€ROSNZ

"Landslides, floods and erosion: new insights from event-based field measurements in the Southern Alps of New-Zealand and stochastic 2D numerical modeling of long-term landscape evolution"

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 Obiettivo del progetto (Objective)

'Long-term erosion of mountain belts is driven by discrete landsliding events that deliver sediment to rivers, and flood events that transport sediment away and incise bedrock. Landsliding and flooding events obey different frequency-magnitude distributions, are partially correlated (e.g., storms trigger landsliding and flooding, earthquakes only trigger landsliding), and interact along the drainage network to generate a complex spatio-temporal response still poorly understood at the event scale (i.e. how fast is a landslide deposit eroded, and how does it impact the downstream evolution of a channel ?) and over the long-term (how important are extreme events on river dynamics, landscape morphology and sediment fluxes ?). To progress on this topic, we propose to combine innovative field measurements using Terrestrial Laser Scanner, documenting individual flood and landslide impacts on channel morphology in the extremely active Southern Alps of New-Zealand, and 2D stochastic numerical modeling of landscape evolution to explore the long-term consequences and improve on the hazard assessment of rare extreme events such as landslide dams. The applicant will complement his leading expertise in numerical and experimental modeling of channel dynamics by being trained in landslide dynamics and risk assessment at Dept of Geological Sciences (Univ. Canterbury, N-Z), a leading institution on this topic with unique access to the nearby Southern Alps. During the return phase, he will apply his new skills to implement a stochastic landslide module to the landscape evolution code developed at Geosciences Rennes (CNRS, Univ. Rennes, Fr), validate model outputs against field data, and explore the long-term consequences for mountain erosion of the combined short-term stochasticity in landsliding and flooding. To further improve his career and strengthen the link between Europe and New-Zealand, the fellow will also prepare and submit a Marie-Curie Initial Training Network proposal.'

Introduzione (Teaser)

Studying an area vulnerable to landslides in New Zealand has helped produce valuable tools and methods to further geoscience and possibly manage natural disasters in a better way.

Descrizione progetto (Article)

Landslides, floods and erosion, which are often caused by earthquakes, can severely impact rivers, destroy surrounding road infrastructure and destabilise nearby communities. This has prompted researchers to seek ways of predicting the catchment response to large earthquakes that could trigger extensive landslides in vulnerable regions of the world. The EU-funded project ROSNZ sought to develop a new approach to explore such phenomena.

Looking at the Southern Alps of New Zealand, the project team explored the complex two-dimensional (2D) dynamics and gathered new data on the impact of landslides on river evolution. It worked on developing an advanced numerical model of mountain landscape evolution incorporating a new bedrock landsliding algorithm.

To achieve its aims, the team studied the impact of landslides and floods on channel morphology using repeat terrestrial light detection and ranging (LIDAR) surveys of rapidly incising rivers. It analysed seven landslide-affected bedrock areas in two rivers, comparing data before and after a 10-year return flood in one river to reveal important data on understanding landslides. Another achievement involved documenting the impact of a large storm on a gorge that resulted in heavy landslides.

Overall, the project team showed the interplay among large rock falls, cliff failure, erosion and landslides that could cause river deviation. A major contribution in this respect was the development of two open-source software solutions for the advanced processing of LIDAR datasets that could significantly further the geomorphology and geoscience involved.

The project produced a valuable dataset on the dominant role of stochastic floods and thresholds in nature, also exploring the combined effect of stochastic landsliding and flooding on landscape dynamics. The findings and practical tools emerging from this project can be used by geoscientists to monitor and assess geohazards based on terrestrial LIDAR data and landscape evolution simulations.

Progress in this area will help understand sedimentary hazards in New Zealand's Southern Alps and may contribute to strategies for studying similar issues worldwide.