No abstract

Abstract. Glaciers of the Tista basin represent an important water source for mountain communities and a large population downstream. The article presents observable changes in the Chhombo Chhu Watershed (CCW) glacier area of the Tista basin, the Sikkim Himalaya. The CCW contains 74 glaciers (> 0.02 km2) with a mean glacier size of 0.61 km2. We determined changes in glaciers from the declassified Hexagon Keyhole-9 (KH-9) (1975), Landsat 5 Thematic Mapper (TM) (1989), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2000), Landsat 5 TM (2010), and Sentinel-2A (2018) images. The total glacier area in 1975 was 62.6 ± 0.7 km2; and by 2018, the area had decreased to 44.8 ± 1.5 km2, an area loss of 17.9 ± 1.7 km2 (0.42 ± 0.04 km2 a−1). Clean glaciers exhibited more area loss of 11.8 ± 1.2 km2 (0.27 ± 0.03 km2 a−1) than partially debris-covered and maximally debris-covered glaciers. The area loss is 5.0 ± 0.4 km2 (0.12 ± 0.01 km2 a−1) for partially covered glaciers and 1.0 ± 0.1 km2 (−0.02 ± 0.002 km2 a−1) for maximally covered glaciers. The glacier area loss in the CCW of the Sikkim Himalaya is 0.62 ± 0.5 km2 a−1 during 2000–2010, and it is 0.77 ± 0.6 km2 a−1 during 2010–2018. Field investigations of selected glaciers and climatic records also support the glacier recession in the CCW due to a significant increase in temperature (0.25 ∘C a−1) and more or less static precipitation since 1995. The dataset is now available from the Zenodo web portal: https://doi.org/10.5281/zenodo.4457183 (Chowdhury et al., 2021).

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.

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.

Abstract. Glaciers of the Tista basin represent an important water resource for mountain communities and large population downstream. The present article attempts to assess the observable changes in the glacier area in the Chhombo Chhu Watershed (CCW) of Tista basin, Sikkim Himalaya. The CCW consists of 74 glaciers (>0.02 km2) with a mean glacier size of 0.61 km2. The change of such glacier outlines obtained from the declassified hexagon KH-9 (1975), Landsat 5 TM (1989), Landsat 7 ETM+ (2000), Landsat 5 TM (2010), and Sentinel 2A (2018). The total glacier area in 1975 was 62.6 ±0.7 km2; by 2018, the area had decreased to 44.8 ±1.5 km2, an area loss of 17.9 ± 1.7 km2 (0.42 ± 0.04 km2 a−1). Debris free glaciers exhibit more area loss by 11.8 ± 1.2 km2 (0.27 ± 0.03  km2 a−1) followed by partially debris-covered (5.0 ± 0.4 km2 or 0.12 ± 0.01 km2 a−1) and maximum debris-covered (1.0 ± 0.1 km2 or −0.02 ± 0.002 km2 a−1) glaciers. The quantum of glacier area loss in the CCW of Sikkim Himalaya took its pace during 2000–2010 (0.62 ± 0.5 km2 a−1) and 2010–2018 (0.77 ± 0.6 km2 a−1) timeframes. Field investigations of selected glaciers and climatic records also support the trend in glacier recession in the CCW due to a significant increase in temperature trend and more or less static precipitation since 1995. Glacier retreat rates in the CCW were almost similar to the Changme Khangpu basin and other selected glaciers in Sikkim Himalaya. This glacier inventory and area change analysis will provide valuable information to the glaciological and hydrological community to model and plan the water resources in the Sikkim state of Eastern Himalaya. The dataset is now available from the Zenodo web portal: http://doi.org/10.5281/zenodo.4457183 (Chowdhury et al., 2021).