Hindu Kush Himalayan Research Articles

Variability of ambient black carbon concentration in the Central Himalaya and its assessment over the Hindu Kush Himalayan region

During 2015–2018, eight black carbon (BC) monitoring sites were established in Nepal and Bhutan to fill a significant data gap regarding BC measurement in Central Himalaya. This manuscript analyzes and presents data from these eight stations and one additional station on the Tibetan plateau (TP). Complex topography, varied emission sources, and atmospheric transport pathways significantly impacted the BC concentrations across these stations, with annual mean concentrations varying from 36 ng m−3 to 45,737 ng m−3. Higher annual mean concentrations (5609 ± 4515 ng m−3) were recorded at low-altitude sites than in other locations, with seasonal concentrations highest in the winter (7316 ± 2541 ng m−3). In contrast, the annual mean concentrations were lowest at high-altitude sites (376 ± 448 ng m−3); the BC concentrations at these sites peaked during the pre-monsoon season (930 ± 685 ng m−3). Potential source contributions to the total observed BC were analyzed using the absorption angstrom exponent (AAE). AAE analysis showed the dominance of biomass burning sources (>50 %), except in Kathmandu. By combining our data with previously published literature, we put our measurements in perspective by presenting a comprehensive assessment of BC concentrations and their variability over the Hindu Kush Himalayan (HKH) region. The BC levels in all three geographic regions, high, mid, and low altitude significantly influenced by the persistent seasonal meteorology. However, the mid-altitude stations were substantially affected by valley dynamics and urbanization. The low-altitude stations experienced high BC concentrations during the winter and post-monsoon seasons. Concentration weighted trajectory (CWT) and frequency analyses revealed the dominance of long-range transported pollution during winter over HKH, from west to east. South Asian sources remained significant during the monsoon season. During pre- and post-monsoon, the local, regional, and long-distance pollution varied depending on the location of the receptor site.

Climate change creates opportunities to expand agriculture in the Hindu Kush Himalaya but will cause considerable ecosystem trade-offs

Theoretically, climate change will create warmer temperatures and greater precipitation in mountainous regions, making agriculture possible in areas that were once unsuitable for cropping. But the extent and the nature of these ‘agricultural frontiers’ is as yet unknown. Building upon recent research on Climate Change Driven Agricultural Frontiers [CCDAFs], this paper assesses the potential of agricultural expansion in the Hindukush Himalaya [HKH]. Using FAO crop suitability data, we estimated the extent of CCDAFs under three Representative Concentration Pathways for 13 crops as well as the potential impacts of developing these frontiers on ecosystem services. We show that under climate change projected by the IPSL- CM5A-LR climate model, 34,507 km2 of agricultural frontiers may emerge in the HKH by 2100 under RCP 6.0. Additionally, results suggest that there will be new opportunities for crop diversification as individual crops will gain frontier area. However, developing these CCDAFs will impact supportive and regulating ecosystem services including carbon storage and sequestration, soil quality, biodiversity, and hydrological processes—with implications for regional water security. These impacts must be considered alongside the benefits of additional food production when evaluating the net benefits of developing CCDAFS.

Landslide susceptibility mapping (LSM) of Swat District, Hindu Kush Himalayan region of Pakistan, using GIS-based bivariate modeling

Landslides are a recurrent environmental hazard in hilly regions and affect the socioeconomic development in Pakistan. The current study area is the tourism and hydro energy hub of Pakistan and is affected by environmental hazard. A landslide susceptibility mapping (LSM) of the Hindu Kush Himalayan, Swat District, Pakistan, can be created to reduce demographic losses due to landslides. This current study is conducted to apply three bivariate models, including weights of evidence (WOE), frequency ratio (FR), and information value (IV) for an LSM that has not been explored or applied in the current study area. For this purpose, first, an inventory map of 495 landslides was constructed from both ground and satellite data and randomly divided into training (70%) and testing (30%) datasets. Furthermore, 10 conditioning factors (elevation, slope, aspect, curvature, fault, rainfall, land use land cover (LULC), lithology, road, and drainage) used for the mapping of landslides were prepared in ArcGIS 10.8. Finally, LSM is generated based on WOE, FR, and IV models and validated the performance of LSM models using the area under receiver operating characteristic curve (AUROC). The findings of success rate curve (SRC) of the WOE, FR, and IV models were 67%, 93%, and 64%, respectively, while the prediction rate curves (PRCs) of the three models were 87%, 95%, and 73%, respectively. The validation results for WOE, FR, and IV justified that the FR model is the most reliable technique of all three of these models to produce the highest accuracy LSM for the present study area. Policymakers can use the findings of current research work to mitigate the loss due to landslide hazard.

