Time Series Data Cleaning and Early Warning of River Basin Water Quality

Abstract

In order to effectively control the safety of water environment and promote the continuous improvement of water environment quality, all national environmental monitoring stations in the basin should conduct intensive monitoring of water quality, so that the environmental protection department can timely understand the water quality dynamics and make decisions on early warning and water quality analysis. How to monitor and warn watershed water quality data has become one of the current research hotspots. However, most water quality sensors often suffer from daily maintenance difficulties, database input errors and sensor measurement errors. Therefore, this paper analyzed the framework and process of data cleaning of time series, then optimized and analyzed the early warning model, and finally analyzed the early warning effect through abnormal early warning algorithm. The water quality warning effect after data cleaning was 15.6% higher than that before data cleaning, and the indicator detection effect was 11.2% higher than that before data cleaning. In short, data cleaning of time series and early warning model can improve water quality.