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Estimation of Water Volume Changes in Typical Alpine Lakes on the Tibetan Plateau by Combining Sentinel-3 Radar Altimetry Data and Optical Images
陈 军高婧潇汪永丰金 璐
(安徽建筑大学 a. 环境与能源工程学院; b.安徽省智慧城市工程技术研究中心,合肥 230000)
CHEN Jun GAO Jingxiao WANG Yongfeng JIN Lu
(a. School of Environmental and Energy Engineering; b. Anhui Smart City Engineering Technology Research Center, Anhui Jianzhu University, Hefei 230000, China)
Sentinel-3 雷达测高 光学影像 湖泊水位 青藏高原
Sentinel-3 radar altimetry optical image lake water level the Qinghai-Tibet Plateau
X87; X821
青藏高原湖泊对气候波动表现出高度的敏感性,其动态监测数据为区域甚至全球气候变化研究提供重要证据。受恶劣自然环境的限制,青藏高原大部分地区缺乏实地观测数据,现有的青藏高原湖泊变化分析,多基于遥感,湖泊水位与面积等数据通常来自不同卫星,数据之间存在时间上的偏离。本研究融合Sentinel-3 SRAL(SAR Radar Altimeter)雷达测高数据与相同卫星搭载的Sentinel-3 SLSTR(Sea and Land Surface Temperature Radiometer)光学影像监测了2016年4月—2022年9月青藏高原四个大型湖泊(阿牙克库木湖、色林错、青海湖、纳木错)的水位及面积变化。通过将监测结果与实测水位及与DAHITI水文产品对比分析,确认Sentinel-3雷达测高数据能够准确地反映高原大型湖泊水位的周际和月际变化特征。结果表明:(1)四个湖泊的水位在监测期内逐年上升,分别上涨了3.01 m、2.04 m、1.62 m、0.28 m。四个湖泊的面积与水位季节变化特征一般表现为:夏季季风期湖面显著增大,非季风期逐渐减小。(2)湖泊水位在第二季度最低,第三季度末或第四季度初上升到峰值。四个湖泊的水量在监测期内也均呈现出不同程度的涨幅,其中青海湖的水量增长最大,达到了7.381 km3; 纳木错水量变化最小,监测期间仅增长0.072 km3。(3)比较DEM估算水量法和经验公式法分别拟合出的水量线性变化趋势,证明基于Sentinel-3数据进行的湖泊水量估算的准确性。(4)以阿牙克库木湖为例,通过探究其水位周变化与降水量日变化之间的对应关系,证明了降水是湖泊水位变化的主要影响因素。本研究利用Sentinel-3同时具备光学影像和测高数据的优势,避免使用不同卫星数据组合由于时间延迟而造成结果的不确定性,为青藏高原的水资源平衡研究提供了独特的数据应用方案。
Lakes in the Qinghai-Tibet Plateau are highly sensitive to climate fluctuations, and dynamic monitoring of the lakes'changes provides crucial evidences for regional and even global climate research. Most of the lakes had little field observation record due to traffic inaccessibility in the Plateau. Some academic comments on the changes of lakes in the Plateau were based on remote sensing; data such as lake water level and area generally referred to mutiple satellites, and there was remarkable temporal deviation between the data, for example, temporal disagreement between measured water levels and lake areas.
In this study, Sentinel-3 SRAL(SAR Radar Altimeter)radar altimetry data and Sentinel-3 SLSTR(Sea and Land Surface Temperature Radiometer)optical images collected by the same satellite were used to detect the water level and area changes of four large lakes, i.e. the Ayakkumu Lake, the Selinco Lake, the Qinghai Lake and the Namco Lake in the Qinghai-Tibet Plateau from April 2016 to September 2022. By comparison in-situ water level measurements with DAHITI data(Database for Hydrological Time Series of Inland Waters), it confirmed that Sentinel-3 radar altimetry could accurately capture weekly and monthly lake level fluctuations.
(1)A consistent annual rise in water levels took place during the monitoring period at the four lakes, rising by 3.01 m, 2.04 m, 1.62 m, and 0.28 m, respectively. Seasonal changes in the area and water level of the four lakes were generally characterized by a significant increase in the lake surface during summer monsoon periods and a gradual decrease during non-monsoon periods.(2)Lake levels were the lowest in the second quarter and rose to peak levels at the end of the third and beginning of the fourth quarter. The water volumes of the four lakes displayed different increases during the monitoring period, among which the Qinghai Lake got the largest rise of 7.381 km3 but the Namco Lake changed the least at only 0.072 km3.(3)Comparing the linear trend of water volumes fitted by DEM estimation and obtained by empirical formula, respectively, it justified the accuracy of lake water volume estimation based on Sentinel-3 data.(4)Further, taking the Lake Ayakkumu as an example, it was demonstrated that there was correspondence between the weekly change of its water level and the daily change of precipitation, proving that precipitation was the main influencing factor on the change of water level in the lake.
Based on the advantages of Sentinel-3, which produced a synchrony of optical images and radar altimetry data, i.e., exact consistency between extraction of lake water level/area and time, it avoided result uncertainty caused by time delay of using multiple satellite data combinations, and provided a unique data resource for in-depth analysis of water resources balance in the Qinghai-Tibetan Plateau.


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收稿日期(Received date): 2023- 07- 06; 改回日期(Accepted date): 2023-12-14
基金项目(Foundation item): 国家自然科学基金(41901129)。[National Natural Science Foundation of China(41901129)]
作者简介(Biography): 陈军(1984-),男,安徽宣城人,博士,副教授/高级工程师,主要研究方向:遥感地学分析、资源环境遥感。[CHEN Jun(1984-), male, born in Xuancheng, Anhui province, Ph.D., associate professor/senior engineer, research on remote sensing geoscience analysis and remote sensing of resources and environments] E-mail: gischen@126.com
更新日期/Last Update: 2023-11-30