Landslides In Nepal Research Articles

At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition

AbstractThe most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the first two elements are usually considered and estimated when working over vast areas. Even then, separate models constitute the standard, with frequency being rarely investigated. Frequency and intensity are dependent on each other because larger events occur less frequently and vice versa. However, due to the lack of multi‐temporal inventories and joint statistical models, modeling such properties via a unified hazard model has always been challenging and has yet to be attempted. Here, we develop a unified model to estimate landslide hazard at the slope unit level to address such gaps. We employed deep learning, combined with extreme‐value theory to analyze an inventory of 30 years of observed rainfall‐triggered landslides in Nepal and assess landslide hazard for multiple return periods. We also use our model to further explore landslide hazard for the same return periods under different climate change scenarios up to the end of the century. Our model performs excellently (with an accuracy of 0.78 and an area under the curve of 0.86) and can be used to model landslide hazard in a unified manner. Geomorphologically, we find that under climate change scenarios (SSP245 and SSP585), landslide hazard is likely to increase up to two times on average in the lower Himalayan regions (Siwalik and lower Himalayas; ≈110–3,500 m) while remaining the same in the middle Himalayan region (≈3,500–5,000 m) whilst decreasing slightly in the upper Himalayan region (≳5,000 m) areas.

Varying Impact of Earthquake- and Monsoon-Induced Landslides

Using nearly 50 years of satellite data and records stretching back millennia, scientists determine the relative frequency—and the erosional power—of monsoon- and earthquake-induced landslides in Nepal.

Roads and landslides in Nepal: how development affects environmental risk

Abstract. The number of deaths from landslides in Nepal has been increasing dramatically due to a complex combination of earthquakes, climate change, and an explosion of informal road construction that destabilizes slopes during the rainy season. This trend will likely rise as development continues, especially as China's Belt and Road Initiative seeks to construct three major trunk roads through the Nepali Himalaya that adjacent communities will seek to tie in to with poorly constructed roads. To determine the effect of these informal roads on generating landslides, we compare the distance between roads and landslides triggered by the 2015 Gorkha earthquake with those triggered by monsoon rainfalls, as well as a set of randomly located landslides to determine if the spatial correlation is strong enough to further imply causation. If roads are indeed causing landslides, we should see a clustering of rainfall-triggered landslides closer to the roads that accumulate and focus the water that facilitates failure. We find that in addition to a concentration of landslides in landscapes with more developed, agriculturally viable soils, that the rainfall-triggered landslides are more than twice as likely to occur within 100 m of a road than the landslides generated by the earthquake. The oversteepened slopes, poor water drainage and debris management provide the necessary conditions for failure during heavy monsoonal rains. Based on these findings, geoscientists, planners and policymakers must consider how road development affects the physical (and ecological), socio-political and economic factors that increase risk in exposed communities, alongside ecologically and financially sustainable solutions such as green roads.

Use of bioengineering techniques to prevent landslides in Nepal for hydropower development

Use of bioengineering techniques to prevent landslides in Nepal for hydropower development

Occurrence of landslides in Nepal and their mitigation options

Landslides are very common occurrences in Nepal that have been affected development infrastructures, lives, and properties of the people every year. Many hill villages are situated on or adjacent to unstable slopes and old landslides are reactivated from time to time. The rapidly increasing construction of infrastructure, such as roads, irrigation canals, and dams without due consideration of natural hazards is contributing to triggering of landslides and debris flows. Thus, this paper has explored the cause and characteristics of landslides occurrences and their mitigation practices in Nepal. Topographic, geologic and triggering factors, and human intervention causing landslides are characterised to suggest the suitable mitigation options that can be implemented in the mountain hill-slopes. Among the wide range of slope stabilisation measures which are available to practitioner engineer, the lowering of groundwater level in combination of controlling of surface infiltration (e.g. sealing of tension cracks) of water into landslide are the most cost effective options for mountainous terrain because the rise in pore water pressure is one of the basic cause of landslides during the rainy season. In addition, removing of unstable slope debris, surface drainage, and retaining walls are the useful landslide mitigation measures depending on site conditions, availability of budget, and specific requirements. Various support systems and elements can be crafted for creative solutions of the slope instability problems in Nepal.

