Hindu Kush Himalayan Region Research Articles

Evaluating the dynamics of climate and anticipated snow cover changes on the hydrological response of rivers in the Hindu Kush Himalaya region

ABSTRACT The research aims to assess the interplay between climate dynamics and snow cover changes, informing water resource management. Utilizing the SWAT model with historical and future data, hydrological responses in the Marshyangdi River Basin are examined. The model's performance confirms its ability to simulate runoff components effectively. Projections indicate a concerning decrease in snow cover area for 2030, 2050, and 2090, with declines of 2.03, 4.03, and 14.20%, respectively, attributed to global warming and human activities. Isolating climate change reveals substantial increases in stream flow, notably pre-monsoon surges under different scenarios, with projected increments of 84 and 130% under SSP245 and SSP585, respectively. Analysis of snow cover impact shows a slight increase in annual stream flow, with a 3.54% anticipated decrease during the post-monsoon period, raising concerns for water availability in the dry season. Comparing both impacts reveals no significant differences in stream flow or precipitation. Annual stream flow increases under different scenarios, driven by precipitation, with varying impacts. Climate change emerges as the dominant driver, affecting surface runoff, groundwater, and evapotranspiration. This research unravels complex relationships between climate change, snow cover, and hydrological responses, providing valuable insights for water resource management in mountainous regions like the Hindu Kush Himalaya.

Comparative Analysis of Snowmelt-Driven Streamflow Forecasting Using Machine Learning Techniques

The rapid advancement of machine learning techniques has led to their widespread application in various domains, including water resources. However, snowmelt modeling remains an area that has not been extensively explored. In this study, we propose a state-of-the-art (SOTA) deep learning sequential model, leveraging a Temporal Convolutional Network (TCN), for snowmelt forecasting of the Hindu Kush Himalayan (HKH) region. To evaluate the performance of our proposed model, we conducted a comparative analysis with other popular models, including Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and Transformer models. Furthermore, nested cross-validation (CV) was used with five outer folds and three inner folds, and hyperparameter tuning was performed on the inner folds. To evaluate the performance of the model, the Mean Absolute Error (MAE), Root-Mean-Square Error (RMSE), R square (R2), Kling–Gupta Efficiency (KGE), and Nash–Sutcliffe Efficiency (NSE) were computed for each outer fold. The average metrics revealed that the TCN outperformed the other models, with an average MAE of 0.011, RMSE of 0.023, R2 of 0.991, KGE of 0.992, and NSE of 0.991 for one-day forecasts of streamflow. The findings of this study demonstrate the effectiveness of the proposed deep learning model as compared to traditional machine learning approaches for snowmelt-driven streamflow forecasting. Moreover, the superior performance of this TCN highlights its potential as a promising deep learning model for similar hydrological applications.

Analysis of hydrological responses using semi-distributed conceptual models in a mountainous catchment in the Hindu Kush Himalayan region

ABSTRACT The Hindu Kush Karakoram Himalaya region, an important global water unit, is the origin of 10 major river basins. The Upper Indus basin, a part of this region, is a primary water source for the downstream population and is primarily fed by snow and glacier melt. Four semi-distributed conceptual hydrological models were used to understand this basin’s hydrological responses. As the observed data was unavailable, global gridded precipitation and discharge data from the Global Flood Awareness System (GloFAS) were used to set up the model at the catchment outlet. Degree-day factor (DDF)-based snow and glacier modules are incorporated into the model structure to measure melt contribution. The results showed very good performance of all four models with Nash-Sutcliffe efficiency > 0.75, with the GR4J model exhibiting superior performance. The dominance of snow and glacier melt during summer monsoon affects the peak discharge and offers insights for investigations at the sub-basin scale.

