Landslide-lake outburst floods accelerate downstream hillslope slippage

The Jinsha River, which has carved a 2–4 km deep gorge, is one of the largest SE Asian rivers. Two successive landslide-lake outburst floods (LLFs) occurred after the 2018 Baige landslides along the river. Using Sentinel-2 images, we examined the LLF impacts on downstream river channels and adjacent hillslopes over a 100 km distance. The floods increased the width of the active river channel by 54 %. Subsequently, major landslides persisted for 15 months in at least nine locations for displacements >2 m. Among them, three moving hillslopes ∼80 km downstream from the Baige landslides slumped more than 10 m 1 year after the floods. Extensive undercuts by floods probably removed hillslope buttresses and triggered a deformation response, suggesting strong and dynamic channel–hillslope coupling. Our findings indicate that infrequent catastrophic outburst flooding plays an important role in landscape evolution. Persistent post-flood hillslope movement should be considered in disaster mitigation in high-relief mountainous regions.

Landslide-lake outburst floods accelerate downstream slope slippage

The Jinsha River, carving a 2–4 km deep gorge, is one of the largest SE Asian rivers. Two successive landslide-lake outburst floods (LLFs) occurred after the 2018 Baige landslides along the river. Using Sentinel-2 images, we examined the LLFs' impacts on downstream river channel and adjacent hillslopes over a 100 km distance. The floods increased the width of the active river channel by 54 %. Subsequently, major landslides persisted for 15 months in at least nine locations for displacements > 2 m. Among them, three moving hillslopes, ~80 km downstream from the Baige landslides, slumped more than 10 m one year after the floods. Extensive undercuts by the floods probably removed hillslope buttresses and triggered deformation response, suggesting a strong and dynamic channel-hillslope coupling. Our findings indicate that infrequent catastrophic outburst flooding plays an important role in landscape evolution. Persistent post-flood hillslope movement should be considered in disaster mitigation in high-relief mountainous regions.

A catastrophic multi-hazard event in 2020 in Kali Gandaki valley, Nepal Himalaya

<p>Multiple hazards (e.g. floods, landslides, earthquakes, glacial and landslide lake outburst floods) are threatening people, their goods and infrastructures in the high mountains of Nepal Himalaya. Floods and landslides are mainly driven by monsoonal precipitation. However, human impact often increases natural risks, like in the Kali Gandaki (KG) valley, the deepest valley (>5500 m) on earth, where the new two-lane road construction (since 2017) has caused many undercut and instable slopes.</p><p>In the light of previous events, we intend to assess the cascading multi-hazard events of 2020 in three tributary catchments of KG.</p><p>We adopted a pluri-disciplinary approach: interpretation of Sentinel-2 satellite images (March and November 2020), analysis of precipitation (stations of Lete and Tatopani, GPM satellite precipitation measurements), hydrologic and seismic data (Beni), geomorphological mapping, hydrological modelling in HEC-RAS, and field visits in July and November 2020, including interviews with locals.</p><p>On 20 July 2020 major hyper-concentrated flood events and landslides occurred in the Rupse, Thaplyang and Kahiku catchments (between Tatopani and Lete) destroying parts of the KG road, road bridges and a hotel (Rupse site). We focus on the Rupse River entering the KG valley at Rupse waterfall (height 108 m; kyanitic gneisses) then flowing down to the KG road and to KG River 200 m below. The major flood event lasted two hours and reached a max. flood level of 35 m at the edge of the waterfall. Upstream of the waterfall, four landslides (each about 250m wide, 200 m high) were triggered. Due to cloud coverage satellite scenes are missing to unravel whether the landslides caused the damming of the river and a landslide lake outburst flood or if the landslides were mainly triggered by the flood and increased sediment input to it.</p><p>Floods from these tributary catchments caused a major KG flood especially south of the Rupse catchment, which led to severe erosion and sedimentation in the channel; i.e. destruction of a pole of the national electricity grid, reactivation of the Kham Bhitta deep-seated landslide, destruction of the KG road (the construction of which probably contributed to this reactivation). <br>Seismic data from Beni, approximately 27 km downstream of the affected catchments, provide constraints on the timing and relative magnitude of the flood in the KG. The data show that a short duration high magnitude flood with a very rapid rise and recession passed through Beni on the afternoon of 20 July. In addition, station data of Lete and Tatopani shows that yearly rainfall totals of 1839.5 and 2140.2 mm, respectively, were the highest since 1970. March and April were already very wet, followed by extremely monthly rainfall totals of 499.7 mm and 551.5 mm at Lete and Tatopani, respectively.</p><p>Assessing the 2020 events demonstrates how important localized events in relatively small areas are to understand cascading multi-hazard processes in Himalayan mountain regions. In addition, such hydro-geomorphic functioning and related hazards should be carefully considered when planning road design and bridge sites together with landslide and water level monitoring, for a better traffic maintenance and safety.</p>

