Geotechnical Investigation and Stability Assessment of Landslide-Prone Slopes along the Mugling-Narayanghat Highway of Nepal

Geotechnical Investigation and Stability Assessment of Landslide-Prone Slopes along the Mugling-Narayanghat Highway of Nepal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Geotechnical Investigation and Stability Assessment of Landslide-Prone Slopes along the Mugling-Narayanghat Highway of Nepal Santosh Banjara, Dipesh Jaisi Poudel, Buddhi Raj Joshi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8963324/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The Mugling-Narayanghat highway corridor in central Nepal is a major trade route frequently disrupted by rainfall induced landslides. This study presents a site-specific geotechnical investigation aimed at characterizing soil properties and assessing the stability of unstable sections along the corridor. Representative soil samples were collected from five active landslide locations (Chainages 16 + 600, 20 + 400, 32 + 300, 34 + 800, and 35 + 600) to determine particle size distribution, Atterberg limits, compaction characteristics, and shear strength parameters. Laboratory results classifies the slope materials as Non-Plastic (NP) soils, ranging from Well-Graded Gravels (GW) to Poorly Graded Sands (SP) and Well-Graded Sands (SW). These characteristics render the soil matrix highly permeable and susceptible to rapid shear strength loss upon saturation due to the absence of cohesive clay minerals. Shear strength parameters determined using direct shear tests yielded friction angles ranging from 26.1° to 29.1° and apparent cohesion values between 38.2 kPa and 102.5 kPa. Analytical factor of safety (FOS) calculations were performed to evaluate slope vulnerability under dry and saturated conditions. The assessment indicates that saturation reduces the FOS by approximately 30% to 36%, with values dropping below unity (FOS ranges from 0.89 to 0.96) in critical sections. These results quantitatively align with field observations of recurrent failures driven by monsoon rainfall and hydraulic forcing. Consequently, site-specific mitigation measures are proposed. This study demonstrates that index-property testing combined with analytical stability assessment provides a cost-effective framework for prioritizing maintenance in highway corridors with similar geotechnical conditions. Slope Stability Landslides Geotechnical Investigation Factor of Safety Mugling-Narayanghat Road Nepal Himalaya Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Landslides represent one of the most pervasive and destructive geophysical hazards globally, functioning as a primary agent of landscape evolution while posing severe risks to human settlements and critical infrastructure networks [ 1 , 2 ]. Historically, these mass movements were categorized as inevitable natural phenomena governed largely by geological predispositions and climatic cycles. However, recent global inventories indicate a significant statistical trend: the frequency and destructiveness of landslides have risen markedly over the past two decades. This upward trend correlates strongly with the combined effects of climate change-induced precipitation variability and rapid anthropogenic expansion into fragile mountain terrains [ 3 – 5 ]. The mechanics of this shift are driven by increasing hydrological extremes, where high-intensity rainfall events frequently exceed the pore-water pressure thresholds required to mobilize debris flows and shallow slides, particularly in tectonically active zones [ 6 – 8 ]. The Himalayan region presents a clear and representative example of this crisis. This region represents a highly dynamic and unstable tectonic regime shaped by the ongoing collision between the Indian and Eurasian plates. The resulting terrain is characterized by rapid uplift rates, high seismicity, and a lithology that is often fractured, weathered, and structurally complex [ 9 – 11 ]. Consequently, the physical landscape exists in a state of fragile equilibrium. This inherent geological fragility is compounded by the South Asian Monsoon, a climatic system that delivers approximately 80% of the region’s annual precipitation in a concentrated window between June and September [ 12 ]. These intense hydrological inputs act as the primary trigger for slope failures by rapidly saturating the soil profile, dissipating matric suction, and reducing the effective shear strength of slope materials [ 13 – 15 ]. Despite the overwhelming influence of these natural factors, contemporary research increasingly identifies human activity as a dominant variable in the modern landslide risk equation in Nepal. Specifically, the aggressive expansion of rural road networks has fundamentally altered the slope stability landscape [ 16 , 17 ]. In an effort to connect remote districts to markets and services, road construction frequently proceeds without adequate geotechnical foresight or engineering controls. This phenomenon is often termed the "bulldozer revolution" [ 18 ], characterizing a shift where mechanical excavation of steep hillslopes disturbs the natural equilibrium of ancient colluvial deposits. This process typically involves undercutting the toe of slopes and indiscriminately disrupting natural drainage corridors [ 19 – 22 ]. Empirical studies suggest that these non-engineered excavations now account for a significant proportion of sediment disasters in the country, effectively transforming transport corridors into linear hazard zones that threaten the sustainability of the infrastructure designed to strengthen development [ 23 , 24 ]. The Narayanghat-Mugling highway corridor serves as a clear example of this intersection between geological vulnerability and infrastructural stress. As a 36-kilometer strategic artery connecting the Terai plains to the capital city of Kathmandu and the tourist hub of Pokhara, the road is the economic lifeline of Nepal. It facilitates over 90% of the country’s cross-border freight traffic and supports a daily volume exceeding 10,000 vehicles [ 25 , 26 ]. Between 2015 and 2021, the corridor underwent a massive widening project to meet Asian Highway standards. While necessary for capacity enhancement, this expansion involved extensive hill cutting, exposing fresh, unweathered geological materials and loose soil masses to the direct environmental forces [ 27 , 28 ]. The removal of stabilizing vegetation and the alteration of slope geometry have left these sections highly susceptible to erosion and saturation. Consequently, the highway suffers from recurrent blockages, particularly along the hazardous Jalbire-to-Mugling segment. High-risk sites such as Tuin Khola, Mauri Khola and Namsi Bridge experience frequent rainfall-induced failures, causing cumulative closure times that result in severe disruptions to national supply chains and endanger road users safety [ 29 , 30 ]. Addressing these risks presents a persistent engineering challenge for concerned authorities. The current approach to risk management often relies on regional-scale hazard maps derived from satellite remote sensing. While useful for broad planning, these maps lack the site-specific resolution required to design effective retaining structures or drainage systems for specific curves in the road [ 31 – 33 ]. On the other end of the spectrum, comprehensive geotechnical investigations involving deep boreholes, extensive subsurface exploration, and advanced numerical modeling are often financially and technically unfeasible for the vast network of roads managed by developing nations [ 34 , 35 ]. There is a disconnect between high-level academic modeling and the practical, budgetary realities of road maintenance divisions. Engineers urgently require rigorous yet cost-effective assessment frameworks that occupy the middle ground. Analytical stability calculations based on fundamental soil index properties offer a viable solution. By quantifying parameters such as particle size distribution, compaction characteristics, and shear strength through standard laboratory testing, engineers can rapidly assess slope vulnerability without the need for prohibitive budgets. This approach focuses on understanding the material behavior, specifically how the Factor of Safety (FoS) degrades when the specific soil type found on site transitions from a dry to a saturated state [ 36 , 37 ]. This study aims to bridge the identified gap through a site-specific geotechnical investigation of the Mugling-Narayanghat corridor. Unlike regional studies that generalize geological features, this research characterizes the engineering properties of the specific soil materials found in active landslide zones. We analyze the influence of index properties on shear strength and utilize analytical factor of safety calculations to evaluate stability. By comparing stability metrics under dry conditions against those under saturated conditions, the study quantifies the precise reduction in stability driven by hydrological factors. The resulting data provides a scientific basis for targeted remedial measures establishing a practical framework for moving beyond reactive clearance toward proactive stabilization. 2. Study Area 2.1. Geographical Location and Physiography The research focuses on the Mugling-Narayanghat road corridor, a vital 36-km strategic highway located in the Chitwan District of the Narayani Zone, central Nepal. The alignment extends geographically from longitude 84°26’00’’E to 84°34’30’’E and latitude 27°45’30’’N to 27°51’30’’N as shown in Fig. 1 . The corridor traverses a rugged mountainous terrain with a sharp elevational gradient, rising from 200 meters above sea level (masl) at Jugedi Bajar to 1,380 masl near Mulethumki. Crucially, approximately two-thirds of the highway alignment runs parallel to the right bank of the Trishuli River. This geomorphological positioning makes the road slopes highly vulnerable to a dual instability mechanism i.e. hydraulic toe undercutting by the river during high-flow seasons and rapid debris deposition from steep hillslopes on the valley side [ 25 ]. 2.2. Geological and Tectonic Setting The study area lies within the tectonically active Lesser Himalayan zone, in close proximity to the Main Boundary Thrust (MBT). This major tectonic fault separates the sedimentary rocks of the Siwalik (Churia) Range from the metamorphic rocks of the Lesser Himalayas [ 9 ]. Consequently, the lithology along the corridor is highly heterogeneous and structurally disturbed. The slopes are dominated by sequences of sandstone, mudstone, slate, quartzite, phyllite, and dolomite, often interbedded with weak bands of graphitic schist [ 38 ]. Due to the active tectonic history, the rock mass is extensively fractured, weathered, and covered by loose colluvial soil deposits ranging from 2 to 8 meters in thickness. These colluvial soils possess low cohesive strength and are prone to saturation-induced failure [ 39 ]. 2.3. Climatic Conditions The corridor experiences a sub-tropical to temperate climate heavily influenced by the South Asian Monsoon. Meteorological records indicate that the region receives an average annual precipitation exceeding 2,000 mm. The spatial distribution of this rainfall is non-uniform, with orographic effects causing intense precipitation pockets. Approximately 80% of the annual volume is concentrated between June and September [ 40 ]. This intense seasonal hydrological input triggers rapid pore-water pressure buildup within the permeable colluvial slopes, acting as the primary catalyst for shallow landslides and debris flows in the region [ 13 ]. 2.4. Profile of Selected Study Zones To capture the lithological and structural heterogeneity of the corridor, five specific high-risk zones were identified for detailed investigation based on field reconnaissance. These sites represent distinct failure mechanisms ranging from hydraulic scour to anthropogenic slope destabilization. The soil samples collected from these zones are labeled as Sample 1 through Sample 5 to correspond with the laboratory testing program: Sample 1 (Chainage 32 + 300): This section exhibits active retrogressive sliding triggered by recent road widening. The slope is composed of loose, unconsolidated coarse colluvium where the mechanical excavation of the toe berm has removed lateral confinement, leaving the upper slope mass in a critical state of limit equilibrium. Sample 2 (Chainage 20 + 400 - Mauri Khola): Historically documented as a critical instability zone [ 26 ], this segment features a deep-seated debris flow channel. The slope morphology is concave, concentrating high-velocity surface runoff from the upper catchment. The material consists of a heterogeneous mixture of rock fragments and fines which are subjected to intense hydraulic scour during the monsoon. Sample 3 (Chainage 16 + 600): Located in a region with compromised natural drainage, this slope exhibits severe erosion. Visual inspection showed that unmanaged runoff flows directly over the slope, causing small underground channels and saturation zones, which is made worse by the intersection with groundwater table. The soil matrix appears fine-grained and erodible, lacking the coarse armor required to resist hydraulic shear stresses. Sample 4 (Chainage 34 + 800): This section is characterized by an extremely steep cut slope (> 55°) resulting from anthropogenic incision. Tension cracks running parallel to the road alignment suggest the onset of rotational failure. Although rock netting has been applied as a countermeasure, the underlying sandy soil-rock interface remains a critical plane of weakness. Sample 5 (Chainage 35 + 600): This site near Mugling often experiences shallow slope failures due to surface runoff and loose, dry soil masses. The slope material is visibly darker and looser, indicating an organic-rich sandy colluvium. The section is currently managed using temporary metal sheet piling, which shows signs of deformation due to active earth pressures. 3. Methodology This study adopted a deterministic geotechnical framework to evaluate the stability of colluvial slopes along the Mugling-Narayanghat highway corridor, integrating field-based hazard identification with laboratory characterization and analytical modeling. Given the geological heterogeneity of the Lesser Himalayas, a random sampling strategy was deemed statistically inefficient for hazard assessment; therefore, a purposive sampling strategy was employed to target specific zones exhibiting active instability markers such as tension cracks, fresh scarps, and toe erosion [ 24 , 25 ]. Based on these visual indicators and historical failure records, five high-risk sections were identified for detailed investigation at chainages 16 + 600, 20 + 400, 32 + 300, 34 + 800, and 35 + 600. At each selected site, test pits were excavated to a depth of 1.0 to 3.0 meters to retrieve material representative of the potential sliding mass. Approximately 30 kg of disturbed bulk samples were collected per site and immediately sealed in moisture-tight bags to prevent the loss of fines and preserve in-situ moisture content [ 41 ]. Disturbed sampling was necessitated by the coarse-grained, gravelly nature of the colluvium, which precludes the retrieval of undisturbed core samples [ 42 ]. 