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In recent decades, landslide disasters in the Himalayas, as in other mountain regions, are widely reported to have increased. While some studies have suggested a link to increasing heavy rainfall under a warmer climate, others pointed to anthropogenic influences on slope stability, and increasing exposure of people and assets located in harm’s way. A lack of sufficiently high-resolution regional landslide inventories, both spatially and temporally, has prevented any robust consensus so far. Focusing on Far-Western Nepal, we draw on remote sensing techniques to create a regional inventory of 26,350 single landslide events, of which 8778 date to the period 1992–2018. These events serve as a basis for the analyses of landslide frequency relationships and trends in relation to precipitation and temperature datasets. Results show a strong correlation between the annual number of shallow landslides and the accumulated monsoon precipitation (r = 0.74). Furthermore, warm and dry monsoons followed by especially rainy monsoons produce the highest incidence of shallow landslides (r = 0.77). However, we find strong spatial variability in the strength of these relationships, which is linked to recent demographic development in the region. This highlights the role of anthropogenic drivers, and in particular road cutting and land-use change, in amplifying the seasonal monsoon influence on slope stability. In parallel, the absence of any long-term trends in landslide activity, despite widely reported increase in landslide disasters, points strongly to increasing exposure of people and infrastructure as the main driver of landslide disasters in this region of Nepal. By contrast, no climate change signal is evident from the data.

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3.
The M w 7.8 2015 Gorkha earthquake and its aftershocks significantly impacted the lives and economy of Nepal. The consequences of landslides included fatalities, property losses, blockades of river flow, and damage to infrastructural systems. Co-seismic landslides triggered by this earthquake were significantly widespread and pose a major geodisaster. There were tens of thousands of landslides triggered by the earthquake, majority of which were distributed in between the epicenter of the main shock and the M w 7.3 aftershock. Although 14,670 landslides triggered by this earthquake were identified, only approximately 23% of them were of moderate to large scale with areas greater than 100 m2. Of the moderate- to large-scale landslides identified, just over 90% were triggered by the main shock and smaller aftershocks prior to the major (M w 7.3) aftershock, while nearly 10% were triggered by the ground shaking induced by the major aftershock. Moreover, the number of landslides triggered by the 2015 Gorkha earthquake, specifically by the main shock, was slightly more than the expected number of landslides for the recorded maximum peak ground acceleration (PGA) in comparison to the co-seismic landslides triggered by 26 earthquakes. Over 90% of those moderate- to large-scale landslides were concentrated within the estimated fault rupture surface. Majority of these moderate- to large-scale landslides were disrupted failures with over 96% of which were classified as earth falls. However, the majority of small-scale landslides were rock or boulder falls. The most number of moderate- to large-scale landslides were triggered in the slate, shale, siltstone, phyllite, and schist of the Lesser Himalayan formation followed by an equally significant number in both schist, gneiss, etc. of the Higher Himalayan formation and the phyllite, metasandstone, schist, etc. of the Lesser Himalayan formation. The sizes (i.e., areas) of the landslides were lognormally distributed, with a mode area of 322.0 m2. Slope inclinations of the moderate- to large-scale landslides followed a normal distribution with a mean slope inclination of 32.6° and standard deviation of 13.5°. There exists a strong correlation between the number of landslides and the peak ground acceleration within the study area, specific for different geological formations.  相似文献   
4.
Nepal was hit by a 7.8 magnitude earthquake on 25th April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Out of 3,716 mapped landslides, we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration (PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success rate of 87.66% and the prediction rate of 86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.  相似文献   
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The goal of this paper is to evaluate and compare the consistency of GIS-based heuristic and bivariate landslide susceptibility mapping techniques in the Himalayan region, taking the Kulekhani watershed of central Nepal as an example. For this purpose, a heuristic and two statistical bivariate landslide susceptibility mapping methods are applied, and three separate landslide susceptibility zonation maps are produced. The maps are compared using three approaches: landslide density analysis, success rate analysis, and agreed area analysis. A comparison of the values obtained from landslide density analysis and the curves of success rate analysis indicate that the two bivariate methods produce almost identical results, whereas the map produced with the heuristic method differs significantly from the others. On the other hand, the agreed area analysis highlights significant spatial differences in the maps obtained from the three methods. Although the three approaches evaluate the consistency of susceptibility maps, only the agreed area analysis is capable of spatially comparing them. Hence, this approach proves to be more suitable for spatially and quantitatively evaluating the consistency of various landslide susceptibility zonation maps.  相似文献   
6.
