基于地统计学——克里格插值法的村镇地表水体水质监测  

Surface water quality monitoring in town based on Geotatistics-Kriging interpolation

作　　者：施周[1,2] 闫杭召 毕晨[1,2] 邓林[1,2] 

机构地区：[1]湖南大学土木工程学院,长沙410082 [2]湖南大学建筑安全与节能教育部重点实验室,长沙410082

出　　处：《环境工程学报》2017年第4期2607-2613,共7页Chinese Journal of Environmental Engineering

基　　金：国家科技支撑计划资助项目(2012BAJ24B03)

摘　　要：采用普通克里格、以溶解氧为辅助变量的协同克里格、以UV254为辅助变量的协同克里格、回归克里格和与BP神经网络相结合的克里格等5种插值方法,对湖南省乔口镇典型地表水体新河中的COD进行空间分布预测。结果表明,新河中COD具有强烈的空间自相关性,半方差函数拟合程度较高,为克里格插值提供了良好的理论基础。5种插值方法预测结果符合污染源分布的现场勘查情况,较好地反映了水体中COD的空间分布规律。插值精度表现为以UV_(254)为辅助变量的协同克里格法最佳,并且随着插值点数量的下降,各种插值方法的精度整体呈下降趋势。Five interpolation methods—ordinary kriging（ OK）,co-kriging with the auxiliary variable of dissolved oxygen（ CK-DO）,co-kriging with the auxiliary variable of UV254（ CK-UV254）,regression kriging（ RK）,and ordinary kriging combined with BP neural network（ BP-OK）-were applied to predict the spatial distribution patterns of COD in the surface water of Xinhe Lake in Qiaokou Town,Hunan Province. The results show that the COD concentration in Xinhe Lake has a strong space autocorrelation and the semivariance models fit well,which provides a good theoretical basis for the kriging interpolation. Moreover,results of the five interpolation methods are in agreement with the local investigation of pollution sources and can reflect the spatial distribution of COD in Xinhe Lake. CK-UV254 is the most accurate method,and the accuracy of each interpolation method shows a declining trend with the decrease in interpolation points.

关 键 词：村镇 地表水体 COD 半方差分析 克里格插值 

分 类 号：X832[环境科学与工程—环境工程]