3.1. Laboratory Characterization The experimental program was executed in a standardized geotechnical laboratory in strict accordance with the Bureau of Indian Standards (IS) codes. Initially, physical and index properties were determined to classify the soil. Wet sieve analysis was performed following IS 2720 (Part 4): 1985 to determine the particle size distribution, a critical factor controlling pore-pressure transmission in the coarse Himalayan colluvium [ 43 , 44 ]. Concurrently, the Liquid Limit and Plastic Limit were determined using the Casagrande and thread rolling methods respectively, as per IS 2720 (Part 5): 1985. This testing was essential to characterize the fines fraction and distinguish between cohesive clay binders and non-plastic rock dust, as the latter is highly susceptible to rapid strength loss upon saturation [ 45 ]. Specific gravity was measured using the pycnometer method (IS 2720 Part 3) to facilitate accurate unit weight and void ratio calculations [ 46 ]. To simulate the field conditions of the slope materials, Standard Proctor tests were conducted following IS 2720 (Part 7): 1980 to determine the Maximum Dry Density (MDD) and Optimum Moisture Content (OMC). Testing loose or uncompacted soil would yield irrelevant strength data; therefore, all subsequent shear strength specimens were remolded to their specific MDD values to replicate the dense and consolidated state of the road embankment and natural slopes [ 47 ]. The effective shear strength parameters, specifically cohesion (c′) and angle of internal friction (ϕ′), were determined using the direct shear test in accordance with IS 2720 (Part 13): 1986. This method was selected over triaxial testing due to the coarse-grained, gravelly nature of the Mugling corridor soils, as direct shear apparatuses better accommodate larger particle sizes and enforce failure along a predetermined horizontal plane, effectively simulating the translational sliding mechanism observed in shallow landslides [ 48 – 50 ]. Remolded specimens were sheared under three distinct normal stresses of 136 kPa, 272 kPa, and 408 kPa. These stress levels were calculated to simulate the overburden pressure at depths of approximately 7m, 14m, and 20m to ensure the derived friction angle is representative of deep-seated conditions [ 51 ]. Strength parameters were derived from the linear regression of the Mohr-Coulomb failure envelope. 3.2. Analytical Stability Modeling To quantify slope vulnerability without the computational expense of complex numerical simulations, an analytical Limit Equilibrium approach was employed using the Infinite Slope Model. This model is mathematically rigorous for translational slides where the failure plane is parallel to the slope surface (L≫z), a geometric characteristic typical of shallow, rainfall-triggered landslides in the considered road sections [ 6 , 52 ]. The Factor of Safety (FoS) was calculated for two critical hydrological scenarios to quantify the destabilizing effect of the monsoon. First, a dry condition scenario was analyzed assuming the slope is unsaturated with no pore water pressure generation (u = 0), serving as the baseline stability metric. In this case, the resisting forces rely on the effective cohesion and the frictional component generated by the soil’s dry unit weight (γ d ) as given in Eq. ( 1 ). $${\text{F}\text{o}\text{S}}_{\text{d}\text{r}\text{y}}=\frac{{\text{c}}^{{\prime}}+{\gamma}\text{z}{\text{c}\text{o}\text{s}}^{2}{\beta}\text{t}\text{a}\text{n}{\upvarphi}{\prime}}{{\gamma}\text{z}\text{s}\text{i}\text{n}{\beta}\text{c}\text{o}\text{s}{\beta}}$$ 1 Second, a saturated condition scenario was modeled to simulate the peak monsoon event where the groundwater table rises to the slope surface and fully saturates the slip plane. This condition introduces pore water pressure (u), which reduces the effective normal stress holding the slope in place as given in Eq. ( 2 ) [ 53 ]. $${\text{F}\text{o}\text{S}}_{\text{s}\text{a}\text{t}}=\frac{{\text{c}}^{{\prime}}+({{\gamma}}_{\text{s}\text{a}\text{t}}\text{z}{\text{c}\text{o}\text{s}}^{2}{\beta}-\text{u})\text{t}\text{a}\text{n}{\upvarphi}{\prime}}{{{\gamma}}_{\text{s}\text{a}\text{t}}\text{z}\text{s}\text{i}\text{n}{\beta}\text{c}\text{o}\text{s}{\beta}}$$ 2 In these equations, c′ and ϕ′ are the effective shear strength parameters determined from laboratory testing, γ and γ sat are the dry and saturated unit weights derived from MDD and specific gravity, z represents the depth of the potential slip surface assumed as 3.0 m based on field observations, β is the slope angle measured during the field survey, and u is the pore water pressure calculated as γ w zcos 2 β. By comparing the FoS dry and FoS sat values, the percentage reduction in stability was quantified, providing a data-driven metric to prioritize mitigation measures [ 32 , 54 ]. 4. Results and Discussion 4.1. Site Observations and Failure Mechanisms Detailed field reconnaissance along the Mugling-Narayanghat corridor established a qualitative baseline for the geotechnical investigation, identifying slope instability as a product of complex interactions between anthropogenic hill cutting, geological weathering, and hydrological erosion. Visual assessments at the five selected high-risk zones, presented in Fig. 3 , confirmed that the removal of lateral toe support during recent road widening operations has reactivated ancient, meta-stable colluvial deposits. At chainage 32 + 300 (Sample 1), a massive debris slide is evident. The mechanical excavation of the soil in the toe region to accommodate the widened carriageway has removed existing support, triggering retrogressive failure within the loose, unconsolidated colluvium. Fresh scarp faces show that the slope is in active limit equilibrium, relying on temporary stability from matric suction that disappears during rainfall. The Mauri Khola section at chainage 20 + 400 (Sample 2) presents a distinct failure morphology characterized by a concave slope profile that concentrates surface runoff from the upper catchment. This hydrological concentration generates high-velocity streams that scour the embankment toe, resulting in debris flow characteristics with large boulders suspended in a fine-grained matrix. This observation aligns with the findings of previous studies [ 55 ], which reported that roadside slope failures are often triggered by the concentration of surface runoff in flash-surging gullies lacking adequate cross-drainage structures. At chainage 16 + 600 (Sample 3), the failure mechanism is driven primarily by inadequate drainage infrastructure. Water was observed cascading directly over the cut slope rather than through designated chutes, causing severe erosion and saturation of the pavement subgrade. This saturation reduces the effective stress in the near-surface soil layers, promoting shallow translational sliding in the cohesionless soil matrix. Further along at chainage 34 + 800 (Sample 4), tension cracks parallel to the road alignment are visible on an extremely steep cut slope (> 55°) in highly weathered rock. These tension features indicate the onset of rotational failure driven by the relaxation of lateral confinement. Although rock netting has been installed, the underlying soil-rock interface exhibits signs of detachment, suggesting that surficial protection is insufficient to arrest deep-seated movement. Finally, at chainage 35 + 600 (Sample 5), the visible deformation and buckling of temporary metal sheet piling suggest that the active earth pressures exerted by the sliding mass have exceeded the structural capacity of the current mitigation measures. These failures highlight that the temporary structures are insufficient to resist the immense forces exerted by landslides originating from very steep mountainous slopes. These observed instabilities are symptomatic of a systemic hazard regime where engineering interventions have disrupted the natural equilibrium. The primary driver of instability across all five sites is the geometric alteration of the slope; increasing the slope angle (β) beyond the material’s natural angle of repose has amplified the gravitational driving forces. These observations corroborate the findings of previous studies [ 25 ], which characterized the corridor’s instability as a function of rapid weathering amplified by anthropogenic toe undercutting. Furthermore, the state of the slopes reflects the "bulldozer revolution" effects where mechanical excavation disrupts ancient, stabilized colluvial deposits, resetting the landscape to a fresh, unstable state [ 18 ]. The structural distress observed at chainage 35 + 600 highlights the limitations of surficial stabilization when deep-seated structural defects are present, a challenge emphasized by past studies in the review of roads in difficult mountainous terrain [ 24 ]. 4.2. Sieve Analysis of Soil The laboratory characterization of particle size distribution provides the fundamental basis for classifying the slope materials and evaluating their hydraulic response in accordance with IS 1498:1970. The grain size distribution curves for all five sampling locations are superimposed in Fig. 4 , and the derived uniformity and curvature coefficients are summarized in Table 1 . The analysis reveals a distinct lithological transition along the corridor, distinguishing between gravel-dominated and sand-dominated zones based on the percentage retained on the 4.75 mm IS Sieve: Gravels (G): Samples 1 (Chainage 32 + 300) and 2 (Chainage 20 + 400) retain a significant coarse fraction, with approximately 60% of the material retained on the 4.75 mm sieve. Both samples exhibit Coefficients of Uniformity (Cu) greater than 4 and Coefficients of Curvature (Cc) between 1 and 3. According to IS 1498, these are classified as Well-Graded Gravel (GW). Sands (S): In contrast, the slope materials at Chainages 16 + 600 (Sample 3), 34 + 800 (Sample 4), and 35 + 600 (Sample 5) are dominated by the sand fraction, with over 80% of particles passing the 4.75 mm sieve. Samples 3 and 4 exhibit curvature coefficients (Cc) of 0.87 and 0.72, respectively. Since these values fall outside the IS 1498 range of 1 ≤ Cc ≤ 3, they indicate a "gap-graded" structure. These are classified as Poorly Graded Sand (SP). Sample 5 displays a smooth distribution curve with Cu = 23.3 and Cc = 2.74. Meeting the IS 1498 criteria for sands (Cu > 6 and 1 ≤ Cc ≤ 3), this sample is classified as Well-Graded Sand (SW). This classification highlights specific vulnerability mechanisms inherent to the soil structure. The Poorly Graded Sands (SP) found at Samples 3 and 4 are geotechnically the most critical. The gap-graded nature, defined by the low C c , implies a meta-stable skeletal structure with high porosity and a lack of intermediate particles to fill voids. Under monsoon conditions, these large interconnected pores allow rapid groundwater infiltration, leading to the quick saturation of the slope mass. Furthermore, these soils are susceptible to suffusion (internal erosion), where fine particles are washed out through the voids of the coarse matrix by seepage forces, progressively increasing the void ratio and leading to sudden volumetric collapse. This classification highlights specific vulnerability mechanisms inherent to the soil structure. The Poorly Graded Sands (SP) found at Samples 3 and 4 are geotechnically the most critical. The gap-graded nature, defined by the low C c , implies a meta-stable skeletal structure with high porosity and a lack of intermediate particles to fill voids. Under monsoon conditions, these large interconnected pores allow rapid groundwater infiltration, leading to the quick saturation of the slope mass. Furthermore, these soils are susceptible to suffusion (internal erosion), where fine particles are washed out through the voids of the coarse matrix by seepage forces, progressively increasing the void ratio and leading to sudden volumetric collapse. Table 1 Gradation Characteristics and IS 1498 Classification Sample Chainage % Gravel (> 4.75 mm) % Sand (< 4.75 mm) C u C c Classification (IS 1498) 1 32 + 300 59.9% 40.1% 13.2 1.75 Well-Graded Gravel 2 20 + 400 57.4% 42.6% 26.8 2.69 Well-Graded Gravel 3 16 + 600 19.8% 80.2% 4.00 0.87 Poorly Graded Sand 4 34 + 800 19.1% 80.9% 12.2 0.72 Poorly Graded Sand 5 35 + 600 0.0% 100.0% 23.3 2.74 Well-Graded Sand Even the Well-Graded Gravels (GW) at Samples 1 and 2 exhibit vulnerability. While they possess better particle interlocking, the IS 1498 classification of GW typically implies high permeability (k > 10 − 2 cm/s). In the absence of plastic fines to seal pores, this permeability allows rapid pressure transmission to the shear plane during intense rainfall bursts. These findings align with previous studies [ 56 ], which established that in soil-rock mixtures, mechanical behavior is governed by the packing density of the matrix; gap-graded mixtures often exhibit lower peak strength due to limited particle contact points. The identification of gap-graded sands at chainage 16 + 600 specifically validates the field observation of erosion, as loose, uniform sands lack the structural complexity to resist hydraulic shear stresses [ 57 ]. The superior performance of Sample 5, classified as Well-Graded Sand (SW), correlates with its field stability; the wider range of particle sizes facilitates denser packing and higher frictional resistance compared to the gap-graded slopes. 