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地球信息科学学报 >

2017 , Vol. 19 >Issue 7: 972 - 982

DOI: https://doi.org/10.3724/SP.J.1047.2017.00972

遥感科学与应用技术

青藏高原湖泊面积动态监测

  • 杨珂含 , 1, 2 ,
  • 姚方方 3 ,
  • 董迪 1, 2 ,
  • 董文 1 ,
  • 骆剑承 , 1, *
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  • 1. 中国科学院遥感与数字地球研究所,北京 100101
  • 2. 中国科学院大学,北京 100049
  • 3. 堪萨斯州立大学地理系,美国堪萨斯曼哈顿 66506
*通讯作者：骆剑承(1970-),男,浙江临安人,博士,研究员,研究方向为遥感大数据协同计算。E-mail:

作者简介：杨珂含（1992-）,女,浙江宁波人,硕士生,研究方向为遥感信息提取与湖泊动态。E-mail:

收稿日期: 2017-02-19

  要求修回日期: 2017-03-29

  网络出版日期: 2017-07-10

基金资助

国家自然科学基金重点基金项目（41631179）

国家重点研发计划课题（2016YFB0502502）

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Spatiotemporal Monitoring of Lake Area Dynamics on the Tibetan Plateau

  • YANG Kehan , 1, 2 ,
  • YAO Fangfang 3 ,
  • DONG Di 1, 2 ,
  • DONG Wen 1 ,
  • LUO Jiancheng , 1, *
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  • 1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing, 100049, China
  • 3. The Department of Geography, Kansas State University, Manhattan, KS, 66506, United States
*Corresponding author: LUO Jiancheng, E-mail:

Received date: 2017-02-19

  Request revised date: 2017-03-29

  Online published: 2017-07-10

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《地球信息科学学报》编辑部 所有
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摘要

高原湖泊的动态变化对区域水循环具有重要影响。受全球气候变化的影响,青藏高原湖泊自20世纪90年代开始呈现剧烈扩张趋势。为揭示近年来青藏高原湖泊面积的时空变化规律,本文提出了一种改进的半自动湖泊提取算法,结合环境减灾卫星（HJ-1A/1B）和Landsat系列卫星影像数据,对青藏高原内流流域中面积大于50 km2的127个湖泊进行了连续6年的动态监测,并分析了该区域2009-2014年湖泊面积时空变化特征。研究结果表明,该区域湖泊整体呈现显著扩张趋势,年均变化速率为231.89 km2yr-1（0.87 %yr-1）,6年间湖泊面积扩张速率有所减缓。其中,扩张湖泊有104个,收缩湖泊有23个,变化速率分别为271.08 km2yr-1（1.02 % yr-1）和-39.19 km2yr-1（-0.15 %yr-1）。不同区域湖泊面积变化具有明显差异,主要表现为东部及北部大部分区域湖泊扩张,南部地区大部分湖泊面积稳定,萎缩湖泊主要分布于研究区四周。最后,本文通过分析冰川融水补给对湖泊面积变化的影响,发现存在冰川融水补给的湖泊面积变化率远大于不存在冰川融水补给的湖泊。由此可见,近年来冰川融水的增加是促进青藏高原内流流域湖泊扩张的主要因素之一。

关键词： 青藏高原; 湖泊; 遥感; 动态制图; 环境减灾卫星

本文引用格式

杨珂含 , 姚方方 , 董迪 , 董文 , 骆剑承 . 青藏高原湖泊面积动态监测[J]. 地球信息科学学报, 2017 , 19(7) : 972 -982 . DOI: 10.3724/SP.J.1047.2017.00972

Abstract

The lakes on the high-altitude plateau play an essential role in the local water cycle. Alpine lakes on the Tibetan Plateau have experienced a rapid expansion since 1990s under the global climate change. In order to understand the changing pattern of alpine lakes on the Tibetan Plateau in recent years, this study monitored 127 lakes larger than 50 square kilometers annually on the endorheic Tibetan basin from 2009 to 2014. Based on a semi-automatic lake extraction method, we combined multi-temporal HJ-1A/1B imagery and Landsat imagery to extract lake boundaries accurately. The results have shown that the surface area of large lakes experienced a significant expansion with an overall rate of 231.89 km2 yr-1 (0.87 %yr-1) and the trend of lake expansion is slowing down during the study period. 104 lakes expanded at a rate of 271.08 km2 yr-1 (1.02 %yr-1), while 23 lakes shrunk at a rate of -39.19 km2 yr-1 (-0.15 %yr-1). The spatial pattern of the lake area dynamics also have shown significant regional difference. The expanded lakes are distributed in the most of the east and north study area, while the stable lakes are mainly distributed in the south basin. Besides, the shrunken lakes are scattered at the border of the study area. Based on the comparison between the changing rates of glacier-fed and non-glacier-fed lakes, glacier-fed lakes have shown a much rapid expansion trend than non-glacier-fed lakes, which indicates that the increase of glacier wastage is one of the main factors that contributed to the expansion of Tibetan lakes.

Key words： Tibetan Plateau; lakes; remote sensing; lake dynamic mapping; HJ-1A/1B

1 引言

高原湖泊作为陆地水循环中一个重要组成部分,其时空动态变化对于区域水循环具有重要影响。青藏高原地处欧亚大陆腹地,是中国以及东南亚地区诸多大江大河的发源地,也是地球上海拔最高的湖泊密集区域[1],其中又以青藏高原内流流域地区湖泊群体分布最为密集。该区域地势险峻,分布有昆仑山脉、喀喇昆仑山脉、冈底斯山脉,念青唐古拉山脉等一系列高山[2],区域内湖泊受人类活动影响较小,绝大部分处于自然状态,其动态变化能够更加真实地反应全球气候变化背景下区域自然环境的变迁[3]。
因其独特的地理位置,青藏高原湖泊的实地勘测资料十分匮乏,不少研究学者借助卫星遥感影像数据对青藏高原湖泊进行长时间尺度动态监测,分析青藏高原湖泊整体与局部动态变化特征[2-5]。受到全球气候变暖影响,青藏高原湖泊自20世纪90年代开始呈现大范围剧烈扩张趋势。进入21世纪之后,湖泊扩张程度加剧,且湖泊变化具有明显的区域性特征[2-12],主要表现为高原西南部湖泊萎缩或缓慢增减,高原东北大部分区域以及青海南部湖泊稳定扩张[13-14]。在对湖泊变化原因的分析中,部分学者认为由全球变暖造成的大量冰川退缩是造成湖泊退缩的主要原因[15-17];Zhu等[18]通过定量地分析降水与冰川融水对于纳木错水量变化的影响,认为降水与冰川融水变化均对湖泊造成了一定影响;而Lei等[19]则认为降水,地表径流以及湖面蒸发是青藏高原中部湖泊变化的主要因素。
现有研究主要集中在长时间跨度低时间分辨率湖泊动态监测[2-3, 5-6, 20-21],季节性以及年尺度湖泊动态研究十分匮乏,或局限于单个湖泊高时序动态监测,少有研究涉及大范围高时序湖泊动态分析。一方面是由于遥感数据缺失,虽然现有的MODIS等中分辨率影像能够实现高时间分辨率动态制图,但是这些影像往往空间分辨率较低,严重影响湖泊面积提取精度;即便是采取混合像元解混等算法,其精度也难以满足要求。而空间分辨率较高的Landsat系列卫星等数据,因其回访周期长,幅宽小,难以实现大区域高时序湖泊制图。因此,环境减灾卫星（HJ-1A/1B）的发射为青藏高原湖泊高时序动态制图提供了新的契机。该系列卫星于2008年9月发射,多光谱影像空间分辨率为30 m,重访周期2天,幅宽700 km,能够有效覆盖整个研究区,实现大范围高时序湖泊动态监测。
本文利用多时序环境减灾卫星影像结合Landsat系列影像数据,通过改进的半自动湖泊面积提取算法,获取了青藏高原内流流域内所有面积大于50 km2湖泊连续6年（2009-2014）的面积时序结果,分析了湖泊面积的时空动态变化特征,并结合历史数据,研究了其中所有大型湖泊（>500 km2）近40年的动态变化;最后,讨论了冰川退缩对湖泊面积变化的影响。

2 研究区概况及数据源

2.1 研究区概况

本文研究区地处青藏高原腹地,是高原内最大的内流封闭流域,整体面积约71万km2。研究区介于29.6°~38.7°N,78.6°~93.7°E之间,包括了喀喇昆仑山脉以东,冈底斯山脉以南,念青唐古拉山脉以北以及昆仑山以南广大地区,平均海拔约为4894 m,是青藏高原的主要组成部分。研究区边界数据来源于美国地质调查局发布的HydroSHEDS流域产品[22]。研究区内分布有世界上海拔最高的内流 湖泊群,其中,面积超过50 km2的湖泊有127个; 面积超过500 km2的湖泊有10个,包括色林错、纳木错2个特大型湖泊（>2000 km2）,扎日南木错、当 惹雍错、阿雅克库木湖、乌兰乌拉湖,米提江占 木错,昂拉仁错,西金乌兰湖和阿其格库勒8个大 型湖泊（>500 km2）,湖泊基本信息如表1所示,湖 泊分布如图1所示。该地区属高原亚寒带半干旱 气候,主要受印度季风与西风控制[23],年均气温约为-0.47 ℃,年均降水约为226.7 mm[20]。20世纪90年代之后,该地区气温明显上升,降水显著增加[24]。
Fig. 1 The study area and the location of large lakes

