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Records of the Geological Survey of India

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Slope Stability And Stabilization Methods

During the Wenchuan Earthquake, with a magnitude of 5.12, collapses and rockfall hazards persisted for a long time after the initial investigations carried out by research fellow S. M. He and his team at the scene of the disaster in October 2008. It is possible that additional incidents of rockfalls in large quantities may continue in the same areas over the next ten to fifteen years. Furthermore, in the vast mountainous region of western China, the topographic relief is evident, and earthquakes occur frequently. Therefore, it is difficult to effectively defend against rockfall hazards. When designing protective structures, the key issue is the analysis of the mechanical response mechanism of the soil cushion layer of the upper cushion when subjected to the impact of rockfall. As such, a theoretical method was used to perform such an analysis. The cavity expansion and energy conservation model were adopted. Analytical solutions for the impact force and penetration depth were then derived. Furthermore, the impact force and penetration depth of rockfall were studied with the LS-DYNA software to obtain values for the impact forces and the penetration depth. Finally, the reliability of the theoretical method was evaluated using the cavity expansion, energy conservation, numerical simulation, Hertz, Japanese, Swiss, Australian, B. S. Guan, tunnel manual, and subgrade methods based on an engineering model. The results show that the cavity expansion and the energy conservation methods yielded consistent results. Meanwhile, the cavity expansion and the energy conservation methods also yielded consistent results with the numerical simulation, Japanese (obtained by laboratory experiment), Swiss (obtained by laboratory experiment), and Australian (obtained by field experiment) methods. The relevant methods and conclusions shall therefore be applied to the design of rockfall protection structure in future investigations.

https://downloads.hindawi.com/journals/ace/2018/9324956.pdf

Theoretical Analysis of Rockfall Impacts on the Soil Cushion Layer of Protective Structures

In this study, using Analytic Hierarchy Process (AHP) and Geographic Information System (GIS), the sensitivity to the occurrence of different types of droughts including meteorological drought (Med), hydrological drought (Hyd), and agricultural drought (Agd) were evaluated. In this research, at first, some of the effective indicators in each type of droughts were selected (four indicators in Med, three indicators in Hyd, and seven indicators in Agd), then using the ArcGIS 10.3 software, the sensitivity map of drought for each indicator were prepared (all indicators classified in four classes including mild, moderate, severe, and very severe). Then, using the AHP method the weight of each indicator in each type of droughts was determined and the final map of drought sensitivity for different types of droughts was prepared by superposition the maps of effective indicators in each drought. The final map of drought sensitivity was prepared by superposition the Med, Hyd, and Agd sensitivity maps (after determining the weight of each using AHP). In the Med, 43.29% of the study area (Fars province, Iran) was classified in the moderate class of drought sensitivity and 56.71% in the severe class. In the Hyd, 0.46%, 33.25%, 62.49%, and 3.80% of the study area were classified in the mild, moderate, severe, and very severe classes (respectively), and in the Agd, 1.18%, 50.23%, and 48.59% of the study area were classified in the mild, moderate, and severe classes. The results showed that in final drought sensitivity, the Med with a weight equal to 0.36 was the most effective variable, and based on the final map, 38.26% and 61.74% of the study area were classified in the moderate and severe classes of drought sensitivity.

Sensitivity Assessment to the Occurrence of Different Types of Droughts Using GIS and AHP Techniques

Hydrogeochemical assessment of carcinogenic and non-carcinogenic health risks of potentially toxic elements in aquifers of the Hindukush ranges, Pakistan: insights from groundwater pollution indexing, GIS-based, and multivariate statistical approaches

The Early Eocene Margalla Hill Limestone is well exposed in core of Hazara Kashmir Syntaxis. A section at Battlian is measured and sampled for paleontological studies, where its lower contact with Patala Formation and upper contact with Chorgali Formation is transitional and conformable. The total observed thickness is 73 meters and 60 samples were collected from bottom to top at different levels, 50 thin sections were studied. 19 species of larger forams including age diagnostic Nummulites mamillatus, Nummulites atacicus, Assilina spinosa, Assilina laminosa, Assilina granulosa, Assilina exponens, Textularia sp., Miliolid sp., Alveoloina pasticillata, Alveolina elliptica, Alveolina ovulum, Quinqueloculina, Discocyclina peruviana, Rotalia trochidiformis, Ranikothalia sindensis, Skeasaria ornata Nodosaria sp., Lockhartia tipper and Dasycladacean algae were also observed. In conclusions, presence of benthic foraminifera indicated that Margala Hill Limestone was deposited in Neotethys warm and shallow marine in the Battlian area Muzaffarabad, whereas early Eocene age is assigned on the basis of benthic foraminifera observed. .

