Pratima Pandey a & Gopalan Venkataraman a a Centre of Studies in Resources Engineering, Indian Institute of

This article was downloaded by: [IIT Indian Institute of Technology - Mumbai] On: 08 May 2013, At: 21:31 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK International Journal of Remote Sensing Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tres20 Changes in the glaciers of Chandra Bhaga basin, Himachal Himalaya, India, between 1980 and 2010 measured using remote sensing Pratima Pandey a & Gopalan Venkataraman a a Centre of Studies in Resources Engineering, Indian Institute of Technology, Mumbai, India Published online: 08 May 2013. To cite this article: Pratima Pandey & Gopalan Venkataraman (2013): Changes in the glaciers of Chandra Bhaga basin, Himachal Himalaya, India, between 1980 and 2010 measured using remote sensing, International Journal of Remote Sensing, 34:15, 5584-5597 To link to this article: http://dx.doi.org/10.1080/01431161.2013.793464 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-andconditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

International Journal of Remote Sensing, 2013 Vol. 34, No. 15, 5584 5597, http://dx.doi.org/10.1080/01431161.2013.793464 Changes in the glaciers of Chandra Bhaga basin, Himachal Himalaya, India, between 1980 and 2010 measured using remote sensing Pratima Pandey* and Gopalan Venkataraman Centre of Studies in Resources Engineering, Indian Institute of Technology, Mumbai, India (Received 11 August 2012; accepted 2 February 2013) This study reports the glacier changes of Chandra Bhaga basin, northwest Himalaya, India, from 1980 to 2010. Satellite remote-sensing data from the Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM), the Linear Imaging Self Scanning Sensor (LISS) and Advanced Wide Field Sensor (AWiFS) of the Indian Remote Sensing (IRS) series, and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) were used to study the changes in glacier parameters such as glacier area, length, snout elevation, and the impact of glacier topographical parameters (glacier slope, aspect, and altitude range) on the glacier changes. It was found that the total glaciated area had shrunk to 368.2 km 2 in 2010 from 377.6 km 2 in 1980, a loss of 2.5%. The average position of glacier terminuses retreated by 465.5 ± 169.1 m from 1980 to 2010 with an average rate of 15.5 ± 5.6myear 1. The decadal scale analysis showed that the average rate of retreat had increased the most in the recent decade. A moraine-dammed lake located in the study region was found to have expanded in area from (0.65 ± 0.01) km 2 in 1980 to (1.26 ± 0.03) km 2 in 2010. Glaciers with steep slope and less altitude range have lost more area than the glaciers having gentle slope and greater altitude range. 1. Introduction The Himalaya is the youngest and the highest mountain chain of the world. There are 9575 glaciers in the Indian Himalaya covering an area of 37,466 km 2 (Kaul 1999; Raina and Srivastava 2008; Sangewar and Shukla 2009). The region is aptly called the Water Tower of Asia as it provides around 8.6 10 6 m 3 of water annually (Dyurgerov and Meier 1997). It is home to many large and small glaciers which feed a number of important rivers such as the Ganges, Amu Darya, Indus, Brahmaputra, Irrawaddy, Salween, Mekong, Yangtze, Yellow, and Tarim and others in Asia. Apart from being a water provider, the Himalaya also has an important role in Indian climatology. The Himalaya acts as a boundary between the two different climatological regions to its north and to its south. The study of Himalaya is therefore important both climatologically and hydrologically. Recent meteorological studies on the Himalaya report changes in the climate in terms of temperature and precipitation. During the last century, a significant rise in temperature (1.6 C) with a rate higher than the global average has been reported in the northwestern Himalaya (Bhutiyani, Kale, and Pawar 2007). A decreasing trend of snowfall and rising temperature have also been observed over the western Himalaya (Shekhar et al. 2010). *Corresponding author. Email: pratimapandey@iitb.ac.in 2013 Taylor & Francis

