## 5 Results and Discussions
### Discrepancies in Collected Seismicity Data  
This analysis utilizes earthquake data from the comprehensive KSUSN, SANDSN, and SNSN seismographic networks in Saudi Arabia. The detailed seismic data, is rigorously recorded and processed, proving invaluable for this study. This dataset offers an in-depth view of seismicity in the Red Sea region. The initial stage of the analysis involves a detailed univariate assessment, systematically exploring the distributions of eight key parameters: Year, Month, Day, Hour, Latitude, Longitude, Magnitude, and Depth. This is depicted in Figure 3, which exclusively presents non-duplicated data as reported by each individual seismic network. The analysis offers insights into temporal trends, diurnal patterns, and spatial concentrations of seismic events. These patterns are pivotal for discerning the operational characteristics of each network, understanding data quality issues, such as contamination, and interpreting the underlying tectonic processes in the Red Sea region. We employed Kernel Density Estimations (KDE) to analyze discrepancies in seismic activity parameters among the KSUSN, SANDSN, and SNSN networks, due to KDE's ability to provide a continuous, smooth visualization of data distributions, crucial for handling the variable and irregular nature of seismic activity data. KDE's suitability for comparative analysis is particularly beneficial, as it highlights differences and similarities in seismic recordings across the networks. It also excels in identifying concentrated zones of seismic activity, aiding in the assessment of regional seismic risks. The use of KDE, given its robustness and flexibility, ensures our analysis is not overly influenced by outliers or rigid distributional assumptions, making it an ideal choice for a nuanced understanding of seismic behavior and potential hazards across these diverse seismological networks. For the year-to-year comparisons, the kernel density estimation (KDE) plots reveal distinct periods of increased seismic activity, as indicated by prominent peaks in the data collected by the SANDSN and KSUSN networks. Such temporal clustering could suggest either episodic seismic episodes or an enhancement in the operational capacity and sensitivity of the recording instruments. The monthly seismicity exhibits noticeable trends. A quasi-seasonal cyclicity is apparent in the KDE plots for all networks, with the SANDSN network showing more significant variability. This implies a temporal pattern in seismicity, potentially linked to natural or anthropogenic factors that fluctuate on a monthly basis. Additionally, diurnal patterns have been observed. The data distributions across the days of the month do not show significant peaks, indicating a lack of daily periodicity in seismic events within the observational scope of these networks. Furthermore, the hourly concentration of seismic activity is highlighted. Distinct peaks at specific hours could indicate diurnal rhythms in seismic activity, although these might also result from data logging methods or the operational schedules of the networks. The latitudinal distribution shows acute peaks at certain latitudes in the SANDSN and KSUSN distributions, indicating localized zones of seismic activity and suggesting concentrated stress or fault line activity in these regions, while the SNSN's distribution is more diffuse, pointing to a more heterogeneous distribution of seismicity across latitudes. In terms of longitudinal spread, the SANDSN exhibits a pronounced peak at a particular longitude, indicative of a concentrated longitudinal seismic zone, whereas the SNSN and KSUSN portray a more distributed pattern, reflecting a broader longitudinal range of seismic activity.