Flash floods induced by heavy rainfall occur frequently in China, which cause severe damages or even casualties every year. Flash floods generally occur in small catchments, and therefore were poorly documented. A Database including 963 flash flood events in China is compiled and studied in this study. Analytical results (a) indicate flash flood condition in China; (b) shed light on the spatial-temporal distribution of flash flood under heavy rainfall and (c) detect the characteristics of the 2016 flash flood. In 2016, the deaths due to flash floods were severe and concentrated, accounting for about half of the elderly and children. Hebei and Fujian provinces were most affected by flash floods. The disasters mainly occurred in July and the major types were river floods. Despite the frequent torrential rains, inadequate monitoring and early warning systems made the flash flooding condition even worse in 2016.

An early warning of a flash flood is essential to prevent the general public from the hazardous flooding events, however, the rapid variation of human activities has led to the uncertainty of risk in prone areas. The lack of a systematic record of flash flood events introduces challenges to flash flood-related research. Herein, we map spatial and temporal variations in flash floods in China from 1950 to 2015 and establish a general ordered logit model in a geographic information environment to estimate the association between the occurrence of flash flood events and natural conditions and the variation of human activities at the watershed level. The results showed that precipitation is an important cause of flash flooding, and demonstrate that anthropogenic intervention (heavy rainfall, density of villages, and vegetation cover) in the environment affect the likelihood of flash floods. We found that the likelihood of flash floods in China may increase with the air quality worsening and that the occurrence of flash floods is strongly correlated with vegetation cover. Our findings suggest a need for further investigation of the link between air quality and flash flooding in flood-prone areas.

In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689–1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production.

With changing climate, coastal areas are facing increasingly threats from the typhoon–rainstorm–storm surge-flood (TRSSF) chain. However, among various exposures of the TRSSF chain, it is still a great challenge to quickly assess the direct losses of houses, due to the complex mechanisms underlying building damage. The objective of this article is therefore to explore a simple method of quickly assessing the house losses caused by the TRSSF chain, based on a small amount of data. To achieve this goal, a method of multi factors regression and a spatial information network were proposed. The results in Haikou City show that the loss rate of house assets is significantly lower than that of indoor property. Spatially, the areas with higher loss rates are generally distributed along the Nandu River. The direct economic losses associated with houses in the return periods of 10, 20, 50, and 100 years range from 1.3 to 2 billion RMB. Our findings highlight the significance and possibility of quickly assessing the direct house losses caused by TRSSF chain using a small amount of data. It indicates that the house losses are not only determined by TRSSF intensity, but also closely related to socio-economic, topography and house location.