International Journal of Remote Sensing 5585 Glaciers are indicators of climate change. Changes in climate are reflected in glacier behaviour. Glaciers respond to climate change in terms of length, area, and volume. It has been reported that the Himalayan glaciers have been in a state of recession since the 1850s (Mayewski and Jeschke 1979). The Himalayan glaciers are retreating with varying rates, ranging from a few metres to 50 m year 1 (Kulkarni 2010). The glaciers of Chenab, Parbati, and Baspa basin (Kulkarni et al. 2007), as well as glaciers of Garhwal Himalaya (Bhambri et al. 2011; Mehta, Dobhal, and Bisht 2011), are reported to be shrinking. Studies of the mass balances of Himalayan glaciers have shown that most of them have a negative mass balance (Dobhal, Gergan, and Thayyen 2004; Kulkarni, Rathore, and Suja 2004; Kulkarni et al. 2007; Kumar et al. 2007; Wagnon et al. 2007; Geological Survey of India, personal communication with Dr S. P. Shukla, April 2011). Some large glaciers of Karakoram regions have been reported to be either stable or advancing (Scherler, Bookhagen, and Strecker 2011). However, it is still difficult to interpret the reason for their advancing, whether it is climatological or due to their surging (Gardelle, Berthier, and Arnaud 2012). Glaciers respond to climate changes depending on their dynamics, slope, orientations, and altitude. Remote sensing has proved to be extremely useful for glaciological studies. Although field methods are the recommended ways to monitor glaciers, long-term field observations are difficult to carry out due to a lack of logistics, financial challenges, and harsh weather at high altitudes. The availability of multitemporal remote-sensing data compensates for the field method with promising results. Remote-sensing data have been well exploited for Himalayan glacier monitoring studies (Kulkarni, Rathore, and Suja 2004; Kulkarni et al. 2007; Bahuguna et al. 2007; Berthier et al. 2007; Bhambri et al. 2011, 2012). Glacier retreat, mass balance, and snow cover have been monitored for glaciers in 11 basins in the Indian Himalaya, including Chandra Bhaga basin in a previous study, using remote-sensing data and topographical maps (Kulkarni 2010; MOEF and SAC Report, 2011; Kulkarni et al. 2011). The study reported a retreat of 1868 glaciers in 11 basins. The present study is focused on selected glaciers of the Chandra Bhaga basin and evaluates the glacier changes and impact of topographic parameters on glacier changes using only satellite remote-sensing data covering a period of 30 years (1980 2010). The aim is to study details about each glacier in terms of its size, slope, aspect terminus position, and altitude range and their interrelations. Uncertainties associated with the use of remote-sensing data with different spatial and temporal resolution and errors in glacier mapping have been quantified. 2. Study area The study was carried out for 15 selected glaciers of Chandra Bhaga basin located in Lahaul Spiti district of Himachal Pradesh (Figure 1). The criteria for choosing glaciers for this study were (1) that they were identifiable on satellite imagery and (2) an absence of cloud. Some glaciers were not included because of difficulty in mapping, identification of the terminus position, and differentiating the ice divide. Keeping in mind the accuracy of mapping and area calculation, only glaciers well identifiable on all of the images were selected. These 15 glaciers were assumed to be representative of the characteristic changes in the basin. The glaciers chosen for the present study are indicated by yellow numbers 1 15 in Figure 1. Chandra Bhaga is the sub-basin of Chenab basin, lying on the northern ridge of Pir Panjal range of the Himalaya with an elevation range between 2400 m above sea level

5586 P. Pandey and G. Venkataraman 77 17 35 E 77 27 40 E 77 37 45 E 77 47 50 E 32 40 50 N 32 40 50 N 32 30 45 N 32 20 40 N 32 10 35 N N 0 5 10 20 km 32 30 45 N 32 20 40 N 32 10 35 N Figure 1. Study area in Chandra Bhaga basin. The yellow numbers indicate the glaciers studied (see also Table 3). The background image was acquired on 11 September 2000 and is a LISS III false colour composite (FCC) with red assigned to LISS band 4, green assigned to band 3, and blue assignedtoband2. (m a.s.l.) and 6400 m a.s.l. The region is composed of metamorphic rocks with their sedimentary cover. This region is important as it falls in the monsoon arid transition zone and marks the boundary of wet climate to its south and a dry climate to its north. The glaciers of this region are influenced by South Asian monsoons in the summer and westerlies in the winter. Therefore, the location of glaciers of this region makes them important for climate change study and also to study the intensity of the monsoon in the northwest. 3. Data Remote-sensing data from the Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM), Line Imaging Self Scanner Sensor (LISS III), and Advanced Wide Field Sensor (AWiFS) sensors of the Indian Remote Sensing (IRS) satellite were used (Table 1). Glaciers are most visible and identifiable during the ablation season (July to September) as the temporary snow cover is at its minimum and the glacier area can be easily demarcated on images. Images were acquired from August to early October, avoiding recent snowfall and cloud cover. Using the LISS III image of 2000 as a base, all other images

