Preprints
https://doi.org/10.5194/egusphere-2024-2195
https://doi.org/10.5194/egusphere-2024-2195
09 Oct 2024
 | 09 Oct 2024
Status: this preprint is open for discussion.

Volumetric evolution of supraglacial lakes in southwestern Greenland using ICESat-2 and Sentinel-2

Tiantian Feng, Xinyu Ma, and Xiaomin Liu

Abstract. Surface meltwater runoff has been the primary factor affecting the trends and interannual variations in the mass balance of the Greenland Ice Sheet. During the melting season, large amounts of surface meltwater accumulate in low-lying areas, forming supraglacial lakes (SGLs). Quantitatively characterizing the spatial and temporal changes in the volume of SGLs can provide further insights into the surface mass balance changes of the ice sheet during the melt season. In this paper, we propose a method for estimating the volume of SGLs by combining optical imagery (Sentinel-2) and satellite altimetry data (ICESat-2). First, the area of SGLs is extracted using a Random Forest (RF) model based on spectral features from Sentinel-2 imagery, achieving an Intersection over Union (IoU) of 90.20 % compared to manually delineated lake extents. Second, the depth of SGLs along the ICESat-2 profile is detected using the kernel density analysis method. Finally, a multi-layer perceptron (MLP) model constructs the nonlinear relationship between the reflectance ratio from Sentinel-2 imagery and the depth of SGLs detected by ICESat-2 data. The accuracy of depth inversion based on the MLP model surpasses traditional empirical formula methods, achieving a mean absolute error of 0.42 m. The trained MLP model is then used to estimate the depth over the entire lake areas. The proposed volume estimation method for SGLs is applied to southwestern Greenland, capturing the volumetric evolution of SGLs throughout the entire melt season of 2022. The results reveal significant variations in the distribution, area, depth, and volume of SGLs throughout the melt season. Initially, SGLs form along the coastlines and later spread inland, expanding in area and depth. The maximum total volume of SGLs is reached on August 1st, amounting to 9.30 × 108 m3. Afterward, SGLs above 1200 m continue to increase in volume, while SGLs below 1200 m begin to decrease. In late August, as the melt season draws to a close, SGLs diminish and retreat to coastal regions, with a notable reduction in volume. Additionally, according to the evolution characteristics of SGLs at different elevations, SGLs above 800 m exhibit a similar evolution pattern. A temporal discrepancy is observed in the attainment of maximum values for both mean area and mean depth, implying a differential rate of development of SGLs in the horizontal and vertical dimensions. The elevation range of 1200 m to 1600 m is the most favorable for the evolution of SGLs.

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Tiantian Feng, Xinyu Ma, and Xiaomin Liu

Status: open (until 20 Dec 2024)

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Tiantian Feng, Xinyu Ma, and Xiaomin Liu
Tiantian Feng, Xinyu Ma, and Xiaomin Liu

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Short summary
During the melting season, substantial quantities of surface meltwater converge in topographically depressed regions, forming supraglacial lakes (SGLs). We extract SGLs area and profile depth using remote sensing data, and then inversion the depth of entire SGLs based on machine learning method. By applying above-mentioned methods, we capture the volumetric evolution of SGLs throughout the entire melt season of 2022 in southwestern Greenland.