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The Ensemble Meteorological Dataset for North America (EMDNA) contains daily precipitation, mean daily temperature, and daily temperature range at the 0.1-degree resolution from 1979 to 2018. Minimum and maximum temperature can be calculated from mean temperature and temperature range. EMDNA merges station observations and reanalysis model outputs to improve the quality of estimates. The dataset is expected to be useful for hydrological and meteorological applications in North America. Two types of datasets are provided by EMDNA, including the probabilistic dataset and the deterministic dataset. The probabilistic dataset has 100 equally plausible ensemble members, which can be used to evaluate the impact of the uncertainties in a myriad of applications. The deterministic dataset is generated during the production of ensemble members and can be applied in studies that do not need uncertainty estimation. See also: www.gwfnet.net/Metadata/Record/T-2020-11-25-i1Fwxi32sBMU2GDhUZ6gAJEg
Intestinal samples were collected from fathead minnows. Fish collected from the field were collected in minnow traps set overnight. All samples were collected with sterile dissection tools, and samples were immediately placed on ice prior to being transferred to a -80C freezer for long-term storage. 16s amplicon sequencing Total genomic DNA was extracted from guts using the DNeasy PowerSoil Kit (Qiagen Inc., Mississauga, ON). Concentrations were measured using a Qubit 4 Fluorometer and dsDNA HS assay kit (ThermoFisher Scientific, Waltham, MA). The V3-V4 variable region of the 16S rRNA gene was amplified using the Bact-0341 forward primer (CCTACGGGNGGCWGCAG) (Klindworth et al., 2013) and the Bact-806 reverse primer (GGACTACNVGGGTWTCTAAT) (Apprill et al., 2015). Samples were dual indexed to increase throughput of sequencing (Fadrosh et al., 2014). Samples were amplified with a 50 μL PCR reaction including Phusion green polymerase (ThermoFisher Scientific) using a SimpliAmp thermal cycler (ThermoFisher Scientific) under the following conditions: initial denaturation at 98°C for 30s, followed by 25 cycles of 98°C for 30s, 58°C for 30s, and 72°C for 30s, with a final extension at 72°C for 10 min. PCR products were assessed for size and specificity using electrophoresis on a 1.2% w/v agarose gel and purified using the Qiagen QIAquick PCR Purification Kit (Qiagen Inc.). All purified products were quantified with the Qubit dsDNA HS assay kit and concentrations were adjusted to 1 ng/ μL with molecular-grade water. Purified products were pooled, and libraries were constructed using the NEBNext® DNA Library Prep Master Mix Set for Illumina® (New England BioLabs Inc., Whitby, ON). Libraries were quantified prior to sequencing using the NEBNext® Library Quant Kit for Illumina®. Sequencing was performed on an Illumina® MiSeq instrument (Illumina, San Diego, CA) using a 2x300 base pair kit. See also: www.gwfnet.net/Metadata/Record/T-2020-11-30-81jA3aJ82ZSUGNzmMj9aYhgw
The Alder Creek field observatory was instrumented by the Southern Ontario Water Consortium as the middle member of three watersheds with different degrees of urbanization. Field data were collected via the deployment of electronic instruments and manual measurements in the Alder Creek watershed to answer questions related to water management at the watershed scale. Field sites were chosen based on: 1) an attempt to distribute measurement locations spatially throughout the watershed, 2) permissions obtained from local residents, businesses, and stakeholders (e.g., the Regional Municipality of Waterloo) for installations, and 3) interest in monitoring local processes such as depression focused recharge. Cellular network telemetry was used to regularly transmit remote field data to a computer at the University of Waterloo. This was part of a “smart” watershed design whereby field data could be reviewed by technicians to make decisions regarding field monitoring and equipment maintenance. Data collection schedules could also be adjusted remotely. Meteorological and hydrological (surface water and groundwater) data were collected within the Alder Creek watershed over about five years. Seven weather stations were deployed in and around the watershed that included instruments for the measurement of rainfall and snow depths, and for recording parameters required to estimate reference evapotranspiration (air temperature, relative humidity, incoming solar radiation, and wind speed). Several single and multi-port wells were installed near the weather stations. Recharge stations were set up at two sites to monitor soil moisture changes and water table fluctuations over time. Each consisted of a network of shallow wells/piezometers and infrastructure for measuring soil moisture both electronically and manually. One of these stations was designed to assess groundwater-surface water interaction and depression focused recharge during extreme/large-magnitude hydrological events. Stream monitoring at different points along the creek included: manual water sampling; testing of automated water sampling using event triggers; measurement of water levels and temperatures; measurement of pH, temperature, dissolved oxygen, electrical conductivity; development of streamflow rating curves; and automated nitrate concentration monitoring. Snow and water samples were analyzed for major cation and ion concentrations, and for O-18 and H-2 isotopes.
