Himalaya Research Articles

Frequent Glacial Hazard Deformation Detection Based on POT-SBAS InSAR in the Sedongpu Basin in the Himalayan Region

The Sedongpu Basin is characterized by frequent glacial debris movements and glacial hazards. To accurately monitor and research these glacier hazards, Sentinel-1 Synthetic Aperture Radar images observed between 2014 and 2022 were collected to extract surface motion using SBAS-POT technology. The acquired temporal surface deformation and multiple optical remote sensing images were then jointly used to analyze the characteristics of the long-term glacier movement in the Sedongpu Basin. Furthermore, historical meteorological and seismic data were collected to analyze the mechanisms of multiple ice avalanche chain hazards. It was found that abnormal deformation signals of glaciers SDP1 and SDP2 could be linked to the historical ice avalanche disaster that occurred around the Sedongpu Basin. The maximum deformation rate of SDP1 was 74 m/a and the slope cumulative deformation exceeded 500 m during the monitoring period from 2014 to 2022, which is still in active motion at present; for SDP2, a cumulative deformation of more than 300 m was also detected over the monitoring period. Glaciers SDP3, SDP4, and SDP5 have been relatively stable until now; however, ice cracks are well developed in SDP4 and SDP5, and ice avalanche events may occur if these ice cracks continue to expand under extreme natural conditions in the future. Therefore, this paper emphasizes the seriousness of the ice avalanche event in Sedongpu Basin and provides data support for local disaster management and disaster prevention and reduction.

First Report on Novel Multifunctional Plant Growth Promoting Bacterium Sporosarcina globispora EU-GRN-46 from Himalayan Region of Kinnaur and Their Role on Growth Promotion of Garlic (Allium sativum L.)

First Report on Novel Multifunctional Plant Growth Promoting Bacterium Sporosarcina globispora EU-GRN-46 from Himalayan Region of Kinnaur and Their Role on Growth Promotion of Garlic (Allium sativum L.)

Spectrum of Non-Traumatic Hollow Viscus Perforation in a Himalayan Population: A 3-Year Retrospective Study

Non-traumatic hollow viscus perforation (NT-HVP) is a common surgical emergency, often resulting in high morbidity and mortality rates. This study examines the epidemiology, aetiology, clinical presentations, and outcomes of NT-HVP among patients in the Himalayan region, by reviewing data from the Indira Gandhi Medical College (IGMC) Surgery Department, Shimla, between 2015 and 2018. A total of 274 cases were analysed. The most common cause of the problem was peptic ulcer disease and the study area had challenges like difficult terrain and limited access to healthcare. The findings aim to improve the understanding of NT-HVP in resource-limited settings and provide insights for better management strategies.

Long‐term time‐dependent deformation and stability analysis of the machine hall of an underground powerhouse cavern using microseismic monitoring

AbstractThe geomechanical behaviour of the main tunnel of an underground powerhouse structure in the Himalayan region after its construction is a challenge for the geotechnical experts due to the issues of time‐dependent deformation and failure of the rock mass support system. The machine hall of the underground powerhouse of Tala Hydropower Plant facing such issues needs demarcation of the failure zone in advance, as well as parameters to assist in the proper support redesign using a real‐time continuous monitoring system. Seismic source parameters deduced using a three‐dimensional microseismic monitoring network at this powerhouse cavern provide information on the deformation zone in the machine hall and its stability status using spatio‐temporal analysis of seismic potency displacement, Gutenberg–Richter relation and log–log (energy–moment) relationship. Sectional analysis demarcates the deformation zone in the upstream and downstream wall of the machine hall and planar analysis at regular intervals of the machine hall has provided a path of propagation of deformation. This analysis has helped to increase the stability of this underground powerhouse, and the same methodology may be applied to other underground structures for marking their deformation zone to increase their long‐term stability in the Himalayan region.