Space matters: reducing energy disparity in Nepal through spatially equitable renewable energy subsidies

:Affordability is a major barrier to the adoption of clean energy technologies in low-income countries, which is partly why many governments provide subsidies to offset some of the upfront (installation) costs. However, simple administrative rules might not fully account for economic geography, resulting in lower subsidies for remote areas. Using regression analysis on a rich dataset of adoption, cost and subsidy for about 4000 Nepalese Village Development Committees over 22 years, we show that administratively determined lumpsum subsidies disproportionately hurt remote communities. Simulations show that adjusting the subsidy spatially to reflect the geographic cost of living, can increase clean technology adoption. Thus, spatial targeting of subsidies is key to accelerating energy access in remote settings such as the Hindu Kush Himalaya.

Remote Sensing-based Spatiotemporal Distribution of Grassland Aboveground Biomass and Its Response to Climate Change in the Hindu Kush Himalayan Region

Remote Sensing-based Spatiotemporal Distribution of Grassland Aboveground Biomass and Its Response to Climate Change in the Hindu Kush Himalayan Region

Protected areas in the Hindu Kush Himalaya: A regional assessment of the status, distribution, and gaps

AbstractProtected areas (PAs) are a key strategy for conserving areas of outstanding biodiversity value and promoting sustainable development. Significant efforts have been made toward establishing PAs over the last few decades across the globe. However, an assessment of PAs in mountain regions, including in the biodiversity rich Hindu Kush Himalaya (HKH), is lacking. We assessed the status, trend, and distribution of PAs and the ecological representativeness in the PA network. Our analysis showed the HKH has a total of 575 PAs covering 40.17% of the region, accounting for 8.49% of global PA coverage. The HKH hosts 335 Important Bird and Biodiversity Areas (IBAs), 348 Key Biodiversity Areas (KBAs), 12 Global 200 Ecoregions, and 4 Global Biodiversity Hotspots. However, the study showed limited ecological representation in the current PA system as 67% of ecoregions, 39% of hotspots, 69% of KBAs, and 76% of IBAs are still outside of the PA system. About 47% of the PAs are small (<250 sq. km) with no connectivity to other PAs and the majority are distributed in the lower reaches of the HKH. These findings suggest the need to assess and demarcate potential corridors to improve connectivity between PAs and integrate PAs into wider conservation landscapes at national and regional scale beyond country boundaries through regional cooperation. There is also a need to assess and strengthen PA management effectiveness and governance and consider other effective area‐based conservation measures especially in the higher elevations and with a specific focus on ecological representation.

Revealing four decades of snow cover dynamics in the Hindu Kush Himalaya

Knowledge about the distribution and dynamics of seasonal snow cover (SSC) is of high importance for climate studies, hydrology or hazards assessment. SSC varies considerably across the Hindu Kush Himalaya both in space and time. Previous studies focused on regional investigations or the influence of snow melt on the local hydrological system. Here, we present a systematic assessment of metrics to evaluate SSC dynamics for the entire HKH at regional and basin scale based on AVHRR GAC data at a 0.05° spatial and daily temporal resolution. Our findings are based on a unique four-decade satellite-based time series of snow cover information. We reveal strong variability of SSC at all time scales. We find significantly decreasing SSC trends in individual summer and winter months and a declining tendency from mid-spring to mid-fall, indicating a shift in seasonality. Thanks to this uniquely spatio-temporally resolved long-term data basis, we can particularly highlight the unique temporally variable character of seasonal snow cover and its cross-disciplinary importance for mountain ecosystems and downstream regions.

Decline in the suitable habitat of dominant Abies species in response to climate change in the Hindu Kush Himalayan region: insights from species distribution modelling.