4.3. Specific Gravity Observations The specific gravity (G s ) tests, conducted using the pycnometer method, yielded values ranging from 2.607 to 2.751. These results provide critical insight into the mineralogical composition of the colluvial matrix. The data is summarized in Table 2 and visualized in Fig. 5 . Table 2 Specific gravity of samples Sample Chainage Specific Gravity (G s ) Inference 1 32 + 300 2.718 Heavy Inorganic Soil 2 20 + 400 2.751 Heavy Inorganic Soil 3 16 + 600 2.714 Heavy Inorganic Soil 4 34 + 800 2.663 Siliceous Sand 5 35 + 600 2.607 Organic/Micaceous Soil The variation in specific gravity reflects the heterogeneous lithology of the corridor. Samples 1, 2, and 3 exhibited high G s values (2.71–2.75). In the absence of plasticity, these high values are indicative of inorganic soils derived from heavy, iron-rich metamorphic parent rocks, such as phyllite and quartzite, which are prevalent in the Lesser Himalayas. Sample 4 yielded a value of 2.663, which is characteristic of clean quartzitic sands. Conversely, Sample 5 recorded the lowest specific gravity at 2.607. This lower value corroborates the field observations of organic-rich topsoil mixing with the colluvium at chainage 35 + 600, as organic matter typically has a specific gravity below 2.4, lowering the overall average. The specific gravity values align with the ranges reported by past studies [ 55 , 58 , 59 ] for Himalayan colluvial soils, confirming the samples are representative of the region’s weathered metasediments. While G s is an index property, it influences the unit weight and, consequently, the driving forces in slope stability calculations. The lower G s in Sample 5 suggests a material with potentially higher compressibility and susceptibility to volume changes under moisture variation [ 46 ]. However, the high G s values in the debris flow material at Mauri Khola (Sample 2) imply a denser, heavier soil matrix, which increases the mobilizeable mass during failure events, contributing to the high-impact forces observed in debris flows at this location. 4.4. Atterberg Limits and Consistency The consistency limits were determined on the soil fraction passing the 425-micron sieve to characterize the behavior of the fines. The results are summarized in Table 3 and the flow curves are presented in Fig. 6 . While the samples exhibited Liquid Limits (w L ) ranging from 17.0% to 23.5%, none of the samples could be rolled into a thread of 3 mm diameter without crumbling, even at moisture contents approaching the liquid limit. Consequently, the Plastic Limit could not be defined, and all five samples are classified as Non-Plastic (NP). The Non-Plastic (NP) nature of the soil is a critical geotechnical indicator of slope vulnerability. Plasticity in soils is typically generated by the electrochemical forces surrounding clay minerals (e.g., illite, montmorillonite), which provide true cohesion. The absence of plasticity in the Mugling-Narayanghat corridor samples confirms that the "fines" identified in the sieve analysis are inert rock flour (silt) produced by the physical pulverization of the parent metamorphic rocks (phyllite and quartzite), rather than chemical weathering products. Mechanistically, this implies that the shear strength of the soil matrix relies entirely on inter-particle friction and apparent cohesion (matric suction). In an unsaturated state, the capillary tension between these silt particles can create significant apparent strength, allowing steep cut slopes to remain stable during the dry season. However, upon saturation during the monsoon, this matric suction vanishes. Unlike clayey soils, which retain some cohesive strength when wet, these non-plastic silty gravels and sands undergo a rapid loss of effective stress, behaving essentially as a cohesionless fluid once the pores are saturated. Table 3 Atterberg Limits and Plasticity Characteristics Sample Chainage Liquid Limit Plastic Limit Plasticity Index Classification 1 32 + 300 23.0% NP NP Non-Plastic 2 20 + 400 21.0% NP NP Non-Plastic 3 16 + 600 20.0% NP NP Non-Plastic 4 34 + 800 17.0% NP NP Non-Plastic 5 35 + 600 23.5% NP NP Non-Plastic These results align with the findings of past studies [ 45 ], which established that the liquid limit of non-plastic silts is strictly a function of specific surface area and does not correlate with undrained shear strength in the same way as clays. The behavior observed here corroborates the "flow-slide" mechanism described by past studies [ 60 ], where non-plastic debris mobilizes rapidly into high-velocity flows due to the collapse of the soil structure upon wetting. Furthermore, prior research cautions that for non-plastic granular soils with low liquid limits (< 30%), long-term stability analysis should conservatively assume a zero cohesive intercept (c′ = 0) [ 48 ]. The low liquid limits observed in this study are characteristic of "Skeletal Soil," where the mechanical behavior is governed by the coarse fraction and the fines act only as a non-binding filler susceptible to suffusion under seepage forces [ 44 ]. 4.5. Maximum Dry Density and OMC Standard Proctor compaction tests (IS 2720 Part 7) were conducted to determine the compaction characteristics of the slope materials. The resulting moisture-density relationships are visualized in Fig. 7 , and the key parameters are summarized in Table 4 . Table 4 Compaction Characteristics of Soil Samples Sample Chainage Max Dry Density (MDD) [g/cm³] Optimum Moisture Content (OMC) [%] 1 32 + 300 2.26 6.8 2 20 + 400 2.22 8.7 3 16 + 600 2.18 11.5 4 34 + 800 2.19 12.8 5 35 + 600 2.14 9.0 The compaction curves reveal distinct behavior corresponding to the soil gradation. Sample 1 (Chainage 32 + 300), classified as Well-Graded Gravel (GW), achieved the highest Maximum Dry Density (MDD) of 2.26 g/cm³ at the lowest Optimum Moisture Content (OMC) of 6.80%. This indicates a highly efficient packing structure where gravel voids are effectively filled by sand, requiring minimal lubrication to achieve densification. Conversely, Sample 5 (Chainage 35 + 600) recorded the lowest MDD of 2.14 g/cm³ with an OMC of 9.00%. Despite being well-graded, this lower density reflects the lower specific gravity (G s = 2.607) and the presence of organic matter in the matrix, which inhibits dense packing. The gap-graded sands (Samples 3 and 4) exhibited intermediate behavior, with MDDs of 2.18–2.19 g/cm³ but significantly higher OMCs (11.50% and 12.80%), indicating a need for substantial water to lubricate the particle contacts for rearrangement. The maximum dry density serves as a proxy for the soil’s natural state of packing and its susceptibility to volume change. The lower MDD observed in Sample 5 and the gap-graded samples (3 and 4) suggests a looser skeletal structure with higher void ratios. In geotechnical terms, loose granular soils are highly susceptible to hydro-collapse (volumetric contraction) upon wetting. If the in-situ soil density is lower than the critical void ratio, saturation during the monsoon can trigger sudden liquefaction or flow-type failures, particularly under seismic loading or rapid drawdown conditions. Furthermore, the high OMCs observed in Samples 3 and 4 (11.5–12.8%) imply that these soils have a high affinity for water retention. In a slope setting, this capacity to hold water increases the unit weight of the sliding mass while simultaneously maintaining high pore-water pressures for longer durations after rainfall events, delaying drainage and prolonging the window of instability. From a remedial engineering perspective, these results dictate material suitability. The high-density, low-OMC material from Chainage 32 + 300 (Sample 1) is excellent for use as structural backfill in reinforced soil walls. In contrast, the materials from Chainages 16 + 600 and 34 + 800 are unsuitable for structural fill without modification or cement stabilization due to their water sensitivity and poor compaction characteristics. These findings align with past studies [ 47 ], which has demonstrated that the shear strength of gravelly soils is exponentially related to their relative density; thus, the lower MDD zones represent the weakest links in the corridor’s geotechnical profile. 4.6. Shear Strength Parameters The effective shear strength parameters, cohesion (c′) and angle of internal friction (ϕ′), were determined using large-scale Direct Shear tests (IS 2720 Part 13) on remolded specimens. Testing was conducted under normal stresses of 136 kPa, 272 kPa, and 409 kPa to simulate field overburden pressures. The failure envelopes for all five samples are superimposed in Fig. 8 , and the derived parameters are summarized in Table 5 . Table 5 Shear Strength Parameters (Direct Shear Test) Sample Chainage Apparent Cohesion (c′) (kPa) Friction Angle (ϕ′) (Degrees) 1 32 + 300 41.4 27.5 2 20 + 400 38.2 26.1 3 16 + 600 54.5 26.8 4 34 + 800 66.5 28.2 5 35 + 600 102.5 29.1 The analysis reveals a consistent range of frictional resistance across the corridor. Sample 2 (Mauri Khola) exhibited the lowest friction angle at 26.1°, correlating with its history as a persistent debris flow zone. Sample 5 (Chainage 35 + 600) yielded the highest friction angle of 29.1°, consistent with its classification as Well-Graded Sand (SW), where superior particle packing enhances inter-granular contact. The apparent cohesion values varied significantly, ranging from 38.2 kPa (Sample 2) to 102.5 kPa (Sample 5). It is imperative to note that given the Non-Plastic (NP) nature of these soils, this strength is not derived from chemical bonding. Instead, it represents apparent cohesion resulting from two mechanisms: matric suction (capillary tension) in the unsaturated state and particle interlocking (dilatancy) of the angular grains during shearing. Previous studies have [ 48 ] stated that this apparent cohesion is transient; while it maintains steep slopes in the dry season, it vanishes upon saturation. Therefore, the high cohesion value observed in Sample 5 (102.5 kPa) provides temporary stability that is liable to be lost during the monsoon, a behavior characteristic of the micaceous colluvium [ 61 ]. 4.7. Factor of Safety and Stability Analysis The stability of the selected slope sections was evaluated using the Infinite Slope Model, comparing the Factor of Safety (FoS) under dry and fully saturated conditions. The results are summarized in Table 6 and visually compared in Fig. 9 . Under Dry Conditions, all five slope sections exhibited an FoS greater than 1.25, theoretically indicating a stable state. This temporary stability is attributed to the high apparent cohesion (c′) provided by matric suction and particle interlocking in the unsaturated colluvium. However, the introduction of the Saturated Condition (simulating peak monsoon intensity) resulted in a drastic reduction in stability. Samples 1, 2, and 4 dropped below the critical equilibrium threshold (FoS < 1.0), indicating active failure. Sample 3 reduced to 1.08, representing a state of marginal stability with negligible safety margin. Sample 5 remained stable (FoS = 1.55), benefiting from its gentler slope angle (35°) and well-graded soil structure. The analysis quantifies the "false sense of security" provided by the dry season strength of these slopes. The most critical failure occurs at Mauri Khola (Sample 2), where the FoS drops to 0.89. This mathematically validates the field observation of recurrent debris flows; once the soil saturates, the resisting forces (friction) are overwhelmed by the driving forces (gravity + seepage pressure), leading to mobilization. For Sample 3 (Chainage 16 + 600), while the saturated FoS is technically above unity (1.08), it falls well below the standard design safety factor of 1.3 required for permanent highway slopes [ 35 ]. This implies that while the slope may not fail catastrophically during minor rains, it is highly susceptible to failure under any additional load, such as seismic acceleration or heavy traffic vibration. The mechanism driving this instability is the generation of positive pore-water pressure (u) and the simultaneous loss of apparent cohesion. The reduction in FoS ranges from 30% to 36% across the critical sections. These findings corroborate past findings [ 53 ], which identified that saturation ratio is the governing parameter for landslide initiation in the Himalayas. The data confirms that the primary trigger for landslides along the Mugling-Narayanghat corridor is hydraulic; the slopes are geometrically over-steepened relative to their saturated shear strength, relying on transient suction forces that dissipate during the monsoon. Table 6 Comparative Factor of Safety (FoS) Analysis Sample Chainage Slope Angle (β) FoS (Dry) FoS (Saturated) Stability Status (Wet) 1 32 + 300 40° 1.42 0.96 Unstable 2 20 + 400 42° 1.28 0.89 Critical Failure 3 16 + 600 38° 1.60 1.08 Marginally Stable 4 34 + 800 55° 1.46 0.94 Unstable 5 35 + 600 35° 2.34 1.55 Stable 5. Conclusion This study addressed the critical need for a site-specific geotechnical assessment of the Mugling-Narayanghat highway corridor, a strategic trade route in Nepal plagued by recurrent monsoon-triggered landslides. By integrating field reconnaissance with rigorous laboratory characterization and analytical stability modeling, the research elucidated the hydro-mechanical mechanisms driving slope instability in this tectonically active region. The following key conclusions are drawn: Laboratory analysis classifies the slope materials predominantly as non-plastic, granular colluvium (Well-Graded Gravels and Poorly Graded Sands). The absence of clay mineralogy indicates that these soils lack true chemical cohesion. Instead, they rely on inter-particle friction and transient apparent cohesion derived from matric suction, rendering them mechanically unstable upon wetting. Analytical modeling confirms that the primary trigger for slope failure is the loss of suction during saturation. The Factor of Safety drops by approximately 30 to 36 percent under saturated conditions, shifting critical sections such as Mauri Khola from a state of marginal stability to active failure (FoS = 0.89). This validates the hypothesis that rainfall-induced pore water pressure is the decisive destabilizing force. The findings substantiate the impact of unplanned road widening on infrastructure resilience. The aggressive toe cutting has steepened slopes beyond the saturated shear strength capacity of the cohesionless regolith, creating a landscape that is mechanically incapable of maintaining equilibrium during the monsoon season. Remedial strategies must shift from reactive debris clearance to proactive hydraulic management and structural confinement. The installation of deep horizontal drains to depress the phreatic surface is identified as the most effective intervention to preserve the apparent cohesion of these soils. Additionally, soil nailing is required to provide confinement for the loose, gap-graded slope faces found in steep cut sections. This research demonstrates that rapid, low-cost geotechnical indexing combined with simplified limit equilibrium analysis is a robust framework for identifying high-risk zones. This approach provides road authorities in developing nations with a cost-effective alternative to prohibitive deep-subsurface exploration for prioritizing maintenance resources. This study utilized the Infinite Slope Model, which assumes a translational failure mode and may oversimplify complex rotational slips in deep-seated landslides. Furthermore, laboratory tests were conducted on remolded samples, potentially altering the in-situ fabric of the colluvium. Future research should address these limitations by incorporating two-dimensional limit equilibrium methods or Finite Element Analysis to capture complex failure geometries and by utilizing undisturbed sampling techniques where feasible. 