Landslide susceptibility assessment for Uttarakhand, a Himalayan state of India, using multi-criteria decision making, bivariate, and machine learning models

BackgroundLandslides, among the most catastrophic natural hazards, result from natural and anthropogenic factors, causing substantial financial losses, infrastructural damage, fatalities, and environmental degradation. Uttarakhand, with its unique topographical and hydrological conditions, unplanned human settlements, and changing precipitation patterns, is highly susceptible to landslides.MethodsThis study evaluates landslide susceptibility for Uttarakhand, a Himalayan state in India, by employing bivariate analysis, multi-criteria decision-making, and advanced machine learning models, such as Random Forest and Extreme Gradient Boosting (XGBoost). A total of sixteen landslide influencing factors were used for performing landslide hazard susceptibility zonation, including the innovative use of geomorphons for detailed terrain analysis.ResultsApproximately 18.47% of the study area was classified as high to very high landslide susceptibility zones, and 21% was classified into the moderate susceptibility category. High to very high susceptibility zones were concentrated in the Uttarkashi, Chamoli, and Pithoragarh districts of the Lesser and Higher Himalayas, areas characterized by rangelands and high annual rainfall. Conversely, very low to low susceptibility zones were predominantly located in the Tarai-Bhabar and Sub-Himalayan districts, including Haridwar and Udham Singh Nagar. The Random Forest and XGBoost models demonstrated superior predictive performance.ConclusionsThe spatially explicit landslide susceptibility maps provide critical insights for urban planners, disaster management agencies, and environmentalists, aiding in developing effective strategies for landslide risk reduction and promoting sustainable development in Uttarakhand. This study exemplifies applying advanced analytical techniques to address landslide susceptibility and related soil erosion and water resource management challenges in Uttarakhand.

Trillium govanianum (Nagchattri): A promising rare and commercially important medicinal herb from higher altitudes of the Himalayas

Secondary metabolites and bioactive compounds derived from naturally occurring sources have been the prime ingredients in modern health care as well as ancient medicine systems like Ayurveda, Yunani, and traditional folk medicines. A large number of plant species and their extracts are utilized to cure several human ailments. Trillium govanianum, belonging to the genus Trillium (family: Melanthiaceae alt. Trilliaceae), is a traditional medicinal herb of the Himalayan region used to cure joint pains, wounds, boils, dysentery, inflammation, menstrual and sexual disorders. T. govanianum root extracts have analgesic, anti-inflammatory, cancer-preventing, anti-fungal, and wound-healing activities. The main bioactive compounds present in this species are steroidal saponins. Indiscriminate and commercial harvesting in an unsustainable manner, along with various other biotic pressures, have created a synergistically severe menace toward the subsistence of T. govanianum in its natural habitat. Population assessment, conservative and in vitro proliferation methods pertaining to mass multiplication and advancement in ex–situ and in–situ environments are required for sustainable use of this species. In lieu of the significance of this herb, the present study aims at the exploration of phytochemical, ethnomedicinal, ecological, pharmacological, and conservational practices of T. govanianum for a better understanding of medicinal activities and sustainable use of this plant. This review summarised the potential resources of T. govaninanum in terms of biologically active compounds and their dependence on the local population. It focuses on the medicinal utility of T. govaninanum in different diseases and ailments.

Tree diversity, carbon sequestration and production potential of Oryza sativa L. in traditional agroforestry systems of Garhwal Himalaya, India

Agroforestry is an alternative land use practice that holds promise for societal benefits and the attainment of ecosystem sustainability. The objectives of this study were to evaluate the tree diversity, carbon sequestration, soil carbon pool, oxygen production and rice productivity under traditional agroforestry systems at different elevations in the Garhwal Himalayan region of India. Tree diversity, carbon sequestration and oxygen production were quantified by field measurements (using 0.04 ha quadrats) and subsequent calculations. Rice productivity was assessed using grain yield, straw yield and biological yield, while soil properties were analyzed in the laboratory using standard methods. Results of the study showed that tree diversity was higher at the 1200–1600 m elevation and had a maximum Shannon Diversity Index (1.29) and Simpson Diversity Index (0.69). The 1600–2000 m elevation stored more carbon (34.43 Mg ha−1) and total oxygen production (91.79 Mg ha−1). Among the agroforestry trees, Quercus leucotrichophora, Melia azedarach and Prunus cerasoides showed the highest carbon storage and total oxygen production. Elevation and soil depth were found to affect the soil properties. The agroforestry systems had higher soil organic carbon and lower bulk density than sole cropping systems. Compared to the agroforestry system, the monoculture produced more rice (Oryza sativa). The study shows that traditional agroforestry is a valuable tool for carbon sequestration and soil improvement, albeit with potential compromises in crop productivity. It emphasises the need for tailored management approaches to harness the ecological and environmental benefits of agroforestry in the Himalayas. This study draws attention to the potential of traditional agroforestry in the Garhwal Himalaya for carbon sequestration, climate change mitigation and soil quality improvement which provides a reference for striking a balance between the ecological advantages of agroforestry and the socio-economic considerations of local communities. However, it also underlines the importance of considering trade-offs between environmental benefits and crop yields when implementing such agroforestry systems.Graphical

