributions to this field. First, we perform a text classification experiment over thirty thousand GitHub review comments to understand what code reviewers typically discuss in reviews. Next, in an attempt to offer an innovative, data-driven approach to automating code reviews, we leverage probabilistic models of source code and graph embedding techniques to perform human-like code inspections. Our experimental results indicate that the proposed algorithm is able to emulate human-like code inspection behaviour in code reviews with a macro f1-score of 62%, representing an impressive contribution towards the relatively ...

Soulis, E.D., K.R. Snelgrove, N. Kouwen, F. Seglenieks and D. Verseghy, (2000). Towards closing the vertical water balance in Canadian atmospheric models: Coupling of the land surface scheme CLASS with the distributed hydrological model WATFLOOD. Atmosphere-Ocean 38, 251-269.

Towards closing the vertical water balance in Canadian atmospheric models: Coupling of the land surface scheme CLASS with the distributed hydrological model WATFLOOD

Glacier melt is an important fresh water source. Seasonal changes can have impacting consequences on downstream water resources management. Today’s glacier monitoring lacks an observation-based tool for regional, sub-seasonal observation of glacier mass balance and a quantification of associated meltwater release at high temporal resolution. The snowline on a glacier marks the transition between the ice and snow surface, and is, at the end of the summer, a proxy for the annual glacier mass balance. It was shown that glacier mass balance model simulations closely tied to sub-seasonal snowline observations on optical satellite sensors are robust for the observation date. Recent advances in remote sensing permit efficient and extensive snowline mapping. Different methods automatically discriminate snow over ice on high- to medium-resolution optical satellite images. Other studies rely on lower ground resolution optical imagery to retrieve snow cover fraction at pixel level and produce re ...

Land surface models have many parameters that have a spatially variable impact on model outputs. In applying these models, sensitivity analysis (SA) is sometimes performed as an initial step to select calibration parameters. As these models are applied to large domains, performing sensitivity analysis across the domain is computationally prohibitive. Here, using a Variable Infiltration Capacity model (VIC) deployment to a large domain as an example, we show that watershed classification based on climatic attributes and vegetation land cover helps to identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. We evaluate the sensitivity of 44 VIC model parameters with regard to streamflow, evapotranspiration and snow water equivalent over 25 basins with a median size of 5078 km2. Basins are clustered based on their climatic and land cover attributes. Performance in transferring parameter sensitivity between basins of the same cluster is evaluated by the F1 ...

Uncertainties of snowpack models and of their meteorological forcings limit their use by avalanche hazard forecasters, or for glaciological and hydrological studies. The spatialized simulations currently available for avalanche hazard forecasting are only assimilating sparse meteorological observations. As suggested by recent studies, their forecasting skills could be significantly improved by assimilating satellite data such as snow reflectances from satellites in the visible and the near-infrared spectra. Indeed, these data can help constrain the microstructural properties of surface snow and light absorbing impurities content, which in turn affect the surface energy and mass budgets. This paper investigates the prerequisites of satellite data assimilation into a detailed snowpack model. An ensemble version of Météo-France operational snowpack forecasting system (named S2M) was built for this study. This operational system runs on topographic classes instead of grid points, so-called ...

Accurate and frequent mapping of transient wetland inundation in the boreal region is critical for monitoring the ecological and societal functions of wetlands. Satellite Synthetic Aperture Radar (SAR) has long been used to map wetlands due to its sensitivity to surface inundation and ability to penetrate clouds, darkness, and certain vegetation canopies. Here, we track boreal wetland inundation by developing a two-step modified decision-tree algorithm implemented in Google Earth Engine using Sentinel-1 C-band SAR and Sentinel-2 Multispectral Instrument (MSI) time-series data as inputs. This approach incorporates temporal as well as spatial characteristics of SAR backscatter and is evaluated for the Peace-Athabasca Delta, Alberta (PAD), and Yukon Flats, Alaska (YF) from May 2017 to October 2019. Within these two boreal study areas, we map spatiotemporal patterns in wetland inundation classes of Open Water (OW), Floating Plants (FP), Emergent Plants (EP), and Flooded Vegetation (FV). Te ...

Microflow cytometers and many other miniaturized microfluidic devices have shown great potential in many fields, such as, particle detection, cell sorting and classification. A reliable signal analysis method is required to improve the measurement accuracy of the emerging microfluidic devices. In this paper, a novel method is presented to analyze the signal from microspheres with different diameters based on transit time and amplitude. Experimental results show that transit time threshold plays a more important role at lower flow rate for particle differentiation and can be used to improve the performance of a microflow cytometer.

Transit time and amplitude thresholds in a microflow cytometer for particle classification

Microflow cytometers and many other miniaturized microfluidic devices have shown great potential in many fields, such as, particle detection, cell sorting and classification. A reliable signal analysis method is required to improve the measurement accuracy of the emerging microfluidic devices. In this paper, a novel method is presented to analyze the signal from microspheres with different diameters based on transit time and amplitude. Experimental results show that transit time threshold plays a more important role at lower flow rate for particle differentiation and can be used to improve the performance of a microflow cytometer.

