## 5 Conclusions  
We conducted an analysis of the tectonic background and structural characteristics pertaining to the Maqin-Maqu segment within the East Kunlun Fault Zone. The segment was divided into two seismogenic structures, and an evaluation was performed to determine the potential maximum magnitude of earthquakes that these structures could trigger. Additionally, a recurrence probability model for the region was established by collecting and organizing paleoseismic data from the northeastern part of the northeastern Tibetan Plateau. Subsequently, the model was employed to assess the seismic hazard associated with the Maqin-Maqu segment of the East Kunlun Fault Zone over the next century. The acquired insights and prevailing issues can be summarized as follows:  
(1) The calculated recurrence probability values for strong earthquakes in the Maqin-Maqu segment of the Eastern Kunlun fault zone reveal distinct patterns. Over the next 100 years, the Maqu segment presents an intermediate probability of 11.47%, whereas the Maqin segments exhibit values below 10%, signifying events of low probability. Although current research results indicate that the Maqin segment exhibits stronger tectonic activity compared to the Maqu segment, such as a decreasing trend in the sliding rate of the East Kunlun Fault from west to east, the seismic hazard in the next century is closely associated with the time since the last earthquake. The Maqu segment has an elapsed time of around 1200 years, signifying a seismic gap on the East Kunlun Fault throughout the last millennium. Furthermore, it has experienced Coulomb stress loading since the occurrence of the 2008 Wenchuan earthquake. Consequently, there is a critical need to concentrate on monitoring and mitigating the seismic hazard in the Maqu segment. (2) The sensitivity of conditional probability P, calculated from the strong earthquake recurrence probability model to the prediction time period \(\Delta\)t, is intricately linked with the length of the recurrence cycle R. In general, as R increases, the probability value P experiences a gradual rise with the expanding prediction time interval \(\Delta\)t. However, when R is exceedingly large and \(\Delta\)t is very small, the prediction outcome may be relatively imprecise, underscoring a limitation of the recurrence model in earthquake prediction. The recurrence intervals for different segments in the east segment of the Eastern Kunlun fault zone all hover around one thousand years. While the calculated conditional probabilities are generally modest, they still offer valuable insights into the seismic activity levels of these three segments for several centuries into the future. (3) We utilized quantitative data on ancient earthquakes pertaining to 22 fault zones in the northeast Tibetan Plateau and subjected it to a normalization process to construct a recurrence probability model for strong earthquakes. A comparative analysis of probability values calculated using the model proposed in our paper and the prevailing universal seismic model reveals that, when the independent variable of the universal model (\(t/R\)) approximates 1, the amplitude for the growth of the calculated recurrence probability value (P) is less sensitive compared to the fitting model in this paper. Consequently, for fault zones with a substantial body of studies providing data on ancient earthquakes, it is arguably \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name of Segment** & **Maqin–Maqu Segment of the Eastern Kunlun Fault** \\ \hline \multirow{2}{*}{Future time interval/a} & 2023–2043 & 2023–2073 & 2023–2123 \\  & (\(\Delta\)t = 20) & (\(\Delta\)t = 50) & (\(\Delta\)t = 100) \\ \hline \multirow{2}{*}{Joint probability} & \multirow{2}{*}{3.24\%} & \multirow{2}{*}{8.11\%} & \multirow{2}{*}{16.14\%} \\  & & & \\ \end{tabular}
\end{table} 
Table 3: Joint probability for the occurrence of at least one large earthquake in Maqin-Tazang segment of the Eastern Kunlun fault zone during the future 20 years, 50 years, and 100 years (calculated from 2023).