区域用水量驱动因子识别及其预测研究

发布时间：2018-06-24 01:23

本文选题：用水量 + 驱动因子　；参考：《合肥工业大学》2014年硕士论文

【摘要】：水资源是人类社会不可替代的自然和环境资源，是可持续发展的基础条件。经济社会的快速发展和人口的增长，以及水污染问题的日益加重，使水资源短缺成为制约我国经济持续健康快速发展的重要瓶颈。科学、准确地预测用水量，对于国家和地区中长期水资源开发利用总体规划和供水规划等具有重要意义。现阶段国内外通过分析影响用水量的驱动因子从而进行用水量预测的研究相对较少，研究成果相对来说也不太完善。论文根据用水系统的内部结构和特点，研究了定量辨识主要驱动因子及其影响程度的方法，提取影响区域用水量大小的主要驱动因子，在此基础上利用多元线性回归方法对区域用水量进行预测分析。选用山东省为研究对象，对影响山东省生产用水、生活用水和生态用水的驱动因子进行分析识别并据此对三类用水量进行预测，得到如下主要结果：（1）分析了山东省水资源开发利用现状及其存在的问题。对研究区的自然地理和社会经济的基本情况进行分析，结果表明：山东省自然地理条件优越且总体经济实力和社会发展水平均处于全国领先水平。1995~2010年以来，山东省用水量总体呈下降趋势，但是由于山东省本身属于严重缺水地区，加之水资源未能得到合理有效的开发利用，水污染严重以及海水入侵等导致山东省水资源紧缺。该结果可为科学制定水资源开发和管理措施提供依据。（2）研究了三类用水量驱动因子，并提取了主要驱动因子。按用户特性将用水分为生产用水、生活用水和生态环境用水三大类，，对每一类用水，分别结合山东省的自然、经济和社会发展特点分析了其驱动因子构成，并综合利用主成分分析法、灰色关联度分析法和集对分析法，最终选定灌溉用水定额、万元产值用水量、旅游总收入为第一、二、三产业用水量首要驱动因子，选定城市居民消费水平和园林绿地面积为生活和生态用水首要驱动因子。（3）预测并讨论了山东省用水量及其驱动因子变化情况。利用灰色GM(1,1)模型预测至2020年所选取驱动因子的取值，利用多元线性回归模型分别预测了2020年第一、二、三产业用水、城镇生活用水、农村生活用水和生态用水量。计算结果表明：第一产业用水总体呈下降趋势，单位灌溉面积和农作物播种面积的下降是引起到第一产业用水量减少的主要因素；第二产业用水量在万元产值用水量减少的影响下将减少6.11亿m3；第三产业用水量驱动因子在未来将会继续稳步上升，由此导致生产用水中第三产业用水量增加至6.77亿m3；城镇生活用水在城市居民消费水平驱动因子的推动下将继续升高，而在农村，外出务工和高速城镇化引起生活用水量不增反减；城市化还将导致园林绿地面积的增加，继而引起生态用水量增加。
[Abstract]:Water resources are the irreplaceable natural and environmental resources of human society and the basic conditions of sustainable development. With the rapid development of economy and society, the increase of population and the aggravation of water pollution, the shortage of water resources has become an important bottleneck restricting the sustained and healthy rapid development of our economy. Scientific and accurate prediction of water consumption is of great significance to the overall planning of water resources development and utilization and water supply planning in countries and regions. At present, the research on water consumption prediction by analyzing the driving factors affecting water consumption is relatively few, and the research results are not perfect. According to the internal structure and characteristics of the water system, the paper studies the method of quantitatively identifying the main driving factors and their influence degree, and extracts the main driving factors that affect the water consumption of the region. On this basis, the multivariate linear regression method is used to predict the regional water consumption. In this paper, Shandong Province is selected as the research object to analyze and identify the driving factors that affect the production water, domestic water and ecological water use in Shandong Province, and to forecast the three kinds of water consumption. The main results are as follows: (1) the present situation and existing problems of water resources exploitation and utilization in Shandong Province are analyzed. The basic situation of natural geography and social economy in the study area is analyzed. The results show that the natural geography conditions of Shandong Province are superior and the overall economic strength and social development level are both in the leading level of the whole country since 1995 ~ 2010. The water consumption of Shandong Province is on the whole decreasing, but the shortage of water resources in Shandong Province is due to the serious water shortage in Shandong Province, coupled with the lack of reasonable and effective development and utilization of water resources, serious water pollution and seawater invasion. The results can provide a basis for the scientific formulation of water resources development and management measures. (2) three kinds of water consumption driving factors are studied and the main driving factors are extracted. According to the characteristics of the users, the water is divided into three categories: production water, domestic water and ecological environment water. The driving factors of each kind of water are analyzed according to the characteristics of natural, economic and social development in Shandong Province. Finally, by using principal component analysis, grey correlation degree analysis and set pair analysis, the primary driving factors of water consumption in the first, second and third industries are selected, such as irrigation water quota, water consumption of ten thousand yuan output value and total tourism income. The consumption level of urban residents and the area of landscape green space were selected as the main driving factors of water consumption. (3) the changes of water consumption and its driving factors in Shandong Province were predicted and discussed. The grey GM (1K1) model was used to predict the value of the driving factors selected from 2020, and the multivariate linear regression model was used to predict the water consumption of the first, second and third industries, urban domestic water, rural domestic water and ecological water consumption in 2020, respectively. The results show that the water consumption of primary industry is decreasing, and the decrease of irrigation area and crop sowing area is the main factor that causes the decrease of water consumption in primary industry. The water consumption of the secondary industry will be reduced by 611 million m3 under the influence of the decrease of the water consumption in the output value of ten thousand yuan, and the driving factor of the water consumption of the tertiary industry will continue to rise steadily in the future, resulting in the increase of the water consumption of the tertiary industry to 677 million m3 in the production water. Urban domestic water consumption will continue to increase driven by the consumption level of urban residents, while in rural areas, urban water consumption will not increase but decrease due to migrant workers and high-speed urbanization, and urbanization will also lead to an increase in the area of green space. In turn, ecological water consumption increases.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TV213.4

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