Reliable predictions of future distribution ranges of ecologically important species in response to climate change are required for developing effective management strategies. Here we used an ensemble modelling approach to predict the distribution of three important species of Abies namely, Abies pindrow, Abies spectabilis and Abies densa in the Hindu Kush Himalayan region under the current and two shared socioeconomic pathways (SSP245 and SSP585) and time periods of 2050 and 2090s. A correlative ensemble model using presence/absence data of the three Abies species and 22 environmental variables, including 19 bioclimatic variables and 3 topographic variables, from known distributions was built to predict the potential current and future distribution of these species. The individual models used to build the final ensemble performed well and provided reliable results for both the current and future distribution of all three species. For A. pindrow, precipitation of the driest month (Bio14) was the most important environmental variable with 83.3% contribution to model output while temperature seasonality (Bio4) and annual mean diurnal range (Bio2) were the most important variables for A. spectabilis and A. densa with 48.4% and 46.1% contribution to final model output, respectively. Under current climatic conditions, the ensemble models projected a total suitable habitat of about 433,003 km2, 790,837 km2 and 676,918 km2 for A. pindrow, A. spectabilis and A. densa, respectively, which is approximately 10.36%, 18.91% and 16.91% of the total area of Hindu Kush Himalayan region. Projections of habitat suitability under future climate scenarios for all the shared socioeconomic pathways showed a reduction in potentially suitable habitats with a maximum overall loss of approximately 14% of the total suitable area of A. pindrow under SSP 8.5 by 2090. A decline in total suitable habitat is predicted to be 9.6% in A. spectabilis by 2090 under the SSP585 scenario while in A. densa 6.67% loss in the suitable area is expected by 2050 under the SSP585 scenario. Furthermore, there is no elevational change predicted in the case of A. pindrow while A. spectabilis is expected to show an upward shift by about 29m per decade and A. densa is showing a downward shift at a rate of 11m per decade. The results are interesting, and intriguing given the occurrence of these species across the Hindu Kush Himalayan region. Thus, our study underscores the need for consideration of unexpected responses of species to climate change and formulation of strategies for better forest management and conservation of important conifer species, such as A. pindrow, A. spectabilis and A. densa.

Distribution characteristics of Spodoptera frugiperda (Lepidoptera: Noctuidae) winter populations in typical Mountain agricultural area of Southwest China

Fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera: Noctuidae) is one of the most damaging crop pests worldwide and has become a significant threat to the food security in many countries. The Lancang River (Mekong) valley and Nujiang River (Salween) valley, which are typical mountain agricultural areas located in the Hindu Kush-Himalayan (HKH) mountain range, are the key channels for the south to north migration of FAW in southwestern China. The purpose of this study was to analyze the population structure and distribution of FAW winter populations in the Lancang River and Nujiang River basins and relate these findings with respect to altitude, latitude, and mean monthly winter temperature in order to explore the spatial and temporal distribution characteristics of the winter population. Our results indicated that overwintering populations of FAW mainly appeared in winter cornfields with a few pupae found in summer cornfields near the middle and lower reaches of the Lancang River basin (south 26.04° N and below 1600 m) and the Nujiang River basin (south of 26.80° N and below 1500 m). Winter corn appeared to be a prerequisite for the occurrence of FAW in winter. The mean monthly temperature of the coldest month being greater than 10 °C is one critical factor determining where FAW populations will occur in winter. Some control options that could be used in these river basins include adjusting crop planting patterns and developing a large-scale non-host isolation band.

Forest Fire in the Hindu Kush Himalayas: A Major Challenge for Climate Action

Forest fire has been one of the compelling issues in the Hindu Kush Himalayan (HKH) region. To promote regeneration, clearing fields for agriculture, hunting, and security reasons, local people deliberately set forests on fire. In this paper, active fire incidents, temperature, precipitation, and the changes of Aerosol Optical Depth (AOD) and Carbon monoxide (CO) value associated with forest fire were evaluated. The active forest fire incidents obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite are supplemented by the ERA5-land dataset to see the relation between precipitation and temperature with forest fires. MODIS and Tropospheric Monitoring Instrument (TROPOMI) sensor datasets were used to see the changes in AOD and CO in the region. MODIS sensor detected more than 30,462 active fires incidents in March and April 2021 in the study areas. Shan State of Myanmar recorded the maximum number of active fire incidents which is due to the practice of shifting cultivation and minimum in Bhutan due to the awareness campaigns and technology improvement. The temperature recorded in the study sites shows an increasing trend as compared to the reference period (2010-2020). Apart from Shan and Bago of Myanmar, precipitation in the study sites is also less during the study period. AOD and CO values show prominent peaks in a fire season which coincide with days of the maximum number of fire counts inferring the influence of forest fire on air quality. Developing countries like Nepal, India, Myanmar, and Bhutan are willing to take part in climate finance and are bound to accept expensive insurance premium due to forest fire incidents. Unless forest fires are effectively managed and mitigated, achieving Nationally Determined Contributions (NDCs) and global agendas, including United Nations Decade of Ecosystem Restoration is onerous.

