This study provides a high resolution glacier database in the Changme Khangpu Basin (CKB) using LANDSAT 8 (2014) and Sentinel-2A image (2016), mapping of 81 glaciers that cover a 75.78 ± 1.54 km² area. Composite maps of land surface temperature, slope and Normalized differential Snow Index have been successfully utilized in delineating near accurate debris cover boundary of glaciers. The cumulative controlling parameters of aspect, elevation, slope, and debris cover have been assessed to evaluate the nature of glacier distribution and dynamics. The local topographic settings seem to have significantly determined the glacier distribution in the CKB. Almost 20% area erstwhile under glacier cover has been lost since 1975 at an average rate of −0.453 ± 0.001 km²a⁻¹. The recent decade (2001–2016) has witnessed a higher rate of area shrinkage (−0.665 ± 0.243 km²a⁻¹), compared to a relatively lower rate of recession (−0.170 ± 0.536 km²a⁻¹) between 1988 and 2001. The lower rates of glacial recession can most likely be induced regionally due to relatively cooler decadal late summer temperatures and peak in the monsoon spell. Glaciers with western and north-western aspects showed more vulnerability to area loss than the rest of the aspects. Lower altitude glaciers have receded faster than ones perched up on higher elevations. The rate of glacier area recession has been nearly twice that on clean glaciers as compared to debris-covered glaciers in the CKB.

Detailed field mapping of glacial and paraglacial landforms and optical dating from these landforms are used to reconstruct the early Holocene glaciation in the semi-arid region of Miyar basin, Lahaul Himalaya. The study identifies three stages of glaciation, of decreasing magnitude and termed, from oldest to youngest, the Miyar stage (MR-I), Khanjar stage (KH-II), and Menthosa advance (M-III). The oldest glacial stage (MR-I) has been established on the basis of detailed geomorphological evidence such as U-shaped valley morphology, trimlines, and truncated spurs. It is speculated to be older than the global Last Glacial Maximum (gLGM) based on the magnitude of ΔELA (Equilibrium-Line Altitude, 606m). No evidence of glacier expansion recorded from the basin correlates with the period of the gLGM. The second stage (KH-II) is well represented by extensive depositional features such as lateral and terminal moraines, drumlins, and lacustrine fills that have been constrained within 10 ± 1 to 6.6 ± 1.0 ka (Optically stimulated luminescence—OSL—ages), dating it to the early Holocene advance following the Younger Dryas cooling event. Exceptionally young glacial records of expansion are limited within a few hundred meters of the present termini of tributary glaciers and correlates with the 18th-century cooling event. Records of this glacial advance, termed the Menthosa advance, are clearly noticed in some tributary valleys.

Glacier shrinkage is a globally occurring phenomena. High-resolution change detection based on frequent mapping and monitoring of high-altitude glaciers is necessary to precisely evaluate future water availability and to understand glacier evolution under different climatic scenarios in the Hindukush-Karakoram-Himalayan (HKH) region. This also holds true for the Bhaga basin of the western Himalaya. This study investigates glacier and glacier lake changes in the Bhaga basin, over the last five decades based on satellite imagery including Corona KH4 (1971), Landsat 7 Enhanced Thematic Mapper Plus (ETM+; 2000), Linear Imaging Self-Scanning Sensor (LISS IV; 2013), and Sentinel 2 (2020). Regional temperature and precipitation trends were evaluated from gridded climatic datasets (1900–2020). In the Bhaga basin 306 glaciers (>0.2 km²) were mapped with a total area of 360.3 ± 4.0 km², of which 55.7 ± 0.6 km²was covered with debris in 2013. The total glacier covered area decreased by ∼8.2 ± 1.5 % (0.16 ± 0.03 % yr⁻¹) during the entire observation period 1971–2020, with noticeable heterogeneity between tributary watersheds. In the past two decades (2000–2020), the deglaciation rate has increased significantly (0.25 % yr⁻¹) compared to the previous decades (1971–2000; 0.12 % yr⁻¹). Glacier lake area increased by 0.6 ± 0.1 km²(0.012 km²yr⁻¹) between 1971 and 2020. The NCEP/NCAR climatic data reveals an increase of 0.63°C in temperature and a decrease of 6.39 mm in precipitation for the period 1948–2018. In comparison, APHRODITE data shows an increasing trend in temperature of 1.14°C between 1961 and 2015 and decreasing trend in precipitation of 31 mm between 1951 and 2007. Both NCEP/NCAR and APHRODITE data reveal significant temperature increase and precipitation decrease since the 1990s, which have probably augmented ice loss in the Bhaga basin during the early 21^stcentury.

The Sikkim Himalayan glaciers and glacial lakes are affected by climate change like other parts of the Himalayas. As a result of this climate variability in the Sikkim Himalaya, a detailed study of the Gurudongmar lake complex (GLC) evolution and outburst susceptibility assessment is required. Glacial lake volume estimation and lake outburst susceptibility assessment were carried out to reveal different characteristics for all four lakes (GL-1, GL-2, GL-3, and GL-4) from the lake complex. Each of these lakes has a moderate to very high potential to outburst. As the dam of GL-1 provides no retention capacity, there is a very high potential of a combined effect with the sudden failure of the moraine-dams of GL-2 or GL-3 located upstream. Temporal analysis of GLC using optical remote sensing data and in-field investigations revealed a rapidly increasing total lake area by ~74 ± 3%, with an expansion rate of +0.03 ± 0.002 km² a⁻¹ between 1962 and 2018 due to climate change and ongoing glacier retreat. The overall lake area expansion rates are dependent on climate-driven factors, and constantly increasing average air temperature is responsible for the enlargement of the lake areas. Simultaneously, changes in GLC expansion velocity are driven by changes in the total amount of precipitation. The deficit in precipitation probably triggered the initial higher rate from 1962 to 1988 during the winter and spring seasons. The post-1990s positive anomaly in precipitation might have reduced the rate of the glacial lake area expansion considerably.

This study focuses on identifying the key drivers of desertification in the Sirsa district of Haryana, India. It takes into account several factors, such as climate, soil, regional hydrology, vegetation condition, land use, available amenities, and economic conditions. Using a hierarchy-based model within a geographic information system framework, these parameters were integrated to create the Desertification-Land Degradation Vulnerability Index (DLVI). The analysis categorizes the results into five vulnerability zones-very high, high, moderate, low, and very low-based on their relative susceptibility to desertification and land degradation. The findings highlight that areas experiencing lower rainfall, higher temperatures, and greater population density with limited social amenities face a higher risk of desertification, particularly in the south-southwest and western parts of Sirsa. To validate the DLVI map, Land Degradation Status Maps are used, employing the Receiver Operating Curve and the Area Under the Curve. This validation process demonstrates an accuracy rate of 61.6%. The model-based approach, which integrates various factors encompassing the geo-environmental and socio-economic aspects, offers valuable insights for the formulation of effective mitigation strategies to combat land degradation and desertification in the future.