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Glacier changes in the west Kunlun Shan from 1970 to 2001 derived from Landsat TM/ETM+ and Chinese glacier inventory data

Published online by Cambridge University Press:  14 September 2017

Donghui Shangguan
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Shiyin Liu
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100029, China
Yongjian Ding
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Jing Li
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Yong Zhang
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Lianfu Ding
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Xing Wang
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Changwei Xie
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
Gang Li
Affiliation:
Key Laboratory of Cryosphere and Environment, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China E-mail: dhguan@lzb.ac.cn
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Abstract

Recent studies have indicated that widespread wastage of glaciers in western China has occurred since the late 1970s. By using digitized glacier outlines derived from the 1970 inventory and Landsat satellite data from 1990/91 to 2001, we obtained area changes of about 278 glaciers with a total area of 2711.57 km2 in the heavily glaciated west Kunlun Shan (WKS) in the northern Tibetan Plateau (TP). Results indicate that the prevailing characteristic of glacier variation is ice wastage, and glacier area decreased by 10 km2 (0.4% of the total 1970 area) between 1970 and 2001. Both the south and north slopes of the WKS presented shrinkage during 1970–2001, but whereas on the north slope a slight enlargement of ice extent during 1970–90 was followed by a reduction of 0.2% during 1990–2001, on the south slope the glacier area decreased by 1.2% during 1970–91, with a small increment of 0.6% during 1991–2001. Comparisons with other glaciated mountainous regions in western China show that glaciers in the research area have experienced less retreat. Based on records from the Guliya ice core, we believe that an increase in air temperature was the main forcing factor for glacier shrinkage during 1970–2001.

Type
Research Article
Copyright
Copyright © The Author(s) [year] 2017

1. Introduction

Glaciers in middle–low latitudes of Asia have retreated continually for the duration of the negative glacier mass balance since the 1990s (Reference Yao, Liu, Pu, Shen and LuYao and others, 2004), and climate scenario simulation has indicated that they will shrink more under warmer conditions in the future (Reference OerlemansOerlemans and others, 1998; Reference Shi and LiuShi and Liu, 2000). Small glaciers and ice caps are believed to have a significant effect on sea level (Reference Dyurgerov and MeierDyurgerov and Meier, 1997; Reference Zuo and OerlemansZuo and Oerlemans, 1997; Reference Van de Wal and WildVan de Wal and others, 2001). Moreover, the glacier runoff derived from changes of glacier mass is an important source of fresh water to support the sustained development of the ecological environment, industry and agriculture in the arid regions of northwest China (Reference Yao, Liu, Pu, Shen and LuYao and others, 2004). Strong glacier ablation has also caused the runoff of some rivers to increase (Reference ShiShi, 2001). The glacier changes not only influence river runoff and sea-level rise but also record the characteristics responding to climatic fluctuation. Therefore, monitoring glacier changes is one of the components of the Global Climate Observing System (GCOS) (Reference Haeberli, Cihlar and BarryHaeberli and others, 2000).

The west Kunlun Shan (WKS) are located in the northern Tibetan Plateau (TP) (centered at 35˚40′ N, 81˚ E), where several large glaciers have developed. These ranges are situated in transitional climatic conditions between the humid and arid parts of the TP monsoon and the west wind. Thus, the WKS is one of the sensitive areas for west wind and monsoon circulation. In addition, glacier changes in the WKS influence human welfare as meltwater supplies the arid Tarim basin. The remote location and large size of the glaciers makes them difficult to investigate by fieldwork. Remote-sensing (RS), Geographical Information System (GIS) and global positioning system (GPS) (3S) technology has provided a new and valid means of research into the cryosphere (Reference Li, Sun and ZengLi and others, 1998; Reference Zhang, Lu and LiuZhang and others, 2001; Reference Paul, Kääb, Maisch, Kellenberger and HaeberliPaul and others, 2004). Moreover, Global Land Ice Measurements from Space (GLIMS) carried out glacier research with 3S (Reference Kääb, Paul, Maisch, Hoelzle and HaeberliKääb and others, 2002; Reference PaulPaul, 2002; Reference Paul, Kääb, Maisch, Kellenberger and HaeberliPaul and others, 2004; Reference KargelKargel and others, 2005). Accordingly, this study used Chinese glacier inventory (CGI), Landsat Thematic Mapper (TM; path 145, row 35, 15 November 1990, and path 145, row 36, 7 October 1991) and Enhanced TM Plus (ETM+; 6 February 2001, 20 October 2001) images to obtain glacier distribution maps in the WKS supported by RS and GIS technology. We investigated the glacier changes over 32 years in this region and discussed the reasons for glacier changes combined with ice-core records.