Assessment of geodiversity of Parbati River Basin in North-Western Himalayan region, India

In light of structural and functional linkages between the geodiversity and biodiversity, mapping geodiversity becomes more important in highly pristine and diverse regions such as Hindu Kush Himalayas as it could lead to better nature conservation strategies. This study represents pioneering efforts in the field of quantitative assessment of geodiversity and its mapping in Parbati River Basin (PRB) using grid overlay. Geodiversity index (GI) so generated was finally interpolated using inverse distance weighting (IDW) model, which resulted in the generation of an isoline map showing spatial distribution of various geodiversity classes in the PRB. The higher GI in the Lower basin is mainly due to rich lithological elements whereas the very high values in the Upper basin can be attributed to geomorphological richness. All these features are facing constant threat due to continuous degradation and damage caused by various anthropogenic activities in the PRB.

Developmental Success and the Sustainability Challenge in a Mountain Region: Case of Himachal Pradesh in India

Himachal Pradesh (HP) is one of the most progressive mountain states in India that has transformed regional development perspective in the country. HP performs better than several Indian states which score high on socio-economic indicators despite its harsh climatic condition. In recent times, however, HP is witnessing a slowdown in several sectors because of its traditional development approach leading to high fiscal deficit. This study aims to identify factors which promote or restrict sustainable development in HP using expert interview and discussion. Results show that, current sustainability challenges in HP require innovation and home-grown policies. Recommendations have been made on critical issues which can enable HP to redesign its development trajectory while maintaining its traditional hill culture and environmental leadership. The findings of this study are expected to add new dimensions and highlight emerging sustainability issues in mountain regions. This will aid policymakers, national and sub-national governments in India, countries in the Hindu Kush Himalayan region and elsewhere in the world, which can benefit from HP’s dynamic story of development and realign or replan their development strategies for a sustainable future.

Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region: A Decade of Experience From SERVIR. Edited by Birendra Bajracharya, Rajesh Bahadur Thapa, and Mir A. Matin

Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region: A Decade of Experience From SERVIR. Edited by Birendra Bajracharya, Rajesh Bahadur Thapa, and Mir A. Matin

Constraints to agroforestry diffusion under the Billion Trees Afforestation Project (BTAP), Pakistan: policy recommendations for 10-BTAP

Effective agroforestry diffusion under the newly started 10-Billion Trees Afforestation Project (10-BTAP) needs a thorough understanding of the policy and implementation shortfalls of the already completed BTAP. This study examines the factors that affected the diffusion of the agroforestry in the Hindu-Kush Himalayan (HKH) region of Pakistan under BTAP. The data were gathered through in-depth interviews with Village Development Committee (VDC) members, Forest Department (FD) officials, and local farmers. Important factors positively affecting agroforestry diffusion included locations of crop fields on the river sides, community dependency on firewood, and market value of agroforestry timber. The logistic regression model shows that household head’s age, access to information, and area under cropland positively affected household level adoption of agroforestry under BTAP; forest cover was negatively related. In-depth interviews show that key barriers to FD in diffusion of agroforestry included provision of false information by farmers to monitoring teams, non-availability of extension staff, lack of communication among project staff and community, as well as a lack of sufficient budget for activities. Primary barriers to community adoption of agroforestry included no participation of VDCs in planning and monitoring of agroforestry programs, lack of plant need assessments on the part of the project staff, poor quality of plants distributed by FD, farmers’ poor know-how of plantations, lack of trust among community and project staff, as well as the waste of plants by farming community. Thus, this study recommends that policy-makers and project designers should consider these factors when planning agroforestry diffusion under 10-BTAP to improve its success.