Population ecology and habitat suitability modelling of an endangered and endemic medicinal plant Meconopsis aculeata Royle under projected climate change in the Himalaya

The Himalayan region is home to the endangered and endemic medicinal plant, Meconopsis aculeata. Habitat degradation due to overexploitation and unscientific collection of the species in recent years has caused the restricted distribution range of species across its range. Therefore, the present study was conducted in the Hindu Kush Himalayan region (4.5 million km2 area) to study population ecology and identify suitable habitats for the habitat distribution modelling under projected climate change to monitor and restore the dwindling populations. Ten sites/populations (20 × 20 m plot) of M. aculeata have been studied. East aspect (5 sites) and rocky habitat (04 sites) represented the maximum number of sites. The density of M. aculeata has a significant negative correlation with slope and available potassium in soil. The MaxEnt algorithm, species occurrence data and environmental variables were used in the current study. CMIP6 project's MIROC6 and BCC-CSM2-MR climate change models were used to identify the potential distribution area for the future under the SSP245 and SSP370 scenarios for the period 2081–2100. The results showed the satisfactory quality of models based on the True-Skill-Statistic (0.838 ±0.149), Area-Under-Curve values (0.958±0.038), and the Receiver-Operating-Characteristic curves. MaxEnt predicted that 1,78,993 km2 (4.10 %) area is favourable for the occurrence of the species. The precipitation of the driest quarter, precipitation of the coldest quarter and elevation were the most influential variables for habitat suitability prediction. The distribution area with an increase in greenhouse gases shows a decrease in the period 2081–2100 in both SSPs and GCMs. The study predicted highly suitable areas that would play a vital role in in situ conservation and improving the status of species. The predicted distribution maps of the species would help policymakers and decision-makers in developing suitable management plans, which will ultimately help in the conservation of species.

Elevation dependent climate assessment and its influence on snow cover variability in Hindu Kush Himalayan region using Google Earth Engine for the period of 2003–2021

The Hindu Kush Himalayan (HKH) regions are taken for this study, which is predominantly characterized by amplified climatic uncertainty and rapid snow melting. Because at the present there is a lack of studies estimating the elevation dependent and climate influenced snow cover variability in the HKH region. This present study examines elevation-dependent (2003–2021) distribution and trends in precipitation, temperature, and snow cover area (SCA) by employing numerous non-parametric statistical applications using the Google Earth Engine (GEE). The Modified Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow cover data is employed to estimate SCA along with the Climate Hazards Group Infrared Precipitation with Station Data version 2.0 (CHIRPS-V2.0) for precipitation and MODIS land surface temperature (LST). The study reveals statistically significant decreasing annual, seasonal, and monthly trends of SCA in most of the elevation zones typically during winter season (−0.256%/year), whereas temperature and precipitation exhibit strong spatial variability. Inclusive investigation portrays maximum mean annual and seasonal increased precipitation at the low-elevated regions, whereas seasonal disparities in temperature ostensible marginal decreased at high-elevation, albeit increased at lowland. Moreover, topographic importance on SCA distribution showcases maximum snow (43.4%) at north-facing less surface inclination with flat topography (14.6%). The comprehensive elevation wise analysis improves our understanding of the overall hydrological challenge and assist in the development of more reliable flood forecasting and water resource management.

Promoting social justice and women's rights: Mitigating the negative impacts of large hydropower projects on tribal women in the Hindu Kush Himalaya region

This study highlights the significance of comprehending the region's caste system and cultural norms and their influence on implementing compensation and resettlement programs in hydropower projects to gain social sustainability. By leveraging Social Justice Theory, we examine how systemic inequalities affect tribal women, particularly in the context of large-scale hydropower projects. Tribal women's social and cultural identities expose them to vulnerabilities, leading to negative consequences concerning large-scale hydropower projects. The lack of access to justice and limited participation in decision-making poses social justice challenges, undermining their fundamental rights, such as basic needs, healthcare, and education. Consequently, their well-being and quality of life suffer, impeding support for such projects. The extent of these adverse effects may vary depending on whether women belong to local (Indigenous) or non-local tribes (non-Indigenous). Our analysis reveals the critical role of tribal affiliation in moderating the relationship between social justice dimensions—such as distributive, procedural, substantive, and recognition justice—and social sustainability, offering new insights into Social Justice Theory. This study explores the potential of careful planning that prioritises the needs of tribal women regardless of tribal affiliation to mitigate these negative social consequences. The study employs a social justice framework to address these challenges. Through the analysis of 511 questionnaires using PLS-SEM, the study revealed that tribal affiliation moderates the relationship between social justice and sustainability. This contribution enriches Social Justice Theory by providing empirical evidence of the intersectionality of social justice issues in the context of development projects. The study further identified that social sustainability and community satisfaction mediate the relationship between social justice and support for hydropower projects, while tribal affiliation moderates this relationship.

