干旱区生态环境知识资源中心(Arid): 基于多变量时间序列模型的大安市地下水埋深预测

Arid

	基于多变量时间序列模型的大安市地下水埋深预测
其他题名	Groundwater table forecast in Da’an City based on multivariate time series model
	张真真 1; 卞建民 1; 韩宇 1; 张琳 2
来源期刊	干旱地区农业研究
ISSN	1000-7601
出版年	2015
卷号	33 期号:3 页码:211-216
中文摘要	依据大安市2000-2009年的降水、蒸发、地下水开采量和地下水埋深等数据资料,首先利用主成分分析法确定了与地下水埋深相关性较大的影响因素,然后利用多变量时间序列CAR模型建立了大安市地下水埋深预测模型,并对模型进行验证,利用模型预测了地下水埋深。结果表明,农业用水量、降水量和蒸发量与地下水埋深的相关系数分别为:0.56,0.46,-0.13,三者对地下水埋深的贡献率分别为:43.09%,27.45%,21.39%,总贡献率达91.93%,是影响地下水埋深的主要因素。CAR模型预测的承压水埋深和潜水埋深与实际观测值之间的相对误差不超过5%。根据预测方案,当降水量减少10%,蒸发量增加9%,农业用水量增加11%时,承压水埋深将达到8.70 m,潜水埋深将达到4.55 m。干旱时期应适当减少农业开采量,增加地表水灌溉,减小土壤沙漠化发生的可能。
英文摘要	At first, the influencing factors which had greatrelevance with groundwater table were determined by the principal component analysis (PCA) method, then established the groundwater table forecast model by using the multivariate time series CAR model, according to the information as rainfall, evapovation, groundwater exploitation and groundwater tables and so on from 2000 to 2009 in Da’an City. Also the model was validated and applied to forecast the groundwater tables. The result shown that: The correlation coefficients ofagricultural water consumption, precipitation and evaporation with the groundwater table were 0.56, 0.46 and -0.13, respectively. The contributions of the three factors with the groundwater table were 43.09%, 27.45% and 21.39%, respectively. The total contribution rate was 91.93% and they were the major factors affecting the groundwater table. The relative error between forecasting value and measured value for confined and unconfined water tables was less than 5%. According to the forecast scheme, when the rainfall was reduced 10% and evaporation was increased 9%, and the agricultural water consumption was increased 11%, the confined water table will be reached 8.70 m, and the unconfined water table will be reached 4.55 m. So in drought period, the agricultural exploitation should be reduced properly, the surface water irrigation should be increased, to reduce the possibility of soil desertification.
中文关键词	地下水埋深 ; 主成分分析 ; 多变量时间序列模型 ; 预测
英文关键词	groundwater table principal component analysis (PCA) multivariate time series model forecasting
语种	中文
国家	中国
收录类别	CSCD
WOS类目	ENGINEERING MULTIDISCIPLINARY
WOS研究方向	Engineering
CSCD记录号	CSCD:5486136
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/232614
作者单位	1.吉林大学环境与资源学院, 长春, 吉林 130021, 中国; 2.北京中环国宏环境资源科技有限公司, 北京 100107, 中国
推荐引用方式 GB/T 7714	张真真,卞建民,韩宇,等. 基于多变量时间序列模型的大安市地下水埋深预测[J],2015,33(3):211-216.
APA	张真真,卞建民,韩宇,&张琳.(2015).基于多变量时间序列模型的大安市地下水埋深预测.干旱地区农业研究,33(3),211-216.
MLA	张真真,et al."基于多变量时间序列模型的大安市地下水埋深预测".干旱地区农业研究 33.3(2015):211-216.