河南糧食生產(chǎn)核心區(qū)干旱時(shí)空演變特征研究
[Abstract]:Drought is one of the most important natural disasters in natural disasters. Under the background of global warming, with the improvement of human life and the development of economy, the shortage of water resources is becoming more and more serious, and the frequent occurrence of drought exacerbates the shortage of water resources. As the largest province with large population and big agriculture in China, the occurrence of drought will directly affect the economic development of Henan Province and the improvement of people's living standard. Therefore, it is of great significance to study the characteristics of drought evolution in 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, the drought conditions of Henan Province were analyzed on monthly scale, seasonal scale and annual scale by using standardized precipitation index and precipitation anomaly percentage. The characteristics of temporal evolution and spatial distribution of different drought grades at different time scales are obtained. Under the analysis of two kinds of drought factors, Henan Province showed a trend of drought. Compared with two different drought factors, the standardized precipitation index is more suitable than the precipitation anomaly percentage to study the drought situation in Henan Province. Based on the monthly precipitation data of 17 meteorological stations, the annual SPI values of each station are calculated, and the spatio-temporal series are preprocessed to obtain a stable spatio-temporal sequence. The space-time sequence is grouped into two classes, and the improved spatial weight matrix is obtained by solving the unknown linear equation by combining the traditional spatial adjacent matrix. STARMA models are established for different spatial weight matrices. Compared with the original results from 2006 to 2010, the improved STARMA model has better prediction performance than the traditional STARMA model. In the later drought research, we can directly predict the change of SPI index by establishing an improved STARMA model for SPI spatiotemporal series, and determine the drought change according to the change of SPI index, and provide more accurate guidance for agricultural production.
【學(xué)位授予單位】:華北水利水電大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:S423
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