图1 研究区及大型湖泊地理位置

Tab.1 Limnologic properties of 10 selected large lakes（>500 km2）[25]

表1 大型湖泊（>500 km2）基本属性[25]

湖泊 湖泊类型 省份 纬度/°N 经度/°E 面积/km2 ② 主要补给方式
色林错① 微咸水湖 西藏 32.1 89.1 2376 地表径流
纳木错 微咸水湖 西藏 30.7 90.6 2026 地表径流,湖面降水
昂拉仁错 微咸水湖 西藏 31.5 83.1 503 地表径流
扎日南木错 微咸水湖 西藏 30.9 85.6 1006 地表径流,湖面降水
当惹雍错 微咸水湖 西藏 31.1 86.6 846 地表径流
乌兰乌拉湖 微咸水湖 青海 34.8 90.5 634 地表径流,湖面降水
西金乌兰湖 盐湖 青海 35.3 90.2 532 地表径流
米提江占木错① 咸水湖 青海、西藏 33.4 90.1 1038 冰川融水径流
阿雅克库木湖 盐湖 新疆 37.5 89.4 950 冰雪融水径流
阿其格库勒 盐湖 新疆 37.1 88.4 507 地表径流

注：①在遥感影像中色林错和雅个冬错相连,为方便统计,视为一个湖泊,下文直接以色林错相称;相同情况的还有多尔索洞错,米提江占木错,玛巧错及周围一个不知名小湖泊,统称为米提江占木错。②表中面积表示湖泊在2009-2014年间平均面积

2.2 数据简介

本文使用的主要数据源是由中国资源卫星中心（http://www.cresda.com）提供的环境减灾卫星影像（HJ-1A/1B）以及美国地质调查局（https://eros.usgs.gov/）提供的Landsat系列卫星影像,并且以HJ-1A/1B影像为主。HJ-1A/1B与Landsat影像在可见光以及近红外波段范围基本一致,因此能够使用相同湖泊提取算法进行处理。
虽然HJ-1A/1B影像几乎能够在9-11月湖泊 稳定期间[3, 7, 11]完全覆盖所有目标湖泊,但是由于研究区范围较大,影像中极个别湖泊受到云覆盖严重,因此采用Landsat-5 TM和Landsat-8 OLI卫星 影像对这部分湖泊进行补充。本文所使用影像详细列表如表2所示,总共包括了87景HJ-1A/1B 数据,8景Landsat TM数据,1景Landsat OLI数据。影像数据绝大部分选自于9-11月湖泊稳定期,无云覆盖。
Tab.2 HJ-1A/1B and Landsat images used in this study

表2 本文所使用的环境减灾卫星以及Landsat卫星影像列表

2009年 2010年 2011年 2012年 2013年 2014年
传感器 轨道号 采集日期 传感器 轨道号 采集日期 传感器 轨道号 采集日期 传感器 轨道号 采集日期 传感器 轨道号 采集日期 传感器 轨道号 采集日期
1A/CCD1 31/72 0927 1A/CCD1 31/72 0901 1A/CCD1 43/72 1012 1A/CCD1 30/72 0913 1A/CCD1 30/72 1010 1A/CCD1 33/76 1031
1A/CCD1 34/80 1013 1A/CCD1 33/76 1026 1A/CCD1 44/73 1028 1A/CCD1 32/76 1002 1A/CCD1 30/76 1010 1A/CCD1 35/72 0918
1A/CCD2 29/80 1108 1A/CCD1 34/80 1030 1A/CCD2 33/79 1014 1A/CCD1 33/68 1021 1A/CCD1 31/80 1010 1A/CCD1 45/72 1005
1A/CCD2 34/74 1024 1A/CCD2 30/80 1029 1A/CCD2 40/76 1011 1A/CCD1 42/80 1022 1A/CCD1 48/72 1016 1A/CCD2 30/78 1111
1A/CCD2 36/71 00927 1A/CCD2 31/73 1029 1A/CCD2 41/80 1023 1A/CCD1 47/72 930 1A/CCD2 34/69 1006 1A/CCD2 38/80 1112
1A/CCD2 39/80 1013 1A/CCD2 35/72 901 1B/CCD1 29/72 1028 1A/CCD2 30/80 1020 1A/CCD2 35/72 1010 1A/CCD2 40/76 0918
1A/CCD2 45/72 1006 1A/CCD2 38/76 1026 1B/CCD1 29/79 1024 1A/CCD2 31/76 0905 1A/CCD2 35/76 1010 1A/CCD2 45/76 1028
1B/CCD1 34/68 1015 1A/CCD2 44/72 1019 1B/CCD1 36/72 1013 1A/CCD2 35/72 0913 1A/CCD2 35/80 1010 1B/CCD1 29/72 1009
1B/CCD1 35/76 1015 1B/CCD1 41/76 1025 1B/CCD1 37/80 1029 1A/CCD2 35/76 0928 1A/CCD2 40/80 1026 1B/CCD1 36/68 1002
1B/CCD1 38/72 926 1B/CCD1 41/80 1025 1B/CCD1 41/72 0920 1A/CCD2 37/80 1002 1A/CCD2 42/72 1007 1B/CCD1 36/72 1006
1B/CCD2 28/76 0928 1B/CCD2 29/72 1019 1B/CCD2 30/76 0914 1A/CCD2 38/80 1021 1B/CCD1 37/72 1009 1B/CCD1 41/80 0917
1B/CCD2 28/79 0928 1B/CCD2 35/69 1008 1B/CCD2 33/72 1012 1B/CCD1 37/72 0912 1B/CCD1 37/76 1009 1B/CCD2 30/76 1113
1B/CCD2 33/72 1022 1B/CCD2 39/76 1015 1B/CCD2 34/68 1028 1B/CCD2 41/72 0927 OLI 138/39 1012 1B/CCD2 31/70 0919
1B/CCD2 39/76 1015 1B/CCD2 45/76 1025 TM 138/35 1108 1B/CCD2 43/76 1001 1B/CCD2 33/80 1005
1B/CCD2 43/72 926 TM 138/39 1020 1B/CCD2 34/76 1013
1B/CCD2 43/76 1031 TM 141/36 1025 1B/CCD2 41/72 1006
TM 138/39 0830① TM 143/35 1108 1B/CCD2 41/76 1006
TM 140/35 0929 TM 143/36 1108
TM 144/36 0928

注：①由于2009年湖泊稳定期间没有色林错有效影像,因此采用8月30日的TM影像作为补充。此外,本文还借助了由寒区旱区科学数据中心（http://westdc.westgis.ac.cn/）提供的中国第二次冰川编目数据集（V1.0）[26],并结合美国地质调查局（https://eros.usgs.gov/）发布的HydroSHEDS河流流向以及流域产品[22],参考V.H.Phan（2013）[27]提出的方法,判定了研究区内湖泊是否存在冰川融水补给

3 研究方法

3.1 影像预处理

本文所选HJ-1A/1B,Landsat-5 TM以及Landsat-8 OLI影像均为几何校正后的产品,并且湖泊有效区域内无云覆盖,整景影像云量覆盖小于10%。HJ-1A/1B影像幅宽较大（700 km）,2级几何校正产品精度无法满足本文研究要求,为进一步提高湖泊面积提取精度,需对HJ-1A/1B影像进行正射校正处理。
Tab. 3 The area of large lakes during 2009-2014

表3 2009-2014年大型湖泊面积变化

湖泊 湖泊面积/km2 年变化率/%yr-1
2009年 2010年 2011年 2012年 2013年 2014年
色林错 2345.04 2346.92 2374.66 2381.37 2403.01 2402.71 0.56*
纳木错 2024.41 2024.58 2026.43 2026.61 2026.79 2027.22 0.03*
扎日南木错 1005.03 1005.00 1006.04 1005.76 1005.23 1006.39 0.02
当惹雍错 844.10 847.78 839.91 853.57 848.94 842.71 0.03
昂拉仁错 502.28 505.06 503.39 503.17 503.72 500.43 -0.08
乌兰乌拉湖 600.04 616.74 640.81 649.84 643.31 655.97 1.66*
西金乌兰湖 498.89 517.15 539.34 547.91 537.90 548.17 1.71*
米提江占木错 1014.70 1022.26 1036.00 1046.66 1054.94 1056.13 0.87*
阿雅克库木湖 871.57 931.37 947.93 975.92 986.22 985.80 2.30*
阿其格库勒 469.14 486.07 497.45 516.51 532.14 542.05 2.94*

注：*表示具有显著变化趋势（P<0.05）

卫星影像在成像过程中,受到投影方式、大气折光、地球曲率以及地形起伏等影响,容易使得影像中各像点产生不同程度的失真。常用的正射校正模型有物理模型和经验模型。由于无法获知HJ-1A/1B卫星轨道星历参数以及传感器参数,本文利用PCI Geomatics 2013软件中的OrthoEngine模块,对HJ-1A/1B影像进行正射校正,具体流程如下所述：
（1）基准数据准备。使用Landsat-5 TM 2009年全色拼接影像作为HJ-1A/1B影像正射校正的基准数据,数据来源于美国国家航空航天局Landsat全球正射校正产品[28-29]。同时,借助SRTM DEM （Shuttle Radar Topography Mission, Digital Elevation Model） 90 m分辨率高程数据产品对HJ-1A/1B影像进行正射校正。首先将基准底图与DEM数字高程底图剪裁至目标影像范围,并对其重采样至与目标HJ-1A/1B影像相同分辨率,即30 m。其中,重采样所使用的算法为较为常用的最邻近法。
（2）影像正射校正。利用PCI Geomatics 2013 OrthoEngine模块,选择软件内置的Toutin模型对HJ-1A/1B影像进行正射校正。参考基准底图影像,并借助Google Earth影像,人工选择影像控制点,保证控制点均匀分布于待校正影像当中。人工检查控制点残差,确保残差在1个像元以内。根据影像几何校正质量决定控制点数量,控制点总数不得少于25个。
（3）人工检查校正。检查HJ-1A/1B正射后的影像,对于正射校正结果较差、形变严重的影像,采取重新选择控制点的方式,重复步骤（2）;对于正射校正结果一般的影像,借助ArcMap软件对其进行几何纠正。以Landsat影像为基准底图,使用Georeference工具对上述正射结果影像进行几何纠正,选择二次多项式模型,确保影像几何误差控制在1个像元以内。

