ALBERT

Description: Producers and scientists are seeking more accurate methods for estimating the N-supplying power of soil at the field level. This has become more urgent as new management technologies, such as precision farming, gain popularity on the Canadian Prairies. We characterized the N status of the soil on an 18-ha site on which a new long-term alternative farming experiment was being initiated at Scott, Saskatchewan, by taking 160 cores in a systematic manner in June 1994. In these cores we determined: i) total soil N; and ii) the N-supplying power of the soil by determining mineralizable N by aerobic incubation at optimum temperature and moisture, and by extracting NH4–N with 2 M KCl at 100°C. Because the field had been fertilized shortly before sampling, residual fertilizer N severely affected the quality of determinations of N supplying power at the 0- to 7.5-cm depth. Consequently, we limited our investigation to the 7.5- to 15-cm depth. We also determined pH, bulk density, and particle size distribution. Using geostatistics, simple correlations, and multiple regression analyses, we demonstrated a close association between the biological and chemical measures of N-supplying power of the soil. Semivariograms revealed that the spatial structure of the variance of both variables was similar, with about 70% of the variance resulting from unidentified processes, and the rest explained by spatial structure. Field maps prepared with block-kriged estimates, revealed that these two measures of N-supplying power were similarly distributed throughout the landscape, and followed closely the spatial distribution of total soil N throughout most of the field. However, we identified two areas of the field where the two estimators of N-supplying power had a weak association with total soil N. Multiple regression and cluster analysis indicated that this disparity was a function of differences in soil pH, bulk density, and geometric mean diameter of soil particles, suggesting that soil erosion-transport processes may have altered the nature of organic N in areas of the field. The relationship between N mineralized during a 24-wk incubation and NH4–N extracted with hot KCl was not affected by these differences, suggesting that the biological and chemical procedures tested were accessing similar pools of soil N. We concluded that hot KCl NH4–N should prove useful for quantifying the N supplying power of soils. Key words: Geostatistics, estimation, kriging, spatial variability, mineralizable N

Description: Information is required on the usefulness and limitations of simulation models for estimating nitrate-nitrogen (NO3-N) and water status of soil in different agroecological zones of western Canada. Therefore, four simulation models (CERES, EPIC, NLEAP and NTRM) were used to predict distribution of NO3-N and water in the soil profile from long-term spring wheat (Triticum aestivum L.) rotations for the 1990 growing season at Melfort and Scott, Saskatchewan. The models estimated NO3-N and water levels in the crop rooting zone (0–1.5 m) of the soil profiles generally well. However, EPIC underestimated NO3-N levels in the top 0.3 m for fallow (F) rotations at Melfort, whereas NLEAP overestimated amounts in the same depth increment of Melfort soil for the majority of rotations. In addition, CERES and NTRM markedly overestimated NO3-N levels in the Melfort soil solum (0–0.6 m) for the unfertilized continuous wheat (W) rotation. Soil water content was overestimated in the top 0.3-m layer of Melfort soil for the two W rotations by CERES and EPIC and for all rotations by NTRM. As well, EPIC markedly overestimated water content in the crop rooting zone for both rotations at Scott. There were differences among models in accurately simulating NO3-N and water status of the soil profile, but these differences were not great. Overall, these models should be effective in estimating soil NO3-N and water content for wheat cropping systems, thereby aiding agronomic decisions and environmental impact assessments. Key words: Crop Estimation through Resource and Environment Synthesis (CERES), Erosion/Productivity Impact Calculator (EPIC), nitrogen, Nitrogen Leaching and Economic Analysis Package (NLEAP), Nitrogen, Tillage, and Residue Management (NTRM), Triticum aestivum L.