摘要
以富阳地区为例,采用主成分分析法,寻找出影响水资源自然支持力的主要驱动因子;再根据富阳地区某一时段内的水资源量(因变量)与其驱动力(自变量)之间存在的线性关系,利用统计资料,对可能引起水资源自然支持力变化的各种驱动力因子进行多变量分析。得出,对富阳地区水资源自然支持力影响较大的指标是水资源可利用量、地表水资源量、地下水资源量、水资源的剩余开采程度和化学需氧量。从计算结果可以看出:富阳地区的水资源自然支持力总体来看在逐年减弱,原因在于近年来富阳地区造纸行业异军突起,用水量急剧加大,总污水排放量增多,使得水资源支持力系统变得越来越脆弱。最后,针对目前的水资源现况提出了一些提高富阳地区水资源自然支持力的措施。
With Fuyang Area as a case,the main component-analysis method is adopted to find out the main driving factor that influences the water resources nature supporting-ability by reducing the dimension of the related indexes influencing the water resources nature supporting-ability in the high dimensional variant space in the premise that the data information is the least.Then, based on the linear relationship between the amount of the water resources(following variant)and its driving force(self-reliant variant) during a certain period in Fuyang area,this paper makes use of the statistical documents to establish a multiple linear regression model of the driving factor of the water resources nature supporting-ability indexes that influence greatly changes.h lastly draws the conclusion that the the water resources nature supporting-ability in Fuyang area are the available water resources amount,surface water resources,groundwater resources,remaining exploitation degree of the water resources and the chemical oxygen demanding amount.These indexes constitute the driving factors of the water resources nature supporting-ability.It can be seen from the calculation results that the water resources nature supporting-ability of Fuyang area is on the whole decreasing because in recent years,the paper making industry has developed too rapidly and the water consumption has been increasing sharply with increasing waste water discharge.Finally,some measures which improve nature supporting-ability of water resource in the area of Fuyang according to the present water resource state are put forward.
出处
《自然资源学报》
CSCD
北大核心
2007年第5期800-807,共8页
Journal of Natural Resources
基金
国家"十五"重大科技专项(2002AA601021)。
关键词
水资源
自然支持力
主成分分析法
主要驱动因子
water resources
nature supporting-ability
principal component analysis method
main driving factor