3.2 湖泊半自动提取算法

水体指数法是湖泊提取算法当中最为常用的一种方法,具有运算简单,提取精度高的特点。常用的水体指数有归一化水体指数NDWI[30]、改进 的归一化水体指数MNDWI[31]、增强型水体指数EWI[32]、高分辨率水体指数HRWI[33]等。由于环境 减灾卫星影像仅有4个波段,在上述4个指数中,只有NDWI和HRWI适用。NDWI和HRWI指数公式如下：
NDWI = （ G - NIR ） （ G + NIR ） （1）
HRWI = 6 × G - R - 6.5 × NIR + 0.2 （2）
式中：G、NIR、R分别表示绿波段、近红外波段以及红波段的反射率。
HRWI最初的设计是用于国产资源三号（ZY-3）卫星影像中城市水体的提取,相较于NDWI而言,HRWI对于不同地表环境下水体提取具有更好的鲁棒性[33],为此本文选择HRWI作为本文水体提取指数,并将HRWI指数应用到“全局-局部”分布迭代水体提取算法当中,通过自适应迭代算法获取湖泊精确边界[34-35]。处理流程如下：
（1）设定全局阈值T0,对影像进行全局分割,获得初步湖泊提取结果。为了避免遗漏部分湖泊信息,初始阈值的选择应遵循保证所有湖泊信息都被提取出来的原则,因此选择较小的阈值-0.1对HRWI计算结果影像进行分割,得到初步湖泊提取结果,湖泊像元数量为N0,并建立与湖泊像元数量一致的缓冲区。
（2）确定单个湖泊的自适应阈值。阈值计算公式如下：
T i = μ w × σ L + μ L × σ W μ W + μ L （3）
式中： μ W 、 μ L 分别表示水体像元和陆地像元的均值; σ W 、 σ L 表示水体和陆地像元指数值的方差; T i 表示湖泊 i 的最佳分割阈值。利用新得到的阈值对影像进行分割,得到新的湖泊单元,像元数量为Ni。
（3）对步骤（2）进行迭代处理,直至 N i - N 0 < N c ,表示湖泊提取结果已经稳定,停止迭代,得到初步湖泊边界提取结果。
（4）人工检查,去除山体、云等阴影误提结果;采用目视解译的方式,编辑湖泊边界提取结果不佳的影像,得到最终湖泊提取结果。

3.3 湖泊面积时序变化统计计算

本文采用一元线性回归模型结合最小二乘算法计算湖泊面积年变化率,计算公式如下所示：
Area = Slop × Year + C （4）
式中：Area表示每年的湖泊面积/km2;Slop表示湖泊面积年变化速率/(km2yr-1),Year表示年份,分别为2009年至2014年;C表示常数。本文利用R语言对湖泊面积年变化回归模型进行参数估计,使用lm（）函数实现一元线性回归模型的构建,并采用T检验模型中P值来判断湖泊年变化是否具有显著趋势。并假定,若P值小于0.05,则认为湖泊年变化具有显著趋势。
文中另一个表示湖泊面积变化的参数是年变化率,用Rate表示/(%yr-1),计算方式如下所示：
Rate = Slop / MeanArea × 100 % （5）
式中：Slop表示湖泊面积年变化速率/（km2yr-1）;MeanArea表示湖泊在2009-2014年间的平均面积。

4 结果及分析

4.1 湖泊面积有效性验证

青藏高原地势复杂,自然环境恶劣,人迹罕至,难以获取实时的湖泊面积记录。现有研究大多应用遥感影像获取湖泊面积。目前,有不少研究人员利用多源遥感影像制图,生成了湖泊面积数据库。其中,全球尺度下湖泊面积数据产品有GLWD（Global Lake and Wetlands Database）, GLWABO （GLObal WAter BOdies database）等;万炜等结合了1:25万地形图,19.5 m空间分辨率中巴资源卫星数据以及16 m空间分辨率的高分1号卫星数据绘制了1960 s,2005以及2014年共3期青藏高原湖泊数据（https://figshare.com/articles/Data_TPLakes/3145369）[36]。本文选择该数据集2014年湖泊制图结果作为准确值,验证文中30 m空间分辨率下湖泊面积提取结果的有效性,两组数据的相关性分析如图2所示。拟合曲线的R2大于0.99,斜率接近于1.00,均方根误差（RMSE）为1.32 km2,湖泊面积提取误差平均值约为0.96%。因此,可以认为采用文中上述方法提取所得到的湖泊面积结果真实有效。
Fig. 2 Comparison between the lake extraction results from this study and Gaofen-1 imagery in 2014

图2 2014年本文湖泊提取结果与高分1号卫星影像湖泊提取结果比较

4.2 湖泊面积时空变化分析

4.2.1 湖泊面积整体变化趋势
湖泊提取结果表明,2009-2014年,研究区内总共有127个湖泊面积超过50 km2,6年平均总面积为26608.09 km2,年均变化速率为231.89 km2yr-1（0.87% yr-1,P<0.01）,具有显著扩张趋势。从图3曲线可以看出,该流域内湖泊面积扩张趋势有所减缓。湖泊快速扩张阶段处于2009-2012年间。从2012年开始湖泊变化处于缓慢增长状态,2013-2014年湖泊面积基本保持稳定。年均变化速率仅为35.55 km2yr-1（0.13 %yr-1）。李均力等[11]在对本研究区内湖泊面积动态的研究中,发现区域内面积大于50 km2的湖泊面积在1970s-1990s,1990s-2000s,2000s-2009年的平均变化速率分别为-8.21 km2yr-1, 164.78 km2yr-1, 446.76 km2yr-1。虽然该研究对于湖泊面积的划分与本文略有不同,但是从整体数值上来看,可以发现,2009-2014年湖泊面积扩张速率较2000s-2009年具有非常明显的减缓（前者仅为后者的52%）,但是该数值依旧大于湖泊在1990s-2000s年间平均变化率。由此可见,青藏高原内流流域内的湖泊很有可能在经历了一个快速扩张的状态后逐渐回到缓慢扩张状态。
Fig. 3 Changing rate of total lake area during 2009-2014

图3 2009-2014年湖泊总面积变化趋势

通过统计湖泊面积变化规律发现,127个湖泊中有104个湖泊处于扩张状态,面积占所有湖泊面积的87.4%,年均变化速率为271.08 km2yr-1;23个湖泊处于收缩状态,年均收缩速率为39.19 km2yr-1。其中具有显著扩张趋势（P<0.05）的湖泊有62个,总面积占所有扩张湖泊面积的70.14%;具有显著萎缩趋势（P<0.05）的湖泊仅有4个,总面积占所有萎缩湖泊面积的13.1%。76%的湖泊年均变化率小于2.0 %yr-1,仅有8个湖泊面积变化超过了4.0 %yr-1。面积变化最为剧烈的两个湖泊分别位于可可西里地区的卓乃湖库赛湖流域和海丁诺尔流域。2011年8月,卓乃湖水位不断上涨最终导致了湖岸溃决引发了洪水。这部分湖水沿着流域内的古河道流向位于下游的库赛湖,造成库赛湖水位骤涨,并有大量湖水继续流向下游地区的海丁诺尔湖[37]。2010-2011年,卓乃湖面积减少了105.53 km2（39.0%）,而库赛湖和海丁诺尔由于卓乃湖湖水的注入,期间面积分别扩张55.75 km2（38.6%）和31.48 km2（16.2%）。
从不同面积湖泊的变化情况来看（图4(b)和(c)）,扩张湖泊的整体变化较萎缩湖泊剧烈。其中,面积处于500~1000 km2的大型湖泊面积增长最为迅速,平均年均增长速率达到了11.32 km2yr-1（1.73 %yr-1）;其次是面积大于1000 km2的特大型湖泊,平均年均增长速率为5.77 km2yr-1（0.37 %yr-1）。而对于萎缩湖泊而言,面积减少最为迅速的是处 于100~250 km2面积段的湖泊,平均年均萎缩速率为-3.05 km2yr-1（-1.71% yr-1）;处于其他面积范围内的湖泊面积变化较小。
Fig. 4 Detailed information of lake dynamics during 2009-2014