Mountainous areas in Nepal are prone to landslides, resulting in an enormous loss of life and property every year. As a first step towards mitigating or controlling such problems, it is necessary to prepare landslide susceptibility maps. Various methodologies have been proposed for landslide susceptibility mapping. This study applies the weight of evidence method to the Tinau watershed in west Nepal. A landslide susceptibility map is prepared on the basis of field observations and available data of geology, land use, topography and hydrology. Predicted susceptibility levels are found to be in good agreement with the locations of past landslides. The results show that about 30?% of the area is highly susceptible to landsliding. The present results provide useful information to the authorities concerning the landslide susceptibility zones and possible improvements for disaster management activities and sustainable development.  相似文献   
7.
Landslides cause extensive loss of life and property in the Nepal Himalaya. Since the late 1980s, different mathematical models have been developed and applied for landslide susceptibility mapping and hazard assessment in Nepal. The main goal of this paper is to apply fuzzy logic to landslide susceptibility mapping in the Ghurmi-Dhad Khola area, Eastern Nepal. Seven causative factors are considered: slope angle, slope aspect, distance from drainage, land use, geology, distance from faults and folds, soil and rock type. Likelihood ratios are obtained for each class of causative factors by comparison with past landslide occurrences. The ratios are normalized between zero and one to obtain fuzzy membership values. Further, different fuzzy operators are applied to generate landslide susceptibility maps. Comparison with the landslide inventory map reveals that the fuzzy gamma operator with a γ-value of 0.60 yields the best prediction accuracy. Consequently, this operator is used to produce the final landslide susceptibility zonation map.  相似文献   
8.
GIS-based landslide susceptibility maps for the Kankai watershed in east Nepal are developed using the frequency ratio method and the multiple linear regression technique. The maps are derived from comparing observed landslides with possible causative factors: slope angle, slope aspect, slope curvature, relative relief, distance from drainage, land use, geology, distance from faults and mean annual rainfall. The consistency of the maps is evaluated using landslide density analysis, success rate analysis and spatially agreed area approach. The first two analyses produce almost identical quantitative results, whereas the last approach is able to reveal spatial differences between the maps and also to improve predictions in the agreed high landslide-susceptible area.  相似文献   
9.
Landslides are one of the major natural disasters that occur in the Himalayan range with recurring frequency, causing enormous loss of life and property every year. Preparation of landslide inventory maps and landslide susceptibility zonation maps are the important tasks to be taken into account initially for safe mitigation measures. The present paper focuses on landslide susceptibility maps of the Ghurmi–Dhad Khola area, east Nepal, using Geographic Information System. For this purpose, the landslide susceptibility maps are prepared by using the heuristic and bivariate statistical methods. The parameters considered for the study are slope angle, slope aspect, elevation, distance from drainage, geology, land cover, rock and soil type, and distance from faults and folds. The landslide susceptibility zonation map produced from the heuristic method shows that 42.59 % of the observed landslide falls under the very high susceptible zone and 33.00 % under the high susceptible zone. Likewise, the landslide susceptibility zonation map produced from the bivariate method depicts that 44.19 % of the observed landslide falls under the very high susceptible zone and 31.59 % under the high susceptible zone. Both the landslide susceptibility zonation maps are identical, and success rates of both the maps are above 80 %. While comparing the landslide susceptibility maps obtained from two different methods, about 78 % of the study area falls in the identical susceptible zones. Special attention should be taken into consideration for the construction works in the areas which have been spatially agreed as very high and high susceptible zones from both techniques. Moreover, these maps can be used for slope management, land use planning, disaster management planning, etc., by the concerned authorities.  相似文献   
10.
Study on hydroclimatological changes in the mountainous river basins has attracted great interest in recent years. Changes in temperature, precipitation and river discharge pattern could be considered as indicators of hydroclimatological changes of the river basins. In this study, the temperatures （maximum and minimum）, precipitation, and discharge data from 1980 to 2009 were used to detect the hydroclimatological changes in the Bagmati River Basin, Nepal. Simple linear regression and Mann-Kendall test statistic were used to examine the significant trend of temperature, precipitation, and discharge. Increasing trend of temperature was found in all seasons, although the change rate was different in different seasons for both minimum and maximum temperatures. However, stronger warming trend was found in maximum temperature in comparison to the minimum in the whole basin. Both precipitation and discharge trend were increasing in the pre-monsoon season, but decreasing in the post-monsoon season. The significant trend of precipitation could not be observed in winter, although discharge trend was decreasing. Furthermore, the intensity of peak discharge was increasing, though there was not an obvious change in the intensity of maximum precipitation events. It is expected that all these changes have effects on agriculture, hydropower plant, and natural biodiversity in the mountainous river basin of Nepal.  相似文献   
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