Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies
Short-Term Variability in Alaska Ice-Marginal Lake Area: Implications for Long-Term Studies
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DOI：
10.3390/rs13193955
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发表时间：
2021-10
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通讯作者：
Anton M. Hengst;W. Armstrong;B. Rick;D. McGrath
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作者：
Anton M. Hengst;W. Armstrong;B. Rick;D. McGrath
与冰川直接接触的湖泊（冰缘湖）遍布高山和极地景观。许多研究在几十年的时间尺度上利用幕式~年度图像或多年马赛克来表征冰缘湖的行为。然而，冰缘湖是动态特征，其面积和体积的短期（即日-年）变化叠加在长期趋势上。通过混叠，这种短期变率可能导致对湖泊变化的错误长期估计。我们在谷歌Earth Engine中开发并实施了一个自动化工作流程，使用Landsat 8图像量化2013年至2019年阿拉斯加中南部冰边缘湖泊的月度行为。我们采用了一个有监督的马氏最小距离土地覆盖分类器，该分类器包含三个数据集，以最大限度地提高分类器的性能：短波红外图像、归一化植被指数（NDVI）和空间滤波全色反射率。我们在次年时间尺度上观察了有物理意义的冰缘湖面积变化，发现冰缘湖的面积波动中值为其平均面积的10.8%。中位信号（湖泊缓慢增长）与噪声（物理上有意义的短期面积变率）之比为1.5:1，表明短期变率占中位冰缘湖泊观测面积变化的约33%。冰缘湖泊和非冰川湖泊的短期面积变化幅度相似，这表明观测到的变化并非源于冰川。这些数据为解释多年代际研究中观察到的行为提供了新的背景，并鼓励在长期研究中关注冰边缘湖泊的次年行为。
Lakes in direct contact with glaciers (ice-marginal lakes) are found across alpine and polar landscapes. Many studies characterize ice-marginal lake behavior over multi-decadal timescales using either episodic ~annual images or multi-year mosaics. However, ice-marginal lakes are dynamic features that experience short-term (i.e., day to year) variations in area and volume superimposed on longer-term trends. Through aliasing, this short-term variability could result in erroneous long-term estimates of lake change. We develop and implement an automated workflow in Google Earth Engine to quantify monthly behavior of ice-marginal lakes between 2013 and 2019 across south-central Alaska using Landsat 8 imagery. We employ a supervised Mahalanobis minimum-distance land cover classifier incorporating three datasets found to maximize classifier performance: shortwave infrared imagery, the normalized difference vegetation index (NDVI), and spatially filtered panchromatic reflectance. We observe physically-meaningful ice-marginal lake area variance on sub-annual timescales, with the median area fluctuation of an ice-marginal lake found to be 10.8% of its average area. The median signal (slow lake growth) to noise (physically-meaningful short-term area variability) ratio is 1.5:1, indicating that short-term variability is responsible for ~33% of observed area change in the median ice-marginal lake. The magnitude of short-term area variability is similar for ice-marginal and nonglacial lakes, suggesting that the cause of observed variations is not of glacial origin. These data provide a new context for interpreting behaviors observed in multi-decadal studies and encourage attention to sub-annual behavior of ice-marginal lakes even in long-term studies.