图4 2009-2014年湖泊变化详情

4.2.2 大型湖泊面积变化
大型湖泊对于高原生态系统以及区域水循环往往具有更为重要的影响,青藏高原内流流域中面积大于500 km2的大型湖泊总共有10个（表1）。2009-2014年期间,除了昂拉仁错面积略有减少外,其他湖泊面积均有不同程度的增长,且其中7个湖泊具有显著增长趋势;扎日南木错和当惹雍错面积变化不明显。本文结合历史研究数据,分析了这10个湖泊近40年以来的面积变化情况。
色林错和纳木错是青藏高原西藏境内面积超过2000 km2的湖泊,均属于微咸水湖。其中纳木错面积从1970年开始呈现稳步上涨趋势,1970-1990年面积变化速率约为1.03 km2yr-1[38],1991-2000年面积增长速率约为1.76 km2yr-1 [38],2000-2009年期间,纳木错面积扩张加速,达到了约6.4 km2yr-1[39]。然而到2009-2014年期间,纳木错面积扩张速率再次下降。从本文面积提取结果来看,纳木错这5年内面积增长速率仅为0.60 km2yr-1。相比较而言,色林错的面积扩张较为剧烈。在1975-2008年间,色林错面积总共增长了574.5 km2。其中1999-2008年湖泊面积就扩张了20%,面积平均扩张速率为41 km2yr-1[15];从本文研究结果来看,2009-2014年间,色林错面积扩张速率明显减小,年均变化速率仅为13.24 km2yr-1（0.56 %yr-1）。
位于冈底斯山脉附近的3个大型湖泊（扎日南木错,当惹雍错和昂拉仁错）在2009-2014年面积变化率均小于0.1%yr-1,且变化不显著。这3个湖泊均属于微咸水湖,以地表径流补给为主,其中扎日南木错的主要补给方式还包括了湖面降水。结合历史数据分析来看,湖泊面积均较为稳定。扎日南木错面积最大,面积超过了1000 km2。从1975年开始,该湖泊面积经历了先减少后增加的过程。1975-1999年面积减少了38.2 km2,并在1999年面积达到最小值944.1 km2;随后面积缓慢稳步增长,至2011年湖泊面积达到1006.7 km2[40]。结合本文数据,2009-2014年扎日南木错面积几乎没有变化,年均变化率不足0.02 %yr-1（0.29 km2yr-1）。当惹雍错和昂拉仁错面积略小于扎日南木错,均位于冈底斯山脉北坡断陷盆地内。其中当惹雍错面积自1999年以来虽有所增加[41],但是整体保持稳定状态,年变化率极小,没有显著的变化趋势;而昂拉仁错面积自1970s以来具有先萎缩后缓慢扩张的状态,其面积在2000s左右达到最小值,随后以极小的增长率波动上涨[42];至2010年后其面积又出现较小的减少趋势。
位于青海境内的乌兰乌拉湖和西金乌兰湖面积均表现出明显的扩张趋势;米提江占木错和多尔索洞错恰巧位于西藏和青海的交界处,由于这两个湖泊湖面相连,在文中被视作一个湖泊进行分析统计。2009-2014年间,这两个相连湖泊也具有显著扩张趋势,扩张率达到了0.87 %yr-1（9.02 km2yr-1）。与历史数据相比,乌兰乌拉湖在经历了1976-1994年面积萎缩阶段之后,出现了快速扩张趋势,并在2002年与2011年出现扩张速率峰值[43],其间,乌兰乌拉湖每年增加的面积均大于10 km2。2009-2014年,乌兰乌拉湖扩率达到了1.66 %yr-1 （10.53 km2yr-1）。西金乌兰湖在1970s和2000s面积分别为351.83 km2和383.61 km2[9],其间年均扩张速率约为1.1 km2yr-1。2000s之后,该湖泊增长速率急剧增加,2000-2009年间湖泊面积变化速率大于 10 km2yr-1;2009-2014年湖泊平均增长速率为 9.01 km2yr-1（1.71 %yr-1）,增长率略微下降。
阿雅克库木湖和阿其格库勒位于新疆境内,均属于盐湖。这2个湖泊扩张极为迅速,2009-2014年扩张率分别达到了2.30 %yr-1（21.82 km2yr-1）和2.94 %yr-1（14.90 km2yr-1）。同历史数据相比,这两个湖泊在1970s-2000s期间均经历了面积“缓慢减少-急剧扩张”的阶段,并从1990s开始,湖泊面积迅速增长[44]。阿雅克库木湖在1970s和2014年的面积分别为591.56 km2和985.80 km2,面积增长了约67%;同样,阿其格库勒在1970s和2014年的面积分别为360.38 km2和542.05 km2,面积增长了约50%[44]。
4.2.2 湖泊空间动态变化特征
青藏高原内流流域内湖泊分布密集,大部分湖泊面积小于1 km2[11]。其中,面积大于50 km2的湖泊主要分布在大型山脉周围,如青藏高原南部冈底斯山脉北坡的深谷湖泊群[3],念青唐古拉山脉西北的纳木错、色林错等,阿尔金山脉以及昆仑山脉附近的湖泊群;位于研究区中部地区的主要是面积较小的湖泊。为分析青藏高原内流流域中湖泊2009-2014年空间变化情况,本文将所有面积大于50 km2的湖泊分为4类,其中年变化率小于-0.5 %yr-1的湖泊为稳定萎缩湖泊,年变化率介于-0.5 %yr-1到0.5 %yr-1之间的湖泊为稳定湖泊,年变化率大于0.5 %yr-1的湖泊为稳定扩张湖泊,并将其中扩张率大于2.0 %yr-1标识为快速扩张湖泊。
从图5湖泊时空动态变化情况来看,扩张湖泊在整个内流流域内分布最广,且数量最大,总共有74个湖泊,湖泊总面积占所有湖泊面积的58%,主要位于研究区北部以及东部大部分区域。其中快速扩张（> 2.0 %yr-1）湖泊主要集中在研究区东北部可可西里地区,如碱水湖（7.35 % yr-1）、振泉错（7.25 % yr-1）①(① 振泉错表示振泉错、碧波错、北岛湖、连水湖、西泉湖相连水域。)、琼浆湖（5.11 % yr-1）②(② 琼浆湖表示琼浆湖、美菊湖、玉琳湖相连水域。)等;仅有4个湖泊位于班戈县和尼玛县境内南部区域,分别为雅根错（2.91 % yr-1）、昂达尔错（2.20 % yr-1）、果根错（2.74 % yr-1）和郭加林湖（2.02 % yr-1）;另有1个湖泊位于新疆和田县境内,为阿克赛钦湖（3.19 % yr-1）;剩余3个湖泊位于新疆阿尔金山脉南麓,分别是阿雅克库木湖（2.30 % yr-1）、阿其格库勒（2.94 % yr-1）和鲸鱼湖（2.02 % yr-1）。
Fig. 5 Spatiotemporal dynamics of lakes during 2009-2014 and the distribution of glacier

图5 2009-2014年湖泊时空动态及流域内冰川分布

稳定湖泊数量仅次于扩张湖泊,湖泊数量为43个,湖泊面积占所有湖泊面积的38%。主要分布在研究区南部冈底斯山脉北麓附近,包括了面积较大的纳木错（0.03 % yr-1）,昂拉仁错（-0.08 % yr-1）、扎日南木错（0.02 % yr-1）、当惹雍错等（0.03 % yr-1）;另有少数湖泊零散地分布于高原西部高山深谷区与东部,如郭扎错（0.08 % yr-1）、结则茶卡（0.42 % yr-1）、阿鲁错（0.32 % yr-1）等。
Fig. 6 Area changes of glacier-fed lakes and non-glacier-fed lakes during 2009-2014

图6 2009-2014年冰川与非冰川融水补给湖泊面积变化

稳定萎缩湖泊数量最少,只有10个,并且湖泊面积较小,其总面积仅占所有湖泊面积的4%,主 要分布在研究区四周,如位于研究区东北部青海境内的尕斯库勒湖（-0.83 % yr-1）,位于昆仑山南部 的卓乃湖（-12.65 % yr-1）和饮马湖（0.54 % yr-1）, 以及位于冈底斯山脉北部高山深谷区的扎布耶 错（-2.30 % yr-1）、曲依错（-1.29 % yr-1）、打加错 （-0.51 % yr-1）等。

4.3 冰川补给对湖泊面积变化的影响

现有研究对于青藏高原湖泊变化的原因尚无定论,不同学者对于高原湖泊于1990 s开始急剧扩张具有不同的解释。李均力等[3]认为降水、蒸发和气温是青藏高原内流流域内湖泊整体变化的主导因素,而湖泊的补给方式是不同区域湖泊变化存在差异的主要原因;姚晓军等[9]对可可西里湖泊时空变化研究发现,降水增加,蒸发减少是该区域湖泊扩张的主要原因,而由于气温升高导致的冰川、冻土融水增加则是次要因素;Chunqiao Song等[45]对青藏高原内面积大于10 km2的湖泊研究发现,2000s后湖泊扩张的主要原因包括了降水以及蒸发的变化,而并不仅仅是由冰川融水增加所导致。本文主要借助中国第二次冰川编目数据集（V1.0）,通过 V.P.Phan提出的算法[27],讨论了研究区内的湖泊是否存在冰川融水补给,并分析了冰川融水补给对于湖泊面积变化的影响（图5）。
冰川融水是高原湖泊的一种主要补给方式,在全球气温上升的趋势下,青藏高原冰川处于明显的退缩状态[46]。研究区内总共有90个湖泊（>50 km2）存在冰川融水补给,不存在冰川融水补给的湖泊面积相对较小,大部分集中于区域东南部地区。从本文所选湖泊的变化情况来看,存在冰川融水补给的湖泊中具有扩张趋势的总共有75个,占所有湖泊数量的83%,同整体扩张湖泊占比（82%）几乎相同,这部分湖泊整体变化率为198.04km2yr-1（0.74%yr-1）,占湖泊整体扩张率的85%。不存在冰川融水的湖泊数量较少,且年均变化速率仅为存在冰川融水补给湖泊变化率的1/6左右。
由此可见,虽然存在冰川融水补给的湖泊与不存在冰川融水补给的湖泊均有相近占比的湖泊数量具有扩张趋势,但是存在冰川融水补给的湖泊扩张率远大于不存在冰川融水补给的湖泊。因此,对于流域内面积大于50 km2的湖泊而言,冰川融水补给在一定程度上加速了湖泊的扩张。

