Research on cross-domain aggregation and sharing technology for massive and high-frequency rainfall monitoring data of geological disasters

Efficiently aggregating multi-industry and multi-source rainfall monitoring data into the provincial meteorological data environment of Sichuan serves as a beneficial supplement and extension to meteorological monitoring, providing enhanced safeguards for meteorological warning and forecasting, as well as disaster prevention and mitigation. Based on a messaging mechanism and a meteorological big data cloud platform, a technical solution for cross-domain aggregation and sharing of massive and high-frequency rainfall monitoring data for geological disasters is proposed, aiming to achieve secondlevel real-time and efficient aggregation and sharing of tens of thousands of rainfall monitoring data points in Sichuan Province. The entire data flow is divided into four stages: cross-domain data aggregation, data processing, distributed data storage, and multi-threaded data ingestion, each with corresponding technical solutions. Taking the data from 16,000 geological disaster rainfall monitoring stations in Sichuan Province as an example for analysis and application. The results demonstrate that the proposed solution is highly feasible and practical, having been stably operational for over a year, providing real-time rainfall monitoring data services from non-meteorological industries to meteorological users in Sichuan Province, and offering robust big data support for meteorological forecasting and disaster prevention and mitigation.