6. Recommendations Based on the geotechnical investigation, field observations, and analytical stability assessment, the following site-specific and strategic recommendations are proposed to mitigate landslide risks along the Mugling-Narayanghat highway corridor. 6.1. Site-Specific Engineering Countermeasures The remedial measures are tailored to the specific failure mechanisms identified at each chainage, distinguishing between slopes driven by hydraulic scour and those failing due to structural unraveling of loose gravel. In zones of Critical Instability (Chainages 32 + 300 & 34 + 800), the analysis indicates that these steep cut slopes consist of Well-Graded Gravels (GW) and Poorly Graded Sands (SP) with Factor of Safety (FoS) values dropping below 1.0 upon saturation. The lack of cohesion necessitates active structural reinforcement. Where right-of-way permits, slope cutting is recommended to reduce the gradient below the material’s internal friction angle (β < 26°) to achieve natural equilibrium. To compensate for the non-plastic nature of the soil, a Soil Nailing System is proposed to anchor the unstable surface wedge to stable bedrock. This should be combined with High-Tensile Rock Nets or fiber-reinforced Shotcrete to prevent the surficial unraveling of the loose gravel matrix. In zones of hydraulic vulnerability (Chainages 20 + 400 & 16 + 600), the Mauri Khola section (Sample 2) and Chainage 16 + 600 (Sample 3) exhibited the highest sensitivity to saturation, with stability governed by pore-water pressure. The installation of deep Horizontal Drains is critical to depress the phreatic surface within the slope. Lowering the water table is the most effective method to restore the apparent cohesion lost during the monsoon. To counteract toe erosion caused by high-velocity runoff, Mechanically Stabilized Earth (MSE) Embankments using geosynthetic reinforcement are recommended. MSE walls offer the necessary flexibility to accommodate differential settlements typical of gap-graded alluvial deposits found in these sections. In zone of Potential Instability (Chainage 35 + 600), although the analytical model indicates a stable Factor of Safety (FoS = 1.55), field observations revealed deformation in existing temporary structures. Current temporary metal sheet piles should be replaced with permanent gabion structures or gravity retaining walls to manage active earth pressures and prevent progressive shallow sloughing during extreme weather events. 6.2. Strategic and Procedural Recommendations To ensure the long-term resilience of the infrastructure, the following procedural guidelines are recommended for future maintenance and expansion projects: The current study relied on disturbed samples for index testing. Future investigations must prioritize Standard Penetration Tests (SPT) and, where feasible, undisturbed core sampling. This is essential to accurately determine in-situ density and stiffness profiles required for the detailed design of soil nails and MSE walls. Slope stabilization activities, particularly toe excavation, must be scheduled strictly during the dry season (October to May). Excavation during the monsoon, when the soil is saturated and matric suction is absent, significantly increases the risk of immediate, catastrophic failure. Given the active nature of the slides at Chainage 32 + 300 and Mauri Khola, the installation of piezometers to monitor pore-water pressure and extensometers to track slope displacement is recommended. Real-time monitoring data is vital for verifying the effectiveness of drainage interventions. Remedial civil works should be supplemented with bio-engineering. Deep-rooted vegetation (e.g., Vetiver grass) should be planted on slope faces (particularly at Chainage 16 + 600) to reduce surface erosion and enhance near-surface shear strength through root reinforcement. The countermeasure concepts proposed here must be subjected to rigorous detailed design. This includes numerical modeling (Finite Element Analysis) to verify the performance of these interventions under seismic loading conditions, which were not covered in the scope of this study. Declarations Author Contributions: S.B. led data collection, preparation, methodology development, analysis, and manuscript drafting. D.J.P. and B.R.J. contributed to model verification, data updating, and draft improvement. All authors have read and approved the published version. Competing Interest declaration: There are no Competing Interests. Use of Artificial Intelligence Tools: All scientific content, research design, data analysis, results interpretation, and substantive conclusions were developed independently by the authors. The AI tool served solely for editorial enhancement without contributing to intellectual content, methodological framework, or scientific conclusions. All AI-assisted text was reviewed, fact-checked, and revised by the authors. Data Availability Statement: Data including laboratory testing are available upon written request to the corresponding author. Acknowledgements: The first author acknowledges support from Pokhara University (Nepal) for providing the laboratory facility for the soil testing. Conflicts of Interest: The authors declare no personal or institutional conflicts of interest. Consent to Participate declaration: Not applicable. Ethics and Consent to Publish declarations: Not applicable. Clinical Trial Number: Not applicable. Concent to Publish: Not applicable. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8963324","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608618528,"identity":"8d031f8c-f2c7-4a97-b5e0-00dc05e05319","order_by":0,"name":"Santosh Banjara","email":"","orcid":"","institution":"School of Engineering, Faculty of Science and Technology, Pokhara University","correspondingAuthor":false,"prefix":"","firstName":"Santosh","middleName":"","lastName":"Banjara","suffix":""},{"id":608618529,"identity":"1600189a-eacd-440d-bab8-780baf516161","order_by":1,"name":"Dipesh Jaisi Poudel","email":"","orcid":"","institution":"School of Engineering, Faculty of Science and Technology, Pokhara University","correspondingAuthor":false,"prefix":"","firstName":"Dipesh","middleName":"Jaisi","lastName":"Poudel","suffix":""},{"id":608618530,"identity":"284ec8e3-947b-4a61-9b91-0a1078abe49e","order_by":2,"name":"Buddhi Raj Joshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYBACAyCSBpEMDAcSGBgbJOTAwjykaDEmUgsMMDYwJDYQ0mIukbzxdkEBQz5/44GHD3/usEjfLpHA+OBtG0OeOQ4tljPSiq1nGADpAweSjXnPSOTunJHAbDi3jaHYsgGHw27kmEnzGAAdeOBAmjRjm0TuhhsJbNK8bQyJGw4Q0CIP1CL5s00i3eBGAvtvorQYALVI8LZJJAC1sDHj02LZ86zYmsdAwsAQ7Jc2CcOdPQ+bJeeck0jcicMv5uzAEOP5Y2Mgd+NM4sOfbXXyQJGDH96U2SRuxxFiUCABRGcSIE4FxQ5IxAC/FiDgbz8A1QLzJkEto2AUjIJRMEIAALrqWw+lMxS3AAAAAElFTkSuQmCC","orcid":"","institution":"School of Engineering, Faculty of Science and Technology, Pokhara University","correspondingAuthor":true,"prefix":"","firstName":"Buddhi","middleName":"Raj","lastName":"Joshi","suffix":""}],"badges":[],"createdAt":"2026-02-25 05:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8963324/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8963324/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105039297,"identity":"a4a1cd1d-427b-4519-86bc-56bf3cf01e03","added_by":"auto","created_at":"2026-03-20 07:45:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":852121,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Area\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/172551ac33ccb873d8e75ac8.png"},{"id":105039359,"identity":"a2c02195-0c21-4f8d-a032-9352d8eaef09","added_by":"auto","created_at":"2026-03-20 07:46:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165460,"visible":true,"origin":"","legend":"\u003cp\u003eMethodology Framework\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/5ea2f9ddaf169130430608dc.png"},{"id":105039295,"identity":"40762540-e51b-47fa-bacc-ac5010be15c4","added_by":"auto","created_at":"2026-03-20 07:45:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":495508,"visible":true,"origin":"","legend":"\u003cp\u003eField photographs of the study zones showing instability features: a) Debris slide at chainage 32+300; b) Debris flow channel at chainage 20+400 (Mauri Khola); c) Surface erosion due to drainage failure at chainage 16+600; d) Tension cracks on steep cut slope at chainage 34+800; e) Deformation of retaining structure at chainage 35+600\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/c97e6c6087b09639753113b3.png"},{"id":105040502,"identity":"dd89f5be-f975-42e0-b649-e306292fbaf6","added_by":"auto","created_at":"2026-03-20 07:50:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":133044,"visible":true,"origin":"","legend":"\u003cp\u003eParticle size distribution curve of soil samples\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/1ba001da8704d1134c61fa0c.png"},{"id":105039364,"identity":"8b878347-e211-44b4-90d2-5a1275844880","added_by":"auto","created_at":"2026-03-20 07:46:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":135107,"visible":true,"origin":"","legend":"\u003cp\u003eSpecific Gravity of soil samples\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/7f9631a795f57bebba3a6630.png"},{"id":105039741,"identity":"300e9810-f2e4-4a42-bd42-e8b6e4797685","added_by":"auto","created_at":"2026-03-20 07:47:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":126392,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Curve\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/e9d1adccfaaee7d72333943a.png"},{"id":105039153,"identity":"ddee2b54-e1f3-437d-9fd1-adfaa33fadc6","added_by":"auto","created_at":"2026-03-20 07:45:11","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":249882,"visible":true,"origin":"","legend":"\u003cp\u003eCompaction Curves\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/ac10f0443fb3ab9ec7760e1a.png"},{"id":105039541,"identity":"6980cd1f-75ad-4205-adf6-490f2558de60","added_by":"auto","created_at":"2026-03-20 07:46:35","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":148851,"visible":true,"origin":"","legend":"\u003cp\u003eShear Strength Envelopes of samples\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/4a1c1389a0ffae82537eb56c.png"},{"id":105040038,"identity":"da0bd74b-59af-4cb9-aefb-7d837ada54cc","added_by":"auto","created_at":"2026-03-20 07:48:01","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":114661,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Factor of Safety (FoS) under Dry vs. Saturated conditions\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/ef7be18ec33871db14e23144.png"},{"id":105562748,"identity":"3168452f-47c2-4850-8e79-9553b8f9e102","added_by":"auto","created_at":"2026-03-27 12:44:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3481725,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8963324/v1/cbf6c76f-f6ac-4275-a6a6-44a782a06b8e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Geotechnical Investigation and Stability Assessment of Landslide-Prone Slopes along the Mugling-Narayanghat Highway of Nepal","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLandslides represent one of the most pervasive and destructive geophysical hazards globally, functioning as a primary agent of landscape evolution while posing severe risks to human settlements and critical infrastructure networks [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Historically, these mass movements were categorized as inevitable natural phenomena governed largely by geological predispositions and climatic cycles. However, recent global inventories indicate a significant statistical trend: the frequency and destructiveness of landslides have risen markedly over the past two decades. This upward trend correlates strongly with the combined effects of climate change-induced precipitation variability and rapid anthropogenic expansion into fragile mountain terrains [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The mechanics of this shift are driven by increasing hydrological extremes, where high-intensity rainfall events frequently exceed the pore-water pressure thresholds required to mobilize debris flows and shallow slides, particularly in tectonically active zones [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Himalayan region presents a clear and representative example of this crisis. This region represents a highly dynamic and unstable tectonic regime shaped by the ongoing collision between the Indian and Eurasian plates. The resulting terrain is characterized by rapid uplift rates, high seismicity, and a lithology that is often fractured, weathered, and structurally complex [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, the physical landscape exists in a state of fragile equilibrium. This inherent geological fragility is compounded by the South Asian Monsoon, a climatic system that delivers approximately 80% of the region\u0026rsquo;s annual precipitation in a concentrated window between June and September [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These intense hydrological inputs act as the primary trigger for slope failures by rapidly saturating the soil profile, dissipating matric suction, and reducing the effective shear strength of slope materials [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the overwhelming influence of these natural factors, contemporary research increasingly identifies human activity as a dominant variable in the modern landslide risk equation in Nepal. Specifically, the aggressive expansion of rural road networks has fundamentally altered the slope stability landscape [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In an effort to connect remote districts to markets and services, road construction frequently proceeds without adequate geotechnical foresight or engineering controls. This phenomenon is often termed the \"bulldozer revolution\" [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], characterizing a shift where mechanical excavation of steep hillslopes disturbs the natural equilibrium of ancient colluvial deposits. This process typically involves undercutting the toe of slopes and indiscriminately disrupting natural drainage corridors [\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Empirical studies