5 结论

本文主要结合了多时相环境减灾卫星与Landsat系列卫星数据,对青藏高原内流流域湖泊面积变化进行了动态监测,讨论了2009-2014年湖泊的时空动态变化,并分析了高原内冰川退缩对于湖泊面积变化的影响,得到以下结论：
（1）2009-2014年间,青藏高原内流流域内湖泊（>50 km2）整体呈显著扩张趋势,6年平均变化速率为231.89 km2yr-1（0.87 % yr-1）,且逐年变化速率有减少趋势。104个湖泊处于扩张状态,扩张速率为271.08 km2yr-1（1.02 % yr-1）,其中62个湖泊具有显著扩张趋势（P<0.05）;23个湖泊处于收缩状态,年均变化速率为-39.19 km2yr-1（-0.15% yr-1）,仅有4个湖泊具有显著收缩趋势（P<0.05）。
（2）2009-2014年,湖泊时空动态变化具有明显的区域特征,主要表现为扩张湖泊分布最广,快速扩张湖泊则集中分布在可可西里地区;稳定湖泊主要分布在研究区南部冈底斯山脉北麓高山深谷区;萎缩湖泊数量最少,主要分布在研究区四周。从整个区域来看,湖泊变化率具有自西南向东北递增的趋势。
（3）冰川融水是青藏高原湖泊的一种主要补给方式,随着青藏高原冰川退缩现象加剧,冰川融水增加成为高原湖泊扩张的原因之一。本文研究区内湖泊中存在冰川融水补给的湖泊年均变化率远大于不存在冰川融水补给的湖泊,虽然扩张湖泊数量在两类湖泊中占比相近,但是可以认为,近年来冰川融水的增加,对高原大型湖泊的扩张起到了一定程度的促进作用。

The authors have declared that no competing interests exist.

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边多,拉巴,王彩云,等.1975-2008 年西藏色林错湖面变化对气候变化的响应[J].地理学报,2010,65(3):313-319.根据1975年地形图、80年代至2008年的TM、CBERS卫星遥感资料和近34年(1975-2008年)的气温、降水量、蒸发量、最大冻土深度等气候资料分析得出,西藏那曲地区西部的色林错及其周围的错鄂、雅根错的面积在近30年来呈较显著的扩大趋势,到2008年面积分别为2196.23km2、279.24km2、103.07km2,与1975年分别增长了574.46km2、11.59km2和68.13km2,增长速度分别为35.4%、4.3%和195%。色林错从1999-2008年湖面扩大速度为20%,平均上涨了420km2/10a,已超过纳木错面积,成为西藏第一大咸水湖。冰雪融水量的增加是湖泊上涨的根本原因,其次与降水量的增加和蒸发量的减少、冻土退化等暖湿化的气候变化存在很大关系。

[ Bian D, La B, Wang C Y, et al.The Response of Water Level of Selin Co to Climate Change during 1975-2008[J]. Acta Geographica Sinica, 2010,65(3):313-319. ]

[16]
Huang L, Liu J, Shao Q, et al.Changing inland lakes responding to climate warming in Northeastern Tibetan Plateau[J]. Climatic change, 2011,109(3):479-502.The main portion of Tibetan Plateau has experienced statistically significant warming over the past 5002years, especially in cold seasons. This paper aims to identify and characterize the dynamics of inland lakes that located in the hinterland of Tibetan Plateau responding to climate change. We compared satellite imageries in late 1970s and early 1990s with recent to inventory and track changes in lakes after three decades of rising temperatures in the region. It showed warm and dry trend in climate with significant accelerated increasing annual mean temperature over the last 3002years, however, decreasing periodically annual precipitation and no obvious trend in potential evapotranspiration during the same period. Our analysis indicated widespread declines in inland lake’s abundance and area in the whole origin of the Yellow River and southeastern origin of the Yangtze River. In contrast, the western and northern origin of the Yangtze River revealed completely reverse change. The regional lake surface area decreased by 11,49902ha or 1.72% from the late 1970s to the early 1990s, and increased by 6,86602ha or 1.04% from the early 1990s to 2004. Shrinking inland lakes may become a common feature in the discontinuous permafrost regions as a consequence of warming climate and thawing permafrost. Furthermore, obvious expanding were found in continuous permafrost regions due to climate warming and glacier retreating. The results may provide information for the scientific recognition of the responding events to the climate change recorded by the inland lakes.

DOI

[17]
Yao T, Pu J, Lu A, et al.Recent glacial retreat and its impact on hydrological processes on the Tibetan Plateau, China, and surrounding regions[J]. Arctic, Antarctic, and Alpine Research, 2007,39(4):642-650.

[18]
Zhu L, Xie M, Wu Y.Quantitative analysis of lake area variations and the influence factors from 1971 to 2004 in the Nam Co basin of the Tibetan Plateau[J]. Chinese Science Bulletin, 2010,55(13):1294-1303.By using remote sensing and GIS technologies, spatial analysis and statistic analysis, we calculated the water area and volume variations of the Nam Co Lake from 1971–2004, and discussed their influence factors from the viewpoints of climatic change and water balance. Data source in this study includes bathymetric data of the lake, aerial surveyed topographic maps of 1970, remote sensing images of 1991 and 2004 in the lake catchment, meteorological data from 17 stations within 1971–2004 in the adjacent area of the lake catchment. The results showed that the lake area expanded from 1920 km 2 to 2015 km 2 during 1971 to 2004 with the mean annual increasing rate (MAIR) of 2.81 km 2 a 611 , and the lake volume augmented from 783.23×10 8 m 3 to 863.77×10 8 m 3 with the MAIR of 2.37×10 8 m 3 . Moreover, the MAIR of the lake area and volume are both higher during 1992 to 2004 (4.01 km 2 a 611 and 3.61×10 8 m 3 a 611 ) than those during 1971 to 1991 (2.06 km 2 a 611 and 1.60×10 8 m 3 a 611 ). Analyses of meteorological data indicated that the continue rising of air temperature conduced more glacier melting water. This part of water supply, together with the increasing precipitation and the descending evaporation, contributed to the enlargement of Nam Co Lake. The roughly water balance analyses of lake water volume implied that, in two study periods (1971–1991 and 1992–2004), the precipitation supplies (direct precipitations on the lake area and stream flow derived from precipitations) accounted for 63% and 61.92% of the whole supplies, while the glacier melting water supplies occupied only 8.55% and 11.48%, respectively. This showed that precipitations were main water supplies of the Nam Co Lake. However, for the reason of lake water increasing, the increased amount from precipitations accounted for 46.67% of total increased water supplies, while the increased amount from glacier melting water reached 52.86% of total increased water supplies. The ratio of lake evaporation and lake volume augment showed that 95.71% of total increased water supplies contributed to the augment of lake volume. Therefore, the increased glacier melting water accounted for about 50.6% of augment of the lake volume, which suggested that the increased glacier melting water was the main reason for the quickly enlargement of the Nam Co lake under the continuous temperature rising.

DOI

[19]
Lei Y, Yao T, Bird B W, et al.Coherent lake growth on the central Tibetan Plateau since the 1970s: Characterization and attribution[J]. Journal of Hydrology, 2013,483:61-67.Although lakes on the central Tibetan Plateau (TP) expanded significantly in recent decades, causes for the lake growth still have not been well addressed. Based on remote sensing and GIS techniques together with bathymetric survey and water balance analysis, we show how climatic changes and glacier mass loss have influenced the inland lake dynamics on the central TP. Our results show that six closed lakes (Siling Co, Nam Co, Bam Co, Pung Co, Darab Co and Zige Tangco) expanded by 20.2% in area, by 8.7m in water depth, and by 37.7Gt in the total storage between 1976 and 2010, with a remarkable acceleration after 1999. The growth rate of lake area, water level and storage between 1999 and 2010 was 5.0, 3.6 and 4.8 times, respectively, than that between 1976 and 1999, corresponding well with the significant climatic changes in the late 1990s. Water balance analysis shows that increased precipitation and runoff, and decreased lake evaporation were the main causes for the coherent lake growth and could contribute by about 70% of total increase in lake storage. Based on modern mass balance results , glacier mass loss between 1999 and 2010 was estimated to contribute to the lake level rise of the three glacial-fed lakes, Siling Co, Nam Co and Pung Co, by 651.0m, 650.7m and 651.1m, respectively, accounting for 11.7%, 28.7% and 11.4% of the total lake level rise.