Anthropogenic and biological activities elevate microplastics pollution in headwater ecosystem of Yangtze tributaries in Hindu Kush-Himalayan region

Microplastic (MP) pollution is widely spread in oceans, freshwater, and terrestrial environments but MPs in mountainous headwater ecosystem are rarely reported. This study focuses on the headwater of Yangtze tributaries of the Hindu Kush-Himalayan (HKH) region. Five streams at elevations of 900 to 3300 m were selected to investigate the distribution of MPs in water and sediments across altitudes. MPs were found in all water and sediment samples from top stream zone nearly in absence of anthropogenic activity, low anthropogenic zone, and high anthropogenic zone, increased from 12–54, 81–185 to 334–847 items/L, and 2–35, 26–84 to 124–428 items/kg, respectively. This elevation-dependent MP distribution indicated that as elevation decreased, anthropogenic activities intensified and increased MPs input and their abundance, size, and diversity. Notably, hydraulic projects, such as damming, were identified as potential barriers to the migration of MPs downstream. Microbiome analyses revealed the presence of bacterial genes associated with plastic biodegradation in all sediment samples. The study indicates that Shangri-la mountainous streams have been polluted with MPs for years with potential risk of generation of nano-sized particles via natural fragmentation and biodegradation, and thus raises concern on MPs pollution in headwaters streams in mountainous regions.

A Systematic Review on the Distribution and Density of <i>Aedes</i> Species in the Hindu-Kush Himalayan Countries

Aedes mosquitoes are effective carriers of virus pathogens such as chikungunya, dengue, yellow fever, zika, and other viruses, leading to high morbidity and mortality. This review compiles information on the geographical distribution of Aedes mosquitoes in the Hindu-Kush Himalayas (HKH). Articles published in SCI-indexed journals from 2000 to 2022 have been reviewed using the key words "Aedes”, "distribution", and "country name (e.g., Nepal)”. A total of 353 articles have been indexed, of which only 52 were ultimately explored. The review highlights a historical prevalence of Aedes spp. in the HKH countries, with their distribution gradually shifting along altitude gradients. Surging dengue cases in the HKH region pose a public health threat. Urgent action is required, including comprehensive nationwide surveys mapping Aedes spp. across diverse altitudes.

Perennial snow and ice cover change from 2001 to 2021 in the Hindu-Kush Himalayan region derived from the Landsat analysis-ready data

The changing climate directly affects spatial and temporal patterns of snow and ice cover globally and in the Hindu-Kush Himalayan (HKH) region. In the HKH, around 3.3 billion people across 11 countries depend on water originating from mountain glaciers and snowfields, and melting snow cover has a direct impact on their livelihood and well-being. Various studies have shown that the snow and ice cover in the HKH is declining at an alarming rate but have been limited in geographic, spatial and temporal scales. Here, we employed the Global Land Analysis and Discovery analysis ready Landsat time-series data (GLAD ARD) to map changes in perennial snow and ice between 2001 and 2021 at five-year epochs using decision tree ensemble models. These maps were used to create a stratified sampling design for reference data collection to estimate area and map accuracy. All five-year epoch maps have user's accuracies above 90% and producer's accuracies above 91%. Our sample data analysis showed that one-eighth of the extent of perennial snow and ice in the HKH, totalling 15,770 km2 (CI ± 3195 km2), disappeared over the last two decades with 105,935 km2 (CI ± 3396 km2) remaining in 2021. From map-based estimates, the largest decline of perennial snow and ice cover among the mountain ranges was found in the Himalayas with an estimated reduction of 5741 km2. Among HKH countries, China had the largest area of perennial snow and ice reduction of 10,654 km2, Nepal had the highest net perennial snow and ice reduction rate (31%). Among the river basins, the maximum net loss of perennial snow and ice cover between 2001 and 2021 was in the Indus (24.8%), followed by Brahmaputra (18.3%), and Tarim (15.7%). Our results confirm wide-spread loss of perennial snow and ice across the HKH region and provide both regionally consistent maps with derived area estimates at landform, national and basin-levels and methodology to continue monitoring snow and ice melt.

