Extreme precipitation induced landslide event on 30 July 2019 in Jølster, western Norway

A torrential rain event struck western Norway on Tuesday 30 July 2019. Most severely affected was the Jølster community, where numerous landslides and floods damaged public infrastructure and private property. This resulted in one fatality, 150 people evacuated from the area and the closure of Highway E39, the main coastal transport route in Norway. Weather radar data reveal large spatial and temporal variations in rainfall intensity and areas with highest intensities correspond to observed shallow landslide clusters where the 200-year rainfall event magnitude was clearly exceeded. The majority of 120 shallow landslide source areas share common characteristics: they are situated above or at the tree line, in thin to very thin soil, in contact with the bedrock or large boulders and in rather steep terrain (>30 degrees). Several lines of evidence suggest that soil in the source areas was not fully saturated, but instead failed due to locally high porewater pressures as short and intense rainfall on dry ground led to water infiltration through open cracks in the surface cover, and commonly at soil-bedrock or soil-boulder contacts. The most far-reaching debris flows of the event have steep upper transport areas, in places with cliff sections, which created sufficient flow-momentum despite small starting volumes. We note that erosion along the flow path was relatively superficial since incomplete soil saturation with depth likely prevented deeper entrainment. Consequently, water-to-solid ratios in the mobilised material was high and the runout possibly longer but less destructive compared to more deep-seated landslide events. This type of summer torrential rain on unsaturated soil require adjustments to how Norwegian society predicts and prepares for shallow landslides triggered during these events, compared with landslides following longer-lasting rainfall.publishedVersio

Extreme precipitation on dry ground in western Norway – characteristics of induced landslides call for adaptation of the Norwegian practice in landuse planning

Following a particularly dry summer, a torrential rain event struck Western Norway on Tuesday 30 July 2019. The resulting floods and shallow landslides caused one fatality and severe damages to public and private infrastructure in the former Jølster municipality. Building on earlier work, in which we identified characteristics of the shallow landslides induced by torrential rains on unsaturated soils, we here present suggestions for adaptation of the Norwegian practice in landuse planning.publishedVersio

Extreme precipitation-induced landslide event on 30th July 2019 in Jølster, western Norway

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Preliminary assessment of thaw slump hazard to Arctic cultural heritage in Nordenskiöld Land, Svalbard

Permafrost-dependent landslides occur in a range of sizes and are among the most dynamic landforms in the Arctic in the warming climate. Retrogressive thaw slumps (RTSs) are enlarging landslides triggered by thawing and release of excess water from permafrost ground ice, causing smaller or larger collapses of ground surface, which in turn exposes new permafrost to rapid thawing and collapse. In this study, a preliminary assessment of previous thaw slump activity in Nordenskiöld Land area of Svalbard is made based on remote sensing digitisation of 400 slump-scar features from aerial images from the Norwegian Polar Institute (NPI). RTS properties and distribution are analysed with an emphasis on their implications for the preservation of the Svalbard’s cultural heritage (CH). Our analysis shows that the areas where RTS scars and CH co-exist in Nordenskiöld Land are, at present, limited and cover mainly areas distributed along north-west (Colesbukta, Grønfjorden, Kapp Starostin), north-east (Sassendalen and Sassenfjorden) and south-west (Van Muydenbukta) coastlines. Taking into consideration the preliminary aspect of this inventory and study, it can be stated that for now, RTS and CH sites do not have a high level of co-existence, except for eight sites which are located at less than 100 m to a RTS and one site that is located inside a currently inactive slump-scar. Further mapping of RTS will be undertaken in order to have a complete picture of these climate triggered landslides potentially threatening the Arctic CH. The results of this study, even if preliminary, can be used by local authorities and stakeholders in prioritising future documentation and mitigation measures and can thus present a powerful tool in disaster risk reduction

Coastal Erosion of Arctic Cultural Heritage in Danger: A Case Study from Svalbard, Norway

Strong cultural heritage management relies on a thorough evaluation of the threats faced by heritage sites, both in the present and in the future. In this study, we analysed the changes in the position of Hiorthhamn shoreline (Svalbard), which is affecting coastal cultural heritage sites, for a period of 93 years (1927–2020). Shoreline changes were mapped by using maps, ortophotos, drone images, terrestrial laser scanning (TLS), and topographic surveys. Also, TLS was used to 3D document the endangered coastal cultural heritage sites. Detailed sedimentological and morphological mapping was made in the field and from the newly acquired drone images in order to understand shoreline-landscape interaction and to depict changes occurring from 2019 to 2020. Short-term (2019–2020) and long-term (1927–2020) shoreline erosion/accretion was made with the help of the Digital Shoreline Analysis System (DSAS) and prompted a subdivision of three sectors, based on change pattern. Compared to a previous long-term analysis (1927–2019), this year’s average erosion rate analysis (expressed by the EPR parameter) for the 93-year period is −0.14 m/yr. This shift in mean development is due to a newly formed spit-bar in Sector 2. Referring strictly to Sector 1, where the protected cultural heritage objects are located, the erosion rate increased from the previous analysis of –0.76 m/yr to −0.77 m/yr. The shoreline forecast analysis highlights that half of the protected cultural heritage objects will likely disappear over the next decade and almost all the cultural heritage objects analysed in this study will disappear in roughly two decades. This shows the great danger the Arctic’s cultural heritage sites is in if no mitigation measures are undertaken by the local authorities

A glimpse into the northernmost thermo-erosion gullies in Svalbard archipelago and their implications for Arctic cultural heritage

