Abstract
Seepage of geological methane through sediments of Arctic lakes might contribute conceivably to the atmospheric methane budget. However, the abundance and precise locations of such seeps are poorly quantified. For Lake Neyto, one of the largest lakes on the Yamal Peninsula in Northwestern Siberia, temporally expanding regions of anomalously low backscatter in C-band SAR imagery acquired in late winter and spring have been suggested to be related to seepage of methane from hydrocarbon reservoirs. However, this hypothesis has not been verified using in-situ observations so far. Similar anomalies have also been identified for other lakes on Yamal, but it is still uncertain whether or how many of them are related to methane seepage. This study aimed to document similar lake ice backscatter anomalies on a regional scale over four study regions (the Yamal Peninsula and Tazovskiy Peninsulas; the Lena Delta in Russia; the National Petroleum Reserve Alaska) during different years using a time series based approach on Google Earth Engine (GEE) that quantifies changes of σ0 from the Sentinel-1 C-band SAR sensor over time. An algorithm for assessing the coverage that takes the number of acquisitions and maximum time between acquisitions into account is presented, and differences between the main operating modes of Sentinel-1 are evaluated. Results show that better coverage can be achieved in extra wide swath (EW) mode, but interferometric wide swath (IW) mode data could be useful for smaller study areas and to substantiate EW results. A classification of anomalies on Lake Neyto from EW Δσ0 images derived from GEE showed good agreement with the classification presented in a previous study. Automatic threshold-based per-lake counting of years where anomalies occurred was tested, but a number of issues related to this approach were identified. For example, effects of late grounding of the ice and anomalies potentially related to methane emissions could not be separated efficiently. Visualizations of Δσ0 images likely reflect the temporal expansions of anomalies and are expected to be particularly useful for identifying target areas for future field-based research. Characteristic anomalies that clearly resemble the ones observed for Lake Neyto could be identified solely visually in the Yamal and Tazovskiy study regions. All data and algorithms produced in the framework of this study are openly provided to the scientific community for future studies and might potentially aid our understanding of geological lake seepage upon the progression of related field-based studies and corresponding evaluations of formation hypotheses.
Highlights
This article is an open access articleMillions of lakes cover vast areas of the Arctic permafrost region [1] and are critical components of the global carbon cycle [2,3]
Geologic methane accumulated in sub-surface hydrocarbon reservoirs, previously sealed by permafrost or glaciers acting as a cryosphere cap, can seep into the atmosphere through lake sediments and the water column [2]
We provided the first regional accounts for lake ice C-band Satellite-based “dar” (SAR) backscatter anomalies using a time series analysis-based algorithm on Sentinel-1 data on Google Earth Engine (GEE)
Summary
This article is an open access articleMillions of lakes cover vast areas of the Arctic permafrost region [1] and are critical components of the global carbon cycle [2,3]. (Pointner et al, accepted) the location of a pixel considered to be regular floating lake ice—green dot; and the location of a pixel considered to be ground-fast lake ice—cyan dot The slope of the example for ground-fast lake ice in Figure 7b indicates a significant increase of backscatter over time, but such an increase was only observed in 2016 and was potentially related to the period of melt that led to the exclusion of several acquisitions (the backscatter after the gap in the time series in Figure 7b is higher than before). Slopes similar to floating lake ice were observed [51]
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