Climate change and rural livelihoods: The potential of extension programs for sustainable development

AbstractAgricultural extension programs promote regenerative land management practices by increasing farmers' awareness of land use, climate risks, and adoption of adaptation practices for sustainable livelihoods. This study focuses on the perceptions of communities that participate in extension programs and those that do not, regarding climate change risks and livelihood sustainability in Pakistan's Hindu Kush Himalayan (HKH) region. The findings indicate that communities participating in extension programs reported poor community land use practices as a cause of negative climate impacts. Farmers identified livestock deaths due to drought and frequent flooding as the main climate risks in their communities. Our study emphasizes the crucial role of extension programs in mitigating and adapting to environmental risks by increasing awareness, promoting a comprehensive understanding of climate risks and adaptation, and planning for land use management. Additionally, our findings underscore the significance of extension initiatives in enhancing livelihoods, such as agriculture, livestock, and forest‐based livelihoods, in the face of climate change challenges. We recommend increasing access to extension programs, strengthening the role of extension initiatives in climate change mitigation and adaptation, and promoting community participation in decision‐making to support sustainable livelihoods.

Climate change challenges to meeting the sustainable development goals in the Hindu Kush Himalayan region

ABSTRACT Understanding the effects of climate change on achieving the Sustainable Development Goals (SDGs) is critical, especially in the Hindu Kush Himalaya (HKH) region, which is experiencing a rate of warming nearly triple the global average. Despite the region’s importance in supporting major ecosystems and a vast population, the impacts of climate change on specific SDGs and their interconnections remain underexplored. This viewpoint article discusses the influence of climate change on the interplay among various SDGs, with a particular emphasis on SDG 6, SDG 7, and SDG 15. By offering insights into these challenges, this article aims to aid in the formulation and achievement of more effective strategies for meeting the SDGs in the Hindu Kush Himalaya (HKH) region.

Ecological factors affecting minerals and nutritional quality of "Dryopteris filix-mas (L.) Schott": an underutilized wild leafy vegetable in rural communities.

Dryopteris filix-mas (hereafter D. filix-mas), a wild leafy vegetable, has gained popularity among high mountain residents in the Hindukush-Himalaya region due to its exceptional nutritional profile, and their commercial cultivation also offers viable income alternatives. Nevertheless, besides phytochemicals with medicinal applications, ecological factors strongly affect their mineral contents and nutritional composition. Despite this, little has been known about how this wild fern, growing in heterogeneous ecological habitats with varying soil physiochemical properties and coexisting species, produces fronds with optimal mineral and nutritional properties. Given its nutritional and commercial significance, we investigated how geospatial, topographic, soil physiochemical characteristics and coexisting plants influence this widely consumed fern's mineral and nutrient content. We collected soil, unripe fern fronds, and associated vegetation from 27 D. filix-mas populations in Swat, NW Pakistan, and were analyzed conjointly with cluster analysis and ordination. We found that the fronds from sandy-loam soils at middle elevation zones exhibited higher nitrogen contents (9.17%), followed by crude fibers (8.62%) and fats (8.09%). In contrast, juvenile fronds from the lower and high elevation zones had lower moisture (1.26%) and ash (1.59%) contents, along with fewer micronutrients such as calcium (0.14-0.16%), magnesium (0.18-0.21%), potassium (0.72-0.81%), and zinc (12% mg/kg). Our findings indicated the fern preference for middle elevation zones with high organic matter and acidic to neutral soil (pH ≥ 6.99) for retaining higher nutritional contents. Key environmental factors emerged from RDA analysis, including elevation (r = -0.42), aspect (r = 0.52), P-3 (r = 0.38), K+ (r = 0.41), EC (r = 0.42), available water (r = -0.42), and field capacity (r = -0.36), significantly impacting fern frond's mineral accumulation and nutrient quality enhancement. Furthermore, coexisting plant species (r = 0.36) alongside D. filix-mas played a pivotal role in improving its mineral and nutritional quality. These findings shed light on the nutritional potential of D. filix-mas, which could help address malnutrition amidst future scarcity induced by changing climates. However, the prevalent environmental factors highlighted must be considered if the goal is to cultivate this fern on marginal lands for commercial exploitation with high mineral and nutrient yields in Hindukush-Himalaya.