Crustal and Upper Mantle Structure of the Assam Valley Region, NE India: A Review of Geophysical Findings

The northeastern region of India is one of the six most seismically active convergent plate tectonic areas in the world. The north–south convergence along the Indo-Tibetan Himalayan Ranges and the east–west subduction within the Indo-Burma Ranges create a complex stress regime, resulting in significant seismic activity and a history of great/large earthquakes. The region’s intricate strain patterns, active faults, and potential seismic gaps underscore the need for detailed subsurface studies to effectively assess seismic hazards and impending seismicity. Geophysical research is essential for understanding the region’s geodynamic evolution, seismotectonics, and mineral resources. This manuscript reviews the geological and tectonic settings of the region and summarizes recent geophysical studies, including seismic, gravity, magnetic, and magnetotelluric surveys conducted in the Assam Valley and adjacent areas (within latitudes 24.5–28.5° N and longitudes 89–97.5° E). The review highlights key findings on hydrocarbon-bearing sediments, the configuration of the crystalline basement, the heterogeneous structures of the crust and upper mantle, and seismic discontinuities. By synthesizing these results, the review aims to enhance the understanding of seismic hazards in Northeast India, guide mitigation strategies, and identify key knowledge gaps to direct future research efforts.

Molecular Taxonomy Suggests Presence of Two Distinct Lineages of Blue Sheep (Pseudois nayaur) in Indian Himalayan Region.

Indian Himalayan Region (IHR) supports a plethora of biodiversity with a unique assemblage of many charismatic and endemic species. We assessed the genetic diversity, demographic history, and habitat suitability of blue sheep (Pseudois nayaur) in the IHR through the analysis of the mitochondrial DNA (mtDNA) control region (CR) and Cytochrome b gene, and 14 ecological predictor variables. We observed high genetic divergence and designated them into two genetic lineage groups, i.e., the Himalayan blue sheep (P. n. nayaur) in the western part, and the Chinese blue sheep (P. n. szechuanensis) in the eastern part. They exhibited poor connectivity due to landscape resistance. The genetic distance value suggested substantial genetic differentiation between them. The habitat selection by blue sheep indicated the disparity between the residence preferences in the western and eastern Himalayas. In both the regions, the habitat suitability was mostly influenced by the minimumtemperature of the coldest month. However, in the eastern Himalayas,precipitation seasonalityemerged as a significant variable influencing habitat suitability. These findings provided strong support for the presumption that the habitats preferred by blue sheep in the western Himalayas are dryer, compared with the preferred habitats in the eastern region, which were moister. The identification of two separate lineages of P. nayaur in the IHR has significant conservation implications as it underlines the necessity for a unique management approach for each lineage. In order to preserve genetic integrity, conservation efforts must make sure that each population is maintained and monitored separately, as genetic divergence across the lineages that might indicate reproductive isolation. This study has potential conservation implications as it provides insights on the crucial ecological information of a relatively lesser-known ungulates species of Himalaya essential for effective conservation planning.