International Journal of Remote Sensing 5587 Table 1. Data used in the study. Sensor Acquisition date Resolution (m) Scene ID Co-registration error (m) Landsat MSS 3 16 September 1980 83 M3158037/38_03719800916 13 Landsat TM 5 9 October 1989 28.5 p147r37_5t19891009 8 LISS III 27 September 1999 23.5 097136000101 12 LISS III 11 September 2000 23.5 1009548L000 12 LISS III 13 September 2001 23.5 0109548L0001 12 LISS III 16 September 2005 23.5 097130400101 12 LISS III 18 September 2006 23.5 097130400201 12 LISS III 30 September 2007 23.5 097130400301 12 AWiFS 14 September 2008 56 36AWFBST00B2345F 24 AWiFS 30 August 2010 56 22AWFBST00B2345F 24 were co-registered and projected to a polyconic projection. Glacier topographical parameters (slope, aspect, and elevation) and snowline were obtained from the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The SRTM is a freely available global digital elevation data set covering over 80% of the globe. The data are available as 3 arc second (approximately 90 m) resolution with vertical accuracy reported to be better than 16 m (Marschalk et al. 2004). The SRTM DEM provides elevation with an uncertainty of less than 16 m in the Himalayan region, and it has even been used for glacier mass balance study by the remote-sensing geodetic method for the northwest Himalaya (Berthier et al. 2007). 4. Methods (glacier area delineation, length, and slope calculation and elevation extraction) Glaciers can be mapped by supervised classification (Aniya et al. 1996; Gratton, Howarth, and Marceau 1990; Sidjak and Wheate 1999), thresholding of ratio images (Paul et al. 2009; Rott 1994), and the normalized difference snow index (NDSI) (Hall, Riggs, and Salomonson 1995; Racoviteanu et al. 2008). Supervised classification, unsupervised classification, and NDSI methods were tested for glacier delineation. These methods are more useful for delineation of clean-ice glaciers. However, most of the glaciers of the study region are covered with debris, and it is difficult to differentiate debris from the surrounding bedrock (Bolch et al. 2008). Bhambri and Bolch (2009) have also reported that NDSI and band ratio methods are not suitable for delineation of the Himalayan glaciers, as most of the glaciers are covered with debris. Manual digitization was, therefore, deemed to be best suited for glacier boundary mapping in this study. Challenges were, nevertheless, encountered for mapping the ice divide and boundary near the terminus regions for debriscovered glaciers. However, the existence of ponds and moraine-damned lakes were used to determine the terminus (Bhambri et al. 2011; Kulkarni et al. 2011). Exposed rocks were excluded from glacier area calculations. The upper boundaries of the glaciers were kept fixed, and it was assumed that they did not change over the studied period (Bhambri et al. 2011). Glacier length was calculated along the centre line of the glacier, i.e. glacier tongue. The average of length lines drawn on the glacier centre from upper boundary to terminus was taken as the glacier length. For the compound glaciers such as Samudra Tapu and Bara Shigri, the average of the lengths measured along the major trunks and branches were considered.