Transit time and amplitude thresholds in a microflow cytometer for particle classification

Accurate classification of the phase of precipitation has important implications for understanding the vulnerability of future water resources in warming cold regions, where a substantial shift from snow to rain fraction is expected to occur over this century. In hydrological models, precipitation is typically partitioned into rainfall and snowfall using empirical near-surface air temperature thresholds methods. Surface air temperature methods require site-specific calibration and lack the physical basis to simulate this partitioning realistically and confidently for future climates. Advanced algorithms using the psychrometric energy balance of falling hydrometeors have demonstrated a solid physical basis and appear scalable across time and space but have only been applied in small basin studies. This study evaluated the impact of the choice of precipitation phase prediction technique on the historical and future hydrology of the 406,000 km2 Saskatchewan River Basin (SRB), from its he ...

This article presents a method to improve the usability of lake ice cover (LIC) maps generated from moderate resolution imaging spectroradiometer (MODIS) top-of-atmosphere reflectance data by providing estimates of aleatoric and epistemic uncertainty. We used a random forest (RF) classifier, which has been shown to have superior performance in classifying lake ice, open water, and clouds, to generate daily LIC maps with inherent (aleatoric) and model (epistemic) uncertainties. RF allows for the learning of different hypotheses (trees), producing diverse predictions that can be utilized to quantify aleatoric and epistemic uncertainty. We use a decomposition of Shannon entropy to quantify these uncertainties and apply pixel-based uncertainty estimation. Our results show that using uncertainty values to reject the classification of uncertain pixels significantly improves recall and precision. The method presented herein is under consideration for integration into the processing chain impl ...

Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data

This article presents a method to improve the usability of lake ice cover (LIC) maps generated from moderate resolution imaging spectroradiometer (MODIS) top-of-atmosphere reflectance data by providing estimates of aleatoric and epistemic uncertainty. We used a random forest (RF) classifier, which has been shown to have superior performance in classifying lake ice, open water, and clouds, to generate daily LIC maps with inherent (aleatoric) and model (epistemic) uncertainties. RF allows for the learning of different hypotheses (trees), producing diverse predictions that can be utilized to quantify aleatoric and epistemic uncertainty. We use a decomposition of Shannon entropy to quantify these uncertainties and apply pixel-based uncertainty estimation. Our results show that using uncertainty values to reject the classification of uncertain pixels significantly improves recall and precision. The method presented herein is under consideration for integration into the processing chain impl ...

Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data

Lake ice coverage products are a requirement identified by the climate community for improving numerical weather prediction and atmospheric reanalysis products, as well as for climate monitoring as determined by the Global Climate Observing System (GCOS). There are many suitable sources of observations available for mapping and monitoring lake ice coverage such as optical satellite data with the most practical ones from the Moderate Resolution Imaging Spectroradiometer (MODIS) over the last two decades. Considering the limitation of the presence of cloud cover and daylight dependency to capture imagery by optical sensors, the high revisit time of NASA’s Terra and Aqua satellites that carry MODIS allows for the production of lake ice maps required for operational and research-based projects. Building on our previous research findings concluded from a GWF-supported project on lake ice cover mapping of Lake Erie from RADARSAT data, we are proposing a method to characterize inherent unce ...

Cavaliere, E., Baulch, H., Basu, N., Wolfe, J., Hoggarth, C., & Hergott, A. (2019). Understanding nutrient retention in prairie wetlands using catchment classes and nutrient regimes. Global Water Futures Annual Science Meeting. Saskatoon, SK Canada. May 15-17, 2019 Conference Poster

Understanding nutrient retention in prairie wetlands using catchment classes and nutrient regimes

Discontinuous permafrost regions are experiencing a change in land cover distribution as a result of permafrost thaw. In wetlands interspersed with discontinuous permafrost, climate change is particularly problematic because temperature increases can result in significant permafrost thaw, thaw-driven landscape changes, and resultant changes in watershed hydrologic responses. The influence of land cover change on the short- and long-term hydrological responses of wetland-peatland complexes is poorly understood. A better understanding of the impacts of climate-related land cover evolution on the hydrology of wetland-covered watersheds requires information about the distribution of hydrologically important lands, their pattern, and the rate at which they change over time. Here, we first developed a machine learning-based land cover evolution model (TSLCM) to estimate the long-term evolution of dominant land covers for application to the discontinuous permafrost regions of Northern Canada. ...