Community-driven ecotourism in the trans Himalayan region: A sustainable model for cultural and environmental preservation

ABSTRACT Himalayan destinations, rich in natural and cultural wealth, are increasingly vulnerable to ecological degradation due to unregulated tourism growth. This research examines community-driven ecotourism (CDE) as a model to reconcile economic imperatives with environmental stewardship in Ladakh, a region facing rapid tourism expansion and ecological fragility. Using a qualitative case study approach, the study draws on semi-structured interviews with 22 stakeholders, including community leaders, tourism entrepreneurs, environmental experts, and hospitality managers. Thematic analysis reveals the interplay between local engagement, cultural preservation, and ecological resilience. Key findings introduce a strategic framework that supports cultural and environmental sustainability while aligning with Sustainable Development Goals (SDGs) 8, 12, and 15. Community-managed homestays, wildlife tours, and heritage conservation emerge as key mechanisms for fostering local livelihoods and preserving heritage. However, challenges such as infrastructure deficits, capacity gaps, and insufficient policy coherence limit the broader impact of these initiatives. This study underscores the importance of local community participation in shaping resilient tourism practices and offers recommendations to bridge policy and practice. The research positions Ladakh as a model for sustainable tourism in the Himalayas, emphasizing the symbiosis between cultural identity and environmental integrity.

A Novel Approach for Most Vulnerable Zone Identification Using MT-InSAR and Machine Learning: A Case Study from Lesser Himalayan Region

A Novel Approach for Most Vulnerable Zone Identification Using MT-InSAR and Machine Learning: A Case Study from Lesser Himalayan Region

Applicability of reanalysis data in calibrating a hydrological model in a data-scarce mountainous watershed

ABSTRACT Understanding the hydrological processes of mountainous regions is crucial for watershed management. The increased frequency of floods in the Himalayan region emphasizes the need to set up a hydrological model in this region. The complex topography and climate patterns of the Himalayas, with a few hydrometeorological stations, make modeling the region challenging. Therefore, the study of hydrological responses using a fully distributed hydrological model in this region is very rare. This study aims to address the challenges of data scarcity in mountain regions using alternative data for observed discharge data for the calibration of the hydrological model. We assess the utility of reanalysis surface runoff data (RSRD) from ERA-5 in calibrating a fully distributed hydrological model WATFLOOD. Six water balance components at nine land-cover classes are analyzed using the WATFLOOD model. The results show that the RSRD can be used as an alternative for the discharge data for calibration of the hydrological model. The evaluation of water balance components shows changes corresponding to wet and dry years. We verified simulation results using observed data, revealing the limitations of calibrating a hydrological model with RSRD.

Adaptive Thermal Comfort in the Different Buildings of Temperate Climates—Comparison Between High-Latitude Europe and Mountainous Himalayas in India

Thermal comfort in buildings is essential for occupant well-being and energy efficiency, particularly in naturally ventilated environments where indoor conditions are closely influenced by outdoor climates. Current studies have not fully explored how thermal comfort varies across regions with similar climatic classifications but distinct geographic and cultural contexts. Addressing this gap, we analyzed and compared the adaptive thermal comfort responses in different naturally ventilated buildings located in temperate oceanic regions arising due to the high latitude in Europe and the elevated Himalayan region of Darjeeling, India. A mixed-methods approach was used with data from classrooms, offices, and residential buildings with adaptive thermal comfort modeling. The results show that European buildings exhibit narrower thermal comfort ranges compared to Darjeeling, for example, 21.2~24.8 °C versus 16.0~21.6 °C for 80% comfortability in classroom settings, respectively. Statistical analysis revealed significant differences in clothing insulation levels, with occupants in Darjeeling buildings demonstrating higher variability (mean rank 2103.31) compared to their European counterparts (mean rank 1207.30, p < 0.001). Additionally, a stronger correlation between indoor and outdoor air temperature was observed in Darjeeling (R: 0.785, p < 0.001), reflecting limited thermal buffering compared to European buildings (R: 0.372, p < 0.001). The paper advances adaptive thermal comfort models that account for regional differences and links these finding to sustainable building practices. The findings provide actionable insights for energy-efficient, climate-responsive building practices while supporting global sustainable development goals.