DOI

[20]
姜永见,李世杰,沈德福,等.青藏高原近 40 年来气候变化特征及湖泊环境响应[J].地理科学,2012,32(12):1503-1512.以青藏高原52个气象台站1971-2008年的逐月气温、降水资料为基础，采用因子分析、气候趋势分析、气候突变分析等方法，对高原内部不同区域的气候变化特征进行研究，并讨论了高原湖泊环境对气候变化的响应。结果表明，近40a来，青藏高原各区域年平均气温整体持续上升，柴达木地区增温尤为显著，年平均气温增长率达0．49℃／lOa；1987年和1998年各区域气温普遍由低向高突变，1998年以来增温尤为显著。年可利用降水的变化特征存在区域差异，柴达木地区、藏北南羌塘高原东部地区整体增湿。除藏东地区，青藏高原其它地区气候条件于20世纪末21世纪初由暖干向暖湿转变，受其影响，以青海湖、鄂陵湖、冬给措纳、兹格塘错为代表的高原大型湖泊表现出水位上升、湖水离子浓度减小的特征，反映了气候暖湿条件下湖泊水量的增加。

DOI

[ Jiang Y J, Li S J, Shen D F, et al.Climate change and its impact on the lake environment in the Tibetan Plateau in 1971-2008[J]. Scientia Geograohica Sinica, 2012,32(12):1503-1512. ]

[21]
朱大岗,孟宪刚,郑达兴,等.青藏高原近 25 年来河流,湖泊的变迁及其影响因素[J].地质通报,2007,26(1):22-30.结合20世纪70年代中期的MSS图像和90年代末期的ETM＋图像解译，对近25年来青藏高原河流、湖泊的分布现状及其变迁进行了分析。研究表明，青藏高原河流总体上变化不明显，部分地区外流水系个别河段略有摆动，内流水系少数河段发生改道、断流，入湖河流河口段发生延伸、退缩等变化。青藏高原多数天然湖泊变化较大，主要是部分湖泊面积缩小或扩大；少数湖泊解体或归并；有的已干涸的湖泊又重新汇水，有的湖泊则接近干涸。导致河流、湖泊演变的主要影响因素有气温变化、降水变化及冰川变化、气候雪线变化等。

DOI

[ Zhu D G, Meng X G, Zheng D X, et al.Changes of rivers and lakes on the Qinghai-Tibet Plateau in the past 25 years and their influence factors[J]. Geological Bulletin of China, 2007,26(1):22-30. ]

[22]
Lehner B, Verdin K, Jarvis A.HydroSHEDS technical documentation, version 1.0[R]. World Wildlife Fund US, Washington, DC. 2006,1-27.

[23]
Yao T, Thompson L, Yang W, Yu W, Gao Y, Guo X, et al.Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings[J]. Nature Climate Change, 2012,2(9):663-667.The Tibetan Plateau and surroundings contain the largest number of glaciers outside the polar regions(1). These glaciers are at the headwaters of many prominent Asian rivers and are largely experiencing shrinkage(2), which affects the water discharge of large rivers such as the lndus(3'4). The resulting potential geohazards(5,6) merit a comprehensive study of glacier status in the Tibetan Plateau and surroundings. Here we report on the glacier status over the past 30 years by investigating the glacial retreat of 82 glaciers, area reduction of 7,090 glaciers and mass-balance change of 15 glaciers. Systematic differences in glacier status are apparent from region to region, with the most intensive shrinkage in the Himalayas (excluding the Karakorum) characterized by the greatest reduction in glacial length and area and the most negative mass balance. The shrinkage generally decreases from the Himalayas to the continental interior and is the least in the eastern Pamir, characterized by the least glacial retreat, area reduction and positive mass balance. In addition to rising temperature, decreased precipitation in the Himalayas and increasing precipitation in the eastern Pamir accompanied by different atmospheric circulation patterns is probably driving these systematic differences.

DOI

[24]
吴绍洪,尹云鹤,郑度,等.青藏高原近 30 年气候变化趋势[J].地理学报,2005,60(1):3-11.以1971~2000年青藏高原77个气象台站的观测数据(最低、最高气温,日照时数,相对湿度,风速和降水量)为基础,应用1998年FAO推荐的Penman-Monteith模型,并根据我国实际状况对其辐射项进行修正,模拟了青藏高原1971~2000年的最大可能蒸散,并由Vyshotskii模型转换为干燥度,力求说明近30年青藏高原的气候变化趋势,以及干湿状况的空间分布。应用线性回归法计算变化趋势,并用Mann-Kendall方法进行趋势检验。结果表明青藏高原近30年气候变化的总体特征是气温呈上升趋势,降水呈增加趋势,最大可能蒸散呈降低趋势,大多数地区的干湿状况有由干向湿发展的趋势。气候因子与地表干湿状况间并不是线性关系,存在很大的不确定性。

DOI

[ Wu S H, Yin Y H, Zhen D, et al.Climate changes in the tibetan Plateau during the Last Three Decades[J]. Acta Geographica Sinica, 2005,60(1):3-11. ]

[25]
王苏民,窦鸿身.中国湖泊志[M].北京:科学出版社,1998.

[ Wang S M, Dou H S.Lakes in China[M]. Beijing:Science Press, 1998. ]

[26]
Guo W, Xu J, Liu S, et al. The second glacier inventory dataset of China (Version 1.0)[R]. Cold and Arid Regions Science Data Center at Lanzhou: Lanzhou, China. 2014.

[27]
Phan V, Lindenbergh R, Menenti M.Geometric dependency of Tibetan lakes on glacial runoff[J]. Hydrology and Earth System Sciences, 2013,17(10):4061.The Tibetan plateau is an essential source of water for South-East Asia. The run-off from its ~ 34 000 glaciers, which occupy an area of ~ 50 000 kmlt;supgt;2lt;/supgt; feed Tibetan lakes and major Asian rivers like Indus and Brahmaputra. Reported glacial shrinkage likely has its impact on the run-off. Unfortunately, accurate quantification of glacial changes is difficult over the high relief Tibetan plateau. However, it has been recently shown that it is possible to directly assess water level changes of a significant part of the ~ 900 Tibetan lakes greater than one square kilometer. This paper exploits different remote sensing products to explicitly create links between Tibetan glaciers, lakes and rivers. The results allow us first to differentiate between lakes with and without outlet. In addition, we introduce the notion of geometric dependency of a lake on glacial runoff, defined as the ratio between the total area of glaciers draining into a lake and the area of the catchment of the lake. These dependencies are determined for all ~ 900 Tibetan lakes. To obtain these results, we combine the so-called CAREERI glacier mask, a lake mask based on the MODIS MOD44W water product and the HydroSHEDS river network product derived from SRTM elevation data. Based on a drainage network analysis, all drainage links between glaciers and lakes are determined. The results show that 25.3% of the total glacier area directly drains into one of 244 Tibetan lakes. The results also give the geometric dependency of each lake on glacial runoff. For example, there are 10~lakes with direct glacial runoff from at least 240 kmlt;supgt;2lt;/supgt; of glacier. Three case studies, including one over the well-studied Nam Tso, demonstrate how the geometric dependency of a lake on glacial runoff can be directly linked to hydrological processes.

DOI

[28]
边金虎,李爱农,雷光斌,等.环境减灾卫星多光谱 CCD 影像自动几何精纠正与正射校正系统[J].生态学报,2014,34(24):7181-91.我国环境减灾光学卫星(HJ)多光谱CCD影像由于具有高时空分辨率、大幅宽等优势,能够提供同一区域不同生长阶段的植被信息,是提取具有生态学意义土地覆盖及开展植被生理生态参量反演的重要数据源之一。然而,目前该数据产品的几何定位不准确及山区地形畸变误差使其难以满足应用需求。高定位精度是遥感影像信息提取、参数反演与应用分析的前提,遥感影像的几何精纠正与正射校正是遥感数据预处理面临的首要问题。在分析国内外卫星影像自动化处理系统研究现状的基础上,结合HJ CCD影像幅宽大的特点,构建了HJ CCD影像的自动几何精纠正与正射校正处理系统。与目前商业软件相比,自动几何精纠正与正射校正处理系统采用了自动化的控制点搜索与过滤方法,能有效提高控制点选取的效率与精度。同时,结合DEM数据,系统自动拟合卫星飞行路径并纠正由偏离星下观测导致的山体位移。系统应用结果表明,自动几何精纠正和正射校正系统能够有效的提高处理效率,节省人力和时间成本。该系统已被成功应用于全国生态十年(2000—2010年)变化遥感调查与评估专项土地覆盖遥感监测的环境减灾卫星多光谱遥感影像预处理工作。

DOI

[ Bian J H, Li A N, Lei G B, et al.Auto-registration and orthorectification system for the HJ-1A/B CCD images[J]. Acta Ecologica Sinica, 2014,34(24):7181-7191. ]

[29]
Tucker C J, Grant D M, Dykstra J D.NASA’s global orthorectified Landsat data set[J]. Photogrammetric Engineering & Remote Sensing, 2004,70(3):313-22.NASA has sponsored the creation of an orthorectified and geodetically accurate global land data set of Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper data, from the 1970s, circa 1990, and circa 2000, respectively, to support a variety of scientific studies and educational purposes. This is the first time a geodetically accurate global compendium of orthorectified multi-epoch digital satellite data at the 30- to 80-m spatial scale spanning 30 years has been produced for use by the international scientific and educational communities. We describe data selection, orthorectification, accuracy, access, and other aspects of these data.

DOI

[30]
McFeeters S K. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features[J]. International Journal of Remote Sensing, 1996,17(7):1425-1432.Not Available

DOI

[31]
Xu H.Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery[J]. International Journal of Remote Sensing, 2006,27(14):3025-3033.The normalized difference water index (NDWI) of McFeeters (1996) was modified by substitution of a middle infrared band such as Landsat TM band 5 for the near infrared band used in the NDWI. The modified NDWI (MNDWI) can enhance open water features while efficiently suppressing and even removing built‐up land noise as well as vegetation and soil noise. The enhanced water information using the NDWI is often mixed with built‐up land noise and the area of extracted water is thus overestimated. Accordingly, the MNDWI is more suitable for enhancing and extracting water information for a water region with a background dominated by built‐up land areas because of its advantage in reducing and even removing built‐up land noise over the NDWI.