Various flood quantiles, corresponding to the return periods of (5, 10, 25, 50, 100, 200, 500, and 1000)-year, are developed at 1119 sites across Canada. The flood quantiles are obtained for each site by fitting each of the Burr Type-III, the Burr TypeXII, and the GEV distributions to the annual maximum observed streamflow using the method of L-moments. An R package called ‘fitsol’ that we recently developed can be used as a tool for estimating these quantiles. See also: www.gwfnet.net/Metadata/Record/T-2021-02-10-u1eDM6FS3mk6DTR5NCu1vu2Xw
One of the priority tasks in the Current Generation Hydrologic Modelling (CGHM) theme of the GWF Core Modelling and Forecasting Team is producing climate change runs for major basins across Canada. Part of this work plan is to set-up and run the climate change production runs for the Fraser River. 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 See also: www.gwfnet.net/Metadata/Record/T-2020-11-25-k1htBLtR8Ok1k2GmoFSlBlCyw
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 GmbH. (2018). Operating instructions Present Weather Sensor OTT Parsivel 2. Kempten, Germany. Retrieved from https://www.ott.com/download/operating-instructions-present-weather-sensor-ott-parsivel2-without-screen-heating/ See also: www.gwfnet.net/Metadata/Record/T-2021-02-12-M1YZJzKrNlkGt5eM2Dta5Scg
Cold regions hydrology is very sensitive to the impacts of climate warming. More physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrologic responses to climate change. However, hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly temperature and precipitation. Cold regions often have sparse surface observations, particularly at high elevations that generate the major amount of runoff. The effects of mountain topography and high latitudes are not well reflected in the observational record. The best available gridded data in these regions is from the high resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and the Canadian Precipitation Analysis (CaPA) reanalysis but this dataset has a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record, but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long record product (WFDEI-GEM-CaPA). First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3h x 0.125ᵒ resolution during the 2005-2016 period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. The variables (units) available are specific humidity, precipitation (kg m-2 s-1), surface_air_pressure (Pa), Surface Downwelling Longwave Radiation (W m-2), surface_downwelling_shortwave_flux_in_air (W m-2), Surface Downwelling Shortwave Radiation (W m-2), wind speed (m/s) and Air Temperature (K). Note that this dataset was created using a 365-day calendar, hence leap years have a missing day. These data are in NetCDF format and can be downloaded via the Cuizinart Platform (http://cuizinart.io) by selecting dataset labelled wfdei-gem-capa. See also: www.gwfnet.net/Metadata/Record/T-2020-05-28-f1DbgowHXckmzH3UuGCBlf2w
Data collected as part of various MWF and past initiatives. Eddy Covariance towers collect standard meteorological variables plus full energy, water and CO2 flux information. Meteorological instruments run year-round with eddy covariance year round at the Wolf Creek forest site. Met towers collect standard meteorological parameters. Most sites typically have precipitation measured at them. They also include ground temperature and soil moisture. There are two sites that are ground temperature/soil moisture profiles. One site is a deeper groundwater well. Hydrometric stations measure streamflow discharge during open water. Most sites have probes that measure temperature and salinity. Occasional water quality data is for major ions, dissolved organic carbon (DOC), and stable isotopes of water. Sampling frequency varies. Granger Basin has been measuring CDOM (coloured dissolved organic matter) since 2015.