Multi-century (635-year) spring season precipitation reconstruction from northern Pakistan revealed increasing extremes

The Hindu Kush Himalaya region is experiencing rapid climate change with adverse impacts in multiple sectors. To put recent climatic changes into a long-term context, here we reconstructed the region’s climate history using tree-ring width chronologies of climate-sensitive Cedrus deodara and Pinus gerardiana. Growth-climate analysis reveals that the species tree-growth is primarily limited by moisture stress during or preceding the growing season, as indicated by a positive relationship between the chronology and precipitation and scPDSI, and a negative one with temperature. We have reconstructed 635 years (1384–2018 CE) of February–June precipitation using a robust climate reconstruction model that explains about 53% variance of the measured precipitation data. Our reconstruction shows several dry and wet episodes over the reconstruction period along with an increase in extreme precipitation events during recent centuries or years. Long, very wet periods were observed during the following years: 1392–1393, 1430–1433, 1456–1461, 1523–1526, 1685–1690, 1715–1719, 1744–1748, 1763–1767, 1803–1806, 1843–1846, 1850–1855, 1874–1876, 1885–1887, 1907–1909, 1921–1925, 1939–1944, and 1990–1992, while long dry periods were observed during the following years: 1398–1399, 1464–1472, 1480–1484, 1645–1649, 1724–1727, 1782–1786, 1810–1814, 1831–1835, 1879–1881, 1912–1918, 1981–1986, 1998–2003, and 2016–2018 CE. We found predominantly short-term periodicity cycles of 2.0, 2.2, 2.3, 2.4, 2.6–2.7, 2.9, 3.3, 4.8, 8.1–8.3, and 9.4–9.6 years in our reconstruction. Spatial correlation analyses reveal that our reconstruction is an effective representation of the precipitation variability in the westerly climate-dominated areas of Pakistan and adjacent regions. In addition to the influence of regional circulation systems like western disturbances, we found possible teleconnections between the precipitation variability in northern Pakistan and broader-scale climate modes or phases like AMO and ENSO. The study also highlights the prospects of tree-ring application to explore linkages between western disturbance, increasing intensity and frequency of extreme climate events, and analysis of long-term atmospheric circulation over the western Himalayan region.

Remote Sensing Based Deforestation Monitoring at the Change Hotspot Area in Hindu Kush Himalayan Region

Forests play an essential role in providing sustainable ecosystem services and livelihood options for a growing population. In the Hindu Kush Himalayan (HKH) region, forests have been continuously reduced due to increasing demand for timber, fuelwood, and agriculture. Identification of deforestation hotspots and monitoring changes in those hotspots will be highly useful for forest managers to prevent illegal deforestation. In this paper, we identified forest cover change hotspots and areas for annual monitoring in those hotspots. For that factors like land cover from 1990 and 2010, shuttle radar topography mission (SRTM) digitalelevation model (DEM), slope, curvature, and distance from the settlement and roads for all four countries which could influence loss in forest area and overplayed to determine forest hotspots, were considered. Land cover maps of 1990 and 2010 and other GIS layers were used for identification of hotspots using the model builder ArcGIS software. For monitoring of deforestation in the hotspot areas, Landsat 8 images (2013, 2014 and 2015) and geographic object-based image analysis (GEOBIA) technique was used. The method was validated in four study sites in Bangladesh, Nepal, Bhutan and Pakistan. The study revealed that the sites in Bangladesh have higher deforestation during 2013-2014 and 2014-2015 with forest loss of 1121.58 and 1773.18 ha respectively. The web-based forest monitoring system provides information on deforestation useful for forest managers to enforce annual management plans.

