Assessing the status of glaciers in part of the Chandra basin, Himachal Himalaya: A multiparametric approach

Abstract

This study investigates the change in multiple glacier parameters of three valley-type glaciers (Sakchum (SC), Chhota Shigri (CS), and Bara Shigri (BS)) located in Chandra basin, Himachal Himalaya, sharing the same climatic regime, and assesses the control of nonclimatic factors on wholesome glacier response. Multitemporal satellite remote sensing data from Landsat-TM/ETM/OLI (1993-2014), and Terra-ASTER (2002-2014) along with an SRTM digital elevation model were used for extraction of the glacier parameters. Results show that while SC and BS retreated (SC: 10.65 ±2.52 m/y; BS: 15.51 ±2.52 m/y) and lost area (SC: 0.49 ±0.0032 km 2 , BS: 1.18 ±0.0032 km 2), the CS remained relatively stable (retreat rate: 4.06 ±2.52 m/y, area loss: 0.19 ±0.0032 km 2) during 1993-2014. However, results of surface ice velocities (SIV) change (SC: 24.41%, CS: 21.60%, and BS: 28.49%) and surface elevation change (SC:-1.22 m/y, CS:-0.91 m/y and BS:-1.21 m/y) suggest a comparable slowing down and surface lowering from 2002 to 2014. Debris cover also varied substantially (SC: 30.25%, CS: 11.96%, BS: 19.61%) on these glaciers. Results reveal that higher retreat/deglaciation of glaciers was associated with higher altitudinal range, slow SIV in lower ablation zones (LAZ), and glacier hypsometry. Debris cover on glaciers was found to be controlled by slope, higher deglaciation rates, higher SIV in the upper ablation zone (UAZ) coupled with lower SIV in LAZ and surface lowering. Glacier SIV was primarily governed by slope gradient, differential surface lowering, and size of accumulation zone (ACZ). The SIV results confirm the presence of stagnant zones in the lower ablations of SC (<1 km upstream) and BS (<6 km upstream) and a major SIV dropdown in the UAZ (SC: 34.48%, BS: 37.35%), indicating the expansion of stagnant zones farther up. Glacier surface lowering seemed to be influenced by ice-flux, changing spatial distribution of debris cover, presence of supraglacial lakes, and ice cliffs bordering them. Melting around supraglacial lakes and backwasting of ice cliffs may be the prime reasons behind intense mass loss observed in the stagnant zone of the Bara Shigri glacier, where surface lowering was ~32% higher than glacier-wide thinning. Differential surface lowering in glaciers reduced the surface gradient and hence the SIV. Also, rapid surface gradient changes and SIV dropdown in the Sakchum glacier indicate possible development of supraglacial lakes on it in the future. Interestingly, despite close proximity, SC, CS, and BS demonstrate three distinct ablation patterns, reemphasizing the role of nonclimatic factors. Overall, the study states that mutual 3 variation of glacier parameters together with nonclimatic factors exercise a great control on glacier response.

Surface Velocity Dynamics of Samudra Tapu Glacier, India From 2013 to 2017 Using Landsat-8 Data

“…However, the surface velocity is showing an increasing pattern. Garg et al (2017) have also observed increasing pattern. The error in surface velocity is estimated in non-glaciated stable area.…”

“…Third error can occur due to poor image contrast in images. To overcome this error, surface velocity is estimated only in ablation zone instead of accumulation zone (Bhushan et al, 2017;Garg et al, 2017;Paul et al, 2015).…”

“…In present study, total ~750 points are selected near the terminus and then mean surface velocity is estimated. This is the most common method to estimate the error in surface velocity, which has previously been used by various authors (Garg et al, 2017;Saraswat et al, 2013).…”

“…The error varied from ± 4.01 to ± 4.71 m/year during 2013-2017 with mean error being ± 4.49 m/year. Surface velocity of Samudra Tapu Glacier is much larger than other glaciers in Chandra basin (Garg et al, 2017;Sahu and Gupta, 2019;Tiwari et al, 2014;Yellala et al, 2019). The surface velocity estimation for Samudra Tapu Glacier using remote sensing data or through field methods is also not available in the literature.…”

“…Paul et al (2017 estimated surface velocity of Hispar Glacier in Karakoram using Landsat ETM+, Landsat OLI, RADARSAT-2 and Sentinel-1 data during 2013-2015 and correlated the same with glacier surging behaviour. In Chandra basin, Garg et al (2017)…”