The objectives of this study are testing the HYPE model for biogeochemical modelling in Canadian catchments, and exploring methodologies to improve biogeochemical prediction in view of uncertainty analysis and scenario investigation. Total phosphorus concentration is simulated using two approaches: 1) the sequential calibration approach that calibrates the hydrology first and then uses the best hydrological model to infer the biogeochemical model parameters, and 2) the joint approach that infers the hydrological and biogeochemical parameters simultaneously. The joint approach uses the total phosphorus load and streamflow as optimization variables. The two approaches were compared concerning identifiability of both the hydrological and biogeochemical model parameters, and the predictive power of both the hydrological and biogeochemical models. A daily computational time step was used. Outputs of the model are total phosphorus concentration and streamflow. The input data used to set up the models are provided below. -The meteorological data used to force the model is available from Asong et al (2018), https://doi.org/10.20383/101.0111 -The Digital Elevation model (DEM) used to generate the sub-basins and the stream network was obtained from the Greater Toronto Area (GTA) Digital Elevation Model 2002 (https://geohub.lio.gov.on.ca/datasets/mnrf::greater-toronto-area-gta-digital-elevation-model-2002). -The land use data was obtained from the Ontario Land Cover Compilation v.2.0 (https://geohub.lio.gov.on.ca/datasets/7aa998fdf100434da27a41f1c637382c). -The streamflow data used for calibrating the model was downloaded from the Environment and climate change Canada website using the “Beaverton” station name. The following link can be used to enter the station name and download the data at a daily time step, https://wateroffice.ec.gc.ca/search/historical_e.html -The soil data was originally obtained from the Soil Landscapes of Canada Working Group (2010), http://sis.agr.gc.ca/cansis/nsdb/slc/v3.2/index.html The total phosphorus load and streamflow produced by our HYPE model is used to test HYPE in the Beaver watershed as part of the broader objective of evaluating the suitability of biogeochemical modelling in Canadian basins and to explore improved calibration strategy of biogeochemical model for uncertainty quantification and management scenarios. This dataset supports the water quality modelling (WQM) theme of the GWF Core Modelling and Forecasting Team. See also: www.gwfnet.net/MetadataEditor/Record/T-2020-11-25-V1xtLuXyAYUKFIsAeV3ZbpqQ
The data collected for this study were used to identify the spatial extent of the Giant and Con mine emissions footprint in the Yellowknife area using primarily arsenic, antimony, and lead concentrations found in lake sediments. Solid-phase metal concentrations were analyzed by ALS Laboratories (Waterloo, ON) following EPA standards 200.2/6020A on lake sediments collected using a Uwitec gravity corer in June 2018. Sediment cores were collected from eight lake sites located at distances between 10 and 80 km from Giant and Con mines in the downwind direction (NW). Lake water samples were also collected at the time of core collection to characterize total and dissolved metal concentrations using a 1 L nalgene at a depth of 5 cm from the water surface. Additional analysis of lake sediment has included the measurement of carbon and nitrogen isotopic composition using a continuous flow isotope ratio mass spectrometer (CF-IRMS) at the University of Waterloo to determine relative sources of organic matter within lakes and identify whether there is evidence of hydrological change. Lake sediments were also subject to a standard loss-on-ignition analyses to determine relative organic matter, carbonate, mineral matter, and water content. Finally, lake sediments were radiometrically dated using measurements of 210Pb and 137Cs on an Ortec HPGE Digital Gamma Ray Spectrometer at the University of Waterloo to assign ages to sediment depths and ultimately determine when contaminants were deposited.