Simulation of social resilience affected by extreme events in ancient China

This study identifies historical extreme events and analyzes their impacts on social vulnerability, stability, and resilience in ancient China. We reconstructed extreme event sequences, simulated social resilience response using our proposed Cascade Catastrophe-Resilience Dynamic Model, and discussed interaction of social vulnerability and stability. We found the following conclusions. First, historical extreme events had cyclic and periodic fluctuations, and usually led to cascade disasters. Cascade disasters enhanced risk and greatly reduced societal stability, while three types of disaster chains were observed: climatic extremes (flood/drought)-famines-wars (uprising/invasions)-epidemic plagues; climatic extremes (flood/drought)-famines -migrations; and droughts-locust plagues-famines. A climate extreme-earthquake chain was also recorded although the mechanism remains unknown. Second, extreme events were synchronous with dynastic changes, although strong social resilience enhanced the opportunity for dynastic survival and modified the stochastic magnitude–frequency relationship between extreme events and social vulnerability. The high frequency of extreme events is consistent with high hazard indices, declining population, high levels of social vulnerability, and low levels of social stability and resilience. However, the strong correlation between high levels of social vulnerability and high frequency of extreme events occurred at the end of dynasties but not when dynasties were thriving. Third, quick response to disasters, efficient disaster relief systems, and sufficient food supplies were essential parts of social resilience to disasters. Extreme events play important roles in shaping agricultural production, and thus food supply. Population fluctuation and migration, economic center shifts, and social and economic structure changes contributed to cascade disasters, which often led to societal instability throughout Chinese history.