STOCHASTIC MODELING AND FORECASTING OF AGROCLIMATIC RESOURCES WITH ADAPTATION OF AGRICULTURE TO REGIONAL CLIMATE CHANGES IN RUSSIA

V. A. Zhukov and O. A. Svyatkina

An approach to stochastic modeling and forecasting of agroclimatic resources is considered that takes into account regional climate changes. The approach is based on a modified group-analog method using pattern recognition algorithms. It provides a description of the behavior of the climate—crop yield system on an analog territory with the help of Markov chains and extrapolation of the system's characteristics to the territory being studied. To adapt agriculture to expected climate changes, the problem of optimization of the structure of sown areas is proposed in a game formulation that minimizes gross crop losses in future climate conditions.

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