Non-parametric ground motion model for displacement response spectra and Fling for Himalayan region using machine learning

Non-parametric ground motion model for displacement response spectra and Fling for Himalayan region using machine learning

Assessment of forest cover dynamics for the detection of deforestation in the Hindu Kush Himalayan region using geospatial and machine learning approaches

Assessment of forest cover dynamics for the detection of deforestation in the Hindu Kush Himalayan region using geospatial and machine learning approaches

Multiphysics Ensemble Framework for Representing Western Himalayan Precipitation Climatology and Extremes: An Assessment from the WRF Model

Abstract Numerical model simulations are sensitive to the choice of physical parameterizations, particularly those related to convection processes, especially over complex terrains like the western Himalayan region. This study evaluates the sensitivity of the Weather Research and Forecasting (WRF) Model to three convective parameterization schemes [Betts–Miller–Janjić (BMJ), Kain–Fritsch (KF), and Grell–Freitas (GF)] and their multiphysics ensemble mean (ENSM) through long-term (2001–16) winter (December–March) simulations. Model outputs are validated against multisource datasets [India Meteorological Department (IMD), IMERG, ERA5, and Indian Monsoon Data Assimilation and Analysis (IMDAA)], with extreme precipitation events (EPEs) identified as those exceeding the 95th-percentile threshold. Climatology analysis reveals systematic precipitation biases across all single schemes, significantly reduced in the ENSM. Improvements in skill scores observed for ENSM highlight the reliability of the ensemble approach as an alternative to account for model errors. Underestimations of low-level clouds and hydrometeors improve in ENSM. BMJ and KF (GF) schemes exhibit overestimated (underestimated) magnitudes and location-wise discrepancies for baroclinic instability and moisture transport. These issues are mitigated in ENSM, resulting in better alignment with reference datasets. Additionally, ENSM and KF’s storm tracks align well with reanalyses, while individual schemes show a minor northward placement. For EPEs, ENSM highlights Jammu and Kashmir, Himachal, and Uttarakhand as zones of maximum heavy precipitation and frequency. ENSM realistically represents the western disturbance (WD)-induced circulation characteristics, southward-displaced subtropical jet, shifts in WD-associated vorticity maxima, and potential vorticity intrusions during extremes. Consistent with reference datasets, ENSM demonstrates the crucial role of vertical advection and dynamical controls in moisture distribution during EPEs. Our analysis indicates that a suitable WRF cumulus configuration includes either the multiphysics ENSM or the KF scheme, while the GF scheme yields the poorest results. The findings underscore the importance of evaluating both precipitation characteristics and underlying physical mechanisms to identify sources of systematic biases in model simulations.

A Comparative Study of Supervised Machine Learning Techniques for Water Leakage Prediction in Drill and Blast Excavated Water Tunnels in the Himalayan Region

In the Himalayan region, drill and blast (DB) method excavated water tunnels often pass through complex geological rock mass conditions which were formed with frequent tectonic movements. Due to these tectonic movements, the rock mass conditions in the Himalayas are highly faulted, folded, jointed, sheared, and fractured. The geological formations are the pathway for the water ingress and leakage out in the water tunnel. This water leakage in the tunnel causes a complicated geological hazard, which significantly increases tunnel instability and can lead to a delay in completion time and finally increase the cost of the tunnel project. Therefore, an efficient water ingress/leakage prediction model is essential to mitigate these challenges. In this research, various field data such as rock mass properties, topography, and permeability data sets were collected from the Nilgiri-II Hydroelectric project water tunnel. These real-time field datasets have been used for comprehensive assessment and to predict the water ingress/leakage in the water tunnel by using four supervised machine learning (ML) approaches such as Support Vector Regression (SVR), Decision Tree (DT) regression, K-Nearest Neighbors (KNN) and Random Forest (RF) regression models. It was observed that the KNN shows the best regression performance of 93% followed by RF of 92%, DT of 86%, and SVR of 66%. Therefore, all these machine learning approaches show good performance in predicting water ingress/leakage based on real field data except the SVR model.

Climatic impacts on spring disappearance in the Indian Himalayas

Due to climate change the drop in spring-water discharge poses a serious issue in the Himalayan region, especially in the higher section of Himachal Pradesh. This study used different climatic factors along with long-term rainfall data to understand the decreasing trend in spring-water discharge. It was determined which climate parameter was most closely correlated with spring discharge volumes using a general as well as partial correlation plot. Based on 40 years (1981–2021) of daily average rainfall data, a rainfall-runoff model was utilised to predict and assess trends in spring-water discharge using the MIKE 11 NAM hydrological model. The model’s effectiveness was effectively proved by the validation results (NSE = 0.79, R2 = 0.944, RMSE = 0.23, PBIAS = 32%). Model calibration and simulation revealed that both observed and simulated spring-water runoff decreased by almost 29%, within the past 40 years. Consequently, reduced spring-water discharge is made sensitive to the hydrological (groundwater stress, base flow, and stream water flow) and environmental entities (drinking water, evaporation, soil moisture, and evapotranspiration). This study will help researchers and policymakers to think and work on the spring disappearance and water security issues in the Himalayan region.