suggest that these non-engineered excavations now account for a significant proportion of sediment disasters in the country, effectively transforming transport corridors into linear hazard zones that threaten the sustainability of the infrastructure designed to strengthen development [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Narayanghat-Mugling highway corridor serves as a clear example of this intersection between geological vulnerability and infrastructural stress. As a 36-kilometer strategic artery connecting the Terai plains to the capital city of Kathmandu and the tourist hub of Pokhara, the road is the economic lifeline of Nepal. It facilitates over 90% of the country\u0026rsquo;s cross-border freight traffic and supports a daily volume exceeding 10,000 vehicles [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Between 2015 and 2021, the corridor underwent a massive widening project to meet Asian Highway standards. While necessary for capacity enhancement, this expansion involved extensive hill cutting, exposing fresh, unweathered geological materials and loose soil masses to the direct environmental forces [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The removal of stabilizing vegetation and the alteration of slope geometry have left these sections highly susceptible to erosion and saturation. Consequently, the highway suffers from recurrent blockages, particularly along the hazardous Jalbire-to-Mugling segment. High-risk sites such as Tuin Khola, Mauri Khola and Namsi Bridge experience frequent rainfall-induced failures, causing cumulative closure times that result in severe disruptions to national supply chains and endanger road users safety [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAddressing these risks presents a persistent engineering challenge for concerned authorities. The current approach to risk management often relies on regional-scale hazard maps derived from satellite remote sensing. While useful for broad planning, these maps lack the site-specific resolution required to design effective retaining structures or drainage systems for specific curves in the road [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. On the other end of the spectrum, comprehensive geotechnical investigations involving deep boreholes, extensive subsurface exploration, and advanced numerical modeling are often financially and technically unfeasible for the vast network of roads managed by developing nations [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. There is a disconnect between high-level academic modeling and the practical, budgetary realities of road maintenance divisions.\u003c/p\u003e \u003cp\u003eEngineers urgently require rigorous yet cost-effective assessment frameworks that occupy the middle ground. Analytical stability calculations based on fundamental soil index properties offer a viable solution. By quantifying parameters such as particle size distribution, compaction characteristics, and shear strength through standard laboratory testing, engineers can rapidly assess slope vulnerability without the need for prohibitive budgets. This approach focuses on understanding the material behavior, specifically how the Factor of Safety (FoS) degrades when the specific soil type found on site transitions from a dry to a saturated state [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study aims to bridge the identified gap through a site-specific geotechnical investigation of the Mugling-Narayanghat corridor. Unlike regional studies that generalize geological features, this research characterizes the engineering properties of the specific soil materials found in active landslide zones. We analyze the influence of index properties on shear strength and utilize analytical factor of safety calculations to evaluate stability. By comparing stability metrics under dry conditions against those under saturated conditions, the study quantifies the precise reduction in stability driven by hydrological factors. The resulting data provides a scientific basis for targeted remedial measures establishing a practical framework for moving beyond reactive clearance toward proactive stabilization.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Geographical Location and Physiography\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe research focuses on the Mugling-Narayanghat road corridor, a vital 36-km strategic highway located in the Chitwan District of the Narayani Zone, central Nepal. The alignment extends geographically from longitude 84\u0026deg;26\u0026rsquo;00\u0026rsquo;\u0026rsquo;E to 84\u0026deg;34\u0026rsquo;30\u0026rsquo;\u0026rsquo;E and latitude 27\u0026deg;45\u0026rsquo;30\u0026rsquo;\u0026rsquo;N to 27\u0026deg;51\u0026rsquo;30\u0026rsquo;\u0026rsquo;N as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The corridor traverses a rugged mountainous terrain with a sharp elevational gradient, rising from 200 meters above sea level (masl) at Jugedi Bajar to 1,380 masl near Mulethumki. Crucially, approximately two-thirds of the highway alignment runs parallel to the right bank of the Trishuli River. This geomorphological positioning makes the road slopes highly vulnerable to a dual instability mechanism i.e. hydraulic toe undercutting by the river during high-flow seasons and rapid debris deposition from steep hillslopes on the valley side [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Geological and Tectonic Setting\u003c/h2\u003e \u003cp\u003eThe study area lies within the tectonically active Lesser Himalayan zone, in close proximity to the Main Boundary Thrust (MBT). This major tectonic fault separates the sedimentary rocks of the Siwalik (Churia) Range from the metamorphic rocks of the Lesser Himalayas [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consequently, the lithology along the corridor is highly heterogeneous and structurally disturbed. The slopes are dominated by sequences of sandstone, mudstone, slate, quartzite, phyllite, and dolomite, often interbedded with weak bands of graphitic schist [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Due to the active tectonic history, the rock mass is extensively fractured, weathered, and covered by loose colluvial soil deposits ranging from 2 to 8 meters in thickness. These colluvial soils possess low cohesive strength and are prone to saturation-induced failure [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Climatic Conditions\u003c/h2\u003e \u003cp\u003eThe corridor experiences a sub-tropical to temperate climate heavily influenced by the South Asian Monsoon. Meteorological records indicate that the region receives an average annual precipitation exceeding 2,000 mm. The spatial distribution of this rainfall is non-uniform, with orographic effects causing intense precipitation pockets. Approximately 80% of the annual volume is concentrated between June and September [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This intense seasonal hydrological input triggers rapid pore-water pressure buildup within the permeable colluvial slopes, acting as the primary catalyst for shallow landslides and debris flows in the region [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Profile of Selected Study Zones\u003c/h2\u003e \u003cp\u003eTo capture the lithological and structural heterogeneity of the corridor, five specific high-risk zones were identified for detailed investigation based on field reconnaissance. These sites represent distinct failure mechanisms ranging from hydraulic scour to anthropogenic slope destabilization. The soil samples collected from these zones are labeled as Sample 1 through Sample 5 to correspond with the laboratory testing program:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSample 1 (Chainage 32\u0026thinsp;+\u0026thinsp;300): This section exhibits active retrogressive sliding triggered by recent road widening. The slope is composed of loose, unconsolidated coarse colluvium where the mechanical excavation of the toe berm has removed lateral confinement, leaving the upper slope mass in a critical state of limit equilibrium.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 2 (Chainage 20\u0026thinsp;+\u0026thinsp;400 - Mauri Khola): Historically documented as a critical instability zone [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], this segment features a deep-seated debris flow channel. The slope morphology is concave, concentrating high-velocity surface runoff from the upper catchment. The material consists of a heterogeneous mixture of rock fragments and fines which are subjected to intense hydraulic scour during the monsoon.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 3 (Chainage 16\u0026thinsp;+\u0026thinsp;600): Located in a region with compromised natural drainage, this slope exhibits severe erosion. Visual inspection showed that unmanaged runoff flows directly over the slope, causing small underground channels and saturation zones, which is made worse by the intersection with groundwater table. The soil matrix appears fine-grained and erodible, lacking the coarse armor required to resist hydraulic shear stresses.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 4 (Chainage 34\u0026thinsp;+\u0026thinsp;800): This section is characterized by an extremely steep cut slope (\u0026gt;\u0026thinsp;55\u0026deg;) resulting from anthropogenic incision. Tension cracks running parallel to the road alignment suggest the onset of rotational failure. Although rock netting has been applied as a countermeasure, the underlying sandy soil-rock interface remains a critical plane of weakness.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 5 (Chainage 35\u0026thinsp;+\u0026thinsp;600): This site near Mugling often experiences shallow slope failures due to surface runoff and loose, dry soil masses. The slope material is visibly darker and looser, indicating an organic-rich sandy colluvium. The section is currently managed using temporary metal sheet piling, which shows signs of deformation due to active earth pressures.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study adopted a deterministic geotechnical framework to evaluate the stability of colluvial slopes along the Mugling-Narayanghat highway corridor, integrating field-based hazard identification with laboratory characterization and analytical modeling. Given the geological heterogeneity of the Lesser Himalayas, a random sampling strategy was deemed statistically inefficient for hazard assessment; therefore, a purposive sampling strategy was employed to target specific zones exhibiting active instability markers such as tension cracks, fresh scarps, and toe erosion [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Based on these visual indicators and historical failure records, five high-risk sections were identified for detailed investigation at chainages 16\u0026thinsp;+\u0026thinsp;600, 20\u0026thinsp;+\u0026thinsp;400, 32\u0026thinsp;+\u0026thinsp;300, 34\u0026thinsp;+\u0026thinsp;800, and 35\u0026thinsp;+\u0026thinsp;600. At each selected site, test pits were excavated to a depth of 1.0 to 3.0 meters to retrieve material representative of the potential sliding mass. Approximately 30 kg of disturbed bulk samples were collected per site and immediately sealed in moisture-tight bags to prevent the loss of fines and preserve in-situ moisture content [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Disturbed sampling was necessitated by the coarse-grained, gravelly nature of the colluvium, which precludes the retrieval of undisturbed core samples [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Laboratory Characterization\u003c/h2\u003e \u003cp\u003eThe experimental program was executed in a standardized geotechnical laboratory in strict accordance with the Bureau of Indian Standards (IS) codes. Initially, physical and index properties were determined to classify the soil. Wet sieve analysis was performed following IS 2720 (Part 4): 1985 to determine the particle size distribution, a critical factor controlling pore-pressure transmission in the coarse Himalayan colluvium [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Concurrently, the Liquid Limit and Plastic Limit were determined using the Casagrande and thread rolling methods respectively, as per IS 2720 (Part 5): 1985. This testing was essential to characterize the fines fraction and distinguish between cohesive clay binders and non-plastic rock dust, as the latter is highly susceptible to rapid strength loss upon saturation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Specific gravity was measured using the pycnometer method (IS 2720 Part 3) to facilitate accurate unit weight and void ratio calculations [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo simulate the field conditions of the slope materials, Standard Proctor tests were conducted following IS 2720 (Part 7): 1980 to determine the Maximum Dry Density (MDD) and Optimum Moisture Content (OMC). Testing loose or uncompacted soil would yield irrelevant strength data; therefore, all subsequent shear strength specimens were remolded to their specific MDD values to replicate the dense and consolidated state of the road embankment and natural slopes [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe effective shear strength parameters, specifically cohesion (c\u0026prime;) and angle of internal friction (ϕ\u0026prime;), were determined using the direct shear test in accordance with IS 2720 (Part 13): 1986. This method was selected over triaxial testing due to the coarse-grained, gravelly nature of the Mugling corridor soils, as direct shear apparatuses better accommodate larger particle sizes and enforce failure along a predetermined horizontal plane, effectively simulating the translational sliding mechanism observed in shallow landslides [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Remolded specimens were sheared under three distinct normal stresses of 136 kPa, 272 kPa, and 408 kPa. These stress levels were calculated to simulate the overburden pressure at depths of approximately 7m, 14m, and 20m to ensure the derived friction angle is representative of deep-seated conditions [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Strength parameters were derived from the linear regression of the Mohr-Coulomb failure envelope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Analytical Stability Modeling\u003c/h2\u003e \u003cp\u003eTo quantify slope vulnerability without the computational expense of complex numerical simulations, an analytical Limit Equilibrium approach was employed using the Infinite Slope Model. This model is mathematically rigorous for translational slides where the failure plane is parallel to the slope surface (L≫z), a geometric characteristic typical of shallow, rainfall-triggered landslides in the considered road sections [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The Factor of Safety (FoS) was calculated for two critical hydrological scenarios to quantify the destabilizing effect of the monsoon.