5588 P. Pandey and G. Venkataraman The changes in glacier characteristics, in terms of area, length, snout elevation, and mean slope, were compared between 1980 and 2010 for about 377 km 2 of glacier area. Comparisons for the same characteristics between the decades 1980 1989, 1989 1999, and 2000 2010 were also made. 5. Uncertainty estimation Since the study uses data from different sources with different spatial and temporal resolutions, uncertainties are likely to be introduced in area and length calculations. It is, therefore, essential to quantify the error introduced in our calculations. The sources of error in area and length estimation are errors due to co-registration and glacier area delineation. The uncertainty in terminus position, e, was estimated using Equation (1): e = a 2 + b 2 + E, (1) where a and b represent the spatial resolution of the two images used, and E is the error of image registration (Hall et al. 2003; Silverio and Jaquet 2005; Wang, Hou, and Liu 2009; Bhambri, Bolch, and Chaujar 2012). The co-registration error for Landsat MSS was approximately 13 m, for Landsat was TM 8 m, for LISS III was 12 m, and for AWiFS was 24 m. Hence, the uncertainties are approximately 99, 45, 45, and 85 m, respectively, for Landsat MSS, Landsat TM, LISS III, and AWiFS. The error in manual digitization of glacier boundaries was estimated to be one pixel (Congalton 1991; Zhang and Goodchild 2002; Hall et al. 2003). The uncertainties of glacier area estimation were determined by the buffer method suggested by Granshaw and Fountain (2006) for each glacier. The area of buffer size around each glacier was set to twice the digitization error (Granshaw and Fountain 2006; Racoviteanu et al. 2008; Wang, Hou, and Liu 2009; Bolch, Menounos, and Wheate 2010). The overall uncertainty in area estimation was, therefore, estimated to be 1.5 4.0% for the various dates (Table 2). Similar uncertainties were found by Bhambri et al. (2011) for glacier changes study carried out in Garwhal Himalaya using remote sensing, and these uncertainties are well within the previously estimated values (Paul et al. 2003; Racoviteanu et al. 2008; Bolch, Menounos, and Wheate 2010; Bolch et al. 2010; Bhambri et al. 2011). Table 2. Glacier area, 1980 2010, in the study area in Chandra Bhaga basin. Year Area (km 2 ) Uncertainty (%) 1980 377.6 1.5 1989 375.0 1.7 1999 373.4 0.6 2000 373.1 2.6 2001 372.7 2.7 2005 371.8 2.5 2006 371.2 1.9 2007 370.6 2.0 2008 369.1 3.0 2010 368.2 4.0

International Journal of Remote Sensing 5589 6. Results and discussion 6.1. Glacier changes From the analysis, it was found that the glaciers of Chandra Bhaga basin are retreating with varying rates. The glacier area has shrunk from 377.6 km 2 in 1980 to 375.0 km 2 in 1989, 373.1 km 2 in 2000 and 368.2 km 2 in 2010 (Table 2, Figure 2). Glaciers lost 0.7% of total area between 1980 and 1989, 0.4% of total area between 1989 and 1999, and 1.3% of total area between 2000 and 2010. A total of about 9.3 km 2 glaciated area was lost in 30 years, a 2.5% loss. The overall rate of recession was estimated as (0.14 ± 0.11)% year 1.However, previous studies (Kulkarni 2010; MOEF and SAC Report 2011; Kulkarni et al. 2011) have N 0 5 10 20 km Glacier extent, 1980 Glacier extent, 2010 Figure 2. Glacier boundaries in 1980 and 2010 overlaying a LISS III false colour composite of 11 September 2000 (red assigned to band 4, green assigned to band 3, and blue assigned to band 2).

