Open AccessComputer prediction of the spatial distribution of the Cs-137 concentration in soil
Author(s) -
P. K. Shalkevich
Publication year - 2021
Publication title -
doklady nacionalʹnoj akademii nauk belarusi
Language(s) - English
Resource type - Journals
eISSN - 2524-2431
pISSN - 1561-8323
DOI - 10.29235/1561-8323-2021-65-2-139-145
Subject(s) - software , environmental science , radionuclide , soil science , spatial distribution , spatial analysis , biosphere , field (mathematics) , computer science , remote sensing , mathematics , geology , nuclear physics , ecology , physics , pure mathematics , biology , programming language
Computer prediction of the migration of radioactive contaminants in soil is a promising scientific direction due to the fact that prediction of the radiation situation on the basis of experimental measurements of radionuclides activity requires the use of mathematical and computer methods of data processing. At the same time, most of the specialized software packages for predicting the spread of radioactive contaminants in soil are based on one- and two-dimensional idealizations of this process, while solving the problem of comprehensive assessment of the biosphere’s state requires the data of the contaminant’s spatial distribution. To obtain such data, the author has developed a software module as a part of SPS (Simulation of Processes in Soil) v2.0 software package, which allows predicting the parameters of the spatial migration of radionuclides in natural dispersed media. To assess the possibility of using the developed software in practice, the prediction results were verified by the experimental data. For this purpose, the spatial distribution of the Cs-137 concentration in the experimental area in the Luninets district of the Brest region was predicted using the measurement data of the Cs-137 activities and the soil characteristics. The comparison of the results obtained on the basis of experimental measurements and the predicted values of the spatial distribution of the Cs-137 concentration showed that the predicted values are within the confidence intervals of the measured values. Consequently, the developed software can be used to solve practical problems in the field of forecasting the migration of radionuclides with obtaining a reliable picture of their distribution over the volume of the modeling area and to comprehensively assess their impact on the environment.