After oil spills occur, regulators require adequate information to select best practices to minimize impacts on environments and to remediate target freshwater ecosystems. Zooplankton are valuable indicators of structure and function of aquatic ecosystems since they play pivotal roles in biochemical cycles while stabilizing food webs. Traditional identification of zooplankton can be costly and time-consuming, while also being difficult to standardize. Compared with classification of individuals by identification, based on visual inspection of morphology, metabarcoding of DNA and or RNA has promise for cost-effective high-throughput and benchmarkable biomonitoring of zooplankton communities. These identification methods were applied in the context of assessing responses of the zooplankton community exposed to simulated spills of diluted bitumen (dilbit), with concurrent exposure of experimental remediation practices of enhanced monitored natural recovery and shoreline cleaner applicatio ...

Space-based, global-extent digital elevation models (DEMs) are key inputs to many Earth sciences applications. However, many of these applications require the use of a ‘bare-earth’ DEM versus a digital surface model (DSM), the latter of which may include systematic positive biases due to tree canopies in forested areas. Critical topographic features may be obscured by these biases. Vegetation-free datasets have been created by using statistical relationships and machine learning to train on local-scale datasets (e.g., lidar) to debias the global-extent datasets. Recent advances in satellite platforms coupled with an increased availability of computational resources and lidar reference products has allowed for a new generation of vegetation- and urban-canopy removals. One of these is the Forest And Buildings removed Copernicus DEM (FABDEM), based on the most recent and most accurate global DSM Copernicus-30. Amongst the more challenging landscapes to quantify surface elevations are dens ...

Ogden Emily. Variation among land classification units in the NWT. Thesis

Variation among land classification units in the NWT

Peatlands in the Rocky Mountains most commonly occur in valley bottoms and are classified as fens. Understanding how fens influence water storage and water release is essential for better predicting water availability as the climate changes. Peatlands located in mountain regions tend to have a complex soil profile due to the geomorphologically dynamic environment. There is little information on the water storage capacity of mountain peatlands. To address this knowledge gap, the water storage capacity of a fen peatland with a complex soil profile in the Canadian Rocky Mountains, Alberta, Canada, was studied. Using the water table fluctuation method, vertical variations in specific yield were estimated. The influence of several factors – soil profile complexity, vegetation cover, water table depth, and seasonality – on specific yield were determined. Results showed that soil profile complexity plays a vital role in determining the spatial variability of vertical specific yield. The effec ...

Flow management has the potential to significantly affect ecosystem condition. Shallow lakes in arid regions are especially susceptible to flow management changes, which can have important implications for the formation of cyanobacterial blooms. Here, we reveal water quality shifts associated with changing source water inflow management. Using in situ monitoring data, we studied a seven-year time span during which inflows to a shallow, eutrophic drinking water reservoir transitioned from primarily natural landscape runoff (2014–2015) to managed flows from a larger upstream reservoir (Lake Diefenbaker; 2016–2020) and identified significant changes in cyanobacteria (as phycocyanin) using generalized additive models to classify cyanobacterial bloom formation. We then connected changes in water source with shifts in chemistry and the occurrence of cyanobacterial blooms using principal components analysis. Phycocyanin was greater in years with managed reservoir inflow from a mesotrophic ups ...

Hassan, Amina (2024) Watershed Classification in the Great Lakes Basin: Implications for Water Quality and Agricultural Management Practices, UWSpace - Theses, https://hdl.handle.net/10012/20623

Watershed Classification in the Great Lakes Basin: Implications for Water Quality and Agricultural Management Practices

Wetlands around the world are increasingly impacted by a shift in environmental conditions due to climate change, land use development, resource extraction, urbanization, and sea level rise, to name a few external pressures (Meng et al., 2016; Walpole and Davidson, 2018). These environmental changes can alter the hydrological regime, impacting the biogeochemical processes that govern important wetland ecosystem services, such as carbon sequestration and water storage. Biogeochemical processes in wetlands are highly dynamic (Reddy et al., 2010; Jackson et al., 2014) and involve complex interactions between hydrological processes, mineralogical transformations, bacterial and vegetation communities, and soil stores of carbon and nutrients (Cherry, 2011; U.S. EPA, 2015). Currently, our understanding of biogeochemical properties of wetlands are derived from mechanistic and statistical links between biological, geological, and chemical processes. However, how climatic and hydrological proces ...

High-latitude forests of North America are characterized by their natural dependence on large and severe wildfires. However, these wildfires also pose a range of social, economic, and environmental risks, with growing concern regarding persistent effects on stream flow volume, seasonal timing of flow, water quality, aquatic ecosystem health, and downstream community drinking water treatment. Here, we present the outcomes of a comprehensive scoping review of post-fire hydrologic studies in high-latitude forests of North America (Canada and Alaska). Our objectives were to (1) create an inventory of studies on post-fire hydrologic effects on surface water; (2) analyze those studies in terms of watershed characteristics and the type and duration of hydrologic effects; (3) identify and evaluate the link between upstream hydrologic effects with hydrologic ecosystem services; and (4) propose a research agenda addressing the link between wildfire science and hydrologic ecosystem services. We s ...