Abstract. The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, pre-processing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to pre-process 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 two-level 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 soils in the SLC, 11,838 soils 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 soils in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soils 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 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 modellers and are publicly available at https://doi.org/10.1594/PANGAEA.877298a.
Analysis of Best Management Practices Implementation on Water Quality Using the Soil and Water Assessment Tool
