Nitrogen effects on water use efficiency in the semi-arid Canadian prairies

Non-Peer ReviewedIn the semiarid environment of the Canadian prairies, water is the main constraint to crop production. Few studies have examined the influence of fertilizer on water use efficiency (WUE) and fewer still have made comparisons on a cropping system basis. We assessed the impact of fertilizer N on WUE in a 39-year crop rotation experiment conducted on a Brown Chernozemic soil at Swift Current, Saskatchewan. The cropping systems included continuous wheat (Cont W) with N+P and P fertilizer alone, and a fallow-wheat-wheat (F-W-W) system with N+P and P only. All cropping systems were managed using conventional tillage practices. We developed an equation to asses WUE of the cropping systems that included water use during the fallow year. We also calculated precipitation use efficiency (PUE, i.e., yield/harvest-to-harvest precipitation). WUE and PUE values and fertilizer effects were greatest in the later third of the study period, due to the increase in recommended fertilizer N rates applied and the more favorable moisture conditions that prevailed. We converted PUE results into net return values ($ha-1 mm-1 water) by assuming an average price over the 39-yr period and found that N fertilizer in the Cont W system earned an average return above fertilizer cost of$36.39 ha-1 yr-1 and $9.81 ha-1 yr-1in the F-W-W system

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

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 14&thinsp;063 unique soil records in the SLC, 11&thinsp;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&thinsp;%, 24.6&thinsp;%, 39.0&thinsp;%, and 15.1&thinsp;% 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&thinsp;%, 26.8&thinsp;%, 36.7&thinsp;%, and 16.5&thinsp;% 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.</p

Deriving Canada-wide soils dataset for use in Soil and Water Assessment Tool (SWAT)

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. Soils with missing records for the required SWAT variables were removed from the analysis. These soils were compiled into a soils list provided as a reference ("incomplete" dataset)