Browsing by Author "Md Alquamar Azad"

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Association of landslides with geological structures and rainfall: a case study of two landslides in Sunkuda, Nepal
(Springer Science and Business Media B.V., 2025) Rabin Rimal; Megh Raj Dhital; Moti Lal Rijal; Rajesh Silwal; Vikas Yadav; Md Alquamar Azad; Ashutosh Kainthola
Nepal is home to numerous large landslides. These landslides emanate from both intrinsic and extrinsic factors. Though, prevalent in Himalaya, landslides resulting from underlying geological features are given lesser attention. The present research investigates the evolution and progression of two landslides from Sunkuda region, Western Nepal—and their association with the underlying geological structure. Two landslides, A, and B, from the study area present continuous downslope movement. In order to understand the causal factor, geological, geomorphological, and geophysical survey was conducted in the landslide affected area. Geotechnical attributes were obtained to understand the behaviour of the groundmass. Investigation led to the discovery of a thick band of shear zone nearly 35–40 m on the upper slope and 10–20 m on the lower slope, affecting the stability of the hill slope. Both landslides occur within the crushed zone of the thrust. The research found that the pore water transmitted through the developed shear zone increases the pore pressure and triggers failure. Intense monsoonal rainfall was observed and taken into consideration. Furthermore, the evidence indicates a major role played by the thrust fault behind the genesis and evolution of both landslides. It is also found that anthropogenic activities, gully erosion, and toe-cutting by the stream also had a crucial role in the evolution of landslides. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Efficiency of Classification Algorithms for Prediction of Rock Mass ÖNORM B Class in Himalayan Tunnelling
(Springer, 2025) Ashutosh Kainthola; Md Alquamar Azad; Abhishek Srivastav; Vikas Yadav; T. N. Singh; Vijay Dangwal
For underground excavation, accurate assessment of rock mass behaviour is imperative for a robust design of support system. For the ambitious, broad gauge rail link project in Uttarakhand Himalaya, India, apart from Q, and RMR, ÖNORM B system is being used for tunnel support recommendation. However, ÖNORM B system is qualitative in nature, and thus measurement of surrounding rock mass deformation is measured to designate the rock class. This approach is expensive and not often feasible. Therefore, present study attempts, perhaps for the first time, to quantify the prediction of ÖNORM B class of rock mass, using five easy to assess parameters. Two parameters from RMR, two from Q-system, and one common in both were used as inputs. Nine standard machine learning classifiers have been trained on 873 rows of data, and validated on 218 data points. Accuracy, precision, and ROC were evaluated for each classification algorithm. Results are quite promising with highest accuracy and precision in predicting the ÖNORM B class, delivered by Extra Tree, Random Forest, and Decision Tree classifiers. However, the authors recommend Extra Tree classifier since they are the least prone to overfitting and can be generalized. © The Author(s), under exclusive licence to Indian Geotechnical Society 2025.
Empirical and numerical hill slope health evaluation at Malling Nala, NH-505, Himachal Pradesh, India
(Springer, 2025) Md Alquamar Azad; Ashutosh Kainthola; Yewuhalashet Fissha; Gaurav Kumar Kushwaha; Vikas Yadav; T. N. Singh
Slope failures and rock mass movements are continuous geomorphic processes, particularly in a dynamically charged terrane like the Himalaya. Thus, failures emanating from weak geology, hydrogeology and anthropogenic disturbances are aplenty. Present research evaluates slope stability in the vicinity of Malling Nala, along NH-505 in Himachal Pradesh, India. For the two most vulnerable sections in the study area, geo-mechanical and structural attributes have initially been ascertained. Field surveys and laboratory tests identified weak and weathered mica schist and gneissic rocks in the study area. Kinematic analysis, Rock Mass Rating (RMR), Geological Strength Index (GSI), Slope Mass Rating (SMR), modified Global Slope Performance Index (mGSPI) led to determination of possible failure mechanism and rock mass behaviour. Finite element analysis provided a comprehensive understanding of slope behaviour under various conditions, highlighting significant shear strain and displacement in both sections. As noticed from the field and classification schemes, planar and localized bench failures were established. Slope section L-1 was found to collapse under saturated water condition, manifesting the influence of snow melt. The findings indicate that both natural and human factors are causing instability. Effective risk management and mitigation strategies are essential to maintain the stability and reliability of this critical frontier region. © The Author(s) 2025.
Towards sustainable sand resource management - Best governance practices and alternatives to river sand in India
(Springer, 2025) Ramesh Murlidhar Bhatawdekar; Edy Tonnizam Mohamad; T. N. Singh; Dato Hock Soon Chengong; Ashutosh Kainthola; Manoj Khandelwal; Feten Chihi; Vynotdni Rathinasamy; Clement Kweku Arthur; Anand Ravi Deshpande; Sanjay Nigam; Sangki Kwon; Rahul V. Ralegaonkar; Md Alquamar Azad
[No abstract available]