Conserving agrobiodiversity for sustainable food systems in the Hindu Kush Himalaya

ABSTRACT The Hindu Kush Himalaya (HKH) is a rich region in agrobiodiversity. As elsewhere in the world, agrobiodiversity is declining in this region, and this is impacting the functioning of ecosystems and has profound implications for agricultural sustainability and food security. Today, the challenge faced by the global community is how to slow or reverse the present trend of loss of agrobiodiversity to safeguard future food supplies. Taking examples from the HKH, this paper explores the link between agrobiodiversity and food security, identifies the key issues and challenges to maintaining agrobiodiversity, and explores potentials and opportunities for improving agrobiodiversity that are conducive to maintaining and increasing food security, ecosystem services, and agricultural sustainability, and thus building resilience. The paper concludes that urgent action and an integrated landscape approach are required, bringing together multiple stakeholders, and integrates agrobiodiversity in national policies and programmes. Appropriate economic measures should be developed to encourage local people to use the Himalayan biodiversity sustainably as a basis to achieve food security and agricultural sustainability.

An Assessment of Glacier Inventories for the Third Pole Region

A glacier inventory contains data that are important for understanding the hydrology, water resources, and impacts of climate change in glaciated regions. Ten glacier inventories have been created for the Third Pole Region (TPR) or high-mountain Asia, but they vary largely in spatial coverage area and data quality. Therefore, it is necessary to assess the data quality to help potential users choose the right glacier inventories for their research. Using the analytical hierarchy process, this study selects eight assessment factors and quantifies the quality of eight glacier inventories of the TPR. The eight glacier inventories that we assessed are the Randolph Glacier Inventory (RGI), the Glacier Area Mapping for Discharge in Asian Mountains (GGI18), the Second Chinese Glacier Inventory (CGI-2), the Glacier Inventory of the Hindu Kush–Himalayan Region (HKHGI), the Glacier Inventory for the Western Himalayas (WHGI), the Glacier Inventory for the Karakoram and Pamir Region (KPGI), the Second Glacier Inventory of Pakistan (PGI-2) and the Glacier Inventory for the Southeastern Tibetan Plateau (SETPGI). The assessment results indicate that the overall quality of the small-scale glacier inventories of WHGI, KPGI, PGI-2, and SETPGI is higher than that of the large-scale inventories of RGI, GGI18, CGI-2, and HKHGI. For the large-scale inventories, the quality-ranking order from high to low is CGI-2, GGI18, RGI, and HKHGI. However, the comprehensive quality of CGI-2 and GGI18 is comparable over the area covered by CGI-2. The comprehensive quality of CGI-2, GGI18, and RGI exhibits clear spatial differences. Overall, the data quality is higher for the inner TPR than for the surrounding areas. By merging the products of the eight glacier inventories, a new glacier inventory product of the best comprehensive quality was derived for the entire TPR. This new product resembles the spatial distribution of the best-quality glacier inventories of the regions where the different products overlap. In terms of specific regions, the CGI-2 and GGI18 are the best products for most parts of the TPR in China, except for an area of southeastern Tibet where the highest-quality data are from the SETPGI. The other main distributions of the best products are the WHGI for the western Himalayas, the GGI18 and HKHGI for the Hindu Kush and the middle and eastern Himalayas, the PGI-2 for Pakistan, the KPGI for the Karakorum–Pamir area, and the GGI18 and CGI-2 for the Tianshan Mountains. The new data product greatly promotes the quality of a single glacier inventory for the entire TPR. This database will meet the needs of a variety of potential researchers, including those who prefer to get information for a particular parameter from a single glacier inventory (http://data.tpdc.ac.cn/en/data).

Capability assessment of Sentinel-1 data for estimation of snow hydrological potential in the Khanabad watershed in the Hindu Kush Himalayas of Afghanistan

The water resource in arid countries like Afghanistan is mainly dependent upon the rivers driven by snowmelt runoff. The Khanabad watershed in Afghanistan contributes significantly to the river network system in this country. This study investigates the role of freely available Sentinel-1 dual polarimetric and interferometric SAR data to determine snow hydrological potential in the Khanabad watershed. The objectives of this study are to assess the Snow Water Equivalent (SWE) estimates derived from the Sentinel-1 data with respect to field observations and ERA5-Reanalysis data for February and March 2019. The snow depth and snow density estimates are derived using the interferometric and polarimetric methods to determine the SWE. The snow depth is determined using differential interferometry with snow-free scenes and snow-covered scenes acquired by Sentinel-1 data. The density is empirically modeled using the permittivity estimates derived from bi-temporal VV-channel Sentinel-1 data corresponding to snow-covered scenes. The comparison between the SWE results observed from Sentinel-1 data with respect to field observations showed high agreement determined by the overall correlation of 0.877 and a Root Mean Square Error (RMSE) of 37 mm. The higher RMSE was attributed to the uncertainties introduced by the presence of liquid water content in the March 2019 dataset.