5590 P. Pandey and G. Venkataraman Table 3. Change in individual glaciers between 1980 and 2010. Glacier Area (1980) (km 2 ) Length 1980 (km) Loss in area (1980 2010) (%) Rate of retreat (1980 2010) (m year 1 ) Upward terminus shift (1980 2010) (m a.s.l.) Glacier 1 4.53 4.64 13.93 17.23 24 Glacier 2 6.95 7.73 6.06 21.17 29 Glacier 3 9.05 7.44 4.39 21.10 39 Glacier 4 12.91 6.60 2.06 12.87 39 Glacier 5 18.67 10.12 1.59 12.23 37 Glacier 6 68.01 16.78 2.31 19.90 44 Glacier 7 24.23 9.83 2.15 11.87 45 Glacier 8 22.04 10.27 1.43 23.63 57 Glacier 9 6.56 6.25 5.54 3.60 53 Glacier 10 12.95 10.00 3.98 8.20 33 Glacier 11 9.33 6.86 7.22 15.20 35 Glacier 12 132.68 28.92 1.50 18.67 45 Glacier 13 15.05 9.55 0.47 7.73 17 Glacier 14 3.28 5.99 7.57 16.80 92 Glacier 15 31.45 12.74 3.37 17.47 46 Figure 3. 2010. Area loss (%) 15 10 5 0 0 50 100 150 Glacier area (km 2 ) Scatter plot of initial glacier area in 1980 versus percentage of area loss between 1980 and reported 20% and 30% glacier retreat in Chandra and Bhaga basins, respectively, between 1962 and 2001/2004. The discrepancy may be attributed to the topographical maps provided by the Survey of India (SOI), which were used in the previous studies. Concerns have been raised over the use of SOI topographical maps and their accuracy by Vohra (1980), Agarwal (2001), Raina and Srivastava (2008), Raina (2009), and Bhambri and Bolch (2009). Similar discrepancies in the rate of recession of glacier due to the use SOI topographical maps have also been reported for Garhwal Himalaya, and the rate of retreat has been found to be less than previously reported (Bhambri et al. 2011). The percentage and rate of area loss was greater for smaller glaciers than the larger glaciers, showing their sensitivity to climate change. The rate of retreat was not uniform for all glaciers (Table 3). A nonlinear relationship was found between the initial glacier area and the percentage of glacier area lost (Figure 3). Smaller glaciers that lose a greater percentage of their area have also been reported in other studies (Wang, Hou, and Liu 2009; Bhambri et al. 2011; Kulkarni et al. 2011). Glacier terminuses retreated, on average, by (113.6 ± 44.2) m between 1980 and 1989, (166.4 ± 8) m between 1989 and 1999 and (170.0 ± 60.2) m between 2000 and 2010.

International Journal of Remote Sensing 5591 Table 4. Decadal change in glacier characteristics of Chandra Bhaga basin. Parameter 1980 1989 1989 1999 2000 2010 1980 2010 Change in glacier area (km 2 ) 2.5 ± 0.1 1.6 ± 0.2 4.8 ± 0.2 9.3 ± 0.5 Loss in area (%) 0.6 0.4 1.3 2.5 Rate of area loss (km 2 year 1 ) 0.28 0.16 0.48 0.31 Rate of terminus retreat (m year 1 ) 12.6 ± 4.9 15.6 ± 8.0 17.0 ± 6.0 15.5 ± 5.6 Terminus elevation change (m a.s.l.) 11.5 ± 7.79 13.9 ± 6.7 15.2 ± 6.9 42.3 ± 17.0 N 0 0.5 1 2 km (a) Glacier extent, 1980 Glacier extent, 2000 Glacier extent, 2010 N 0 1 2 4 km (b) Glacier extent, 1980 Glacier extent, 2000 Glacier extent, 2010 Figure 4. Comparison of glaciers 1 and 13 (see Figure 1), which have lost, respectively, the largest and smallest percentages of area between 1980 and 2010. The boundary is shown on a false colour composite of an 11 September 2000 LISS image. The inset images show the frontal loss in the glaciers (false colour composite: red assigned to band 4, green assigned to band 3, and blue assigned to band 2). On average, glacier terminuses retreated by (465.5 ± 169.1) m from 1980 to 2010 with a rate of (15.5 ± 5.6) m year 1. The rate of terminus retreat has increased over the years, being (12.6 ± 4.9) m year 1 between 1980 and 1989, (15.6 ± 8.1) m year 1 between 1989 and 1999, and (17.0 ± 6.0) m year 1 between 2000 and 2010 (Table 4). The terminus retreat rate of Chhota Shigri glacier (glacier 13) located in the basin was found to be (7.7 ± 1.0) m year 1 between 1980 and 2010. This is in agreement with the rate reported in a previous study done on the Chhota Shigri glacier between 1988 and 2010 (Azam et al. 2012). Glacier 1 has experienced the greatest loss among the glaciers studied by losing about 14% of its area between 1980 and 2010, while Chhota Shigri has experienced the least loss, about 0.47% of its area (Figure 4). The rate of terminus retreat of Samudra Tapu (glacier 6) was estimated to be (19.9 ± 5.8) m year 1 between 1980 and 2010. Another study on the same glacier has reported a rate of 19.5 m year 1 and a loss of 11% of glacier area between 1962 and 2000 (Kulkarni et al. 2006). The agreement of the present study with the previous study