Biostratigraphy of early eocene margala hill limestone in the muzaffarabad area (kashmir basin, azad jammu and kashmir)

Globally, and in Pakistan, among natural hazards, landslides are considered one of the most dangerous and frequently occurring events having devastating impacts on society and economy. The present study deals with the susceptibility mapping and detailed geological and geotechnical investigations on two large-scale landslides named Shahkot and Sandok, Lesser Himalayas, Pakistan. Inventory of 74 landslides was developed by SPOT-5 images and further classified in the field. The goodness of developed landslide susceptibility map was assessed by success rate curve (SRC) and prediction rate curve (PRC) which were 83.1% and 79.2%, respectively. Geotechnical investigations of selected landslides were carried out to identify the causative factors and landslide triggering mechanism. The Shahkot landslide is classified as complex (debris slide and slump failure), whereas the Sandok landslide is classified as rockslide. Laboratory testing, i.e., sieve analysis, Atterberg limits, specific gravity, and X-Ray Diffraction (XRD) analysis of the disturbed soil samples, reveal that the soils of Shahkot landslide are silty sand to clayey silty sand with plasticity index (PI) ranging from 2.05 to 14.96%. Petrographic studies showed that the schist and granite of the Shahkot and Sandok landslides contain quartz and feldspar with fair amounts of flaky minerals like chlorite, biotite, and muscovite. The XRD analysis showed mineral composition of quartz, muscovite, kaolinite, goethite, aragonite, hematite, plagioclase, siderite, montmorillonite, calcite, gypsum, orthoclase, dolomite, and illite. Intense jointing and fracturing in granite due to close proximity to faults imparts low unconfined compressive strength (UCS) values which holds the major cause of Sandok landslide beside other geomorphological and geological causes. The study depicts that drainage network, anthropogenic activities along steep slopes, fragile geology, active faults, freeze, and thaw action are influential parameters which significantly contribute to the landslide events.

Geotechnical investigation and landslide susceptibility assessment along the Neelum road: a case study from Lesser Himalayas, Pakistan

This paper presents an analysis of rockfall travel distance for incidents along the roads of the Abbottabad and Mansehra Districts, Khyber Pakhtunkhwa, Pakistan. Data for 121 rockfall events ranging from 100 m 3 to 10 000 m 3 volume were gathered during field investigations and used to facilitate an assessment of parameters such as height of fall, travel angle, travel distance and rockfall volume. The relationship between the height of fall and travel distance was investigated using well-established empirical approaches published in the literature. This analysis showed that travel angle decreased with increase in the rockfall volume, but that there was a weak correlation between the volume of rockfall and travel distance. A strong positive relationship between the travel distance and the height of fall was also identified. Comparison of the rockfall events identified during this study and existing data published from other regions in the world shows that the characteristics of the rockfalls are largely consistent with those identified by previous investigations. The study findings provide a useful set of data for empirical analyses that may be used for hazard and risk assessment in the region.

Effects of volume and topographic parameters on rockfall travel distance: a case study from NW Himalayas, Pakistan

Abstract Landslide predictive performance is expected to vary with different sampling techniques, such as landslide random and cluster sampling. Current advancements in remote sensing technologies and machine learning (ML) have enhanced landslide prediction performance. The Himalayan Mountain range in Pakistan poses an unadorned threat to the ecosystem and valley population because of landslide occurrence. The present study explores, and tests alternative sampling technique based on spatial pattern characterization in the wake of increased landslide prediction efficacy, rather than a renowned random technique for training and testing sampling. Thereupon, landslide inventory data with 17 geo-environmental factors (i.e. topographic, hydrological and seismic factors) were determined. Landslide cluster patterns were confirmed by the Nearest Neighbor Index (NNI) method and after getting the cluster patterns, the predicted performance of landslide sampling was tested using ML and statistical methods. Advanced ML algorithms including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Naive Bayes (NB), K-nearest Neighbors (KNN) and statistical methods including Weight-of-Evidence (WofE) and Logistic Regression (LR) were used and validated. The landslide-prone district of Azad Jammu and Kashmir (Neelum Valley), Kashmir Himalayas, Pakistan, was selected as a case study. Prediction performance rates are high with area under the curve (AUC) ranging from 0.802 to 0.912; accuracy (ACC) ranges from 0.78 to 0.89, and kappa ranges from 0.50 to 0.68 with cluster sampling technique, whereas the performance was low with random sampling technique, with AUC ranges from 0.768 to 0.895; ACC ranges from 0.74 to 0.86 and kappa ranges from 0.48 to 0.64. The descending order of accuracy of the six algorithms was XGboost, RF, KNN, NB, LR and WofE. Our results confirmed that the landslides followed cluster patterns in the study area, and ML algorithms with cluster training samples positively affected landslide susceptibility prediction with a statistically significant difference. The outcomes support the hypothesis that using landslides spatial natural existence, as training samples, instead of random concepts, improves the prediction ability; and highlights that alternative landslide partitioning technique could be a practicable and robust choice for landslides prediction modelling.

Yasir Sarfraz

Papers

Biostratigraphy of early eocene margala hill limestone in the muzaffarabad area (kashmir basin, azad jammu and kashmir)

Geotechnical investigation and landslide susceptibility assessment along the Neelum road: a case study from Lesser Himalayas, Pakistan

Effects of volume and topographic parameters on rockfall travel distance: a case study from NW Himalayas, Pakistan

Improvement of the predictive performance of landslide mapping models in mountainous terrains using cluster sampling

An integrated geotechnical and geophysical investigation of a catastrophic landslide in the Northeast Himalayas of Pakistan