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    全格陵兰冰盖表面融水卫星遥感观测

    Remote sensing observation of surface meltwater on the Greenland Ice Sheet

    • 摘要: 每年夏季,格陵兰冰盖表面消融产生大量融水。冰面融水由冰面河输送,存储在冰面湖或注水冰裂隙中,形成了规模庞大、结构复杂的水文系统。然而,目前研究对全格陵兰冰面融水空间分布的理解十分有限。文章利用134景10 m空间分辨率的Sentinel-2遥感影像,提取了2019年消融旺盛期格陵兰冰面融水遥感信息; 进一步,对比分析了遥感观测的冰面融水分布与区域大气气候模型(regional atmospheric climate model,RACMO)模拟的冰面融水径流量。结果表明: ①2019年消融旺盛期,格陵兰冰面融水面积为9 900.9 km2,融水体积为6.8 km3; ②格陵兰冰面融水的空间分布差异较大,呈现明显的“西多东少”“北多南少”的态势; ③格陵兰冰面融水主要由冰面河组成,冰面河占冰面融水总体积的57.1%,其次是注水冰裂隙(25.6%)和冰面湖(17.3%); ④RACMO在多数流域准确模拟了冰面融水径流区域。研究反映了高分辨率遥感在格陵兰冰面水文研究中的应用潜力,提升了对冰面融水输送与存储等关键水文过程的理解。

       

      Abstract: Every summer, the surface melting on the Greenland Ice Sheet (GrIS) results in a large amount of surface meltwater, which is transported via supraglacial rivers and stored supraglacial lakes and water-filled crevasses, forming a large-scale and complex hydrologic system. However, there is a lack of studies on the spatial distribution of surface meltwater on the GrIS. This study extracted the surface meltwater information of the GrIS during the peak melting period in 2019 using 134 scenes of 10-m-resolution Sentinel-2 satellite images. Furthermore, we compared the surface meltwater distribution derived from the remote sensing observation and the surface meltwater runoff simulated by the regional atmospheric climate model (RACMO). The results show that: ① During the peak melting period in 2019, the GrIS exhibited a surface meltwater area of 9 900.9 km2 and a surface meltwater volume of 6.8 km3; ② The GrIS surface meltwater exhibited a significantly varying spatial distribution characterized by high volumes in the western and northern basins and low volumes in the eastern and southern basins; ③ The surface meltwater on the GrIS was primarily composed of supraglacial rivers, which accounted for 57.1% of the overall surface meltwater volume, followed by water-filled crevasses (25.6%) and supraglacial lakes (17.3%); ④ RACMO accurately simulated the surface meltwater runoff regions in most GrIS basins. This study enhanced the understanding of key hydrologic processes such as surface meltwater routing and storage, demonstrating the high application potential of high-resolution remote sensing images in the hydrologic research of the GrIS.

       

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