Given the inherent uncertainties in the design of nuclear power plants (NPPs), it is essential to incorporate an appro priate safety margin. The Risk-Informed Safety Margin Characterization (RISMC) method integrates both deterministic and probabilistic approaches to identify typical sequences through dynamic characteristic analysis. Key dynamic parameters are determined based on a combination of probabilistic safety analysis, deterministic safety analysis, engineering judgment, and an evaluation of the design characteristics of nuclear power plants, with their uncertainty distributions calculated to support the RISMC coupling model. Utilizing the HPR1000 NPP as a case study, this paper examines and identifies typical sequences that exhibit a higher risk of Small Loss of Coolant Accidents (SLOCA). These sequences are analyzed to ascertain the key dynamic parameters within the RISMC analysis method. The findings provide a reference for determining essential dynamic parameters in future applications of the RISMC method.