The effects of forest cover and disturbance on torrential hazards: large-scale evidence from the Eastern Alps

Abstract

Global human population growth, limited space for settlements and a booming tourism industry have led to a strong increase of human infrastructure in mountain regions. As this infrastructure is highly exposed to natural hazards, a main role of mountain forests is to regulate the environment and reduce hazard probability. However, canopy disturbances are increasing in many parts of the world, potentially threatening the protection function of forests. Yet, large-scale quantitative evidence on the influence of forest cover and disturbance on natural hazards remains scarce to date. Here we quantified the effects of forest cover and disturbance on the probability and frequency of torrential hazards for 10 885 watersheds in the Eastern Alps. Torrential hazard occurrences were derived from a comprehensive database documenting 3768 individual debris flow and flood events between 1986 and 2018. Forest disturbances were mapped from Landsat satellite time series analysis. We found evidence that forests reduce the probability of natural hazards, with a 25 percentage point increase in forest cover decreasing the probability of torrential hazards by 8.7%±1.2%. Canopy disturbances generally increased the probability of torrential hazard events, with the regular occurrence of large disturbance events being the most detrimental disturbance regime for natural hazards. Disturbances had a bigger effect on debris flows than on flood events, and press disturbances were more detrimental than pulse disturbances. We here present the first large scale quantification of forest cover and disturbance effects on torrential hazards. Our findings highlight that forests constitute important green infrastructure in mountain landscapes, efficiently reducing the probability of natural hazards, but that increasing forest disturbances can weaken the protective function of forests.

The influence of climate change and canopy disturbances on landslide susceptibility in headwater catchments

“…In Central Europe, for instance, disturbances have already increased in the past decades (Senf et al, 2018) and a climate-induced increase in forest disturbances is highly likely also for the future (Seidl et al, 2014). Based on data for more than 10,000 watersheds collected for the last 32 years in Austria Sebald et al (2019) showed that such natural disturbances increase the probability of torrential hazard events in steep headwater catchments. They found that a regular occurrence of disturbances is the most detrimental reason for the occurrence of torrential events such as landslides.…”

Phenology Modelling and Forest Disturbance Mapping with Sentinel-2 Time Series in Austria

“…Recent studies underlined the importance of a vital forest at stand or even single-tree level [12]. Forest disturbances can decrease the capability of forest ecosystems to protect against natural hazards, which is a major regulating function, especially of mountainous forests [13]. From a global perspective, it will not be sufficient to avoid deforestation to meet global climate change mitigation goals.…”

“…Previous research shows different methodological approaches to cope with these challenges. Most of the mainly Landsat-based TSAs rely on an image composite analysis [13,19] or on some variant of a harmonic modelling approach [13,[19][20][21][22][23][24]. Harmonic modelling approaches are robust but show some limitations regarding the quality of temporal information [25] and allow only little detail in reconstructing seasonal vegetation courses.…”

Phenology Modelling and Forest Disturbance Mapping with Sentinel-2 time series in Austria

“…Recent studies underlined the importance of a vital forest at stand or even single-tree level (Bastin et al 2019). Forest disturbances can decrease the capability of forest ecosystems to protect against natural hazards, which is a major regulating function, especially of mountainous forests (Sebald et al 2019).…”

“…Previous research shows different methodical approaches to cope with these challenges. Most of the mainly LANDSAT-based TSAs are based on an image composite analysis (Nguyen et al 2018;Sebald et al 2019) or on some variant of a harmonic modelling approach (Zhu and Woodcock 2014;Moisen et al 2016;Pasquarella et al 2017;Nguyen et al 2018;Hermosilla et al 2019;Sebald et al 2019;Bullock et al 2020). Harmonic modelling approach robust but shows some limitations regarding the quality of temporal information (Jönsson et al 2018) and allow only little detail in reconstructing seasonal vegetation courses.…”