Gully erosion is one of the most destructive geomorphological processes on relatively flat surfaces. This is exacerbated in the Arctic regions, where gullies are referred to as thermo-erosion gullies because of their unique connection to permafrost. As the surface of the permafrost freezes and thaws, soil particles destabilize, inducing erosion along preferential incisions, giving rise to widespread thermo-erosion gullies. In this study, we present the first thermo-erosion gully inventory in the Svalbard region (Nordenskiöld Land). The inventory was created using a combination of available aerial photographs from 2009 to 2011, direct field observations and measurements. The spatial distribution of thermo-erosion gullies is then exploited to investigate potential threats to the Arctic cultural heritage (CH). Analyses of thermo-erosion gullies are increasingly important for artic administrations, which require more detailed hazard assessments as the effect of climate change becomes increasingly evident across these landscapes. The inventory is comprised of 810 thermo-erosion gullies in Nordenskiöld Land, most of which are located in close proximity to coastlines. We assess the inventory size statistics and correlation with terrain characteristics to investigate potential predisposing factors. No gullies occurs at elevations greater than 200 m a.s.l., but gullies occur up to a maximum steepness of 37 degrees and along the whole topographic profile and, looking at the potential threat to CH, we found 44 of these sites within a 100 m buffer from the gullies. This distance is the reference that local administrations use to prioritize actions and safeguard the existence of artic CH sites. In fact, a 100 m distance implies that future evolution of thermo-erosion gullies, especially enhanced by climate change may eventually erode away soil from the CH surroundings, threatening their stability and existence

Multi-Temporal Satellite Image Composites in Google Earth Engine for Improved Landslide Visibility: A Case Study of a Glacial Landscape

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Multi-Temporal Satellite Image Composites in Google Earth Engine for Improved Landslide Visibility: A Case Study of a Glacial Landscape

Regional early warning systems for landslides rely on historic data to forecast future events and to verify and improve alarms. However, databases of landslide events are often spatially biased towards roads or other infrastructure, with few reported in remote areas. In this study, we demonstrate how Google Earth Engine can be used to create multi-temporal change detection image composites with freely available Sentinel-1 and -2 satellite images, in order to improve landslide visibility and facilitate landslide detection. First, multispectral Sentinel-2 images were used to map landslides triggered by a summer rainstorm in Jølster (Norway), based on changes in the normalised difference vegetation index (NDVI) between pre- and post-event images. Pre- and post-event multi-temporal images were then created by reducing across all available images within one month before and after the landslide events, from which final change detection image composites were produced. We used the mean of backscatter intensity in co- (VV) and cross-polarisations (VH) for Sentinel-1 synthetic aperture radar (SAR) data and maximum NDVI for Sentinel-2. The NDVI-based mapping increased the number of registered events from 14 to 120, while spatial bias was decreased, from 100% of events located within 500 m of a road to 30% close to roads in the new inventory. Of the 120 landslides, 43% were also detectable in the multi-temporal SAR image composite in VV polarisation, while only the east-facing landslides were clearly visible in VH. Noise, from clouds and agriculture in Sentinel-2, and speckle in Sentinel-1, was reduced using the multi-temporal composite approaches, improving landslide visibility without compromising spatial resolution. Our results indicate that manual or automated landslide detection could be significantly improved with multi-temporal image composites using freely available earth observation images and Google Earth Engine, with valuable potential for improving spatial bias in landslide inventories. Using the multi-temporal satellite image composites, we observed significant improvements in landslide visibility in Jølster, compared with conventional bi-temporal change detection methods, and applied this for the first time using VV-polarised SAR data. The GEE scripts allow this procedure to be quickly repeated in new areas, which can be helpful for reducing spatial bias in landslide databases

Multi-Temporal Satellite Image Composites in Google Earth Engine for Improved Landslide Visibility: A Case Study of a Glacial Landscape

Regional early warning systems for landslides rely on historic data to forecast future events and to verify and improve alarms. However, databases of landslide events are often spatially biased towards roads or other infrastructure, with few reported in remote areas. In this study, we demonstrate how Google Earth Engine can be used to create multi-temporal change detection image composites with freely available Sentinel-1 and -2 satellite images, in order to improve landslide visibility and facilitate landslide detection. First, multispectral Sentinel-2 images were used to map landslides triggered by a summer rainstorm in Jølster (Norway), based on changes in the normalised difference vegetation index (NDVI) between pre- and post-event images. Pre- and post-event multi-temporal images were then created by reducing across all available images within one month before and after the landslide events, from which final change detection image composites were produced. We used the mean of backscatter intensity in co- (VV) and cross-polarisations (VH) for Sentinel-1 synthetic aperture radar (SAR) data and maximum NDVI for Sentinel-2. The NDVI-based mapping increased the number of registered events from 14 to 120, while spatial bias was decreased, from 100% of events located within 500 m of a road to 30% close to roads in the new inventory. Of the 120 landslides, 43% were also detectable in the multi-temporal SAR image composite in VV polarisation, while only the east-facing landslides were clearly visible in VH. Noise, from clouds and agriculture in Sentinel-2, and speckle in Sentinel-1, was reduced using the multi-temporal composite approaches, improving landslide visibility without compromising spatial resolution. Our results indicate that manual or automated landslide detection could be significantly improved with multi-temporal image composites using freely available earth observation images and Google Earth Engine, with valuable potential for improving spatial bias in landslide inventories. Using the multi-temporal satellite image composites, we observed significant improvements in landslide visibility in Jølster, compared with conventional bi-temporal change detection methods, and applied this for the first time using VV-polarised SAR data. The GEE scripts allow this procedure to be quickly repeated in new areas, which can be helpful for reducing spatial bias in landslide databases