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The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A twolevel screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14 063 unique soil records in the SLC, 11 838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3 %, 24.6 %, 39.0 %, and 15.1 % of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost twothirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0 %, 26.8 %, 36.7 %, and 16.5 % of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at https://doi.org/10.1594/PANGAEA.877298.Published by Copernicus Publications.

Prediction of soil salinity risk by digital terrain modelling in the Canadian prairies. Can. J. Soil Sci. 80: [455][456][457][458][459][460][461][462][463]. Soil salinisation is a typical problem for the Canadian prairies. At macro-topographic scale, build-up of salts occurs in depressions. However, this relationship is not displayed on existing small-scale maps of soil salinity. To improve these maps, one can use a concept of accumulation, transition and dissipation zones of the landsurface. The concept allows one to reveal depressions (topographically expressed accumulation zones) using digital models of horizontal and vertical curvatures, or accumulation and mean curvatures derived from a digital elevation model. We applied the concept of accumulation, transition and dissipation zones to improve an existing small-scale map of the salinity risk index for the prairies and adjacent areas. A comparison of the old and the improved maps demonstrated that once data on depressions have been taken into account, areas marked by salinity risk decreased significantly. We suggest that the method used may prevent an overestimation in predictions of soil cover degradation due to salinisation. The method used can also reveal saline areas linked with discharges of saline aquifers. This is because sites marked by high discharges of groundwater usually relate to sites of intensive fracturing of geological materials, which are closely associated with topographically expressed accumulation zones.

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