The Gloria storm rainfalls affected Catalonia from 20 to 23 January 2020 and triggered multiple landslides, some of which affected buildings and infrastructures (such as roads and railways). This paper presents the rainfall and landslide datasets collected during the event, and evaluates the performance of a regional landslide early warning system (LEWS) during the Gloria storm applying a fuzzy verification method. The majority of the inventoried landslides can be classified as slides, involving a limited volume of sediment (up to 10 m³), and were triggered in cut slopes along linear infrastructures. Rainfall accumulations were significant in the whole region, especially in the Montseny area, where over 450 mm were registered in 96 h. Generally, the LEWS computed moderate and high warnings in the areas where large rainfall amounts were recorded, and showed good correspondence with the locations where landslides were reported. The fuzzy verification method has been applied using neighbouring windows of different sizes to obtain scale-dependant information on the LEWS performance. The skill of the LEWS considerably improves when enlarging the neighbouring window size from 500 m to 1 km.

Soil moisture plays a vital role in slope stability. As water infiltrates into the soil, shear strength decreases eventually leading to failure. However, most of the existing regional-scale landslide early warning systems (LEWS) rely solely on rainfall information and use rainfall thresholds to determine if the landslide triggering conditions are met. The original version of the Catalonia region LEWS combines real-time rainfall observations and susceptibility to compute warnings. The LEWS applies a set of rainfall intensity-duration thresholds to determine if the rainfall conditions have the potential to trigger a landslide. This work explores the potential of using modelled soil moisture data in the Catalonia region LEWS. Volumetric water content (VWC) from the LISFLOOD hydrological simulations of the European Flood Awareness System and rainfall estimates have been analysed at the location of recent landslide events. Based on this data, a set of empirical hydrometeorological thresholds combining rainfall and soil moisture information has been obtained for their application into the Catalonia region LEWS. The LEWS has been run for nine months (April–December 2020) using two approaches: (i) combining susceptibility and rainfall intensity-duration (I-D) thresholds and (ii) combining susceptibility and the new hydrometeorological thresholds including soil moisture information. Generally, both LEWS approaches issued moderate or high warnings in the areas where significant rainfall accumulations were recorded. The outputs have been compared at specific locations where landslides were reported during the analysed period. Results show that at the analysed locations false positives are generally reduced when employing the hydrometeorological thresholds in the LEWS. Therefore, this approach is promising and could help improve regional scale LEWS in Catalonia.

The sensitive mountain catchment of Portainé (Eastern Pyrenees, Iberian Peninsula) has recently experienced a significant change in its torrential dynamics due to human disturbances. The emplacement of a ski resort at the headwaters led to the surpassing of a geomorphological threshold, with important consequences during flood events. Consequently, since 2008, channel dynamics have turned into sediment-laden, highly destructive torrential flows. In order to assess this phenomenon and o acquire a holistic understanding of the catchment’s behaviour, we carried out a field work-based multidisciplinary study. We considered the interaction of the various controlling factors, including bedrock geology, geomorphological evolution, derived soils and coluvial deposits, rainfall patterns, and the hydrological response of the catchment to flood events. Moreover, anthropogenic land-use changes, its consequential hydrogeomorphic effects and the role of vegetation were also taken into account. Robust sedimentological and geomorphological evidence of ancient dense debris flows show that the basin has shifted around this threshold, giving rise to two different behaviours or equilibrium conditions throughout its history: alternating periods of moderate, bedload-laden flows and periods of high sediment-laden debris flow dynamics. This shifting could have extended through the Holocene. Finally, we discuss the possible impact of climate and global change, as the projected effects suggest future soil and forest degradation; this, jointly with more intense rainfalls in these mountain environments, would exacerbate the future occurrence of dense sediment-laden flows at Portainé, but also in other nearby, similar basins.

Rainfall-induced landslides represent an important hazard in mountainous regions worldwide. Landslides commonly impact the functioning of infrastructure assets such as roads and railways and occasionally damage buildings or result in fatalities. In the Nordic region, rainfall-induced landslides constitute a significant hazard, accounting for a considerable amount of Norway's national landslide database entries.Because of climate change, the frequency of rainfall and soil moisture conditions that usually trigger landslides will become more variable. This leads to weaker predictions for the location and frequency of future landslide events from current models. Understanding how the landslide hazard will change can help plan mitigation along linear infrastructure and reduce the risk to the population.Here, we report the findings from the NordicLink project, financed by Nordforsk, where a methodology to characterise landslide hazard at a global scale has been adopted to develop Nordic hazard maps.The methodology to characterise the landslide hazard at a global scale has been developed within the activities of the "Global Infrastructure Resilience Index" (GIRI) project, funded by the Coalition for Disaster Resilient Infrastructure (CDRI). The method combines landslide susceptibility and rainfall to compute landslide probability at a global scale. The susceptibility map classifies terrains into five susceptibility classes by combining slope, vegetation, lithology, and soil moisture information from global datasets. Rainfall information has been obtained from the W5E5 dataset for the period 1979-2016 and the IPSL-CM6A-LR climate model from ISIMIP3b dataset SSP126 and SSP585 scenarios for the period 2061-2100. To characterise the rainfall triggering potential, the 24 h rainfall intensities have been used to distinguish between five rainfall hazard classes. Finally, a hazard matrix has been employed to combine landslide susceptibility and rainfall. The output is a probabilistic hazard map covering the world with a resolution of three arc seconds (approximately 90 m at the equator).In the NordicLink project, higher-quality Nordic-scale data and landslide inventories are used as input to the above-mentioned procedure to obtain probabilistic hazard maps covering Norway, Sweden, and Finland. The study concludes with a comparison between the NordicLink hazard maps and the (global) GIRI model. As expected, landslide hazard is higher in western Norway and decreases towards the East. Finland is the country with the lowest landslide hazard.