According to the China Meteorological Administration, the bureau recently officially launched the construction of the "Agricultural Meteorological Disaster Risk Warning Project for the Whole Chain of Major Grain Crops" (hereinafter referred to as the "Project"), aiming to build a full-growth disaster warning system covering staple grain crops such as winter wheat, summer corn, and spring corn through digital and intelligent means, and build a solid line of defense for food production safety.

He Liang, deputy director of the Ecological and Agricultural Meteorological Office of the National Meteorological Center, said that the project plans to complete construction and put into operation by the end of 2025. By then, the coverage rate of meteorological disaster warnings for major grain crops in my country will reach more than 95%, injecting stronger meteorological momentum into stabilizing the "China's rice bowl".

The project focuses on the weak links in the disaster risk warning chain, integrates satellite remote sensing, machine learning and meteorological big data technology, and builds a disaster risk warning system that is linked to the state and the province. After the project is completed, it can use wind and cloud satellite data and 1 kilometer high-resolution meteorological real-time and prediction results to dynamically extract crop planting distribution status, timely track the risk status of more than 10 types of disasters such as drought in winter wheat and high temperature and heat damage in summer corn, and extend the disaster risk warning time to 30 days, accurately predict "where is the disaster, how big the degree, how long the impact will take", and realize the transformation from "disaster response" to "risk prediction".

In order to solve the problem of agricultural meteorological services' benefits assessment, the project will pilot the deployment of 177 sets of intelligent monitoring equipment in four provinces including Hebei and Anhui, carry out field tests, and quantify the "disaster reduction accounts" of meteorological services. By comparing the crop yields, irrigation water and other data of experimental fields and conventional fields, we can quantify and analyze the disaster reduction benefits of meteorological early warning in the entire chain of "cultivation management, storage and storage". The experiment will form standardized evaluation specifications to provide a scientific basis for optimizing meteorological service models.

The project will also upgrade the intelligent water-saving irrigation system, which can provide soil moisture monitoring and intelligent meteorological water-saving irrigation services covering the whole country, expand the categories of soil moisture monitoring products, and carry out soil moisture monitoring product inspection.

The meteorological department will work with the agricultural and rural departments to promote the deep integration and collaborative innovation of disaster warning and agricultural production, and provide data support for accurate pricing of agricultural insurance and high-standard farmland construction planning by sharing county-level output databases and disaster loss assessment models.