Research on the analysis of Yellow River water and sand monitoring data based on ARIMA model

Abstract

The article uses hydrological data from a hydropothe paperr station in Xiaolangdi Reservoir spanning six years. the paper use mutability analysis, seasonal decomposition method, and ARIMA model to reveal hydrological change trends and cyclic characteristics. the paper also use the CUSUM algorithm to identify the water-sand flux mutation points. The study's findings demonstrate that ARIMA(1,2,1) can be used to predict trends in total water flux and total sand content. It also reveals that there is significant seasonality and periodicity in the water-sand fluxes. These results offer a solid scientific foundation for decision-making and have substantial implications for the management and control of the region's water resources.