Slope-unit-based assessment of landslide susceptibility in Central Nepal

Slope units, defined by the portions of terrain bounded by drainage and divide lines, are specific mapping units that can be used to prepare landslide susceptibility maps, as they have better geomorphological content than grid cells. Researchers have progressed in delineating and optimizing slope unit maps in the past decades [1, 2], and in landslide susceptibility and hazard assessment [3,4]. We present a slope unit map delineated and published for the first time in the Himalayas [5], containing 112,674 polygons in a geographic extent that cover central Nepal and some sections of Tibet, China. We used this map to (i) compare landslide inventories, and their corresponding landslide susceptibility [6] and (ii) generate a rockfall susceptibility map along a highway [7]. We compared five inventories from different authors after the Gorkha earthquake in 2015, adopting statistical and geospatial techniques. The outcome shows differences in the geospatial clustering of the susceptibility maps corresponding to different inventories. We prepared a potential source map of earthquake-triggered rockfall along a highway in Rasuwa district, Nepal. Then, we ran STONE [8,9], a physically based application, to a grid map with a rockfall trajectory map based on which we generated a segment-wise rockfall susceptibility map. Results helped to identify areas with high susceptibilities, such as Dandagaun and Syaprubesi. The findings could be helpful for rockfall hazard and risk assessment and land use planning. Through these studies, we stress that slope-unit-based studies are an excellent alternative to grid cells for large-scale studies as they help select specific slopes for further hazard assessment. 
References:
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[2]    M. Alvioli et al., “Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling”. Geosci Model Dev, 9, 3975–3991 (2016). DOI: 10.5194/gmd-9-3975-2016
[3]    M. Alvioli et al., “Rockfall susceptibility and network-ranked susceptibility along the Italian railway”. Engineering Geology 293, 106301 (2021). DOI: 10.1016/j.enggeo.2021.106301
[4]    M. Alvioli et al., “Seismically Induced Rockfall Hazard from Ground Motion Scenarios in Italy”. SSRN Electronic Journal (2022). DOI: 10.2139/ssrn.4156514
[5]    M. Alvioli, I. Marchesini, B. Pokharel, K. Gnyawali, and S. Lim, “Geomorphological slope units of the Himalayas”. J. Maps (2022). DOI: 10.1080/17445647.2022.2052768
[6]    B. Pokharel, M. Alvioli, and S. Lim, “Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics,” Sci Rep 11, 21333 (2021). DOI: 10.1038/s41598-021-00780-y
[7]         B. Pokharel, S. Lim, T.N. Bhattarai, and M. Alvioli, “Rockfall susceptibility along Pasang Lhamu and Galchhi-Rasuwagadhi highways, Rasuwa, Central Nepal”. (under review)
[8]    F. Guzzetti, G. Crosta, R. Detti, F. Agliardi, “STONE: a computer program for the three-dimensional simulation of rock-falls”. Computers & Geosciences 28, 1079-1093 (2002). DOI: 10.1016/S0098-3004(02)00025-0
[9]     M. Alvioli, A. De Matteo, R. Castaldo, P. Tizzani, P. Reichenbach, “Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation”. Geom Nat Haz and Risk, 2712-2736 (2022). DOI: 10.1080/19475705.2022.2131472