5592 P. Pandey and G. Venkataraman Figure 5. The terminus of Samudra Tapu glacier (glacier 6 from Table 3) and moraine-dammed lake. The red ellipse indicates the elongated portion of the snout area. The image is a LISS III false colour composite of 11 September 2000 (red assigned to band 4, green assigned to band 3, and blue assignedtoband2). in terms of rate of retreat of glacier length and the discrepancy in total glacier area loss could possibly be due to the glacier s terminus structure. The terminus area of the Samudra Tapu glacier is elongated and narrower than the main body of the glacier, as shown in the Figure 4. Therefore, even though the glacier length is decreasing at a faster rate, this contributes only to a minimal area loss due to the narrow width of the glacier at this point. The moraine-dammed lake located downstream of the Samudra Tapu glacier (Figure 5) was also monitored for its spatial change during the 30 years studied. The analysis of lake area from remote sensing shows an increase in the area from 1980 to 2010. The total area of the lake was (0.65 ± 0.01) km 2 in 1980, and it has increased to (1.26 ± 0.03) km 2 in 2010 with an average rate of (0.019 ± 0.003) km 2 year 1. The rate of the areal expansion of the lake was also found to be increasing over the years. The average terminus elevation of the glacial area was 4504 m a.s.l. in 1980, which has shifted upward to 4546 m a.s.l. in 2010. The changes in the study area between 1980 and 2010 are summarized in Table 4. The mean snow line altitude at the end of ablation season (August to early October) of the glacial area (excluding glacier 14) has also risen from 4987 m a.s.l. in 1980 to 5204 m a.s.l. in 2010. The snowline altitude at the end of ablation season is considered as the equilibrium line altitude and reflects the current climatic conditions (temperature and precipitation) on the glacier. 6.2. Glacier characteristics If climate is the driving force behind the glacier change, the glacier topographical parameters are the controlling factors for the change. The topography of individual glaciers is,

International Journal of Remote Sensing 5593 potentially, the reason for their varying behaviour and response to the same climatic conditions. Glacial topography is an important factor which explains the variability in the recession rates of glaciers of the same basin. A detailed analysis was carried out to study the impact of topographical parameters such as glacier slope, minimum and maximum elevation, altitude range, and aspect on glacier area change. All of the statistical analyses discussed in the study are statistically significant with p < 0.001. There is a negative relationship between the initial glacier area and the percentage loss in glacier area (Figure 3). A significant statistical correlation with a coefficient of determination, R 2, greater than 0.069 (i.e. R 2 > 0.69, p = 0.001) exists between the initial glacier area and altitude range (Figure 6(a)), which confirms the important role of initial glacial size and its altitude range in the subsequent shrinkage process (Kaser and Osmaston 2002; Ye et al. 2003; Mark and Seltzer 2005; Wang, Hou, and Liu 2009). A nonlinear inverse relation was found between the percentage of glacier area lost and its altitude range (Figure 6(b)). The relation shows that glaciers with smaller altitude range have lost more area. The altitude range of a glacier was calculated as the maximum minus minimum SRTM DEM elevation (Wang, Hou, and Liu 2009). It can be inferred that smaller glaciers are narrower and tend to lose more area than comparatively wider and larger glaciers. The slope of glacier also plays a major role in the relative balance between retreat and advance (Venkatesh, Kulkarni, and Srinivasan 2011). The statistical analysis shows that larger glaciers tend to have gentle slope, while smaller glaciers have steep slope, though the correlation is very moderate (R 2 = 0.095, p < 0.0001) (Figure 6(c)). Further, glaciers with steeper slopes were found to be retreating faster than those with smaller slopes (R 2 = 0.115, p < 0.0001, Figure 6(d)). (a) Glacier area, 1980 (km 2 ) (b) Area loss (%) 150 125 100 R 2 = 0.694 75 50 25 0 0.5 1.0 1.5 2.0 2.5 Altitude range (km) 15 10 5 R 2 = 0.314 0 0.5 1.0 1.5 2.0 2.5 Altitude range (km) (c) Glacier area, 1980 (km 2 ) (d) Rate of retreat (m year 1 ) 150 125 100 75 50 25 0 5 10 15 20 Slope ( ) 25 20 15 10 5 0 R 2 = 0.095 R 2 = 0.155 5 10 15 20 Slope ( ) Figure 6. Scatter plots between (a) glacier altitude ranges versus glacier area in 1980, (b) glacier altitude range versus percentage loss of glacier area between 1980 and 2010, (c) glacier slope versus glacier area in 1980 and (d) glacier slope versus rate of retreat of glacier between 1980 and 2010.

