The 24th IAHR-APD Congress (24th IAHR-APD Congress)

The analysis of evacuation patterns for populations at risk in the event of dam failure is crucial for enhancing emergency response systems and reducing potential loss of life. Because of the complexity of the problem and the lack of historical data, the existing evaluation models do not make a comprehensive study on the horizontal evacuation or vertical evacuation in dam-break flood affected areas. This paper introduced a method based on the "Extreme Evacuation State Hypothesis" and the Bass Diffusion Model (BASS model) to calculate the ratios of horizontal and vertical evacuations for populations in dam-break affected areas. The proposed method determines the appropriate evacuation mode by comparing the time taken for dam-break flood progression to pose a threat to human safety (evolution time) with the time people receive warning information (warning transmission time). The evolution time is computed through dam-break flood progression, while the warning transmission time is relatively complex, and is the focus of this paper. This paper refined the original BASS model's information contagion patterns and introduced adjust coefficients for daytime and nighttime information propagation. The resulting model is applicable to calculating warning transmission times for dam-break disasters, which in turn can be used to calculate the ratio of horizontally evacuated and vertically evacuated populations. Finally, a case study was presented to illustrate the application of the proposed model. The study analyzed the effects of the Zipingpu Hydropower Station dam failure on the population of Chengdu Plain. It examined the proportion of people evacuated horizontally and vertically at various locations and provided recommendations to minimize potential loss of life. The model, utilizing readily available time data, enables the rapid calculation of evacuation ratios after dam-bread disaster, so as to prompt strategies of emergency response and support  more detailed calculations of potential life loss in dam-break scenarios.