Two Decades of Meteorological Risk Early Warning for Geological Disasters in China and New Research Advances

Abstract

China is one of the country’s most severely affected by geo-hazards in the world. China’s geological conditions are complex and diverse, and geo-hazards are widely distributed. Rainfall serves as the primary triggering factor for these disasters. Since the launch of the early warning of geo-hazards based on meteorological factors in 2003, it has played an important supporting role in geo-hazard prevention and reduction. This paper reviews the 20-year development of China’s geo-hazard meteorological risk early warning, highlighting advances in technology, methodology, and disaster prevention effectiveness. It further presents recent progress in machine learning based early warning methods using big data and artificial intelligence. From the model construction process of training sample-set construction, sample learning and training, model parameter optimization, model preservation, warning output, and so on, a method for constructing a regional landslide early-warning model based on machine learning was systematically proposed.