Моделирование как прогноз трансформации почв при техногенном засолении

Abstract

The problem of soil salinization is relevant not only for agricultural areas but also for mining, where brines enter the surface as formation water or runoff from sludge storage facilities and salt dumps of mining enterprises. Currently, there is little elaboration of assessment and lack of normative support (MPC, APC) for assessment of technogenic salinisation of soils. The aim of this research is to develop a mathematical model for predicting the transformation of soils affected by technogenic salinization. The research focuses on soils in three types of landscapes, namely eluvial, transitional, and alluvial, located in the area of technogenic salinization. To develop the model, information-logical analysis and soil indicators were employed. These indicators were determined by standard methods. According to the information-logical analysis the sodium adsorption coefficient is the dominant factor of soils’ salinity; descending further: calcium ion content, sulfates content in the soil water extract and the calculated indicators (∆pH and pH) of the salt extract. The model showed that the highest amount of toxic salts is observed when pHKCl ranges from 5.3 to 7.4, sulfate content is above 500 mg/kg, calcium content is above 1000 mg/kg, SAR is above 10, and ∆pH is below 0.5. These indicator values correspond to alluvial soils found in small river valleys; these soils are highly prone to transformation. Using the obtained information-logical model and soil indicators, it is possible to make a forecast of soil transformation under technogenic salinization.