Numerical Analysis of Francis Turbine being operated in variable speed from sediment erosion perspective

Sediment erosion in hydro turbines is one of the most daunting reasons incurring huge losses to power plant owners located in the Hindu Kush Himalayan region. Repetitive repair and maintenance of runners of Francis turbines installed in such power plants have been one of the major contributor to these losses. There is no measure of how much these power plant owners have lost due to reduction in efficiency brought about by the eroded surfaces of runners. Amidst several optimizations performed in changing the runner design, this study has been conducted to study the applicability of the pre-existing designs being operated in variable speed conditions, irrespective of its practical difficulties. Numerical simulations have been performed to determine the sediment erosion of the runners at different operating conditions. In addition to the guide vane angles, and the amount of sediment injected into the system; which is parametrized as a function of the guide vane angles; rotational speed of the runner has also been varied. Complete efficiency hill diagram and sediment erosion hill diagram have been developed to analyse the efficiency and sediment erosion at several operating conditions. Finally a comparison of the variations in efficiency and sediment erosion upon operating the turbine in synchronous speed and variable speed modes have been shown. Basically, the efficiency of the turbine and sediment erosion on blade surface can be increased and decreased respectively, at off design conditions by operating the turbine in variable speed.

Rise in Mid-Tropospheric Temperature Trend (MSU/AMSU 1978–2022) over the Tibet and Eastern Himalayas

The high-altitude Hindu Kush-Himalayan region (HKH, average ~5 km from msl) and the adjacent Indo-Gangetic plains (IG plains, ~0–250 m msl), due to their geographical location and complex topography, are reported to be highly sensitive to climatic changes. Recent studies show that the impacts of climate change and associated changes in water resources (glacial/snow melt water and rainfall) in this region are multifaceted, thereby affecting ecosystems, agriculture, industries, and inhabitants. In this study, 45 years of Microwave Sounding Unit/Advanced Microwave Sounding Unit (MSU/AMSU)-derived mid-tropospheric temperature (TMT, 3–7 km altitude) and lower tropospheric temperature (TLT, 0–3 km altitude) data from the Remote Sensing Systems (RSS Version 4.0) were utilized to analyze the overall changes in tropospheric temperature in terms of annual/monthly trends and anomalies. The current study shows that the mid-tropospheric temperature (0–3 km altitude over the HKH region) has already alarmingly increased (statistically significant) in Tibet, the western Himalayas, and the eastern Himalayas by 1.49 °K, 1.30 °K, and 1.35 °K, respectively, over the last 45 years (1978–2022). As compared to a previous report (TMT trend for 30 years, 1979–2008), the present study of TMT trends for 45 years (1978–2022) exhibits a rise in percent change in the trend component in the high-altitude regions of Tibet, the western Himalayas, and the eastern Himalayas by approximately 310%, 80%, and 170%, respectively. In contrast, the same for adjacent plains (the western and eastern IG plains) shows a negligible or much lower percent change (0% and 40%, respectively) over the last 14 years. Similarly, dust source regions in Africa, Arabia, the Middle East, Iran, and Pakistan show only a 130% change in warming trends over the past 14 years. In the monthly breakup, the ‘November to March’ period usually shows a higher TMT trend (with peaks in December, February, and March) compared to the rest of the months, except in the western Himalayas, where the peak is observed in May, which can be attributed to the peak dust storm activity (March to May). Snow cover over the HKH region, where the growing season is known to be from September to February, is also reported to show the highest snow cover in February (with the peak in January, February, or March), which coincides with the warmest period in terms of anomaly and trend observed in the long-term mid-tropospheric temperature data (1978–2022). Thus, the current study highlights that the statistically significant and positive TMT warming trend (95% CI) and its observed acceleration over the high-altitude region (since 2008) can be attributed to being one of the major factors causing an acceleration in the rate of melting of snow cover and glaciers, particularly in Tibet and the Eastern Himalayas.

