磴口县地下水埋深时空变化特征  

Temporal and spatial variation characteristics of groundwater depth in Dengkou County

作　　者：李宁[1] 岳德鹏[1] 于强[1] 张启斌[1] 马欢[1] 

机构地区：[1]北京林业大学林学院精准林业重点实验室,北京100083

出　　处：《南水北调与水利科技》2017年第3期49-54,79,共7页South-to-North Water Transfers and Water Science & Technology

基　　金：国家自然科学基金项目(41371189);"十二五"国家科技支撑计划(2012BAD16B00)~~

摘　　要：选取荒漠绿洲区磴口县1988年-2013年17个观测站逐月水位埋深数据,运用kernel K-means及经验模态分解(EMD)方法,探索26年来研究区地下水埋深时空变化特征。结果表明:17个测站分为三个聚类中心,第一聚类中心包括6个测站,地下水平均埋深最大。第二聚类中心包括4个测站,地下水平均埋深次之。第三聚类中心包括7个测站,地下水平均埋深最小;26年来第一和第二聚类中心地下水埋深呈增大趋势,增大幅度分别为0.014 m、0.26m。第三聚类中心地下水埋深呈减小趋势,减小幅度为0.08m;三个聚类中心地下水埋深年内变化趋势基本相同。This paper selected the monthly observed groundwater depth data during 1988-2013 from 17 monitoring wells at Dengkou County in the desert oasis region, and explored the temporal and spatial variation characteristics of the groundwater depth in study area during the 26 years by using kernel K-means and Empirical Mode Decomposition method. The results indicated the following findings： Firstly, 17 monitoring wells can be divided into 3 clusters. The first cluster contains 6 monitoring wells with the largest average depth of groundwater. The second cluster contains 4 monitoring wells with the second largest average depth of groundwater. The third cluster contains 7 monitoring wells with the smallest average depth of groundwater. Secondly, during the past 26 years, the groundwater depths of the first and second clusters tend to increase, respectively up by 0.014m and 0.26m. The groundwater depth of the third cluster tends to decrease, down by 0.08m. Thirdly, the groundwater depths of the three clusters basically show the same annual variation tendency.

关 键 词：经验模态分解 KERNEL K-MEANS 磴口县 地下水埋深 时空变化 

分 类 号：P642[天文地球—工程地质学]