Abstract:

In order to satisfy the refined service requirements of modern agriculture, this study established a snow disaster warning system of solar greenhouses, which could guide farmers to take effective measures to reduce or avoid economic losses that caused by snow disasters. The extreme probability distribution model was used to analyze the maximum snow depth data of 13 counties in Hehuang Valley of Qinghai Province from 1978 to 2021, and calculated the maximum snow pressure of the solar greenhouse with 30°, 35°and 40° slope angles during the 30-year return period, and then the snow disaster critical index of the solar greenhouse was obtained. It was selected the actual snow disaster data, the snow depth data of solar greenhouse, and the loss rate caused by the snow disaster year as a factor in Hehuang Valley from 1985 to 2021 based on the previous foundation. According to the method of calculating the standardized precipitation index to the proportion of different levels disasters in the total disaster, the threshold values of different levels of snow disasters of solar greenhouse were determined, and then the snow disaster warning indicator system was established based on the solar greenhouse loss rate according to the relationship between snow depth and greenhouse loss rate. It was classified the warning levels of solar greenhouse snow disasters into three levels: mild, moderate, and severe. This new method puts forward new ideas for the division of snow disaster indicators in solar greenhouses. It is not only simple, but also has regional universality and is convenient for meteorological service business applications.

Key words: modern agriculture, refined service, solar greenhouse, snow disaster, loss rate, early warning level, extreme probability distribution model, standardized precipitation index