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
Key words
Time Series Model/ARIMA/water and sediment flux/Machine Learning
维普
万方数据