Effect of geological structures, rock weathering, and clay mineralogy in the formation of various landslides along Mugling-Narayanghat road section, Central Nepal Himalaya

The present study was conducted on the landslide prone area around Mugling-Narayanghat road section that consists of Lesser Himalayan and Siwaliks rocks. From more than 250 mapped landslides, ten were selected for detailed study that are supposed to the representative of the whole area. Detailed study showed that large and complex landslides are related to deep rock weathering followed by the intervention of geological structures as faults, joints, and fractures. Large landslides formed by gravitational deformation are related to the rock structures, while rock weathering plays a minor role. Rotational types of landslides are observed in weathered rocks, where the dip direction of the foliation plane plays a principle role. Shallow landslides are common in slopes covered by residual soil or colluviums. Some shallow landslides (rock topples) occur in less weathered rocks where the attitude of the foliation plays a major role, while others (rock plane failure) occur in cut slopes with less weathered rocks. Debris slides/flows occur in colluviums or residual soil covered slopes. In few instances, rock fall may occur on the upper slope, which then is mixed with the colluviums, residual soil, and other materials lying downhill and come down as debris flow. Rock falls are mainly related to the joint pattern and the slope angle and are found in less weathered rocks.ArticleJournal of the Faculty of Science Shinshu University 45: 1-44(2013)departmental bulletin pape

Effect of rock weathering, clay mineralogy, and geological structures in the formation of large landslide, a case study from Dumre Besei landslide, Lesser Himalaya Nepal

The Dumre Besi landslide is one of the largest and most problematic failures on the Mugling-Narayanghat Highway in central Nepal. Though it was triggered by the monsoon rain of 2003, geological structures and rock weathering have played a key role in its initiation and further aggravation. The slide is also controlled to some extent by the groundwater and rugged topography with high slope angles. The landslide zone comprises thinly laminated light grey siltstone with numerous crosscutting quartz veins, grey metasandstone (quartzite), bluish grey to white phyllite, black carbonaceous slate, and dolomite. A thrust fault passes through the centre of the landslide, creating a thick deposit of loose, weathered rock material, and the fault has developed a very thick shattered zone where weathering is very intense. Using field and laboratory analyses, the rocks in the landslide zone can be divided into five zones based on the severity of weathering: none, slight, moderate, severe, and complete. Laboratory analyses showed that the chemically weathered rocks are significantly rich in smectite and vermiculite. Out of these, smectite is the most critical one, as it swells when wet. The formation mechanism of the clay minerals was analysed by various techniques, including X-ray diffraction, X-ray fluorescence, and thin-section analysis, and it was found that most of them were derived from weathering of rock. The clay minerals significantly reduced the rock strength and facilitated the extensive failure of Dumre Besi. The wide fault zone with deeply weathered and clay-rich debris is also responsible for the formation of debris flows in the monsoon season.ArticleLANDSLIDES. 10(1):1-13 (2013)journal articl

Continental weathering in the Early Triassic in Himalayan Tethys, central Nepal: Implications for abrupt environmental change on the northern margin of Gondwanaland

The geochemistry of Triassic mudstones in the Himalayan Tethys sequence, central Nepal, was studied with respect to changes in sedimentary facies, grain size, and source rocks. The Triassic sedimentary facies of mudstone and carbonates show deposition in offshore to hemiplegic environments. The rare earth element (REE) pattern of the Permian and Triassic mudstones suggests uniformity correlatable to average shale. The major element geochemistry of the Early Triassic Griesbachian-early Smithian mudstones indicates a sediment supply from strongly weathered sources with the chemical index of alteration (CIA) values of 76–81. However, the mudstones in the late Smithian show weakly weathered sources with CIA values of 68–74. The lower part of the Middle Triassic Anisian mudstones return to Early Triassic paleoweathering levels. There are no significant relationships among lithofacies, the grain size of the sediments, and CIA values. Thus, the abrupt change of the degree of paleoweathering in the Early Triassic, late Smithian time, suggests a dramatic decrease in continental weathering, which is related to a predominantly arid climate in the northern marginal area of Gondwana.ArticleJOURNAL OF ASIAN EARTH SCIENCES.79, Part A:288-301(2014)journal articl

Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya

Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling-Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling-Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.ArticleNATURAL HAZARDS. 65(1):135-165 (2013)journal articl

Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya.

Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling–Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling–Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose

Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning

Rock toppling assessment at Mugling-Narayanghat road section: a case study from Mauri Khola landslide, Nepal

Mugling–Narayanghat road section in Nepal has suffered from a variety of slope failure including rockslides, rock topples, debris slide/flow, and some combination of these. Based on the prominent type of failure, the highway can be divided into three sections (a) Ch10 to Ch17 (dominated by shallow landslides and debris slides/flows), (b) Ch17 to Ch28 (dominated by large-scale, deep-seated landslides), and (c) Ch28 to Ch35 (dominated by rock topples). Rock topples are frequently observed along the highway, mainly on both the limbs of Jalbire Syncline as well as at the upstream of Maure Khola and some in Siwaliks. Slates, phyllites, quartzite, amphibolite and sandstones are affected by these topples. The Maure Khola landslide that is highly affected by rock toppling falls in Nourpoul Formation and consists of amphibolite, quartzite, and slate/phyllite. It lies at the upper reach of the Simaltal Thrust. Steep slopes characterize the upper slope, whose base is covered by thick debris forming a huge debris fan. According to the selected methodological approaches, data from detailed geological, geomorphological and geomechanical surveys, it is clear that these topples are mainly related to the geological structures of the region. Additionally, the landslide contains several sheared zones where the rocks are considerably weathered. These sheared zones act as the sliding plane. Also, the debris fan at the lower part suggests that the landslide has been reactivated several times in the past. Furthermore, it is seen that flexural toppling occurs in weak, mica-rich slate/phyllite at the upper slope, while block toppling is prominent in stronger amphibolites and quartzite lying in the central part

Weathering and mineralogical variation in gneissic rocks and their effect in Sangrumba Landslide, East Nepal

Sangrumba landslide is one of the largest and the most active landslides in Nepal Himalaya. Geologically the landslide belongs to the Higher Himalaya and consists of Pre-Cambrian biotite–garnet and sillimanite gneiss with some quartzite. The present paper aims at describing various degrees of rock weathering and their effect in Sangrumba landslide. Field study followed by mineralogical, geochemical and geotechnical analyses of the collected rock and soil samples from the landslide zone were used in characterizing weathering degree. The gneisses are intensely weathered while quartzite is unweathered. Petrographical and X-ray diffraction analyses showed that the rocks in the landslide zone had undergone weathering process with the formation of different types of clay minerals as kaolinite, vermiculite, smectite and chlorite. This was further confirmed by the Scan Electron Microscope and Energy Dispersive X-ray analyses. These clay minerals drastically reduced the rock strength facilitating the extensive failure of the Sangrumba landslide. The major and trace element composition of the rock and soil samples was calculated from the XRF analyses. The geochemical analyses and weathering indexes of rocks showed that they are significantly weathered and had a major influence in the formation of the Sangrumba landslide. In addition, mechanical strength measurement of rock/soil showed that the strength drastically decreases as the weathering intensity increases. Rainfall followed by the rock type are the most dominant parameters influencing the weathering process which leads to the formation of large landslide as the present one. These findings can be used in other areas with similar geological and topographical conditions

Landslide susceptibility mapping along Bhalubang-Shiwapur area of mid-Western Nepal using frequency ratio and conditional probability models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang-Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping (LSM) of this region was carried out using frequency ratio (FR) and weights-of-evidence (W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226 (70%) were randomly selected for model training and the remaining 106 (30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified and compared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region (W of E model (success rate = 83.39%, prediction rate = 79.59%); FR model (success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area