2. Study Area

The WKS (35˚20′–36˚ N, 80–82˚ E) (Fig. 1) is located in the northern TP. The topographic features of its two slopes are very different. The terrain on the north slope drops steeply towards the Tarim basin, whereas the south slope, where a planation surface has remained at about 6400 m, is a low slope towards the TP (Reference Li, Li, Zheng and YangLi and others, 1986; Reference Yang and AnYang and An, 1992). Consequently, we investigated the glacier change on the north and south slopes separately. According to the CGI (Reference Yang and AnYang and An, 1992), there are 278 polar-type glaciers with a total area of 2711.57 km2 in the WKS. These are made up of 105 glaciers with a total area of 1108.92 km2 on the south slope, and 173 glaciers with a total area of 1602.66 km2 on the north slope. Figure 2 shows the share of the total number and area of WKS glaciers on each slope comprised by different area-size classes. The majority of glaciers are <5km2 in area and these cover about 6% of the total area on the south slope and 9% on the north slope. On the north (south) slope, 5% (2%) of glaciers are >20km2 in area, and

Fig. 1. Distribution map of existing glaciers in the WKS, from the CGI.

Fig. 2. Frequency of glacier number (bars) and area (lines) according to seven area classes on the south (black bars; solid line with triangles) and north (white bars; dot-dashed line with crosses) slopes of the WKS.

these cover about 85% (83%) of the total area. Of these glaciers, 16 are >50km2 in area. Some noted glaciers (e.g. west Kunlun, Kunlun and Yulong glaciers and Guliya ice cap) (see Fig. 1) are considered to be representative of large alpine glaciers in the Kunlun Shan. Based on the fieldwork record, Guliya ice cap is the coldest site on the TP, with a lowest temperature of –24.1˚C and a monthly mean temperature of –17.8˚C in May and –19.0˚C at 10 m depth of ice temperature (Reference Yao, Jiao, Tian, Yang and ShiYao and others, 1995).

3. Data Sources and Methods

Among the data used in this study were the CGI for Kunlun Shan (Reference Yang and AnYang and An, 1992) which was derived from aerial photographs and topographic maps (1 : 100 000) from 1970 onwards. The glacier outlines of the CGI were interpreted from aerial photographs by stereophotogrammetry and were transferred to 1 : 100 000 topographic maps, and then vectored by commercial GIS software (ArcView). Two Landsat TM images (path 145, row 35, 15 November 1990, and path 145, row 36, 7 October 1991) and two ETM+ images (path 145, row 35, 2 June 2001, and path 145, row 36, 20 October 2001) with cloud-free and low snow cover were used. This study used ETM+ bands 5, 4, 3, 2 and band 8 (panchromatic data). A digital elevation model (1 : 100 000) of this region was derived from topographic maps.

To establish co-registration of these images, 30–35 ground-control points (GCPs) were selected from topographic map features that could be identified on each image. However, it is difficult to distinguish the marked ground objects in the two images for the temporal difference of the two images, which led to difficulty in selecting the GCPs. Thus, the residual root-mean-square error (rmse) of verification points compared with topographic maps is <45.2 m. The ratio image from bands 5 and 4 (Reference Zhang, Lu and LiuZhang and others, 2001; Reference PaulPaul, 2002) (TM4/TM5≥2.1) was used to classify glaciers from Landsat TM/ETM+ mainly based on glacier ice with very low reflectance in the middle infrared. Those glacier distribution maps derived from the CGI and Landsat images were vectorized, and then the glacier changes in 1970, 1990/91 and 2001 were obtained with GIS-based processing.

