基于时间序列模型的黄河水沙监测数据分析研究  

Research on the Analysis of Yellow River Water and Sediment Monitoring Data Based on Time Series Model

作　　者：李长生 刘素军 刘宗成 刘晓龙 LI Changsheng;LIU Sujun;LIU Zongcheng;LIU Xiaolong(Lanzhou Petrochemical University of Vocational Technology,Lanzhou 730060,China)

机构地区：[1]兰州石化职业技术大学,甘肃兰州730060

出　　处：《现代信息科技》2024年第20期159-163,168,共6页Modern Information Technology

基　　金：兰州石化职业技术大学科研项目(KY2023-28);兰州石化职业技术大学科研项目(KY2023-30)。

摘　　要：黄河水沙通量的变化规律对沿黄流域的环境治理、气候变化和人民生活具有深远的影响。文章以黄河某水文站2016—2021年的水位、水流量与含沙量的实际监测数据为研究对象,对该水文站水沙通量的变化规律进行挖掘和分析;以此应用机器学习中的时间序列分析算法构建了一种可对黄河水沙通量趋势预测的时间序列模型SARIMAX,通过对模型的参数优化和显著性检验分析,确定了黄河水沙通量预测的最优时间序列模型SARIMAX(0,1,1,12),对该水文站未来两年的黄河水沙通量进行了分析预测,为黄河水文环境的保护和黄河水域“调水调沙”等工作提供准确的参考依据。The variation law of water and sediment flux in the Yellow River has a profound impact on environmental governance,climate change,and people's lives along the Yellow River basin.This paper takes the actual monitoring data of water level,water flow rate,and sediment concentration at a hydrological station on the Yellow River from 2016 to 2021 as the research object,and explores and analyzes the variation law in water and sediment flux at the hydrological station.A Time Series Analysis algorithm in Machine Learning is applied to construct a Time Series Model SARIMAX that can predict the trend of Yellow River water and sediment flux.Through parameter optimization and significance testing analysis of the model,the optimal Time Series Model SARIMAX(0,1,1,12)for predicting Yellow River water and sediment flux is determined.The Yellow River water and sediment flux of the hydrological station in the next two years is analyzed and predicted,providing accurate reference for the protection of the Yellow River hydrological environment and the work of“water and sediment transfer”in the Yellow River water area.

关 键 词：时间序列模型 ARIMA 水沙通量 机器学习 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]