Informational assessment of changes in silt and physical clay content in arable chernozems of the Irtysh plain

The aim of the study was to quantify changes in particle size distributions of southern chernozems under the influence of long-term arable use and to determine information standards for silt and physical clay content in arable soils at different time points. Location and time of the study. The south of West Siberia, the central part of the Irtysh Plain, the period 60-90 years of the 20th century. Methods. The quantitative soil status model, used in the study, is a set of probabilistic-statistical distributions of soil properties in soil horizons. Calculations and graphic analysis of information entropy and divergence of soil properties were performed. Results. During the study period there was an increase in central values and a decrease in variability in the silt and physical clay content in the southern chernozems on the territory of the Irtysh plain in the upper 0-20 cm soil layer. The revealed changes occurred due to the restructuring of probability-statistical distributions of these indicators, which consisted in reducing the probabilities of the lower values. Similar trends, albeit less expressed, were also identified in 20-30 and 30-50 cm layers, but deeper in profile they were minimal. Changes in the probability-statistical distributions of silt and physical clay content occurred within the ranges of variation inherent to the studied lithological varieties. Conclusions. To assess the condition and general changes in soils on a territory, it is necessary to use information characteristics. The obtained probabilistic-statistical distributions of silt and physical clay content represent the informational standards for these indicators of the soils of the Irtysh plain. They can be used for comparison with the results of past, current and future monitoring studies of soils in the studied and neighboring territories. The values ​of information entropy and divergence are scalar indicators for characterizing variability and transformations of probability-statistical distributions of soil properties.