China's natural disaster losses reach $30 billion in first nine months of 2026
China's natural disasters caused direct losses of 199.36 billion yuan ($29.9 billion) in the first nine months of 2026, down 8% year-on-year. The Ministry of Emergency Management reported 1,162 deaths or missing persons, a sharp rise from 742 a year earlier, driven by severe typhoons, flooding and l
China recorded 199.36 billion yuan ($29.9 billion) in direct losses from natural disasters in the first nine months of 2026, mainly driven by severe typhoons, flooding and landslides, its Ministry of Emergency Management said on Thursday.
The losses were down 8 per cent from 217.65 billion yuan over the same period last year. The ministry said 562 people had died or remained missing after the catastrophic flash floods in August along the Nepal-Tibet border, holding the casualty toll unchanged from previous official counts.
Southwestern and southern China accounted for the majority of affected populations and fatalities. "Several sudden extreme disasters in southern regions led to a significant increase in deaths and missing persons compared to the five-year-average," the ministry said.
Overall, 1,162 people have died or have been classified as missing from China's natural disasters in the first nine months of the year, up from 742 a year earlier. Eastern coastal provinces suffered the heaviest property destruction and economic losses due to repeated typhoon landfalls.
Geological hazards, which include rain-triggered landslides and mudslides, caused the highest proportion of fatalities and made up 60 per cent of all disaster types, while typhoons caused the largest amount of direct financial damage, the ministry said. More than 5 million people were forced to relocate or seek emergency shelter across the country during the nine-month period.
A total of 26 typhoons formed in the Northwest Pacific and South China Sea through September, with 7 making landfall along China's coastline — both figures exceeding the historical averages for the same time frame.
