期刊论文

Analyzing the Uncertainty Induced by Methods Used to Calculate the Missing Data in Time Series: A Case Study Based on Meteorological and Hydrological Data in Small Watershed

中文

灌溉排水学报

1672-3317

2019

38

2

84-92

10.13522/j.cnki.ggps.2017.0421

水利部公益性行业科研专项经费项目(201501055) 国家科技支撑计划项目(2014BAD14B02) 河南省重大科技专项项目(161100310600).

本校为第一机构

[目的]对普遍存在的时间序列缺失值进行有效估值,进而改善时间序列数据的质量.[方法]以亚热带典型小流域长期定位观测的气象(最低气温、最高气温、太阳辐射)及水文(降水量、地表径流量)数据为样本并利用计算机模拟的方法,比较了线性内插法、K-最近邻插值法、多项式插值法、样条插值法和核密度估值法5种估值方法的性能差异,分析了不同取样时间步长(日和月)及不同数据缺失量(1％、5％、10％、15％、20％)条件下对缺失值进行估值的不确定性.均方根误差(RMSE)、绝对值平均误差(MAE)和Pearson相关系数(r)3个交叉验证指标用于评估5种估值方法的性能优劣.[结果]①5种方法估值性能较好,Pearson相关系数为...

【Objective】Incomplete data is common in meteorological and hydrological analysis and this paper analyzed uncertainty caused by estimating such missing date using different interpolation methods. 【Method】We take meteorological data, including minimum temperature, maximum temperature, solar radiation; and hydrological data, including rainfall and stream flow, collected from a long-term field experiment in a typical small watershed in a subtropical zone as examples. We developed a computer model to simulate them. The difference between the sim...