| 引用本文: | 穆玉珠,王燕鹏,张凤华,等.基于非线性多尺度模型的黄河三角洲降水量预测[J].灌溉排水学报,2021,(8):123-128. |
| MU Yuzhu,WANG Yanpeng,ZHANG Fenghua,et al.基于非线性多尺度模型的黄河三角洲降水量预测[J].灌溉排水学报,2021,(8):123-128. |
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| 摘要: |
| 【目的】提高降水量的预测精度，反映降水量的实际特征。【方法】基于经验模态分解对非线性时间序列的分析和处理的优势，对黄河三角洲气象站点1954—2018年连续65 a月均降水量数据进行经验模态分解（Empirical Mode Decomposition, EMD），得到了系列本征模态函数(Intrinsic Mode Function，IMF)，对IMF进行Hilbert变换，在此基础上建立了2种黄河三角洲降水量多尺度预报模型。【结果】黄河三角洲降水量存在着9、13、23、76、135月左右的周期，并以9个月的波动为主；65 a月均降水量数据预测结果显示：模型一的相对误差在0.9%~9.8%之间，模型二的相对误差在1.6%~11.8%之间，在建模时不考虑初相位的模型一平均预测误差为2.70%，整体预测精度要优于考虑初相位的模型二。【结论】2种模型的拟合精度及显著性均符合要求。 |
| 关键词: ：降水量；时间序列；多尺度；EMD；预测 |
| DOI：10.13522/j.cnki.ggps.2021149 |
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| Precipitation Forecast in Yellow River delta Based on Nonlinear Multi-scale Mode |
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MU Yuzhu，WANG Yanpeng，ZHANG Fenghua，QIAO Dongmei
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(1. Henan Xinxiang Hydrology and Water Resources Survey Bureau, Xinxiang 453000, China;
2. Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China
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| Abstract: |
| 【Background】Precipitation is closely related to human production, life and ecology. The change of precipitation is related to the sustainable utilization of regional water resources, the protection of ecological environment and the development of economy and society, The research on the variation characteristics and evolution trend of precipitation has become a hot topic in the field of climate and water resources. Scholars and researchers has paid much attention on the accurate prediction of precipitation. 【Objective】The purpose of this paper is to improve the prediction accuracy of precipitation, and reflect the actual characteristics of precipitation. 【Method】Based on the advantages of empirical mode decomposition in the analysis and processing of nonlinear time series and other fields, Empirical Mode Decomposition (EMD) was carried out for the monthly average precipitation data of the Yellow River Delta Meteorological Station from 1954 to 2018, and a series of eigenmode functions were obtained. Hilbert transform was performed on IMF, and on this basis, two multi-scale forecast models of precipitation in the Yellow River Delta were established. 【Result】The results showed that there were periods of 9, 13, 23, 76 and 135 months in precipitation in the Yellow River Delta, and 9-month fluctuations were the main ones; The 65-year monthly average precipitation data was predicted. The relative error of the model 1 was between 0.9% and 9.8%, and the relative error of the model 2 was between 1.6% and 11.8%. When modeling, the average prediction error of model 1 without considering the initial phase was 2.70%, and the overall prediction accuracy was better than that of model 2 considering the initial phase.【Conclusion】The fitting accuracy and significance of the two models meet the requirements. |
| Key words: precipitation; time series; multiscale; EMD; predict |