\u003c/p\u003e \u003cp\u003eFirst, a dry condition scenario was analyzed assuming the slope is unsaturated with no pore water pressure generation (u\u0026thinsp;=\u0026thinsp;0), serving as the baseline stability metric. In this case, the resisting forces rely on the effective cohesion and the frictional component generated by the soil\u0026rsquo;s dry unit weight (γ\u003csub\u003ed\u003c/sub\u003e) as given in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$${\\text{F}\\text{o}\\text{S}}_{\\text{d}\\text{r}\\text{y}}=\\frac{{\\text{c}}^{{\\prime}}+{\\gamma}\\text{z}{\\text{c}\\text{o}\\text{s}}^{2}{\\beta}\\text{t}\\text{a}\\text{n}{\\upvarphi}{\\prime}}{{\\gamma}\\text{z}\\text{s}\\text{i}\\text{n}{\\beta}\\text{c}\\text{o}\\text{s}{\\beta}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eSecond, a saturated condition scenario was modeled to simulate the peak monsoon event where the groundwater table rises to the slope surface and fully saturates the slip plane. This condition introduces pore water pressure (u), which reduces the effective normal stress holding the slope in place as given in Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${\\text{F}\\text{o}\\text{S}}_{\\text{s}\\text{a}\\text{t}}=\\frac{{\\text{c}}^{{\\prime}}+({{\\gamma}}_{\\text{s}\\text{a}\\text{t}}\\text{z}{\\text{c}\\text{o}\\text{s}}^{2}{\\beta}-\\text{u})\\text{t}\\text{a}\\text{n}{\\upvarphi}{\\prime}}{{{\\gamma}}_{\\text{s}\\text{a}\\text{t}}\\text{z}\\text{s}\\text{i}\\text{n}{\\beta}\\text{c}\\text{o}\\text{s}{\\beta}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn these equations, c\u0026prime; and ϕ\u0026prime; are the effective shear strength parameters determined from laboratory testing, γ and γ\u003csub\u003esat\u003c/sub\u003e are the dry and saturated unit weights derived from MDD and specific gravity, z represents the depth of the potential slip surface assumed as 3.0 m based on field observations, β is the slope angle measured during the field survey, and u is the pore water pressure calculated as γ\u003csub\u003ew\u003c/sub\u003ezcos\u003csup\u003e2\u003c/sup\u003eβ.\u003c/p\u003e \u003cp\u003eBy comparing the FoS\u003csub\u003edry\u003c/sub\u003e and FoS\u003csub\u003esat\u003c/sub\u003e values, the percentage reduction in stability was quantified, providing a data-driven metric to prioritize mitigation measures [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Site Observations and Failure Mechanisms\u003c/h2\u003e \u003cp\u003eDetailed field reconnaissance along the Mugling-Narayanghat corridor established a qualitative baseline for the geotechnical investigation, identifying slope instability as a product of complex interactions between anthropogenic hill cutting, geological weathering, and hydrological erosion. Visual assessments at the five selected high-risk zones, presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, confirmed that the removal of lateral toe support during recent road widening operations has reactivated ancient, meta-stable colluvial deposits.\u003c/p\u003e \u003cp\u003eAt chainage 32\u0026thinsp;+\u0026thinsp;300 (Sample 1), a massive debris slide is evident. The mechanical excavation of the soil in the toe region to accommodate the widened carriageway has removed existing support, triggering retrogressive failure within the loose, unconsolidated colluvium. Fresh scarp faces show that the slope is in active limit equilibrium, relying on temporary stability from matric suction that disappears during rainfall.\u003c/p\u003e \u003cp\u003eThe Mauri Khola section at chainage 20\u0026thinsp;+\u0026thinsp;400 (Sample 2) presents a distinct failure morphology characterized by a concave slope profile that concentrates surface runoff from the upper catchment. This hydrological concentration generates high-velocity streams that scour the embankment toe, resulting in debris flow characteristics with large boulders suspended in a fine-grained matrix. This observation aligns with the findings of previous studies [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], which reported that roadside slope failures are often triggered by the concentration of surface runoff in flash-surging gullies lacking adequate cross-drainage structures.\u003c/p\u003e \u003cp\u003eAt chainage 16\u0026thinsp;+\u0026thinsp;600 (Sample 3), the failure mechanism is driven primarily by inadequate drainage infrastructure. Water was observed cascading directly over the cut slope rather than through designated chutes, causing severe erosion and saturation of the pavement subgrade. This saturation reduces the effective stress in the near-surface soil layers, promoting shallow translational sliding in the cohesionless soil matrix.\u003c/p\u003e \u003cp\u003eFurther along at chainage 34\u0026thinsp;+\u0026thinsp;800 (Sample 4), tension cracks parallel to the road alignment are visible on an extremely steep cut slope (\u0026gt;\u0026thinsp;55\u0026deg;) in highly weathered rock. These tension features indicate the onset of rotational failure driven by the relaxation of lateral confinement. Although rock netting has been installed, the underlying soil-rock interface exhibits signs of detachment, suggesting that surficial protection is insufficient to arrest deep-seated movement.\u003c/p\u003e \u003cp\u003eFinally, at chainage 35\u0026thinsp;+\u0026thinsp;600 (Sample 5), the visible deformation and buckling of temporary metal sheet piling suggest that the active earth pressures exerted by the sliding mass have exceeded the structural capacity of the current mitigation measures. These failures highlight that the temporary structures are insufficient to resist the immense forces exerted by landslides originating from very steep mountainous slopes.\u003c/p\u003e \u003cp\u003eThese observed instabilities are symptomatic of a systemic hazard regime where engineering interventions have disrupted the natural equilibrium. The primary driver of instability across all five sites is the geometric alteration of the slope; increasing the slope angle (β) beyond the material\u0026rsquo;s natural angle of repose has amplified the gravitational driving forces. These observations corroborate the findings of previous studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], which characterized the corridor\u0026rsquo;s instability as a function of rapid weathering amplified by anthropogenic toe undercutting. Furthermore, the state of the slopes reflects the \"bulldozer revolution\" effects where mechanical excavation disrupts ancient, stabilized colluvial deposits, resetting the landscape to a fresh, unstable state [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The structural distress observed at chainage 35\u0026thinsp;+\u0026thinsp;600 highlights the limitations of surficial stabilization when deep-seated structural defects are present, a challenge emphasized by past studies in the review of roads in difficult mountainous terrain [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Sieve Analysis of Soil\u003c/h2\u003e \u003cp\u003eThe laboratory characterization of particle size distribution provides the fundamental basis for classifying the slope materials and evaluating their hydraulic response in accordance with IS 1498:1970. The grain size distribution curves for all five sampling locations are superimposed in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and the derived uniformity and curvature coefficients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe analysis reveals a distinct lithological transition along the corridor, distinguishing between gravel-dominated and sand-dominated zones based on the percentage retained on the 4.75 mm IS Sieve:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eGravels (G): Samples 1 (Chainage 32\u0026thinsp;+\u0026thinsp;300) and 2 (Chainage 20\u0026thinsp;+\u0026thinsp;400) retain a significant coarse fraction, with approximately 60% of the material retained on the 4.75 mm sieve. Both samples exhibit Coefficients of Uniformity (Cu) greater than 4 and Coefficients of Curvature (Cc) between 1 and 3. According to IS 1498, these are classified as Well-Graded Gravel (GW).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSands (S): In contrast, the slope materials at Chainages 16\u0026thinsp;+\u0026thinsp;600 (Sample 3), 34\u0026thinsp;+\u0026thinsp;800 (Sample 4), and 35\u0026thinsp;+\u0026thinsp;600 (Sample 5) are dominated by the sand fraction, with over 80% of particles passing the 4.75 mm sieve.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSamples 3 and 4 exhibit curvature coefficients (Cc) of 0.87 and 0.72, respectively. Since these values fall outside the IS 1498 range of 1\u0026thinsp;\u0026le;\u0026thinsp;Cc\u0026thinsp;\u0026le;\u0026thinsp;3, they indicate a \"gap-graded\" structure. These are classified as Poorly Graded Sand (SP).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 5 displays a smooth distribution curve with Cu\u0026thinsp;=\u0026thinsp;23.3 and Cc\u0026thinsp;=\u0026thinsp;2.74. Meeting the IS 1498 criteria for sands (Cu\u0026thinsp;\u0026gt;\u0026thinsp;6 and 1\u0026thinsp;\u0026le;\u0026thinsp;Cc\u0026thinsp;\u0026le;\u0026thinsp;3), this sample is classified as Well-Graded Sand (SW).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis classification highlights specific vulnerability mechanisms inherent to the soil structure. The Poorly Graded Sands (SP) found at Samples 3 and 4 are geotechnically the most critical. The gap-graded nature, defined by the low C\u003csub\u003ec\u003c/sub\u003e, implies a meta-stable skeletal structure with high porosity and a lack of intermediate particles to fill voids. Under monsoon conditions, these large interconnected pores allow rapid groundwater infiltration, leading to the quick saturation of the slope mass. Furthermore, these soils are susceptible to suffusion (internal erosion), where fine particles are washed out through the voids of the coarse matrix by seepage forces, progressively increasing the void ratio and leading to sudden volumetric collapse.\u003c/p\u003e \u003cp\u003eThis classification highlights specific vulnerability mechanisms inherent to the soil structure. The Poorly Graded Sands (SP) found at Samples 3 and 4 are geotechnically the most critical. The gap-graded nature, defined by the low C\u003csub\u003ec\u003c/sub\u003e, implies a meta-stable skeletal structure with high porosity and a lack of intermediate particles to fill voids. Under monsoon conditions, these large interconnected pores allow rapid groundwater infiltration, leading to the quick saturation of the slope mass. Furthermore, these soils are susceptible to suffusion (internal erosion), where fine particles are washed out through the voids of the coarse matrix by seepage forces, progressively increasing the void ratio and leading to sudden volumetric collapse.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGradation Characteristics and IS 1498 Classification\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% Gravel (\u0026gt;\u0026thinsp;4.75 mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e% Sand (\u0026lt;\u0026thinsp;4.75 mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003csub\u003eu\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC\u003csub\u003ec\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eClassification (IS 1498)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWell-Graded Gravel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWell-Graded Gravel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePoorly Graded Sand\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePoorly Graded Sand\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWell-Graded Sand\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEven the Well-Graded Gravels (GW) at Samples 1 and 2 exhibit vulnerability. While they possess better particle interlocking, the IS 1498 classification of GW typically implies high permeability (k\u0026thinsp;\u0026gt;\u0026thinsp;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e cm/s). In the absence of plastic fines to seal pores, this permeability allows rapid pressure transmission to the shear plane during intense rainfall bursts.\u003c/p\u003e \u003cp\u003eThese findings align with previous studies [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], which established that in soil-rock mixtures, mechanical behavior is governed by the packing density of the matrix; gap-graded mixtures often exhibit lower peak strength due to limited particle contact points. The identification of gap-graded sands at chainage 16\u0026thinsp;+\u0026thinsp;600 specifically validates the field observation of erosion, as loose, uniform sands lack the structural complexity to resist hydraulic shear stresses [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The superior performance of Sample 5, classified as Well-Graded Sand (SW), correlates with its field stability; the wider range of particle sizes facilitates denser packing and higher frictional resistance compared to the gap-graded slopes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Specific Gravity Observations\u003c/h2\u003e \u003cp\u003eThe specific gravity (G\u003csub\u003es\u003c/sub\u003e) tests, conducted using the pycnometer method, yielded values ranging from 2.607 to 2.751. These results provide critical insight into the mineralogical composition of the colluvial matrix. The data is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecific gravity of samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecific Gravity (G\u003csub\u003es\u003c/sub\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeavy Inorganic Soil\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeavy Inorganic Soil\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeavy Inorganic Soil\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSiliceous Sand\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOrganic/Micaceous Soil\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe variation in specific gravity reflects the heterogeneous lithology of the corridor. Samples 1, 2, and 3 exhibited high G\u003csub\u003es\u003c/sub\u003e values (2.71\u0026ndash;2.75). In the absence of plasticity, these high values are indicative of inorganic soils derived from heavy, iron-rich metamorphic parent rocks, such as phyllite and quartzite, which are prevalent in the Lesser Himalayas. Sample 4 yielded a value of 2.663, which is characteristic of clean quartzitic sands. Conversely, Sample 5 recorded the lowest specific gravity at 2.607. This lower value corroborates the field observations of organic-rich topsoil mixing with the colluvium at chainage 35\u0026thinsp;+\u0026thinsp;600, as organic matter typically has a specific gravity below 2.4, lowering the overall average.