Disaster risks are increasingly exhibiting complex characteristics of multi-dimensional coupling and dynamic evolution. To better understand the dynamic evolution mechanisms of disaster risks and systematically improve urban risk prevention and control capabilities as well as safety resilience, this study innovatively constructs an event-driven analytical framework for dynamic evolution patterns and mitigation strategies of multidimensional coupled risks. The event logic graph method is first employed to extract the intricately complex associations among multi-dimensional risk factors, including natural, social, infrastructural, and economic aspects. And the N-K model is applied to quantify the intensity of the coupling effects among risk factors. Furthermore, the comprehensive impacts of risk coupling effects and intervention measures are explicitly incorporated into the traditional SIR risk evolution model to creatively depict the dynamic evolution process of multi-dimensional coupled risks. Finally, a simulation analysis is conducted taking urban waterlogging risk as an example. The results demonstrate that: 1) The coupling effect of risks significantly accelerates the speed of risk propagation and expands the scope of its impact during the early stages of disaster evolution. The timing of intervention plays a decisive role in the scale of risk propagation. Earlier interventions lead to more effective risk control. However, in cases of delayed action, implementing high-intensity intervention measures can still rapidly and intensively control risks. 2) Targeted interventions at critical risk factors can curb the propagation of risks to some extent, whereas a hierarchical and differentiated intervention strategy can achieve even more effective risk mitigation. However, such interventive strategies show a threshold effect in terms of their marginal benefits for risk prevention and control. Beyond this threshold, further increases in intervention intensity result in diminishing marginal returns. This study provides some managerial insights for understanding multi-dimensional coupled dynamic evolution mechanisms of complex disaster risks and developing effective measures to enhance urban resilience in risk prevention and control.