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Atmospheric, soil, surface and groundwater data from the St Denis National Wildlife Area, Saskatchewan, Canada
Federated Research Data Repository / dépôt fédéré de données de recherche
Bam, Edward; Brannen, Rosa; Budhathoki, Sujata; Ireson, Andrew; Spence, Chris; Van der Kamp, Garth — 2024-03-27 The St Denis National Wildlife Area database contains data for the prairie research site, St Denis National Wildlife Research Area, and includes atmosphere, soil, and groundwater. The meteorological measurements are observed every 5 seconds, and half-hourly averages (or totals) are logged. Soil moisture data comprise volumetric water content, soil temperature, electrical conductivity and matric potential for probes installed at depths of 5 cm, 20 cm, 50 cm, 100 cm, 200 cm and 300 cm in all soil profiles. Additional data on snow surveys, pond and groundwater levels, and water isotope isotopes collected on an intermittent basis between 1968 and 2018.The metadata table provides location information, information about the full range of measurements carried out on each parameter and GPS locations that are relevant to the interpretation of the records. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-11-553-2019.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/
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Canadian Prairie Watershed Classification
Federated Research Data Repository / dépôt fédéré de données de recherche
Wolfe, Jared; Whitfield, Colin J.; Shook, Kevin R.; Spence, Chris — 2024-03-27 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. The associated manuscript, which includes methods and data sources, can be found here: https://doi.org/10.5194/hess-23-3945-2019 https://creativecommons.org/licenses/by/4.0/

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(Source Repository: Global Water Futures (FRDR)) AND (Author: Spence, Chris)

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