DOI

[32]
徐涵秋. 从增强型水体指数分析遥感水体指数的创建[J].地球信息科学学报,2012,10(6):776-80.

[ Xu H Q.Comment on the Enhanced Water Index(EWI):A Discussion on the Creation of a Water Index[J]. Journal of Geo-Infornation Science, 2012,10(6):776-780. ]

[33]
Yao F, Wang C, Dong D, Luo J, Shen Z, Yang K.High-resolution mapping of urban surface water using ZY-3 multi-spectral imagery[J]. Remote Sensing, 2015,7(9):12336-12355.Accurate information of urban surface water is important for assessing the role it plays in urban ecosystem services under the content of urbanization and climate change. However, high-resolution monitoring of urban water bodies using remote sensing remains a challenge because of the limitation of previous water indices and the dark building shadow effect. To address this problem, we proposed an automated urban water extraction method (UWEM) which combines a new water index, together with a building shadow detection method. Firstly, we trained the parameters of UWEM using ZY-3 imagery of Qingdao, China. Then we verified the algorithm using five other sub-scenes (Aksu, Fuzhou, Hanyang, Huangpo and Huainan) ZY-3 imagery. The performance was compared with that of the Normalized Difference Water Index (NDWI). Results indicated that UWEM performed significantly better at the sub-scenes with kappa coefficients improved by 7.87%, 32.35%, 12.64%, 29.72%, 14.29%, respectively, and total omission and commission error reduced by 61.53%, 65.74%, 83.51%, 82.44%, and 74.40%, respectively. Furthermore, UWEM has more stable performances than NDWI鈥檚 in a range of thresholds near zero. It reduces the over- and under-estimation issues which often accompany previous water indices when mapping urban surface water under complex environmental conditions.

DOI

[34]
骆剑承,盛永伟,沈占锋,等.分步迭代的多光谱遥感水体信息高精度自动提取[J].遥感学报,2009,13(4):610-615.以LANDSAT卫星遥感数据为信息源, 在归一化差异水指数(NDWI)计算的基础上, 采用“全域―局部”的分步迭代空间尺度转换机制, 将全域分割、全域分类、局部分割与分类等计算过程有机地结合起来, 分阶段地融合了水体信息提取所需的不同层次知识, 并建立迭代算法实现了水体最佳边缘的逐步逼近, 获得了高精度的水体信息提取。通过对青藏高原试验区湖泊信息提取的实验表明, 该方法除了能够实现对复杂多样的水体信息进行高精度自动提取外, 还可有效避免与阴影等信息的混淆。

DOI

[ Luo J C, Sheng Y W, Shen Z F, et al.Automatic and high-precise extraction for water information from multispectral images with the step-by-step iterative transformation mechanism[J]. Journal of Remote Sensing, 2009,13(4):610-615. ]

[35]
Wang J, Sheng Y, Tong TSD.Monitoring decadal lake dynamics across the Yangtze Basin downstream of Three Gorges Dam[J]. Remote Sensing of Environment, 2014,152:251-269.61Systematic monitoring of lake area dynamics in the Yangtze Basin downstream of TGD61Accurate lake extents produced by a novel mapping scheme61Lake area in the downstream Yangtze Basin uncovered in a net decadal decline61The most substantial lake decline concurred with the TGD water storage season61Lake decline in the Yangtze Plain contrasted to lake area increase beyond the plain

DOI

[36]
Wan W, Long D, Hong Y, et al.A lake data set for the Tibetan Plateau from the 1960s, 2005, and 2014[J]. Scientific Data, 2016,3:160039.Long-term datasets of number and size of lakes over the Tibetan Plateau (TP) are among the most critical components for better understanding the interactions among the cryosphere, hydrosphere, and atmosphere at regional and global scales. Due to the harsh environment and the scarcity of data over the TP, data accumulation and sharing become more valuable for scientists worldwide to make new discoveries in this region. This paper, for the first time, presents a comprehensive and freely available data set of lakes’ status (name, location, shape, area, perimeter, etc.) over the TP region dating back to the 1960s, including three time series, i.e., the 1960s, 2005, and 2014, derived from ground survey (the 1960s) or high-spatial-resolution satellite images from the China-Brazil Earth Resources Satellite (CBERS) (2005) and China’s newly launched GaoFen-1 (GF-1, which means high-resolution images in Chinese) satellite (2014). The data set could provide scientists with useful information for revealing environmental changes and mechanisms over the TP region.

DOI PMID

[37]
刘宝康,李林,杜玉娥,等.青藏高原可可西里卓乃湖溃堤成因及其影响分析[J].冰川冻土,2016,38(2):305-311.受青藏高原暖湿化趋势的影响，近年来高原湖泊水位普遍上涨，湖泊溃堤时有发生.利用青藏高原可可西里卓乃湖、库赛湖、海丁诺尔湖和盐湖所在区域的TM（ETM+）等历史文献数据和环境减灾卫星（HJ1A/B） CCD数据，结合五道梁气象站气温、降水资料，分析了卓乃湖周边湖泊面积变化情况.结果表明：1961-2014年近54 a来，可可西里地区持续增加的降水是卓乃湖溃堤的基础，2011年8月22日之前的两次强降水过程和之后的持续降水是导致卓乃湖湖水大量外泄，并最终溃堤的主要原因；溃堤前的两次地震可能对卓乃湖的湖盆结构产生了一定的影响，从而加速了溃堤过程.溃堤导致湖岸线退缩，并产生大片的沙化土地，恶化了藏羚羊的产仔环境，对周边草地生态环境和重大工程设施产生了不利影响.

DOI

[ Liu B K, Li L, Du Y E, et al.Causes of the outburst of Zonag Lake in Hoh Xil, Tibetan Plateau, and its impact on surrounding environment[J]. Journal of Glaciology and Geocryology, 2016,38(2):305-311. ]

[38]
吴艳红,朱立平,叶庆华,等.纳木错流域近 30 年来湖泊—冰川变化对气候的响应[J].地理学报,2007,62(3):301-310.利用1970航测地形图和1991、2000年两期卫星影像数据，人工建立数字高程模型 （DEM），解译不同时期的湖泊、冰川边界，在GIS技术支持下采用图谱的方法，定量分析了湖泊、冰川的面积变化情况。结果表明，自1970-2000年 期间，纳木错湖面面积从1941．64km^2增加到1979．79km^2，增加的速率为1．27km^2／a；流域内冰川的面积从 167．62km^2减少到141．88km^2．退缩速率为0．86km^2／a。其中．湖面面积在1991-2000年的增加速率为 1．76km^2／a．明显大于其在1970-1991年的1．03km^2／a；而冰川面积在1991-2000年的退缩速率为0．97km^2／a， 明显大于其在1970-1991年的0．80km^2/a。对比该流域前后两个时期的气温、降水和蒸发变化．发现升温幅度的增加是冰川加速退缩的根本原 因．而湖面的加速扩张主要受冰川的加剧退缩及其引起的融水增加影响．但与区域降水量略微增加和蒸发量显著减少也具有密切联系。区域降水增加和蒸发减少及其 与湖面扩张之间的内在联系仍是一个需要深入探讨的问题。

DOI

[ Wu Y H, Zhu L P, Ye Q H, et al.The response of Lake-Glacier area change to climate variations in Namco Basin, Central Tibetan Plateau during the Last Three Decades[J]. Acta Geographica Sinica, 2007,62(3):301-310. ]

[39]
马颖钊,易朝路,吴家章,等.1970-2009年纳木错湖泊面积扩张的遥感卫星观测证据及原因之商榷[J].冰川冻土,2012,34(1):81-88.By using remote sensing images of different periods, aerial topographic map and digital elevation model, the change in surface area of Nam Co during 1970-2009 is analyzed based on geographical information system (GIS) and remote sensing (RS) techniques. According to the correlative meteorological data, the possible reasons on lake area variation are discussed by analyzing the lake pan-evaporation and precipitation, glacier ablation, as well as influx water supply. It is found that lake surface has expanded since the 1970s and even more severe during the last ten years, with an expansion more than 50 km from 2001 to 2009. Precipitation variation is the direct cause of the lake expansion. Furthermore, the decline of lake pan-evaporation is another reason for the extension.

[ Ma Y Z, Yi C L, Wu J Z, et al.Lake surface expension of Nam Co during 1970-2009: Evidence of satellite remote sensing and cause analysis[J]. Journal of Glaciology and Geocryology, 2012,34(1):81-88. ]

[40]
拉巴,陈涛,杨秀海.基于多源卫星数据扎日南木错湖面变化和气象成因分析[J].湖泊科学,2014,26(6):963-970.

