Comparing earthquake and rainfall-induced landslide inventories in the Himalayan region

C.J. van Westen, S.R. Meena, Jianqiang Zhang

Research output: Contribution to conferenceAbstractAcademic

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Abstract

This paper gives an overview of recent research on generating landslide inventories of triggering events by earthquake and extreme rainfall in the Himalayan context, and how these influence subsequent landslide susceptibility, hazard and risk assessment. Within a collaboration project between between ITC, GSI and NRSC , a number of techniques were developed for landslide inventory mapping, ranging from using Object Based Image Analysis, to the use of available records and collaborative mapping using Google Earth Images for the generation of event-based landslide inventories. The completeness of landslide inventories and its spatial and thematic accuracy are discussed in relation to the effect they have on the evaluation of landslide susceptibility and hazard assessment. Also a collaboration with the USGS is discussed for the generation of a web-based portal of earthquake-induced landslide inventories for major historical earthquakes. It is very important to collect as many of these event-based inventories in order to better correlate them with the specific characteristics of the earthquake that triggered them and the terrain conditions, in order to develop methods for earthquake-induced landslide hazard. Event based landslide inventories are used to estimate the relation between temporal probability, landslide density and landslide size distribution. Examples are given of the work that was carried out after the 2015 Gorkha earthquake in Nepal. Object Based Image Analysis (OBIA) combined with machine learning methods were used to generate landslide inventories from before, during and after the earthquake, and the characteristics of earthquake-induced landslide inventories were compared with rainfall-induced landslide inventories. The contributing factors related to topography, geological and land cover were analyzed for both inventories for different landslide types and sizes. In order to develop rainfall thresholds as a basis for Landslide Early Warning a study was carried out in the Rasuwa district of Nepal, using a combination of satellite based rainfall estimates, rainfall station data, and physically-based modelling of soil water conditions and slope stability. Also multi-hazard relationships (earthquake-landslides-flooding-debrisflows) were modelled using a physically-based model in comparable environments affected by earthquakes, in order to analyze the post-earthquake changes in landslide hazard intensity.
Original languageEnglish
Pages41-42
Number of pages2
Publication statusPublished - 28 Oct 2020

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