摘要
选取9口固体潮观测井的3种典型水位数据,用5种插值方法进行插值分析。结果表明,三次多项式插值法对少量数据缺失的插值效果最佳;线性插值法对趋势变化大、固体潮汐波动被压制水位的插值效果最好;ARMA模型预测法对固体潮显著、趋势变化平缓水位的插值效果最佳;线性插值和ARMA模型预测法对固体潮清晰、短期起伏波动水位的插值效果各有其优势。
Three typical groundwater level data of nine solid tide observation wells are selected and interpolated with five interpolation methods. The results show when the number of missing values is small, the cubic polynomial interpolation is the best. For groundwater level with large trend change, and the solid tide is suppressed, the linear interpolation effect is the best. For groundwater level with obvious solid tidal effect and gentle change, the ARMA model prediction method is better than other methods. For groundwater level with clear solid tide and short-term fluctuation, linear interpolation and ARMA model prediction method have their own advantages.
作者
韩孔艳
崔博闻
孙小入
费伯秀
HAN Kongyan;CUI Bowen;SUN Xiaoru;FEI Boxiu(Beijing Earthquake Agency,28 Suzhou Street,Beijing 100080,China)
出处
《大地测量与地球动力学》
CSCD
北大核心
2023年第3期318-321,共4页
Journal of Geodesy and Geodynamics
基金
北京市地震局科技项目(BJWC-2022015,BJWC-2022014)。
关键词
井水位
固体潮效应
线性插值
ARMA模型
groundwater level
solid tide effect
linear interpolation
ARMA model
