基于最优变分模态分解的渭河流域多步径流预报
Multi-step runoff forecast in Weihe River Basin based on optimal variational mode decomposition
邱绪迪 1王坤 1陈飞 2相里宇锡 1王斌1
作者信息
- 1. 西北农林科技大学水利与建筑工程学院,陕西 杨凌 712100
- 2. 武汉大学 水资源工程与调度全国重点实验室,湖北武汉 430072
- 折叠
摘要
针对渭河流域月径流序列的非平稳性日益加剧而难以对其进行精准预测的问题,提出了一种基于最优变分模态分解(OVMD)、随机配置网络(SCN)和递归多步预测策略的月径流序列多步预测模型.首先,利用OVMD将径流数据投影到不同频率的子序列中;然后通过SCN对每个分解部分进行预测,叠加得到单步预测结果;最后通过递归多步预测方法对未来较长时间的径流数据进行预测,得到多步预测结果.选取渭河流域华县水文站和咸阳水文站1970～2019 年的实测月径流时间序列进行实例分析,并与其他常用模型进行对比,选取均方根误差RMSE、平均绝对误差MAE、平均绝对百分比误差MAPE以及纳什效率系数NSE对预测结果进行评价.研究结果表明:在华县水文站和咸阳水文站的单步预测试验中,OVMD-SCN模型的NSE分别达98.15%和98.52%,显著高于其他流行模型;在两个水文站的多步预测试验中,OVMD-SCN的各项评价指标均优于其他流行模型,表明所提方法可以精准预测5 个月后的径流量.研究成果可为渭河流域的月径流精准预测提供技术支持.
Abstract
The non-stationarity of monthly runoff series in Weihe River Basin is increasing and it is difficult to predict accu-rately,a multi-step prediction model of monthly runoff series based on optimal variational mode decomposition(OVMD),sto-chastic configuration networks(SCN)and recursive multi-step prediction strategy was proposed.Firstly,OVMD was used topro-ject the runoff data into subsequences with different frequencies.Then,SCN was used to predict each decomposition part,and the single-step prediction results were obtained by superposition.Finally,the recursive multi-step prediction method was used to predict the runoff data for a long time in the future,and the multi-step prediction results were obtained.The measured monthly runoff time series of Huaxian Hydrological Station and Xianyang Hydrological Station from 1970 to 2019 were selected for case a-nalysis,and we compared the predicted results with other popular models.RMSE,MAE,MAPE and NSE were selected to evaluate the prediction results.The results showed that the NSE of the OVMD-SCN model in the single-step prediction experiments of Huaxian Hydrological Station and Xianyang Hydrological Station reached 98.15%and 98.52%,respectively,which were signifi-cantly higher than other popular models.In the multi-step prediction experiments of two hydrological stations,the evaluation in-dexes of OVMD-SCN were better than other popular models.It showed that the proposed method can accurately predict the runoff in the future 5 months.The research results can provide a new method for monthly runoff prediction in the Weihe River Basin.
关键词
径流预报/最优变分模态分解/随机配置网络/递归多步预测/渭河流域Key words
runoff forecast/optimal variational mode decomposition/randomly configuring network/recursive multi-step pre-diction/Weihe River Basin引用本文复制引用
基金项目
国家自然科学基金项目(51509210)
陕西省重点研发计划项目(2021NY-181)
出版年
2024
国家科技期刊平台
NSTL
万方数据