The spatial divergence of climatic changes necessitates the creation of predictive models of the state of vegetation cover. Our proposed solution for the spatial modeling of the biological productivity of natural ecosystems creates the basis for a further quantitative assessment of the potential absorption of CO₂, which is currently considered one of the most urgent environmental issues. In the proposed work, using the methods of geoanalysis of growing conditions, an original technology for modeling the potential spread of biocenoses and their productivity has been developed, reflecting the internal attractor of the development of biocenoses under the influence of local hydrological and climatic conditions of their growth. The methodology was implemented for the southeast of Western Siberia within the framework of publicly available GIS Saga based on a digital terrain model and data from the WorldClim 2.0 climate reanalysis. To forecast data for the period of the third decade of the 21st century, V.V. Paromov’s regional climate forecast was used on the basis of an adaptive model—the exponential smoothing method. The verification of the simulation results was carried out on the basis of the Productivity of Ecosystems of Northern Eurasia database. As a result, spatially distributed data were obtained in the form of rasters with high spatial resolution for the average long-term potential bioproductivity according to reanalysis data for 1970–2000 and predicted data for 2021–2030. Both positive and negative trends of potential bioproductivity for various natural zones of the southeast of Western Siberia due to the spatial divergence of changes in heat and energy resources and precipitation over the territory have been revealed. In general, warming in sufficiently drained areas contributes to an increase in the biological productivity of agro and biocenoses and, in hydromorphic areas, to a decrease.

The scientific novelty of the relevance of this study is caused by the fact that for the effective development and use of space, an integral criterion is needed, calculated on the basis of spatially distributed data, characterizin the local hydrological and climatic conditions of growth, formed under the influence of landscape conditions. The aim of the work is to develop and verify a method for assessing the quality of land based on the results of hydrological and climatic modeling of the stages of humidification by L. G. Ramensky. The lands with moisture scale 55-70 were accepted as the most suitable for agroindustrial use. The studied territory, even within the same agricultural zone, is very heterogeneous, with a mosaic distribution of moisture levels. Unfavorable technological properties of land – high waterlogging, small-contour fields increase the cost of their processing, making agriculture in modern conditions low-profitable. For agricultural zones of the Tomsk region, according to the described method, the calculation of moisture scale was performed. A comparison of the estimates of land suitability based on the results of hydrological and climatic modeling of moisture scale with those previously obtained for agricultural zones of the Tomsk region showed good convergence for 8 zones out of 10. This allows us to consider the calculation of L. G. Ramensky's moisture scale as a working tool for optimizing land management. It should be noted that the use of the SRTM-height matrix, due to its inherent disadvantages, does not allow performing a fully adequate on-farm land assessment. It is necessary to use better digital terrain models. The received assessments of the quality of land resources confirm that high-quality land resources in the Tomsk region are very limited and appropriate efforts should be made to preserve them. In particular, the least productive arable land should be transferred to hayfields, and distant unused agricultural land to forest plantations with valuable tree species.