4. Results

4.1. Glacier changes

Glacier area changes in the WKS were obtained in order to compare the glacier extents derived from aerial photographs in 1970 and from Landsat TM/ETM+ in 1990/91 and 2001. The relative changes in seven classes by glacier area, the three time intervals and the separation into two regions are plotted in Figure 3. Glacier area on the south slope decreased by 12.90 km2 (1.2% of the total 1970 area) from 1970 to 1991 and increased by 6.10 km2 (0.6% of the total 1991 area) from 1991 to 2001, and thus decreased by 6.8 km2 (0.6% of the total 1970 area) for the whole period 1970–2001 (Fig. 3a). Glacier area on the north slope increased by 0.28 km2 from 1970 to 1990 and decreased by 3.51 km2 (0.2% of the total 1990 area) from 1990 to 2001, and thus decreased by 3.23 km2 (0.2% of the total 1970 area) during 1970–2001 (Fig. 3b). Figure 3c summarizes the glacier area changes for the periods 1970–90/1991– 2001 for individual glacier area classes. Glacier area in the WKS decreased by 12.60 km2 during 1970–1990/91 and increased by 2.60 km2 during 1990/91–2001. For the whole period 1970–2001 the total area loss is 10.00 km2, or 0.4% with respect to the 1970 area.

Fig. 3. Relative changes in glacier area (%) for the south (a) and north (b) slopes of the WKS and the whole mountain range (c), separated into area classes and the periods 1970–1990/91, 1990/91–2001 and 1970–2001. Note that the y-axis scales differ. Data from the CGI (1970), Landsat TM (1990/91) and Landsat ETM+ (2001).

Altogether, glaciers in the 0.5–1km2 class experienced an area loss of about 4.1% between 1970 and 1990/91 (with respect to the 1970 area), and about 1.6% between 1990/91 and 2001 (with respect to the 1990/91 area). Thus, the total area loss is 4.4% for the whole period 1970–2001. Glacier-area changes in the class <0.5km2 are smaller than those in the class 0.5–1 km2 during 1970–2001 because the increment of glacier area in the class <0.5km2 in 1990/91 offsets part of the decrease in 1970–1990/91. However, all the glaciers in the classes 1–5 and >20km2 together contributed 30% and 49% of total area loss during 1970–2001.

Recently, records of glacier changes in west China have been obtained by fieldwork investigation, ground and aerial photographic measurements and high-resolution RS monitoring. Table 1 shows the changes in the extremely continental-type glaciers in west China. Glacier changes in the WKS in the last few decades have been the smallest in west China, smaller than those in, for example, Xinqingfeng ice cap in the north central Kunlun Shan (Reference LiuLiu and others, 2004) and Geladandong in the Yangtze River source region (Reference Yang, Ding, Chen, Liu and LuYang and others, 2003).

Table 1. Statistics of the extremely continental-type glacier change in west China

5. Discussion and Conclusions

Glaciers are one of the most distinctive natural indicators for studying changes from space related to climate. Analysis of repeated space images has been applied to 278 glaciers in the WKS. Because there was no meteorological station in the alpine zone of WKS, the Guliya ice-core records were selected to reflect the temperature and precipitation (Fig. 4). The δ18O record from the Guliya ice core (Yao and others, 1996) indicated that it was warm after the 1950s, but temperatures cooled in the 1970s (Fig. 4b). Reference Su, Wei and HanSu and others (2003) found that the temperature has risen about 0.1– 0.3˚C (decade)–1 on the north slope of the WKS since the early 1960s; and for one region, the higher the altitude was, the more the temperature rose. The net accumulation from the ice core is the direct record for precipitation in the glacier region (Reference Yao, Jiao, Tian, Yang and ShiYao and others, 1995). The accumulation from Guliya ice cap showed that precipitation greatly increased after the 1950s (Fig. 4a). The atmospheric warming and precipitation increase recorded by meteorological stations in northwestern China has also been reported after 1957 (Reference ShiShi and others, 2003). The above-mentioned data indicated high temperature and precipitation after the 1950s in the alpine area of the WKS. Annual increases in precipitation represent favourable climatic conditions for glaciers, and increased accumulation in the WKS could offset losses attributable to surface melting. Therefore, we believe that glacier wastage in the WKS can probably be correlated with regional warming.

