No abstract

The paper presents an algorithm for modeling the production of agricultural products in the formation of agrometeorological events. Stochastic models of variability of downpours, early snow-fall and crop yields are constructed to assess the likelihood of extreme events. Based on a probabilistic assessment of crop bio-productivity by a normative method, economic losses from agrometeorological events are determined. A model for optimizing crop production taking into account natural risks was built and implemented for an agricultural organization. The results were obtained according to data of the Irkutsk district.

In the article, based on statistics on emergency outages in the Levoberezhniy and Pravoberezhniy districts of Irkutsk and the sums of average daily temperatures in years 2010-2017 regression models are built. As an auxiliary factor for the models built on values that were grouped by year, the seasonality index was calculated using the “Kassandra” model. In the model, built for values that were grouped by month, a trend was added in addition to the seasonal component. A retrospective prediction of emergency outages based on the data of the Levoberezhniy district, gathered in April 2020 showed that a model with a trend and a seasonal component gives a more accurate prediction. Since the sum of the average daily temperatures can be considered a random variable, the proposed factor models can be used to predict emergency outages only with some probability. The solution of inverse problems, when the factor value is determined for a given number of emergency outages, can be used to assess the risks associated with the influence of low and high temperatures on the objects of the electric grid complex.

The article presents the results of assessing the variability of extreme events, which include droughts and rainfall. The statistical properties of long-term series of maximum daily precipitation and yield of grain crops are determined. It is shown that the maximum daily precipitation affecting water erosion can be described by the Pearson type III distribution law, and the soil erosion potential by the truncated gamma distribution. Examples of risk assessment as a result of water erosion affecting the productivity of agricultural crops are given. The methodology of calculating damages and insurance compensation from drought effects is considered. Groups of models that make it possible to assess the variability in yields of cereals are selected. In some cases, it is possible to use regression models of the relationship of the effective trait with factors, time and previous values, and in others, the probability distribution laws with and without autocorrelation constraints. The example of a combination of extreme events in one year-a drought and a shower is given. To plan the production of agrarian products, we propose extreme tasks for one unfavorable climatic event and a combination of two events. The resulted models are realized for the agricultural enterprise of Irkutsk district. The proposed algorithms and models allow solving the problems of choosing the most acceptable control option in the conditions of drought and rainfall manifestations.