Etrophication and flooding are perennial problems in agricultural watersheds of the northern Great Plains. A high proportion of annual runoff and nutrient transport occurs with snowmelt in this region. Extensive surface drainage modification, frozen soils, and frequent backwater or ice-damming impacts on flow measurement represent unique challenges to accurately modelling watershed-scale hydrological processes. A physically based, non-calibrated model created using the Cold Regions Hydrological Modelling platform (CRHM) was parameterized to simulate hydrological processes within a low slope, clay soil, and intensively surface drained agricultural watershed. These characteristics are common to most tributaries of the Red River of the north. Analysis of the observed water level records for the study watershed (La Salle River) indicates that ice cover and backwater issues at time of peak flow may impact the accuracy of both modelled and measured streamflows, highlighting the value of evaluating a non-calibrated model in this environment. Simulations best matched the streamflow record in years when peak and annual discharges were equal to or above the medians of 6.7 m³ s⁻¹ and 1.25 × 10⁷ m³, respectively, with an average Nash–Sutcliffe efficiency (NSE) of 0.76. Simulation of low-flow years (below the medians) was more challenging (average NSE < 0), with simulated discharge overestimated by 90 % on average. This result indicates the need for improved understanding of hydrological response in the watershed under drier conditions. Simulation during dry years was improved when infiltration was allowed prior to soil thaw, indicating the potential importance of preferential flow. Representation of in-channel dynamics and travel time under the flooded or ice-jam conditions should also receive attention in further model development efforts. Despite the complexities of the study watershed, simulations of flow for average to high-flow years and other components of the water balance were robust (snow water equivalency (SWE) and soil moisture). A sensitivity analysis of the flow routing model suggests a need for improved understanding of watershed functions under both dry and flooded conditions due to dynamic routing conditions, but overall CRHM is appropriate for simulation of hydrological processes in agricultural watersheds of the Red River. Falsifications of snow sublimation, snow transport, and infiltration to frozen soil processes in the validated base model indicate that these processes were very influential in stream discharge generation.

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 14 063 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 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.

Forage production in northern latitudes is challenging and uncertain in the future. In this case-study, the integrated farm system model (IFSM) was used to assess the impact of climate change and cropland expansion scenarios on forage production in a dairy farm in Newfoundland, Canada. Climatic projections indicated increases in temperature in the recent past (1990–2016) and under any future climate (2020–2079), thus enhancing agronomic performance. Temperature increases ranged from 2.8 °C to 5.4 °C in winter and from 3.2 °C to 6.4 °C in spring. Small precipitation increases (<10%) create narrower time windows to perform farm operations in the already stringent condition of excess moisture in the region. Results of land use scenarios including expansions of 20, 30, and 40% in cropland area, out of which 5% was dedicated to corn silage and the remainder to grass-legume mixtures, indicated increased yield and total production. Improvements in grass-legume yield ranged from 8% to 52%. The full range of production increases ranged from 11% to 105%. Increments in corn silage yield ranged from 28% to 69%. Total farm corn silage production increases ranged from 29% to 77%. An attainable cropland expansion of 20% would enable the farm to become self-sufficient in forage production under any climate scenario.

Electromagnetic induction (EMI) has been used to map soil properties such as salinity and water content. The objective of this research is to use EMI to map the potential distribution of nutrients around beef cattle pens and to relate this distribution to major physiographic field features. Beef cattle farms in different physiographic locations were surveyed in Manitoba, Canada, using an EM-38 conductivity meter georeferenced with a GPS receiver. Samples were collected using a response surface design and analysed for electrical conductivity (EC _e), which was used as a proxy for determining potential build-up of nutrients. Multiple linear regression models (MLR) were used for calibration of the EM readings. The results showed that areas 1 through 4 had EC _e≤3.5 dS m ⁻¹, but areas 5 and 6 exceeded this concentration and reached maximum values of 5.5 and 7.0 dS m⁻¹, respectively. Higher values in area 6 were probably due to the presence of a rocky layer at 0.3 m depth, leaving a thin soil layer to accumulate the nutrients. Micro-depressions played a major role in salt accumulation, with the depressions corresponding to higher values of EC _e. The presence of features such as drainage ditches and compacted soils beneath roads strongly affected the direction of the plumes. Based on these results, the location of the pens on high elevations and the provision to collect the run-off from the pens were identified as good design criteria. Highly permeable soils may require a low permeability liner to capture the deep percolation and redirect it towards a collection area.