Fig. 4. Trend of glacial accumulation (a) and δ18O (b) decadal variation since the Little Ice Age recorded in the Guliya ice core (Reference Yao, Jiao, Tian, Yang and ShiYao and others, 1995). Glacier accumulation and δ18O are positively correlated with air temperature and precipitation in the study region.

The work presented here shows that the glaciated part of the WKS has decreased by about 0.4% during 1970–2001, the smallest decrease in the extremely continental-type glacier area of west China. However, glacier changes differed between the north and south slopes of the WKS. Some parts of glaciers in the WKS advanced. Unfortunately, we cannot tell whether the glacier mass is loss or not because of the lack of mass-balance observations, but we believe that the terrains of the two slopes have great influence on glacier kinematics; furthermore, increased accumulation could offset losses attributable to surface melting. Also glaciers of different size respond at different speeds to climate change (Reference DingDing, 1995), and some glaciers may not have begun to respond yet.

Acknowledgements

We are grateful to GLIMS for maintaining parts of the satellite data and software through the Earth Resources Observation Systems (EROS) Data Center. This research is financially supported by the National Natural Science Foundation of China (grants 40371026, 40601022 and 40571034) and the Chinese Academy of Sciences (grants KZCX3-SW-345 and 339).

References

Ding, Y. 1995. The reflection of the global glacier fluctuation to the climate change during the past forty years. Sci. China B, 25(10), 10931098. [In Chinese.]Google Scholar
Dyurgerov, M.B. and Meier, M.F.. 1997. Year-to-year fluctuations of global mass balance of small glaciers and their contribution to sea-level changes. Arct. Alp. Res., 29(4), 392402.Google Scholar
Haeberli, W., Cihlar, J. and Barry, R.G.. 2000. Glacier monitoring within the Global Climate Observing System. Ann. Glaciol., 31, 241246.Google Scholar
Kääb, A., Paul, F., Maisch, M., Hoelzle, M. and Haeberli, W.. 2002. The new remote-sensing-derived Swiss glacier inventory: II. First results. Ann. Glaciol., 34, 362366.Google Scholar
Kargel, J.S. and 16 others. 2005. Multispectral imaging contributions to Global Land Ice Measurements from Space. Remote Sens. Environ., 99(1–2), 187219.Google Scholar
Li, J. and 6 others. 1986. Glaciers in Xizang. In Li, J., Zheng, B., Yang, X. and others, eds. Glaciers in Xizang. Beijing, Science Press, 176193. [In Chinese.]Google Scholar
Li, Z., Sun, W. and Zeng, Q.. 1998. Measurement of glacier variation in the Tibetan Plateau using Landsat data. Remote Sens. Environ., 63(3), 258264.Google Scholar
Liu, S. and 8 others. 2004. Variation of glaciers studied on the basis of RS and GIS: a reassessment of the changes of the Xinqingfeng and Malan Ice Caps in the northern Tibetan Plateau. J. Glaciol. Geocryol., 26(3), 244252. [In Chinese.]Google Scholar
Lu, A., Yao, T., Liu, S., Ding, L. and Li, G.. 2002. Glacier change in the Geladandong area of the Tibetan Plateau monitored by remote sensing. J. Glaciol. Geocryol., 24(5), 559562. [In Chinese.]Google Scholar
Oerlemans, J. and 10 others. 1998. Modelling the response of glaciers to climate warming. Climate Dyn., 14(4), 267274.Google Scholar
Paul, F. 2002. Changes in glacier area in Tyrol, Austria, between 1969 and 1992 derived from Landsat TM and Austrian glacier inventory data. Int. J. Remote Sens., 23(4), 787799.Google Scholar