\u003c/p\u003e \u003cp\u003eThe specific gravity values align with the ranges reported by past studies [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] for Himalayan colluvial soils, confirming the samples are representative of the region\u0026rsquo;s weathered metasediments. While G\u003csub\u003es\u003c/sub\u003e is an index property, it influences the unit weight and, consequently, the driving forces in slope stability calculations. The lower G\u003csub\u003es\u003c/sub\u003e in Sample 5 suggests a material with potentially higher compressibility and susceptibility to volume changes under moisture variation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, the high G\u003csub\u003es\u003c/sub\u003e values in the debris flow material at Mauri Khola (Sample 2) imply a denser, heavier soil matrix, which increases the mobilizeable mass during failure events, contributing to the high-impact forces observed in debris flows at this location.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Atterberg Limits and Consistency\u003c/h2\u003e \u003cp\u003eThe consistency limits were determined on the soil fraction passing the 425-micron sieve to characterize the behavior of the fines. The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and the flow curves are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. While the samples exhibited Liquid Limits (w\u003csub\u003eL\u003c/sub\u003e) ranging from 17.0% to 23.5%, none of the samples could be rolled into a thread of 3 mm diameter without crumbling, even at moisture contents approaching the liquid limit. Consequently, the Plastic Limit could not be defined, and all five samples are classified as Non-Plastic (NP).\u003c/p\u003e \u003cp\u003eThe Non-Plastic (NP) nature of the soil is a critical geotechnical indicator of slope vulnerability. Plasticity in soils is typically generated by the electrochemical forces surrounding clay minerals (e.g., illite, montmorillonite), which provide true cohesion. The absence of plasticity in the Mugling-Narayanghat corridor samples confirms that the \"fines\" identified in the sieve analysis are inert rock flour (silt) produced by the physical pulverization of the parent metamorphic rocks (phyllite and quartzite), rather than chemical weathering products.\u003c/p\u003e \u003cp\u003eMechanistically, this implies that the shear strength of the soil matrix relies entirely on inter-particle friction and apparent cohesion (matric suction). In an unsaturated state, the capillary tension between these silt particles can create significant apparent strength, allowing steep cut slopes to remain stable during the dry season. However, upon saturation during the monsoon, this matric suction vanishes. Unlike clayey soils, which retain some cohesive strength when wet, these non-plastic silty gravels and sands undergo a rapid loss of effective stress, behaving essentially as a cohesionless fluid once the pores are saturated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAtterberg Limits and Plasticity Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiquid Limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePlastic Limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlasticity Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-Plastic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-Plastic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-Plastic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-Plastic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-Plastic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese results align with the findings of past studies [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], which established that the liquid limit of non-plastic silts is strictly a function of specific surface area and does not correlate with undrained shear strength in the same way as clays. The behavior observed here corroborates the \"flow-slide\" mechanism described by past studies [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], where non-plastic debris mobilizes rapidly into high-velocity flows due to the collapse of the soil structure upon wetting. Furthermore, prior research cautions that for non-plastic granular soils with low liquid limits (\u0026lt;\u0026thinsp;30%), long-term stability analysis should conservatively assume a zero cohesive intercept (c\u0026prime; = 0) [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The low liquid limits observed in this study are characteristic of \"Skeletal Soil,\" where the mechanical behavior is governed by the coarse fraction and the fines act only as a non-binding filler susceptible to suffusion under seepage forces [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Maximum Dry Density and OMC\u003c/h2\u003e \u003cp\u003eStandard Proctor compaction tests (IS 2720 Part 7) were conducted to determine the compaction characteristics of the slope materials. The resulting moisture-density relationships are visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, and the key parameters are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCompaction Characteristics of Soil Samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMax Dry Density (MDD) [g/cm\u0026sup3;]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimum Moisture Content (OMC) [%]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe compaction curves reveal distinct behavior corresponding to the soil gradation. Sample 1 (Chainage 32\u0026thinsp;+\u0026thinsp;300), classified as Well-Graded Gravel (GW), achieved the highest Maximum Dry Density (MDD) of 2.26 g/cm\u0026sup3; at the lowest Optimum Moisture Content (OMC) of 6.80%. This indicates a highly efficient packing structure where gravel voids are effectively filled by sand, requiring minimal lubrication to achieve densification. Conversely, Sample 5 (Chainage 35\u0026thinsp;+\u0026thinsp;600) recorded the lowest MDD of 2.14 g/cm\u0026sup3; with an OMC of 9.00%. Despite being well-graded, this lower density reflects the lower specific gravity (G\u003csub\u003es\u003c/sub\u003e = 2.607) and the presence of organic matter in the matrix, which inhibits dense packing. The gap-graded sands (Samples 3 and 4) exhibited intermediate behavior, with MDDs of 2.18\u0026ndash;2.19 g/cm\u0026sup3; but significantly higher OMCs (11.50% and 12.80%), indicating a need for substantial water to lubricate the particle contacts for rearrangement.\u003c/p\u003e \u003cp\u003eThe maximum dry density serves as a proxy for the soil\u0026rsquo;s natural state of packing and its susceptibility to volume change. The lower MDD observed in Sample 5 and the gap-graded samples (3 and 4) suggests a looser skeletal structure with higher void ratios. In geotechnical terms, loose granular soils are highly susceptible to hydro-collapse (volumetric contraction) upon wetting. If the in-situ soil density is lower than the critical void ratio, saturation during the monsoon can trigger sudden liquefaction or flow-type failures, particularly under seismic loading or rapid drawdown conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the high OMCs observed in Samples 3 and 4 (11.5\u0026ndash;12.8%) imply that these soils have a high affinity for water retention. In a slope setting, this capacity to hold water increases the unit weight of the sliding mass while simultaneously maintaining high pore-water pressures for longer durations after rainfall events, delaying drainage and prolonging the window of instability.\u003c/p\u003e \u003cp\u003eFrom a remedial engineering perspective, these results dictate material suitability. The high-density, low-OMC material from Chainage 32\u0026thinsp;+\u0026thinsp;300 (Sample 1) is excellent for use as structural backfill in reinforced soil walls. In contrast, the materials from Chainages 16\u0026thinsp;+\u0026thinsp;600 and 34\u0026thinsp;+\u0026thinsp;800 are unsuitable for structural fill without modification or cement stabilization due to their water sensitivity and poor compaction characteristics. These findings align with past studies [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], which has demonstrated that the shear strength of gravelly soils is exponentially related to their relative density; thus, the lower MDD zones represent the weakest links in the corridor\u0026rsquo;s geotechnical profile.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Shear Strength Parameters\u003c/h2\u003e \u003cp\u003eThe effective shear strength parameters, cohesion (c\u0026prime;) and angle of internal friction (ϕ\u0026prime;), were determined using large-scale Direct Shear tests (IS 2720 Part 13) on remolded specimens. Testing was conducted under normal stresses of 136 kPa, 272 kPa, and 409 kPa to simulate field overburden pressures. The failure envelopes for all five samples are superimposed in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, and the derived parameters are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eShear Strength Parameters (Direct Shear Test)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApparent Cohesion (c\u0026prime;) (kPa)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFriction Angle (ϕ\u0026prime;) (Degrees)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe analysis reveals a consistent range of frictional resistance across the corridor. Sample 2 (Mauri Khola) exhibited the lowest friction angle at 26.1\u0026deg;, correlating with its history as a persistent debris flow zone. Sample 5 (Chainage 35\u0026thinsp;+\u0026thinsp;600) yielded the highest friction angle of 29.1\u0026deg;, consistent with its classification as Well-Graded Sand (SW), where superior particle packing enhances inter-granular contact. The apparent cohesion values varied significantly, ranging from 38.2 kPa (Sample 2) to 102.5 kPa (Sample 5). It is imperative to note that given the Non-Plastic (NP) nature of these soils, this strength is not derived from chemical bonding. Instead, it represents apparent cohesion resulting from two mechanisms: matric suction (capillary tension) in the unsaturated state and particle interlocking (dilatancy) of the angular grains during shearing. Previous studies have [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] stated that this apparent cohesion is transient; while it maintains steep slopes in the dry season, it vanishes upon saturation. Therefore, the high cohesion value observed in Sample 5 (102.5 kPa) provides temporary stability that is liable to be lost during the monsoon, a behavior characteristic of the micaceous colluvium [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.7. Factor of Safety and Stability Analysis\u003c/h2\u003e \u003cp\u003eThe stability of the selected slope sections was evaluated using the Infinite Slope Model, comparing the Factor of Safety (FoS) under dry and fully saturated conditions. The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and visually compared in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eUnder Dry Conditions, all five slope sections exhibited an FoS greater than 1.25, theoretically indicating a stable state. This temporary stability is attributed to the high apparent cohesion (c\u0026prime;) provided by matric suction and particle interlocking in the unsaturated colluvium. However, the introduction of the Saturated Condition (simulating peak monsoon intensity) resulted in a drastic reduction in stability.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSamples 1, 2, and 4 dropped below the critical equilibrium threshold (FoS\u0026thinsp;\u0026lt;\u0026thinsp;1.0), indicating active failure.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 3 reduced to 1.08, representing a state of marginal stability with negligible safety margin.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample 5 remained stable (FoS\u0026thinsp;=\u0026thinsp;1.55), benefiting from its gentler slope angle (35\u0026deg;) and well-graded soil structure.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe analysis quantifies the \"false sense of security\" provided by the dry season strength of these slopes. The most critical failure occurs at Mauri Khola (Sample 2), where the FoS drops to 0.89. This mathematically validates the field observation of recurrent debris flows; once the soil saturates, the resisting forces (friction) are overwhelmed by the driving forces (gravity\u0026thinsp;+\u0026thinsp;seepage pressure), leading to mobilization.\u003c/p\u003e \u003cp\u003eFor Sample 3 (Chainage 16\u0026thinsp;+\u0026thinsp;600), while the saturated FoS is technically above unity (1.08), it falls well below the standard design safety factor of 1.3 required for permanent highway slopes [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This implies that while the slope may not fail catastrophically during minor rains, it is highly susceptible to failure under any additional load, such as seismic acceleration or heavy traffic vibration.\u003c/p\u003e \u003cp\u003eThe mechanism driving this instability is the generation of positive pore-water pressure (u) and the simultaneous loss of apparent cohesion. The reduction in FoS ranges from 30% to 36% across the critical sections. These findings corroborate past findings [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], which identified that saturation ratio is the governing parameter for landslide initiation in the Himalayas. The data confirms that the primary trigger for landslides along the Mugling-Narayanghat corridor is hydraulic; the slopes are geometrically over-steepened relative to their saturated shear strength, relying on transient suction forces that dissipate during the monsoon.