5594 P. Pandey and G. Venkataraman The advance and retreat of glaciers also depend on the direction in which the glaciers are exposed to the sun. To quantify the effect of exposure, glaciers were grouped into north south (including exposure from northeast, northwest, and southwest) and east west. The percentage of area loss was found to be greater for glaciers exposed in a north south direction (2.5%) than glaciers exposed in an east west direction (2.3%). A study done by Pandey, Kulkarni, and Venkataraman (forthcoming) on the equilibrium line altitude variation of the same region shows that the equilibrium line altitude of glaciers facing north south have shifted to higher elevations than the snowline altitude of the glaciers facing east west. Generally, north-facing glaciers have been found to be shrinking less than south-facing glaciers (Wang, Hou, and Liu 2009; Bhambri et al. 2011) when they were categorized into north and south in other parts of the Himalaya and world. Here, glaciers have two predominant orientations. Most of them are either exposed to the north (including northwest and northeast) or to the east; this aspect should be looked into further. The glaciers of Chandra Bhaga basin are mainly of winter accumulation type; however, they are also moderately influenced by the South Asian monsoon in summer. The change of glacier terminus is due to the long-term mass balance variability. Mass balance in turn depends on the accumulation and ablation. The glaciers of the study region get maximum snowfall in winter from western disturbances. Winter disturbances have uniform synoptic intensity throughout this region and cause the maximum amount of snowfall. The southwest monsoon in summer may also contribute to some amount of snow at a higher altitude in this region. The intensity of precipitation, wind direction, and mountain orography play a significant role in snow distribution on a glacier. The reason behind the difference in the area loss for glaciers with different orientations, due to difference in the amount of snowfall they receive, can be studied by monitoring and comparing intraseasonal snowline altitude of the glaciers in the basin. 7. Conclusions This study investigated the status of the glaciers of Chandra Bhaga basin in terms of their fluctuations, their interrelationship with different topographical parameters, and quantification of errors and uncertainties associated with the use of multisource remote sensing used for the study and glacier mapping. The glaciers of Chandra Bhaga basin have fluctuated significantly since 1980. The glacier area has decreased from 377.6 km 2 in 1980 to 368.2 km 2 in 2010, losing 2.5% of total area in 30 years. Smaller and steeper glaciers have decreased faster than the larger and gentle glaciers. The rate of terminus recession on average was (15.5 ± 5.6) m year 1 with the rate going higher in recent decades. Glacier terminus elevations of the basin on average have shifted up to a mean elevation of 4546 m a.s.l. in 2010 from 4504 m a.s.l. in 1980. The rising of average equilibrium line altitude of the basin by about 217 m in the 30 year span between 1980 and 2010 indicates a decreasing snowfall and rising temperature trend in the region. The expansion of the area of the moraine-dammed lake located near the terminus of Samudra Tapu glacier links the temperature increase in the western Himalaya and glacier retreat. The higher rate of retreat of Samudra Tapu glacier and the rate of expansion of the glacier lake at its terminus presents an example of the effect of global warming on glaciers, showing that as the glaciers retreat, lakes grow. Temperature rise in the northwest Himalaya has been reported (Bhutiyani, Kale, and Pawar 2007) and the expanding lake found in this study provides evidence for the effect of temperature rise on glacier melting. As the lake is expanding at the cost of glacier melt, due to rise in temperature, it is also negatively

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