Design of Reservoir Safety Early Warning System Based on Big Data

In order to realize the timeliness and accuracy of monitoring and early warning of reservoir hydrological information, and to fully protect the safety of people’s lives and property downstream, a reservoir safety early warning system based on meteorological big data is researched and designed. Use a certain web crawler tool to crawl the meteorological data of a certain reservoir, clean and normalize the data and store it in the database, use the web crawler technology to analyze the crawled data, and measure and control the current real-time hydrological data of the reservoir combined with the Internet of Things. Through the big data Spark parallel framework and GBDT algorithm, the change trend and main causes of meteorological rainfall and the storage capacity of a certain reservoir are analyzed, and the future development of the storage capacity of the reservoir is predicted and early warning according to the current environmental parameters. The application development shows that the use of big data algorithm technology to predict the future of the reservoir once an emergency occurs, the system can automatically alarm and notify the management personnel, which makes the reservoir dam safe and efficient before the problem occurs.