河南粮食生产核心区干旱时空演变特征研究

发布时间：2018-12-18 07:43

【摘要】：干旱是自然灾害中影响人类生活最大的自然灾害之一。在全球变暖的大背景下,随着人类生活的提高和经济的发展,水资源短缺问题日益严重,干旱的频发加剧了水资源的短缺。河南省作为中国第一人口大省、农业大省,干旱的发生将直接影响河南省经济的发展、人民生活水平的提高。因此研究河南粮食生产核心区的干旱演变特征对河南省的农业生产具有重要的意义。利用1961-2010年河南省17个气象站逐月降水数据,采用标准化降水指数和降水距平百分率两种干旱因子分别在月尺度、季尺度和年尺度下对河南省干旱情况进行分析,得到了不同时间尺度下不同干旱等级的时间演变特征和空间分布特征。两种干旱因子分析下河南省均呈现干旱化趋势。比较两种不同干旱因子,标准化降水指数比降水距平百分率更适合用来研究河南省的干旱情况。利用17个气象站点的逐月降水数据计算各站点的年SPI值,对时空序列进行数据预处理,得到平稳的时空序列。把时空序列聚成两类,结合传统的空间邻接矩阵,通过对未知线性方程的求解,得到改进的空间权重矩阵。针对不同的空间权重矩阵分别建立STARMA模型。通过2006-2010年的预测结果和原始结果比较可知,改进的STARMA模型比传统的STARMA模型预测性能更好。在以后的干旱研究中,可以通过对SPI时空序列建立改进STARMA模型直接预测SPI指数的变化,根据SPI指数的变化确定干旱的变化情况,为农业生产提供更加精确的指导。
[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.
【学位授予单位】：华北水利水电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S423

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