Paul, F., Kääb, A., Maisch, M., Kellenberger, T. and Haeberli, W.. 2004. Rapid disintegration of Alpine glaciers observed with satellite data. Geophys. Res. Lett., 31(21), L21402. (10.1029/2004GL020816.)CrossRefGoogle Scholar
Shangguan, S. and 9 others. 2006. Monitoring the glacier changes in the Muztag Ata and Konggur mountains, east Pamirs, based on Chinese Glacier Inventory and recent satellite imagery. Ann. Glaciol., 43, 7985.Google Scholar
Shi, Y. 2001. Estimation of the water resources affected by climatic warming and glacier shrinkage before 2050 in western China. J. Glaciol. Geocryol., 23(4), 333341. [In Chinese with English summary.]Google Scholar
Shi, Y. and Liu, S.. 2000. Estimation of the response of glaciers in China to the global warming in the 21st century. Chinese Sci. Bull., 45(7), 668672. [In Chinese.]Google Scholar
Shi, Y. and 6 others. 2003. Discussion on the present climate change from warm-dry to warm-wet in northwest China. Quat. Sci., 23(2), 152164. [In Chinese with English summary.]Google Scholar
Su, H., Wei, W. and Han, P.. 2003. Changes in air temperature and evaporation in Xinjiang during recent 50 years. J. Glaciol. Geocryol., 25(2), 174178. [In Chinese]Google Scholar
Van de Wal, R.S.W. and Wild, M.. 2001. Modeling the response of glaciers to climate change by applying volume–area scaling in combination with a high resolution GCM. Climate Dyn., 18(3–4), 359366.Google Scholar
Yang, H. and An, R.. 1992. Glacier inventory of China, Vol. VI: Kunlun Mountains. Beijing, Science Press. [In Chinese.]Google Scholar
Yang, J., Ding, Y., Chen, R., Liu, S. and Lu, A.. 2003. Causes of glacier change in the source regions of the Yangtze and Yellow rivers on the Tibetan Plateau. J. Glaciol., 49(167), 539546.Google Scholar
Yao, T., Jiao, K., Tian, L., Yang, Z. and Shi, W.. 1995. Climatic variations since the Little Ice Age recorded in the Guliya ice core. Sci. China D, 25(10), 557596. [In Chinese.]Google Scholar
Yao, T., Liu, S., Pu, J., Shen, Y. and Lu, A.. 2004. Recent retreat of high Asian glaciers and the impact to water resource of northwest China. Sci. China D, 34(6), 535543. [In Chinese.]Google Scholar
Zhang, S., Lu, J. and Liu, S.. 2001. Deriving glacier border information on Qinghai Tibet by TM high spectrum image. Geomat. Inform. Sci. Wuhan Univ., 26(5), 435440. [In Chinese.]Google Scholar
Zuo, Z. and Oerlemans, J.. 1997. Contribution of glacier melt to sea-level rise since AD 1865: a regionally differentiated calculation. Climate Dyn., 13(12), 835845.Google Scholar
Figure 0

Fig. 1. Distribution map of existing glaciers in the WKS, from the CGI.

Figure 1

Fig. 2. Frequency of glacier number (bars) and area (lines) according to seven area classes on the south (black bars; solid line with triangles) and north (white bars; dot-dashed line with crosses) slopes of the WKS.

Figure 2

Fig. 3. Relative changes in glacier area (%) for the south (a) and north (b) slopes of the WKS and the whole mountain range (c), separated into area classes and the periods 1970–1990/91, 1990/91–2001 and 1970–2001. Note that the y-axis scales differ. Data from the CGI (1970), Landsat TM (1990/91) and Landsat ETM+ (2001).

Figure 3

Table 1. Statistics of the extremely continental-type glacier change in west China

Figure 4

Fig. 4. Trend of glacial accumulation (a) and δ18O (b) decadal variation since the Little Ice Age recorded in the Guliya ice core (Yao and others, 1995). Glacier accumulation and δ18O are positively correlated with air temperature and precipitation in the study region.