Drang Drung and Pensilungpa are neighbouring glaciers in the western Himalayas, sharing the same meteorological conditions and climate zone. The Drang Drung glacier is a clean glacier, whereas the Pensilungpa glacier is notable for its considerable accumulation of debris. The present study explores the topographical features of the Drang Drung and Pensilungpa glaciers and investigates how topography affects their response to climate change. Additionally, a comparison is made between these glaciers with others in the basin to assess their representativeness of the region. The study utilized Landsat Imagery and ASTER GDEM data from 1976 to 2020. The results revealed that the mean accumulation area ratio (AAR) for Drang Drung and Pensilungpa was 54% and 49%, respectively, during this period. Drang Drung has lost 8.16 km² (10.73%) of its area, while Pensilungpa has lost 2.25 km² (9.84%) of its area. The debris cover of Pensilungpa increased from 1.86 km² in 1976 to 2.32 km² in 2020, whereas the debris cover area of Drang Drung has increased comparatively more, from 4.01 km² to 4.76 km². Within the same time frame, the snowline altitude (SLA) shifted upward by an average of 104 m and 88 m for Drang Drung Pensilungpa, respectively. Further, our findings revealed a substantial connection between the size of glaciers and the speed at which their area is diminishing. The mean slope was identified as a key factor in influencing the rate at which the area is lost, and the retreat rates of the glaciers. The reduction in glacial area, increased debris coverage, and changes in SLA are key indicators of ice volume loss under prevailing climatic conditions. The present study recommends that long-term field-based data and the incorporation of multi-temporal satellite imagery are crucial to mitigate uncertainties in detecting changes in Himalayan glaciers. These approaches would contribute to a more accurate understanding of glacial changes, and would aid in forecasting future scenarios considering ongoing global warming trends.

Land use/land cover (LULC) change significantly influences a range of environmental and socio-economic issues, including climate change, deforestation, biodiversity loss, soil degradation, ecosystem services, and food security, at local, regional, and global levels. In the northwestern Himalayan region, particularly in Rajouri district of Jammu and Kashmir (J&K), LULC change has profound environmental and socio-economic implications. Understanding the temporal and spatial dimensions of LULC change is crucial for assessing the impact of human activities on the region’s environment. The present study aimed to analyze LULC change in Rajouri district of J&K, India over a 30-year period from 1990 to 2020 and to project future LULC dynamics for the next 30 years up to 2050. Landsat imagery with a supervised classification technique was used for classification and generation of LULC maps. Moreover, CA Markov model was used to predict the future LULC status of the area. The model validation exhibited strong performance, with Kappa statistics exceeding 0.90, indicating a high level of reliability in the projections. The results indicate considerable changes in different land use classes from 1990 to 2020. Over the 30-year period, dense forest showed the maximum reduction of about −20.69 Km², followed by open forest (−15.87 Km²) and grassland (−13.75 Km²). Wasteland showed the maximum increase of about +28.24 Km², followed by built-up (+17.90 Km²) and cropland (+12.50 Km²). The cumulative impact of deforestation from 1990 to 2020 amounts to approximately 43.17 Km², while afforestation efforts only managed to reclaim 6.61 Km² of land. The future prediction using the CA Markov model suggests further changes in LULC patterns, with built-up, cropland, and wasteland projected to increase exponentially by 2050, accompanied by sharp declines in forests. Therefore, policymakers should prioritize sustainable land management and forest conservation strategies to mitigate the potential negative impacts of LULC changes on the environment, ensuring balanced and sustainable development.

The Western Himalayan Glacial lakes are undergoing rapid transformation as a result of intensified glacier retreat driven by changing climatic conditions, increasing the likelihood of glacial lake outburst floods (GLOFs). This study conducts an automated, multi-decadal analysis of glacial lakes in the Upper Indus Sub-Basin using Landsat imagery spanning 1990 and 2025, processed within the Google Earth Engine (GEE) platform. A Modified Normalized Difference Water Index (MNDWI), integrated with topographic constraints and morphological filtering, was employed for accurate lake extraction, followed by manual refinement. Results reveal a substantial increase in glacial lake number from 255 in 1990 to 775 in 2025, and the overall lake area increased from 34.81 to 37.72 km², which indicates a gradual but consistent growth (0.083 km²·a⁻¹). The expansion is primarily driven by the rapid formation of small lakes (< 1 km²), whereas larger lakes remain limited in number but contribute significantly to total area. Elevation analysis shows that most lakes are concentrated between 4000 and 5000 m a.s.l., which highlights strong altitudinal control on lake development. Additionally, 520 new glacial lakes were identified during the study period, which reflects persistent hydrological stability alongside dynamic lake formation. Hazard assessment based on lake characteristics, glacier proximity, expansion rate, and topographic conditions indicates increasing susceptibility of several lakes to GLOF events. The observed trends are strongly linked to regional warming and enhanced glacier melt. This study suggests the effectiveness of GEE-based approaches for large-scale cryospheric monitoring and provides critical insights for hazard assessment and water resource management in the Upper Indus Sub-Basin.