In order to explore the influencing factors of urban residents' water consumption in Ningxia, eight influencing factors are selected, and the model of 2009-2016 data is used to establish the model. The principal component analysis method is used to analyze the factors affecting the domestic water demand of urban residents in Ningxia and Ningxia. Specifically, the following conclusions are drawn: From the perspective of Ningxia, shower water heaters, population, and per capita disposable income have a significant impact on the domestic water consumption of urban residents in Ningxia. That is, household indicators> urbanization level> economic indicators. The main influencing factors of urban residents' water consumption demand in Wuzhong City are: water price, per capita disposable income and per capita housing area.The influencing factors in Guyuan City are: per capita disposable income, domestic water withdrawal, and water price. The influencing factors of Shizuishan City are: per capita disposable income, domestic water withdrawal, and shower water heaters. The influencing factors of Zhongwei City are: per capita disposable income, per capita housing area, and washing machine. The main influencing factors of domestic water consumption demand of residents in Yinchuan City are per capita disposable income, population, washing machine and shower.
Key words
domestic water consumption /
influencing factors /
principal component analysis /
SPSS software
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References
[1]Schefter J E, David E L. Estimating residential water demand under multi-part tariffs using aggregate data[J]. Land Economics, 1985,61(3):272-280.
[2]王亚丽,冯利华,赵丹丹,等.金华市区居民用水量影响因素的关联分析[J].水资源与水工程学报, 2011,22(3):51-54.
[3]吕王勇,赵凌,陈东.基于主成分分析的四川省用水量预测[J].水资源与水工程学报,2009,20(6):84-87.
[4]周戎星,潘争伟,吴成国,等.山东省用水量变化趋势分析及驱动因子分析[J].环境工程,2016,34(增1):837-840.
[5]赵丽蓉,伍靖伟,杨霄,等.应用方差分析方法研究内蒙古河套灌区用水量影响因素[J].节水灌溉, 2009(7):1-3.
[6]陈慧.基于聚类分析的山西用水量分区研究[J].山西水利,2014,30(11):10-11.
[7]刘呈玲,方红远.基于时差相关分析与回归模型的用水总量预测[J].节水灌溉, 2017(10):70-73,83.
[8]王鹏,况福民,邓育武,等.基于主成分分析的衡阳市土地生态安全评价[J].经济地理,2015,35(1):168-172.
[9] 田韶英,李晓春,杨宝中,等.西安市城镇居民生活用水量需求影响因素分析[J].中国农村水利水电, 2014(2):35-38.
[10] 孙红,韩晶,张雪.城市居民生活用水量影响因素分析与评价[J].科技创新导报,2012(14):254,256
[11] 李高伟,韩美,刘莉,等.基于主成分分析的郑州市水资源承载力评价[J].地域研究与开发, 2014,33(3):139-142.
[12] 金巍,章恒全,张洪波,等.城镇化进程中人口结构变动对用水量的影响[J].资源科学, 2018,40(4):784-796.
[13] 杜军,宁凌,胡彩霞.基于主成分分析法的我国海洋战略性新兴产业选择的实证研究[J].生态经济, 2014,30(4):103-109.
Funding
National Natural Science Foundation;Ningxia Natural Science Foundation
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