Spatio-temporal rainfall controls on landslide triggering: can space be used in place of time in threshold definitions?

Rainfall-induced landslides are among the most damaging natural hazards in humid and mountainous regions, posing severe threats to human life, infrastructure, and environmental systems. Despite extensive research, accurately identifying the rainfall conditions that trigger slope failures remains a major scientific challenge, particularly during extreme hydrometeorological events. Between late April and early May 2024, the state of Rio Grande do Sul (southern Brazil) experienced an unprecedented rainfall episode, resulting in one of the largest documented clusters of rainfall-triggered mass movements in the world. Over 15,000 landslides were recorded across an area of approximately 63,000 km², causing severe social, environmental, and economic impacts. The spatial extent of the affected area enables an investigation into whether spatial variability can be used in place of temporal information to establish intensity–duration thresholds for landslide triggering.

This study investigates the rainfall characteristics associated with landslide triggering during the 2024 extreme event, with emphasis on the temporal, spatial, and pluviometric conditions preceding and coinciding with slope failures. The research integrates high-resolution rainfall records from selected meteorological stations with detailed landslide occurrence data obtained through field campaigns and interviews with residents directly affected by the event, allowing the reconstruction of failure timing with sub-hourly precision. This integration enables a direct comparison between landslide occurrence and rainfall dynamics, including intensity, duration, cumulative rainfall, and antecedent precipitation.

The primary objective is to identify rainfall patterns linked to landslide initiation and to estimate empirical rainfall thresholds, defined as critical values of rainfall intensity and/or accumulation beyond which landslides are likely to occur. Thresholds are derived using conventional intensity–duration and cumulative rainfall approaches, focusing on empirical methods supported by historical observations. Particular attention is given to the role of antecedent rainfall conditions and to the clustering of landslides triggered by a single rainfall episode.

In addition to the temporal analysis, this study investigates the relationship between rainfall thresholds and the spatial extent of affected areas, evaluating whether the magnitude of the impacted area can serve as a complementary or alternative indicator to classical time-based thresholds. Across the landslide-affected area previously identified, landslides were triggered at different times over a three-day period, reinforcing the central hypothesis that spatial variability can be used in place of temporal information under spatially extensive extreme rainfall conditions. Accordingly, a threshold curve was derived from the same extreme event. Despite being based on a single event, the resulting threshold is consistent with intensity–duration relationships commonly reported in the literature.

Overall, these results highlight the potential of spatially informed approaches to refine rainfall threshold analyses during widespread landslide events.