Climate change may plunder the facultative top predator Yellow-throated Martin from the Hindu-Kush Himalayan Region

The mountain ecosystems are fragile because of topography and extreme climatic conditions. The Hindu-Kush Himalayan (HKH) region is a biodiversity-rich ecosystem and highly vulnerable to climate change and anthropogenic activities among the mountains. In HKH, the climate change impacts on ecologically specialist species are already evident, but generalist species are not much studied. One such generalist species distributed throughout the HKH is Yellow-Throated Marten (YTM) (Martes flavigula Boddaert, 1785), a facultative predator that occupies the Southern flank of the HKH. The YTM is one of the least studied animals distributed up to 4510-m elevation. The HKH covers 61 terrestrial ecoregions and 304 Protected Areas (PAs). An ecologically successful facultative predator of the region is seriously threatened because of habitat loss and climate change. Hence, we used an ensemble model to map the distribution of suitable habitats and their representativeness in terms of ecoregions and PA coverage. The results indicated that by 2050, the distribution range might decline to 58.78% and 49.33% with reference to the current scenario under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios, respectively. The species may lose much of its range, mainly in the eastern part of the HKH landscape. Furthermore, the centroid of the distribution may also shift to the northwest, thereby abandoning many areas and occupying new refugia. The Upper Gangetic plains moist deciduous forests ecoregion possess the highest suitable habitats for the YTM, with a mean value of 0.744. At the same time, the existing PA network represents only 12.2% of its suitable habitat in HKH. Hence, for the long-term viability of the species, there is a need to enhance protection and improve habitat quality.

Trends in Deforestation as a Response to Management Regimes and Policy Intervention in the Hindu Kush Himalaya of Pakistan

Based on the annual rate of deforestation as a forest conservation outcome, this study evaluated how effective is the existing forest management regime in controlling deforestation in the study area. Remote sensing data were used to measure the rate of deforestation. Furthermore, the existing forest management regime in the study area, as well as in other regions of the Himalayan and Karakoram ranges of Pakistan and the Himalayan temperate biome of India, China, Nepal, and Bhutan, was reviewed to compare deforestation. The results showed that, with regional-wise management regimes, the overall annual rate of deforestation was recorded much higher in the study area (0.8 yr−1) compared to the Himalayan and Karakoram ranges of Azad Kashmir (0.13% yr−1), Punjab (0.20% yr−1), and Gilgit Baltistan (0.31% yr−1). The cross-national and site-regional findings highlighted that lowest deforestation was associated with management regimes characterized by effective monitoring and law enforcement with the inclusion of conservation and community. Deforestation was higher in forest management regimes that aimed to maximize economic growth, unstable rights, weak law enforcement, and exclusion of conservation and community-based management/use. In conclusion, the best forest conservation outcomes are associated with management regimes that include conservation and community and stable and secure rights supported by high-ranking monitoring and law enforcement. Therefore, the inclusion of community and conservation supplemented with stable rights and high-rank monitoring and law enforcement into the existing management regimes is suggested.

Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data

Abstract. Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic changes in the intra-annual (accumulating season and melting season) and interannual variations in snow and glacial cover over the HKH region. The zonal and altitudinal (hypsographic) analyses were carried out for the melting season and accumulating season. The altitude-wise linear trend analysis (Pearson's) of snow cover, shown as a hypsographic curve, clearly indicates a major decline in snow cover (average of 5 % or more at 100 m interval aggregates) between 4000–4500 and 5500–6000 m altitudes, which is consistent with the median trend (Theil–Sen – TS) and the monotonic trend (Mann–Kendall – MK; statistics) analysis. This analysis also revealed the regions and altitudes where major and statistically significant increases (10 % to 30 %) or decreases (−10 % to −30 %) in snow cover are identified. The extrapolation of the altitude-wise linear trend shows that it may take between ∼ 74 and 7900 years, for 3001–6000 and 6000–7000 m altitude zones respectively, for mean snow cover to decline approximately 25 % in the HKH. More detailed analysis based on longer observational records and model simulations is warranted to better understand the underlying factors, processes, and feedbacks that affect the dynamic of snow cover in HKH. These preliminary results suggest a need for continued monitoring of this highly sensitive region to climate variability and change that depends on snow as a major source of freshwater for all human activities.