APPLICATION OF REMOTE SENSING BIG DATA FOR RAPID RESPOND TO LANDSLIDE LAKE DISASTER MONITOR

Landslide dam, a common disaster around the world, always forms landslide lake because of blocking the river. Landslide lake is always with potentially immense hazard from rapid release of a large of water masses. Nowadays, with the development of remote sense technology, remote sensing big data has been widely applied to disaster monitor, which has broad prospect in landslide lake monitor. This study provided the processing flow of remote sensing image and flow of technology system in the landslide lake monitor based on remote sensing big data, which have been successfully applied to Baige landslide lake monitor. The result shows remote sensing technology as an objective, fleet and dynamic change of landslide lake with large monitor range and meets the requirement of all-weather dynamic monitor of landslide lake, which will provide basic information of landslide lake for decisionmaking departments to make disaster prevention and reduction. Lastly, the research points out the disadvantage of landslide lake monitor based on remote sensing big data. Drone images and aerial images will be an important supplement to remote sensing big data for landslide lake monitor.

Recent catastrophic landslide lake outburst floods in the Himalayan mountain range

Among the more complex and devastating interactions between climate and hydromorphological processes in mountain environments are landslide lake outburst floods (LLOFs), resulting from mass movements temporarily blocking a drainage system. This work reviews these processes in the Himalayas and highlights the high frequency of this type of phenomenon in the region. In addition, we analyse two recent catastrophic trans-national LLOFs occurring in the Sutlej river basin during 2000 and 2005. Based on high resolution satellite images, Tropical Rainfall Measuring Mission (TRMM), Moderate-Resolution Imaging Spectroradiometer (MODIS) derived evolution of snowline elevation and discharge data we reconstruct the timing and hydrometeorological conditions related to the formation and failure of landslide dams. Results showed that the 2005 flood, originating from the outburst of the Parchu Lake, was not related to heavy precipitation, but was likely enhanced by the rapid and late snowmelt of an unusually deep and widespread snowpack. The flood in 2000 was triggered by the outburst of an unnamed lake located on the Tibetan plateau, identified here for the first time. In this case, the outburst followed intense precipitation in the lake watershed, which raised the level of the lake and thus caused the breaching of the dam. As stream gauges were damaged during the events detailed discharge data is not available, but we estimated the peak discharges ranging between 1100 m3 s−1 and 2000 m3 s−1 in 2005, and 1024 m3 s−1 and 1800 m3 s−1 in 2000. These events caused significant geomorphic changes along the river valleys, with observed changes in channel width exceeding 200 m. Results also demonstrate that remotely-sensed data enables valuable large-scale monitoring of lake development and related hydrometeorological conditions, and may thereby inform early warning strategies, and provide a basis for flood risk reduction measures that focus on disaster preparedness and response strategies.

Temporal and spatial responses of river discharge to tectonic and climatic perturbations: Choshui River, Taiwan, and Typhoon Mindulle (2004)

One reason that small mountainous rivers discharge disproportionately large quantities of sediment to the coastal ocean is because they are particularly susceptible to short-term episodic events, such as earthquakes and floods. The impact of such events, both temporally and spatially, however, has seldom been monitored. Here we report on the results of probably the most thorough monitoring of a flood ever undertaken: the effect of Typhoon Mindulle (2–4 July 2004) on the character of the water transported by the Choshui River, central western Taiwan, during which 74 million tons of sediment were discharged to the adjacent Taiwan Strait. Results from a series of 113 water samples obtained between 2nd and 4th July from five stations along the middle and lower reaches the river indicate that more than half of the suspended sediment was generated in nearby mountains before the river reached its flood plain. While the concentration of dissolved solids remained more or less constant along the mainstem of the river, the composition changed considerably, reflecting the imprints of local geology. An order-of-magnitude downstream increase in NO3− concentrations reflects the rapid draining of the Tsaoling landslide lake on the Chingshui River, as the 1999 earthquake-generated landslide dam was breached.