Enhancing the Glacial Lake Inventory in Bhutan through Semi-Automatic Techniques using Google Earth Engine and QGIS for the Phochhu Basin

Bhutan located in the Hindu Kush Himalayan (HKH) region consists of several glaciers and glacial lakes at higher elevations. With the rapid change in global temperature, glaciers are found to melt at an accelerated rate. This rapid melt of glaciers gets accumulated in weak moraine walls forming a glacial lake, posing a major threat to the downstream communities. As per the Bhutan Glacial Lake Inventory 2021, Bhutan has 567 glacial lakes. Furthermore, the Phochhu basin has the maximum glacial lakes (0.05%) and of which 9 are PDGL. Hence a need for a time monitoring system is imminent. With the availability of free High-resolution Satellite Imageries and Advanced Remote Sensing tools, it has been a sine qua no for monitoring glacial lakes in high areas. Therefore, using the Google Earth Engine and Qgis Platform a semi-automated technique was used to generate glacial lake inventories for Phochhu Sub-basin for the year 2021. We found out that there are 166 glacial lakes covering an area of 24.051 km2.

Preference, perceived change, and professed relationship among ecosystem services in the Himalayas

The demand side of ecosystem service (ES), especially preference and perception of supply and interactions among ES, is an important yet underexplored research area for landscape planning and management in human-dominated landscapes. Taking a case of multifunctional landscape in the Hindu-Kush Himalayan region, we carried out a social survey of ES, focusing on preference, perceived change, and observed relationship among six major ES from the local people's perspective. Using a semi-structured questionnaire, data collection was done from 300 households from 10 categories of human settlements, based on watershed and land cover types. Garrett mean score (GMS), ordinal logistic regression estimates, and Chi-square test were performed for quantitative data, while an inductive approach was adopted for qualitative data analysis. The results show that at the landscape level, local people preferred water yield (GMS = 70) and crop production (GMS = 66) as the most preferred ES, whereas habitat quality (GMS = 37) and carbon sequestration (GMS = 35) were among the least preferred ES. More than 70% of the respondents believed that the supply of crop production has decreased over the last two decades; however, the supply of other provisioning and non-provisioning ES has increased as observed by majority of the respondents. Among the 15 pairs of ES, local people believe that co-occurrence of ES is possible. Majority of the respondents said that there exist synergistic relationship among 13 pairs of ES, except crop production which is negatively related with timber production and carbon sequestration. Among the identified trade-offs in ES, majority of local people believed that direct trade-offs (i.e., linear inverse relationship) is dominant as observed in 8 pairs of ES, followed by concave and convex trade-offs. Based on our analysis, we argue that the preference and perceived change of ES is more dependent on spatial heterogeneity of communities (i.e., watershed type, municipal category, and land cover type of residence) than socio-economic determinants. Further, we have discussed and suggested few policy and management measures including place-based spatial assessment of the social demand and preference, embracing agroforestry practices in ecosystem management programs, mainstreaming non-local ES in local decision making by incentives, and optimizing the supply of desired ES though integrated biophysical and socio-economic assessment of the landscape.

Advancing Sustainable Development in the Hindu-Kush-Himalaya Region Through Certification Strategies

This study investigates the potential of certification as a driving force for sustainable development in the Hindu-Kush-Himalaya (HKH) region, characterized by its unique high-altitude ecosystems, rich biodiversity, and susceptibility to climate change. Focusing on small and medium-sized enterprises (SMEs) within the tourism, renewable energy, and agriculture sectors, the research emphasizes their critical role in the region's economic growth and livelihoods. Nonetheless, the implementation of certification in the HKH region encounters several obstacles, including constrained resources, regulatory barriers, financial accessibility, and limited marketing capabilities. By examining certification initiatives in Bhutan and Nepal, such as organic certification and energy labeling, this study elucidates the advantages and challenges associated with both mandatory and voluntary certification schemes. To address these concerns, the establishment of an HKH Standards and Certification Council is proposed. This Council would facilitate the development and adoption of credible certification and accreditation processes, thereby promoting sustainability and energy efficiency throughout the region. By supporting SMEs, fostering collaboration, and ensuring the relevance, accessibility, and efficacy of standards for small businesses, the HKH Standards and Certification Council could significantly contribute to the sustainable development of the HKH region.

A geospatial analysis of long-term trends in snow depth in the Hindu Kush Himalayan region: 1999–2019

A geospatial analysis of long-term trends in snow depth in the Hindu Kush Himalayan region: 1999–2019