Water Resources and Geopolitical Tensions in the Himalayas: Analysing Nepal’s Mediating Role

The Himalayan region, often regarded as the 'water tower' of Asia, is crucial for sustaining millions of people across Asia. As climate change exacerbates water scarcity, competition over shared water resources has intensified geopolitical tensions between India and China, particularly concerning the Indus and Brahmaputra river basins. This research posits that the escalating competition over shared water resources in the Himalayan region, intensified by climate change and nationalistic narratives from India and China, necessitates an exploration of Nepal's mediating role, cooperative frameworks from other regions, and sustainable practices to alleviate tensions and promote regional stability, ultimately informing policymakers on effective strategies for conflict resolution and governance amid growing geopolitical challenges. Furthermore, it examines Nepal's diplomatic strategies aimed at balancing its relationships with both powers while asserting its own interests. By analysing successful frameworks for mediation and cooperation from other regions, such the Mekong River basin, this study proposes actionable strategies for enhancing collaborative water management among India, China, and Nepal. This article is based on both secondary information as well as primary data sources. Under primary sources, in-depth interview has been taken from the three selective experts. Such experts were selected purposively on the basis of their fields of expertise. Similarly, for the secondary information, previously published articles and journals of the scholars from the diverse background has been reviewed and critically analysed. Their views are compared and contrasted to come to the logical conclusion regarding this field. The findings of this research suggest that the regional disputes in the twenty first century is an established fact, and one of the reasons of this tension is, of course, not other than the water resources and geopolitical strategies. Fostering sustainable practices and establishing transparent data-sharing mechanisms can alleviate such tensions and promote regional stability between and among the countries. Ultimately, this research emphasizes the importance of cooperative frameworks in addressing the challenges posed by water resource competition in the Himalayas and calls for further exploration of Nepal's role in facilitating peace and conflict management in the region. This study contributes to the understanding of the intersection between water resources and geopolitics, providing insights that are critical for policymakers and stakeholders invested in the sustainable management of shared water resources in the Himalayas.

Unravelling flash flood dynamics of Song watershed, Doon Valley: key insights for floodplain management

The Himalayan foothills are highly prone to rainfall induced flash floods. This research focuses on the August 19–20, 2022 flash flood event in Song watershed of Doon valley, Uttarakhand caused significant damages to buildings and a road bridge. The study aims to assess the flood intensity through flood simulation in a semi-distributed hydrological model by utilizing rainfall data, land use and soil data. Further, the flood hydrographs generated through hydrological modelling were used to simulate hydrodynamic model to estimate flood depth. Pre and post-flood inundation assessments were conducted using PlanetScope and Sentinel-1 imagery. Furthermore, development activities on river courses were analyzed utilizing Google earth and Bing maps high resolution imagery. Cumulative rainfall observations revealed 344 mm rainfall in Rishikesh and 225 mm in Sahastradhara on 19–20 August for the 24 hrs, contributed in a peak flood discharge 2679 m3/s at the Rishikesh outlet. The simulated flood depth depicted 4.81 m flood depth at the damaged Thano-Bhogpur bridge. The PlanetScope satellite imagery showed 182 m expansion in the cross-sectional width of river at Maldevta after the flood. A 5.36 sq. km. flood area observed throughout the entire Song catchment in two days post event Sentinel-1 imagery. Analysis of high-resolution imageries revealed increasing development activities in floodplains of the catchment, which got affected by flood. The findings indicate urgent need of floodplain management by implementing comprehensive flood risk management plans including early warning systems, land-use regulations based on flood hazard zonation and flood resilient infrastructure to mitigate future flood exposure to society.