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Factor of Safety (FoS) Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"+\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChainage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSlope Angle (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFoS (Dry)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFoS (Saturated)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStability Status (Wet)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;+\u0026thinsp;300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnstable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCritical Failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMarginally Stable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e34\u0026thinsp;+\u0026thinsp;800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnstable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"+\" colname=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;+\u0026thinsp;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study addressed the critical need for a site-specific geotechnical assessment of the Mugling-Narayanghat highway corridor, a strategic trade route in Nepal plagued by recurrent monsoon-triggered landslides. By integrating field reconnaissance with rigorous laboratory characterization and analytical stability modeling, the research elucidated the hydro-mechanical mechanisms driving slope instability in this tectonically active region. The following key conclusions are drawn:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLaboratory analysis classifies the slope materials predominantly as non-plastic, granular colluvium (Well-Graded Gravels and Poorly Graded Sands). The absence of clay mineralogy indicates that these soils lack true chemical cohesion. Instead, they rely on inter-particle friction and transient apparent cohesion derived from matric suction, rendering them mechanically unstable upon wetting.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAnalytical modeling confirms that the primary trigger for slope failure is the loss of suction during saturation. The Factor of Safety drops by approximately 30 to 36 percent under saturated conditions, shifting critical sections such as Mauri Khola from a state of marginal stability to active failure (FoS\u0026thinsp;=\u0026thinsp;0.89). This validates the hypothesis that rainfall-induced pore water pressure is the decisive destabilizing force.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe findings substantiate the impact of unplanned road widening on infrastructure resilience. The aggressive toe cutting has steepened slopes beyond the saturated shear strength capacity of the cohesionless regolith, creating a landscape that is mechanically incapable of maintaining equilibrium during the monsoon season.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRemedial strategies must shift from reactive debris clearance to proactive hydraulic management and structural confinement. The installation of deep horizontal drains to depress the phreatic surface is identified as the most effective intervention to preserve the apparent cohesion of these soils. Additionally, soil nailing is required to provide confinement for the loose, gap-graded slope faces found in steep cut sections.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThis research demonstrates that rapid, low-cost geotechnical indexing combined with simplified limit equilibrium analysis is a robust framework for identifying high-risk zones. This approach provides road authorities in developing nations with a cost-effective alternative to prohibitive deep-subsurface exploration for prioritizing maintenance resources.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThis study utilized the Infinite Slope Model, which assumes a translational failure mode and may oversimplify complex rotational slips in deep-seated landslides. Furthermore, laboratory tests were conducted on remolded samples, potentially altering the in-situ fabric of the colluvium. Future research should address these limitations by incorporating two-dimensional limit equilibrium methods or Finite Element Analysis to capture complex failure geometries and by utilizing undisturbed sampling techniques where feasible.\u003c/p\u003e"},{"header":"6. Recommendations","content":"\u003cp\u003eBased on the geotechnical investigation, field observations, and analytical stability assessment, the following site-specific and strategic recommendations are proposed to mitigate landslide risks along the Mugling-Narayanghat highway corridor.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e6.1. Site-Specific Engineering Countermeasures\u003c/h2\u003e \u003cp\u003eThe remedial measures are tailored to the specific failure mechanisms identified at each chainage, distinguishing between slopes driven by hydraulic scour and those failing due to structural unraveling of loose gravel.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn zones of Critical Instability (Chainages 32\u0026thinsp;+\u0026thinsp;300 \u0026amp; 34\u0026thinsp;+\u0026thinsp;800), the analysis indicates that these steep cut slopes consist of Well-Graded Gravels (GW) and Poorly Graded Sands (SP) with Factor of Safety (FoS) values dropping below 1.0 upon saturation. The lack of cohesion necessitates active structural reinforcement. Where right-of-way permits, slope cutting is recommended to reduce the gradient below the material\u0026rsquo;s internal friction angle (β\u0026thinsp;\u0026lt;\u0026thinsp;26\u0026deg;) to achieve natural equilibrium. To compensate for the non-plastic nature of the soil, a Soil Nailing System is proposed to anchor the unstable surface wedge to stable bedrock. This should be combined with High-Tensile Rock Nets or fiber-reinforced Shotcrete to prevent the surficial unraveling of the loose gravel matrix.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn zones of hydraulic vulnerability (Chainages 20\u0026thinsp;+\u0026thinsp;400 \u0026amp; 16\u0026thinsp;+\u0026thinsp;600), the Mauri Khola section (Sample 2) and Chainage 16\u0026thinsp;+\u0026thinsp;600 (Sample 3) exhibited the highest sensitivity to saturation, with stability governed by pore-water pressure. The installation of deep Horizontal Drains is critical to depress the phreatic surface within the slope. Lowering the water table is the most effective method to restore the apparent cohesion lost during the monsoon. To counteract toe erosion caused by high-velocity runoff, Mechanically Stabilized Earth (MSE) Embankments using geosynthetic reinforcement are recommended. MSE walls offer the necessary flexibility to accommodate differential settlements typical of gap-graded alluvial deposits found in these sections.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIn zone of Potential Instability (Chainage 35\u0026thinsp;+\u0026thinsp;600), although the analytical model indicates a stable Factor of Safety (FoS\u0026thinsp;=\u0026thinsp;1.55), field observations revealed deformation in existing temporary structures. Current temporary metal sheet piles should be replaced with permanent gabion structures or gravity retaining walls to manage active earth pressures and prevent progressive shallow sloughing during extreme weather events.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e6.2. Strategic and Procedural Recommendations\u003c/h2\u003e \u003cp\u003eTo ensure the long-term resilience of the infrastructure, the following procedural guidelines are recommended for future maintenance and expansion projects:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe current study relied on disturbed samples for index testing. Future investigations must prioritize Standard Penetration Tests (SPT) and, where feasible, undisturbed core sampling. This is essential to accurately determine in-situ density and stiffness profiles required for the detailed design of soil nails and MSE walls.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSlope stabilization activities, particularly toe excavation, must be scheduled strictly during the dry season (October to May). Excavation during the monsoon, when the soil is saturated and matric suction is absent, significantly increases the risk of immediate, catastrophic failure.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGiven the active nature of the slides at Chainage 32\u0026thinsp;+\u0026thinsp;300 and Mauri Khola, the installation of piezometers to monitor pore-water pressure and extensometers to track slope displacement is recommended. Real-time monitoring data is vital for verifying the effectiveness of drainage interventions.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRemedial civil works should be supplemented with bio-engineering. Deep-rooted vegetation (e.g., Vetiver grass) should be planted on slope faces (particularly at Chainage 16\u0026thinsp;+\u0026thinsp;600) to reduce surface erosion and enhance near-surface shear strength through root reinforcement.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe countermeasure concepts proposed here must be subjected to rigorous detailed design. This includes numerical modeling (Finite Element Analysis) to verify the performance of these interventions under seismic loading conditions, which were not covered in the scope of this study.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e S.B. led data collection, preparation, methodology development, analysis, and manuscript drafting. D.J.P. and B.R.J. contributed to model verification, data updating, and draft improvement. All authors have read and approved the published version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest declaration:\u0026nbsp;\u003c/strong\u003eThere are no Competing Interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUse of Artificial Intelligence Tools:\u003c/strong\u003e All scientific content, research design, data analysis, results interpretation, and substantive conclusions were developed independently by the authors. The AI tool served solely for editorial enhancement without contributing to intellectual content, methodological framework, or scientific conclusions. All AI-assisted text was reviewed, fact-checked, and revised by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e Data including laboratory testing are available upon written request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The first author acknowledges support from Pokhara University (Nepal) for providing the laboratory facility for the soil testing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no personal or institutional conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and Consent to Publish declarations:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConcent to Publish:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e No supplementary material is required and available in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePetley D. 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B-Soil Plant Sci. - ACTA AGR SCAND SECT B-SOIL PL 59 (2009) 197\u0026ndash;207. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09064710802006021\u003c/span\u003e\u003cspan address=\"10.1080/09064710802006021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Slope Stability, Landslides, Geotechnical Investigation, Factor of Safety, Mugling-Narayanghat Road, Nepal Himalaya","lastPublishedDoi":"10.21203/rs.3.rs-8963324/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8963324/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Mugling-Narayanghat highway corridor in central Nepal is a major trade route frequently disrupted by rainfall induced landslides. This study presents a site-specific geotechnical investigation aimed at characterizing soil properties and assessing the stability of unstable sections along the corridor. Representative soil samples were collected from five active landslide locations (Chainages 16\u0026thinsp;+\u0026thinsp;600, 20\u0026thinsp;+\u0026thinsp;400, 32\u0026thinsp;+\u0026thinsp;300, 34\u0026thinsp;+\u0026thinsp;800, and 35\u0026thinsp;+\u0026thinsp;600) to determine particle size distribution, Atterberg limits, compaction characteristics, and shear strength parameters. Laboratory results classifies the slope materials as Non-Plastic (NP) soils, ranging from Well-Graded Gravels (GW) to Poorly Graded Sands (SP) and Well-Graded Sands (SW). These characteristics render the soil matrix highly permeable and susceptible to rapid shear strength loss upon saturation due to the absence of cohesive clay minerals. Shear strength parameters determined using direct shear tests yielded friction angles ranging from 26.1\u0026deg; to 29.1\u0026deg; and apparent cohesion values between 38.2 kPa and 102.5 kPa. Analytical factor of safety (FOS) calculations were performed to evaluate slope vulnerability under dry and saturated conditions. The assessment indicates that saturation reduces the FOS by approximately 30% to 36%, with values dropping below unity (FOS ranges from 0.89 to 0.96) in critical sections. These results quantitatively align with field observations of recurrent failures driven by monsoon rainfall and hydraulic forcing. Consequently, site-specific mitigation measures are proposed. This study demonstrates that index-property testing combined with analytical stability assessment provides a cost-effective framework for prioritizing maintenance in highway corridors with similar geotechnical conditions.\u003c/p\u003e","manuscriptTitle":"Geotechnical Investigation and Stability Assessment of Landslide-Prone Slopes along the Mugling-Narayanghat Highway of Nepal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 07:29:57","doi":"10.21203/rs.3.rs-8963324/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"209879958675940997346988599076812076601","date":"2026-05-03T00:35:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T12:42:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179557861202604262265738645745961891078","date":"2026-05-01T06:44:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T06:35:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42756295883626249270965727652979014879","date":"2026-03-19T04:52:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-18T08:48:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-16T11:07:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-04T07:12:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-04T07:07:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Geoscience","date":"2026-02-25T05:07:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d74beba-081e-45a6-b367-8b64cd5a1a9f","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"209879958675940997346988599076812076601","date":"2026-05-03T00:35:22+00:00","index":58,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T12:42:31+00:00","index":56,"fulltext":""},{"type":"reviewerAgreed","content":"179557861202604262265738645745961891078","date":"2026-05-01T06:44:28+00:00","index":54,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T07:29:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 07:29:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8963324","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8963324","identity":"rs-8963324","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}