基于主成分分析的干旱对甘肃省粮食种植的影响探究
首发时间:2018-06-15
摘要:在本篇论文中我们将会对干旱对甘肃省粮食种植的影响进行研究,甘肃省位于黄土高原、青藏高原和内蒙古高原三大高原交汇地带。该省虽然耕地面积较多,但由于降水稀缺,旱灾频繁,粮食产量低而不稳。由此可见,干旱问题已经成为甘肃地区影响粮食产量的主要因素。现如今,如何最小化干旱对粮食产量的影响,利用甘肃山区耕地资源丰富的优势发展现代农业,是当前该地区面临的现实问题。因此,首先本文将利用甘肃地区降水距平百分率标准和西北地区Z指数分级标准来衡量干旱程度,其次利用数据拟合计算干旱周期,预测未来几年的干旱程度,最后利用主成分分析衡量该干旱对于哪一种作物有最大的影响,以此来给甘肃未来几年的粮食耕种策略给出一个合理的建议。在此前提下,经过合理的分析与验证,我们得到以下结论:甘肃地区迎来大程度干旱的周期为七年,受干旱影响程度最大的作物为甜菜,因此,甘肃地区应该以七年为周期,每到七年,减少甜菜的种植,改种其他作物。
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Study on the effects of drought about agriculture in Gansu province based on PCA
Abstract:In this paper, a study on the effects of drought about growing foods in Gansu province will be done. Gansu province is located in the intersection of the three major Highlands which is the Loess Plateau, the Qinghai Tibet Plateau and the Inner Mongolia plateau. Although the province has a large area of arable land, its grain output is low and unstable due to the scarcity of rainfall and frequent drought. This shows that drought has become a major factor affecting grain production in Gansu province. Nowadays, how to minimize the impact of drought on Grain Yield and to develop modern agriculture with the advantage of rich cultivated land in Gansu mountain area is a realistic problem in the region. Therefore, this article will firstly use the precipitation anomaly percentage standard of Gansu region and the Z index grading standard of northwest region to measure drought degree and then use data fitting to calculate the drought cycle and predict the drought degree in the next few years. Finally it will use principal component analysis to measure which crops are affected most by the drought, so as to give a reasonable suggestion to the grain cultivation strategy of Gansu in the next few years.Under this premise, through reasonable analysis and validation, we get the following conclusion:the period of great drought in gansu is seven years, and the crop which is most affected by drought is sugarbeet. Therefore,Gansu should reduce the production of sugar beets and plant other crops every seven years.
Keywords: applied mathematics principal component analysis drought period agriculture
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