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Volume 10, issue 3 | Copyright
Earth Syst. Sci. Data, 10, 1673-1686, 2018
https://doi.org/10.5194/essd-10-1673-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review article 13 Sep 2018

Review article | 13 Sep 2018

Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada (SLC) database for use in Soil and Water Assessment Tool (SWAT) simulations

Marcos R. C. Cordeiro1, Glenn Lelyk2, Roland Kröbel1, Getahun Legesse3, Monireh Faramarzi4, Mohammad Badrul Masud4, and Tim McAllister1 Marcos R. C. Cordeiro et al.
  • 1Science and Technology Branch, Agriculture and Agri-Food Canada, Lethbridge, AB, T1J 4B1, Canada
  • 2Science and Technology Branch, Agriculture and Agri-Food Canada, Winnipeg, MB, R3T 2N2, Canada
  • 3Department of Animal Science, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada
  • 4Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB, T6G 2E3, Canada

Abstract. 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 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 14063 unique soil records in the SLC, 11838 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 two-thirds 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.

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The Soil and Water Assessment Tool (SWAT) is one of the most used hydrological models worldwide. Lack of soil datasets in a SWAT-ready format hinders application of this model. This work discusses the preparation of a soil dataset for the agricultural extent of Canada compiled from the publicly available Soil Landscapes of Canada (SLC) database. Estimations of the hydrologic soil groups and erodibility factor variables not reported in the SLC database are important contributions of this work.
The Soil and Water Assessment Tool (SWAT) is one of the most used hydrological models worldwide....
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