[ La B, Chen T, Yang X H.Lake area variation of Thari Namtso and its meteorological causes based on multi-sensor satellite data[J]. Journal of Lake Sciences, 2014,26(6):963-970. ]

[41]
拉巴,边多,陈涛.基于TM 影像的西藏当惹雍错湖面积变化及可能成因[J].气象科技,2012,40(4):685-688.根据1999—2004年及2008、2009年的TM卫星遥感资料和离湖泊较近的西藏申扎、改则两县1999—2009年气温、降水量、蒸发量资料,利用ARCGIS、ARCVIEW、ENVI等遥感、地理信息系统和数据统计处理软件分析了西藏当惹雍错湖面积变化。结果表明,西藏当惹雍错湖面积在近11年内呈较显著的扩大趋势,湖泊面积11年内增长了15.04km2,增长率为1.8%;湖泊面积在东南部区域有明显的扩大。湖泊面积变化原因分析表明,湖区气温持续升高引起流域内冰川和永久积雪的加速融化和降水量不断增大是湖泊面积增长的原因。

DOI

[ La B, Bian D, Chen T.Possible causes of area change of lake Tangra Yumco, Tibet Based on TM Images[J]. Meteorological Science and Technology, 2012,40(4):685-688. ]

[42]
张淑萍,张虎才,陈光杰,等. 1973-2010 年青藏高原西部昂拉仁错流域气候,冰川变化与湖泊响应[J].冰川冻土,2012,34(2):267-276.In this paper, all the materials adapted are as follow: 1) meteorological data from three stations nearby Ngangla Ringsto, namely, Gaize, Shiquanhe and Pulan, from 1973 to 2010; 2) Landsat remote sensing images covering the water area of Ngangla Ringsto in 1973, 1976, 1990, 2000, 2001, 2002, and 2009, which were used to extract the information of lake changes, and images covering the whole catchment in 1976, 1990/1992, 2000 and 2009, which were used to gain the information of glacier changes in the drainage basin. On the base of above information, the changes in climate, lake and glacier during the past 40 years were analyzed, and the relationship between every factor that causes the lake area change of Ngangla Ringsto was preliminarily studied. It is fond that: (i) during the past 38 years, the lake area of Ngangla Ringsto decreased before 2000 and increased after that, with a general trend of increase; (ii)The glacierized area in the catchment has shrunk and consistently contributed the Ngangla Ringsto during that time span; (iii) After comparing the changing tendencies of temperature, annual precipitation and maximum of potential evaporation at the three meteorological stations, the data from Gaize Station is chosen as a reference to analyze the cause of the lake area change in Ngangla Ringsto. The result shows that in every changing stage it is a gap between the annual precipitation and maximum of potential evaporation in the catchment that controls the change in the lake area of Ngangla Ringsto. When the water input from precipitation and constantly increasing melt water is less than the amount of evaporation in the catchment, the lake area will decease, but when the water from the glacier melting and frozen soil thawing in a accelerated speed due to the rapidly rising temperature plus gradually increasing precipitation in the catchment finally surpasses the output from evaporation, the lake begins to expand.

[ Zhang S P, Zhang H C, Chen G J, et al.Climate and glacier changes and lake response in the NganglaRingsto Catchment in Western Tibetan Plateau[J]. Journal of Glaciology and Geocryology, 2012,34(2):267-276. ]

[43]
姜丽光,姚治君,刘兆飞,等. 1976-2012 年可可西里乌兰乌拉湖面积和边界变化及其原因[J].湿地科学,2014,12(2):155-162.高原湖泊对气候变化极为敏感,通过湖泊变化能够真实地反映气候变化状况。在地理信息系统和遥感技术支持下,基于多源、多时相的数字遥感影像、地形图和DEM数据,并结合其他相关研究文献资料,对乌兰乌拉湖37 a来湖泊面积变化及其与自然要素(气温、降水量等)之间的关系进行了研究,并从湖泊补给的构成角度分析了其变化原因。结果表明,自1976~2012年期间,乌兰乌拉湖范围总体上有所扩张,期间经历了先萎缩、后扩张的过程。1976年乌兰乌拉湖的面积为555.97 km2,1994年其面积为496.50 km2,这期间湖泊在逐年萎缩,递减幅度为3.12 km2/a;从1998年开始,湖泊面积开始迅速扩大,1998年湖泊面积为499.83 km2,到2012年湖泊面积达655.25 km2,扩张速率为10.36 km2/a。乌兰乌拉湖水域面积变化主要集中在湖的南部河流入湖口处。1976~2012年期间,乌兰乌拉湖流域的年降水量增加,年平均气温升高。1998年以来,乌兰乌拉湖水域面积扩张的原因有二:年降水量增加;年平均气温升高导致冻融水量增加。在湖泊主要年补给水量构成中,湖面年降水量、流域年降水径流量、冻融水年补给量分别约占23.3%、43.7%和33.0%。

[ Jiang L G, Yao Z J, Liu Z F, et al.Variation of lake area and boundary of Ulan Ul Lake in Hoh Xil Region during 1976-2012 and Their Reasons[J]. Wetland Science, 2014,12(2):155-162. ]

[44]
闰立娟,郑绵平.我国蒙新地区近 40 年来湖泊动态变化与气候耦合[J].地球学报,2014,35(4):463-472.湖泊对气候变化有着敏感的反应,是气候变化的镜子。本文以RS和GIS技术为基础,从20世纪70年代、90年代、2000年前后和2010年前后四期Landsat遥感影像中提取了我国内蒙古和新疆所有湖泊信息,建立了蒙新地区湖泊空间数据库。一方面,用ArcGIS软件对研究区湖泊信息进行了统计和空间分析,从时间和空间上分析了蒙新地区湖泊从20世纪70年代至2010年前后近40年湖泊的动态变化情况;另一方面,选取了蒙新地区面积大于5 km2的所有湖泊,逐个分析其在四个时期的变化情况,并根据变化结果进行分区。从20世纪70年代至90年代,内蒙古东南部和新疆西部的湖泊呈现萎缩的趋势,其余地区则在扩张;20世纪90年代至2000年前后,内蒙古东南部湖泊呈现萎缩的趋势,内蒙古北部和新疆全区湖泊呈现扩张的趋势;从2000年前后至2010年前后,内蒙古东北部和新疆西部的湖泊呈现萎缩的趋势,其余地区湖泊呈现扩张的趋势。在全球气候变暖的背景下,本文分析了蒙新地区40个气象台站的气温、降雨量和蒸发量数据,可知:近40年来,蒙新地区气温持续上升;2000年之前,内蒙古的降雨量呈增加的趋势,2000年之后骤减,而新疆大部分地区的降雨量呈增加的趋势;蒙新地区蒸发量整体呈现减少的趋势。湖泊的动态变化基本上与气候的变化趋势相吻合。最后,笔者以新疆博斯腾湖为例,分析了湖泊变化的影响因素:气候环境和人类活动。

DOI

[ Run L J, Zhen M P.Dynamic changes of lakes in Inner Mongolia-Xinjiang region and the climate interaction in the past forty years[J]. Acta Geoscientica Sinica, 2014,35(4):463-472. ]

[45]
Song C, Huang B, Richards K, et al.Accelerated lake expansion on the Tibetan Plateau in the 2000s: induced by glacial melting or other processes[J]. Water Resources Research, 2014,50(4):3170-3186.Alpine lakes on the Tibetan Plateau are minimally disturbed by human activities and are sensitive indicators of climate variability. Accelerated lake expansion in the 2000s has been confirmed by both dramatic lake-area increases (for 312 lakes larger than 10 km) derived from optical images, and rapid water-level rises (for 117 lakes with water-level data) measured by satellite altimetry. However, the underlying climate causes remain unclear. This paper analyzes the relationship between the water-level changes of lakes on the plateau and the potential driving factors, such as the glacier meltwater supply and a dependency on precipitation and runoff over the whole plateau and in each zone. The results show that the rates of change of non-glacier-fed lakes in the 2000s were as high as those of glacier-fed lakes across the whole plateau and the lake-level changes were closely associated with the lake supply coefficients (the basin/lake area ratio). The lake variations agreed well with the spatial pattern of precipitation changes. However, in different zones, especially at around 33 N north of the plateau, glacier-fed lakes did exhibit faster lake level increases than no-glacier-fed lakes, indicating that the presence of a glacier meltwater supply augmented the precipitation-driven lake expansions in these areas. Despite the absence of quantitative modeling due to limited data availability, this study provides qualitative support that the lake expansions on the Tibetan Plateau in the 2000s have been driven primarily by changes in precipitation and evapotranspiration and not solely by the effect of glacier wastage.

DOI

[46]
鲁安新,姚檀栋,王丽红,等.青藏高原典型冰川和湖泊变化遥感研究[J].冰川冻土,2005,27(6):783-92.Glaciers and lakes on the Tibetan Plateau play an important role in the earth climatic system.The remote sensing techniques and the Geographic Information System technology is an efficient tool to analyze the status and fluctuations of glaciers and lakes.In this paper,the variations of typical glaciers and lakes throughout the Tibetan Plateau were investigated by analyzing the datasets from aerial photos,satellite images,topographical and the derived digital elevation models during the period of 1960-2000.The results show that variation of lake area depends clearly on local climate change.Over the past 30 years,the most of lakes in the middle Tibetan Plateau,such as the Seling Lake and Nam Lake,expanded and glaciers around the lakes retreated dramatically.It is inferred that the increasing of precipitation,decreasing of potential evaportranspiration and runoff from glacier melting are responsible mainly for the lake expanding.However,the lakes in the head regions of the Yellow River in the northeastern plateau shrunk in the period of 1960-2000 despite of glacier retreating.In the source regions of the Yellow River,the changing trend of precipitation,although positive,is not significant while temperature increased apparently,indicating water loss of the lakes enhanced through increasing of evaportranspiration and thus lakes shrunk in the past 30 years.It is also argued that ecosystem regression resulted from human activity in the regions played an important role in the lake shrinking.

DOI

[ Lu A X, Yao T D, Wang L H, et al.Study on the fluctuations of typical glaciers and lakes in the Tibetan Plateau using remote sensing[J]. Journal of Glaciology and Geocryology, 2005,27(6):783-792. ]

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