Distribution probability of large-scale landslides in central Nepal

Large-scale landslides in the Himalaya are defined as huge, deep-seated landslide masses that occurred in the geological past. They are widely distributed in the Nepal Himalaya. The steep topography and high local relief provide high potential for such failures, whereas the dynamic geology and adverse climatic conditions play a key role in the occurrence and reactivation of such landslides. The major geoscientific problems related with such large-scale landslides are 1) difficulties in their identification and delineation, 2) sources of small-scale failures, and 3) reactivation. Only a few scientific publications have been published concerning large-scale landslides in Nepal. In this context, the identification and quantification of large-scale landslides and their potential distribution are crucial. Therefore, this study explores the distribution of large-scale landslides in the Lesser Himalaya. It provides simple guidelines to identify large-scale landslides based on their typical characteristics and using a 3D schematic diagram. Based on the spatial distribution of landslides, geomorphological/geological parameters and logistic regression, an equation of large-scale landslide distribution is also derived. The equation is validated by applying it to another area. For the new area, the area under the receiver operating curve of the landslide distribution probability in the new area is 0.699, and a distribution probability value could explain >65% of existing landslides. Therefore, the regression equation can be applied to areas of the Lesser Himalaya of central Nepal with similar geological and geomorphological conditions.

Community Vulnerability to Floods and Landslides in Nepal

We addressed the issue of differential vulnerability to natural disasters at the level of village communities in Nepal. The focus lay on the relative importance of different dimensions of socioeconomic status and in particular, we tried to differentiate between the effects of education and income/wealth, the latter being measured through the existence of permanent housing structures. We studied damage due to floods and landslides in terms of human lives lost, animals lost, and other registered damage to households. The statistical analysis was carried out through several alternative models applied separately to the Terai and the Hill and Mountain Regions, as well as all of Nepal. At all levels and under all models, the results showed consistently significant effects of more education on lowering the number of human and animal deaths as well as the number of households otherwise affected. With respect to the wealth indicator, the picture was less clear and particularly with respect to losses in human lives, the estimated coefficients tended to have the wrong signs. We concluded that the effects of education on reducing disaster vulnerability tended to be more pervasive than those of income/wealth in the case of floods and landslides in Nepal.

A Study on Relationship between Landslide forming mechanism and Climate Change since mid-Pleistocene in the upper Yellow River

Large-scale landslides in the Himalaya are defined as huge, deep-seated landslide masses that occurred in the geological past. They are widely distributed in the Nepal Himalaya. The steep topography and high local relief provide high potential for such failures, whereas the dynamic geology and adverse climatic conditions play a key role in the occurrence and reactivation of such landslides. The major geoscientific problems related with such large-scale landslides are 1) difficulties in their identification and delineation, 2) sources of small-scale failures, and 3) reactivation. Only a few scientific publications have been published concerning large-scale landslides in Nepal. In this context, the identification and quantification of large-scale landslides and their potential distribution are crucial. Therefore, this study explores the distribution of large-scale landslides in the Lesser Himalaya. It provides simple guidelines to identify large-scale landslides based on their typical characteristics and using a 3D schematic diagram. Based on the spatial distribution of landslides, geomorphological/geological parameters and logistic regression, an equation of large-scale landslide distribution is also derived. The equation is validated by applying it to another area. For the new area, the area under the receiver operating curve of the landslide distribution probability in the new area is 0.699, and a distribution probability value could explain > 65% of existing landslides. Therefore, the regression equation can be applied to areas of the Lesser Himalaya of central Nepal with similar geological and geomorphological conditions.

Rainfall-induced Landslides in Nepal

Rainfall-induced Landslides in Nepal

Trapped bedfellows: A comment on windle and neigher

Large-scale landslides in the Himalaya are defined as huge, deep-seated landslide masses that occurred in the geological past. They are widely distributed in the Nepal Himalaya. The steep topography and high local relief provide high potential for such failures, whereas the dynamic geology and adverse climatic conditions play a key role in the occurrence and reactivation of such landslides. The major geoscientific problems related with such large-scale landslides are 1) difficulties in their identification and delineation, 2) sources of small-scale failures, and 3) reactivation. Only a few scientific publications have been published concerning large-scale landslides in Nepal. In this context, the identification and quantification of large-scale landslides and their potential distribution are crucial. Therefore, this study explores the distribution of large-scale landslides in the Lesser Himalaya. It provides simple guidelines to identify large-scale landslides based on their typical characteristics and using a 3D schematic diagram. Based on the spatial distribution of landslides, geomorphological/geological parameters and logistic regression, an equation of large-scale landslide distribution is also derived. The equation is validated by applying it to another area. For the new area, the area under the receiver operating curve of the landslide distribution probability in the new area is 0.699, and a distribution probability value could explain > 65% of existing landslides. Therefore, the regression equation can be applied to areas of the Lesser Himalaya of central Nepal with similar geological and geomorphological conditions.