Large volumes of meltwater produced on the northern Greenland Ice Sheet (GrIS) are directly routed into proglacial rivers, forming continuous supraglacial-proglacial catchments. Thereby, estimating proglacial river discharge is crucial for better understanding of northern Greenland hydrology and mass balance. We propose a method for estimating proglacial river discharge solely from space by combining Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), ArcticDEM, and Harmonized Landsat and Sentinel-2 (HLS) data. Firstly, we use the modified normalized difference water index to extract proglacial river water masks from 30 m HLS imagery time series and calculate river effective width (We). Secondly, we derive near-dry riverbed cross-sectional curves from ICESat-2 ATL06 data. Thirdly, we intersect proglacial river water masks with riverbed cross-sectional curves to calculate the mean depth, wetted perimeter, cross-sectional area, and hydraulic radius, and combine ArcticDEM to estimate the channel bed slope. Finally, with these hydraulic geometry estimates, we calculate proglacial discharge and analyze its uncertainty via error propagation. We apply this method to estimate the proglacial discharge (Qs) of the Denmark catchment (area ∼ 3254 km2) in northern Greenland during the 2020–2021 melt seasons and compare Qs with the surface meltwater runoff (Qm) simulated by two regional climate models (RCMs, including MARv3.12 and RACMO2.3p2), and validate the accuracy and spatial transferability of the method with in-situ proglacial discharge (Qin-situ) of the Watson River in southwestern Greenland. The results show that: (1) the satellite-estimated We and Qs exhibit significant seasonal variations, with the average We of 579 ± 371 m for 2020, 505 ± 394 m for 2021, and a maximum of 2040 m, and Qs has the average value of 207.6 ± 134.1 m3/s for 2020, 210.4 ± 243.2 m3/s for 2021, and a maximum of 1509.4 ± 190.3 m3/s; (2) the satellite-estimated Qs is positively correlated with the RCM-simulated Qm (R2 = 0.82 and 0.69 for MAR and RACMO, respectively), indicating that RCMs can reflect the overall seasonal variations of proglacial discharge reasonably well; (3) the RCM-simulated Qm is considerably higher than our satellite-estimated Qs, with the bias, RMSE, and RRMSE for MAR (RACMO) being 116.6 ± 5.9 m3/s (130.3 ± 5.9 m3/s), 174.7 ± 6.7 m3/s (208.9 ± 6.1 m3/s), and 83 ± 4 % (100 ± 4 %), respectively, and (4) our satellite-based method can be successfully applied to the Watson River in southwestern Greenland and the resultant Qs matches well with Qin-situ (RRMSE = 27 %). In conclusion, multi-temporal and multi-source satellite observations facilitate the estimation of proglacial river discharge and provide an approach to directly estimate GrIS ice surface meltwater runoff.

中文翻译：

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从太空监测格陵兰岛北部前冰河的流量


格陵兰岛北部冰盖 （GrIS） 产生的大量融水直接进入前冰河，形成连续的冰上-前冰期集水区。因此，估计冰期河流流量对于更好地了解格陵兰岛北部水文和物质平衡至关重要。我们提出了一种通过结合冰、云和陆地高程卫星 2 （ICESat-2）、ArcticDEM 以及协调 Landsat 和 Sentinel-2 （HLS） 数据来估计冰川前河流流量的方法。首先，我们使用修正的归一化差值水指数从 30 m HLS 影像时间序列中提取冰期前河流水掩模，并计算河流有效宽度 （We）。其次，我们从 ICESat-2 ATL06 数据中得出近干涸的河床横截面曲线。然后，我们将前冰期河流水面罩与河床横截面曲线相交，计算平均深度、润湿周长、横截面积和水力半径，并结合 ArcticDEM 估计河床坡度。最后，通过这些水力几何估计，我们计算了前冰川流量并通过误差传播分析了其不确定性。我们应用该方法估算 2020-2021 年融化季节格陵兰北部丹麦集水区（面积 ∼ 3254 km2）的冰川前流量 （Qs），并将 Qs 与两个区域气候模式（RCM，包括 MARv3.12 和 RACMO2.3p2）模拟的地表融水径流 （Qm） 进行比较，并验证了该方法的准确性和空间传递性格陵兰岛西南部沃森河的原位冰川排放 （Qin-situ）。 结果表明：（1）卫星估计的We和Qs表现出显著的季节变化，2020年的平均We为579 ± 371 m，2021年为505 ± 394 m，最大值为2040 m，Qs的平均值为207.6 ± 134.1 m3/s，2021年为210.4 ± 243.2 m3/s，最大值为1509.4 ± 190.3 m3/s;（2） 卫星估计的 Qs 与 RCM 模拟的 Qm 呈正相关（MAR 和 RACCO 的 R2 = 0.82 和 0.69），表明 RCM 可以很好地反映冰期流出的总体季节性变化;（3） RCM 模拟的 Qm 远高于我们的卫星估计的 Qs，偏差、RMSE 和 MAR 的 RRMSE （RACMO） 分别为 116.6 ± 5.9 m3/s （130.3 ± 5.9 m3/s）、174.7 ± 6.7 m3/s （208.9 ± 6.1 m3/s） 和 83 ± 4 % （100 ± 4 %），以及 （4） 我们基于卫星的方法可以成功应用于格陵兰岛西南部的沃森河，所得的 Qs 与原位 （RRMSE = 27%） 非常匹配。综上所述，多时相和多源卫星观测有助于估算冰期前河流流量，并为直接估算 GrIS 冰表融水径流提供了一种方法。