## 1 Introduction
Understanding the patterns, predicting future occurrences, and mitigating the impacts of natural and man-made (technological) disasters hinge significantly on temporal analysis. [PERSON] et al. [53] provide comprehensive guidance on conducting time-to-event analysis in observational studies, with a particular focus on hazard models and the Cox proportional hazards regression model. In another study, [PERSON] et al. [40] introduce a framework for evaluating community resilience to multiple hazards in the Anning River basin, underscoring the significance of socio-economic factors in enhancing adaptive risk management. [PERSON] et al. [54] analyze geophysical data in North Ossetia, Russia, and develop a complex hazard map aimed at improving risk assessments in the region. Also, [PERSON] et al. [55] examine the temporal assessment of disaster risk, using case studies from China to demonstrate how risk varies over time and proposing long-term mitigation strategies. Over the past century, studies have shown a general uptick in both the frequency and intensity of natural disasters, with pronounced peaks in recent decades [37; 56; 57]. [PERSON] et al. [58]found that from 1995 to 2022, there were 11,360 natural disasters, averaging 398 annually. They mentioned that Asia reported the highest number of disasters (4390) and the greatest number of fatalities (918,198). Also, hydrological disasters were the most frequent, totaling 4969, whereas geophysical disasters were the deadliest, with 770,644 deaths. Finally, they found that biological disasters, primarily affecting Africa, resulted in the highest number of injuries (2544) [58]. From another perspective, [PERSON] et al. [59] investigate disaster records from EM-DAT for 2000-2018 to understand multi-hazard risk patterns. Using an algorithm that considers hazard associations and their spatial and temporal overlaps, their study reveals that multi-hazard events are twice as frequent when there is at least a 25% spatial overlap and a time difference of up to 1 year. Also, they found that these events contribute to 78% of total damages, 83% of affected populations, and 69% of total fatalities [59]. In a different view, [PERSON] et al. [60] explored the occurrence of rainstorms and floods in the Tarim Basin from 1980 to 2019. Their findings show a notable rise in these events, especially between April and September. The western and northern regions of the basin are particularly vulnerable, with severe incidents significantly impacting the damage index. Similarly, [PERSON] et al. [46] conducted a geospatial analysis of 9962 natural disasters from 1960 to 2018, examining their frequency and impact across different continents. This study also provides a predictive outlook on future trends, highlighting the influence of climatic factors on disaster patterns. In addition, [PERSON] et al. [38] investigated changes in the frequency, intensity, and spatial distribution of hazards like hurricanes, tropical storms, and droughts. Their research connects these variations to climate change, using empirical data to bolster previous theories. Furthermore, [PERSON] and [PERSON] [61] examined the relationship between precipitation patterns and landslides in the Aburra Valley. Their study revealed that rainfall-induced landslides are affected by macroclimatic phenomena such as ENSO, with specific hotspots identified in the valley's eastern hills. The geospatial and temporal distribution patterns of various disasters have been analyzed in multiple studies [37; 46]. Over the past century, natural disasters like droughts, floods, and storms have generally become more frequent and severe, with a marked increase in intensity observed in recent decades [37; 46; 62]. [PERSON] and [PERSON] [37] conducted a geospatial analysis of 9962 natural disasters occurring worldwide between 1960 and 2018, covering 39,953 locations. They found that Asia, particularly the southeastern region, was the most disaster-affected area, with countries like China, India, the Philippines, and Indonesia being heavily impacted.