Spatial And Temporal Evolution Of Drought In Core Area Of Grain Production In Henan Province

Drought is one of the greatest natural disasters in natural disasters that affect human life.Under the background of global warming,with the improvement of human life and economic development,the problem of water shortage is becoming more and more serious.The frequent drought has aggravated the shortage of water resources.Henan Province,as the largest population and agricultural province in China,the occurrence of drought will directly affect the development of the national economy,people's living standards.Therefore,it is of great significance to study the drought evolution characteristics of the core area of grain production in Henan province.Based on the monthly precipitation data of 17 meteorological stations in Henan Province from 1961 to 2010,using standardized precipitation index and the precipitation anomaly of two drought factor respectively in monthly scale,seasonal scale and annual scale in Henan Province under the drought characteristics,obtained under different time scales of different drought time evolution characteristics and spatial distribution.Under the analysis of two kinds of drought factors,the drought trend in Henan Province.Comparing two different drought factors,the standardized precipitation index is more suitable for studying the drought situation in Henan Province than the percentage of precipitation anomaly.The annual SPI values of each site are calculated using the monthly precipitation data of 17 meteorological stations.The temporal and spatial sequences are preprocessed to obtain a stable temporal and then the temporal and spatial sequences are clustered into two categories.Combining with the traditional spatial adjacency matrix,an improved spatial weight matrix is obtained by solving the unknown linear equations.With different spatial weight matrix the STARMA model is established.By comparing the predicted results with the original 2006-2010,the improved STARMA model is better than the traditional STARMA model.In the later drought studies,the improved STARMA model can be used to directly predict the changes in the SPI index and provide a more accurate guidance for agricultural production.