Challenges and opportunities in regional hydrometeorological landslide assessment

Forecasting of landslides is crucial because these natural hazards pose significant threats to human lives, infrastructure, economies, and ecosystems. Understanding the spatial and temporal drivers of landslides enables better risk assessment, mitigation, and adaptation strategies. In previous decades, numerous studies have shown that adding hydrological information and advancements in modelling techniques have improved regional landslide early warning systems (LEWS). However, operational LEWSs are still a few. This brings up the question how the next generation LEWS needs to look like.

Landslide hazard assessment on regional scale has been founded on two main pillars: the essential inventories of slope failures and on the quantification of the hydrometeorological drivers. First, the lack of landslide inventories and the dominance of seemingly stable slopes in a region constraints our ability to empirically train landslide early warning systems. The inclusion of more multi-source slope deformation information is a logical development, however, turns out to have its own challenges; it merges different physical properties within one database. Second, causal and triggering hydrometeorological conditions are needed both in space and time for effective landslide prediction. Ideally, one would start with high spatial and temporal resolution rainfall and soil hydrological information. While acknowledging existing challenges, impressive progress has been made in this field. Combined monitoring and advanced modelling on a range of scales has resulted in valuable information on, for example, subsurface water storage. Similarly, near real-time and forecasted high resolution rainfall information from ground based rain radars shows promising results. The improved representation of the hydrometeorological conditions improves the performance of LEWS.

Starting from a brief review of the developments and limitations of regional hazard assessment, the presentation will discuss the opportunities to improve the landslide inventory site as well as through hybrid measurement and modelling approaches to quantify the dynamic hydrometeorological conditions. Landslides are an anomaly in a seemingly stable environment, and inherently, forecasting of such rare events in space and time is associated with uncertainty, but this uncertainty can be reduced which is key for protecting society from the impact of landslide hazards.