DOI: 10.5281/zenodo.10991228
title: Water sample analysis and satellite imagery of a thermo-erosion gully and its surroundings in Adventdalen, Svalbard.

description: Data description

This dataset is part of the supplemental information to the paper "Rapid Ice-Wedge Collapse and Permafrost Carbon Loss Triggered by Increased Snow Depth and Surface Runoff" by Parmentier et al. (2024). It includes the analysis of water quality in and around a thermo-erosion gully on the high-Arctic archipelago of Svalbard, and three satellite images that give an overview of the wider area around this gully in the context of a snow fence experiment (Cooper et al. 2011). More details are provided in Parmentier et al. (2024).

Background

Thicker snow cover in permafrost areas causes deeper active layers and thaw subsidence, which alter local hydrology and may amplify the loss of soil carbon. However, the potential for changes in snow cover and surface runoff to mobilize permafrost carbon remains poorly quantified. The data presented here is part of a study that showed that a snow fence experiment on High-Arctic Svalbard inadvertently led to surface subsidence through warming, and extensive downstream erosion due to increased surface runoff. Within a decade of artificially-raised snow depths, several ice wedges collapsed, forming a 50 m long and 1.5 m deep thermo-erosion gully in the landscape. We estimate that 1.1 to 3.3 tons C may have eroded, and that the gully is a hotspot for processing of mobilised aquatic carbon. Our study show that interactions among snow, runoff and permafrost thaw form an important driver of soil carbon loss.

Water samples

The following datafile includes the analysis of several water samples taken in and near a thermo-erosion gully on Svalbard on August 5th and 6th, 2017. These were analyzed for dissolved organic carbon (DOC), particulate organic carbon (POC), particulate nitrogen (PN) content, and stable carbon isotope ratios δ13C-DOC and δ13C-POC. In addition, temperature, pH, oxygen, and electrical conductivity were measured in the field on the day of sampling. This data is provided in the following Excel file that also includes the latitude and longitude for each sample point: 



Parmentier et al - 2024 - Water Sample Analysis.xlsx


 Sample analysis

A full description of the analysis is repeated here from the supplemental information in the accompanying publication (Parmentier et al. 2024). The water samples were filtered on the day of collection through a pre-combusted glass fiber filter with pore size of 0.7 µm (Whatman, Grade GF/F). After filtration, the filters were packed in aluminum foil and frozen for later analysis of the collected particulate matter. From the filtrate, three samples of ~50 ml were taken and immediately frozen for transport.

The filtered water samples were analyzed for their dissolved organic carbon (DOC) content and their stable carbon isotope ratio δ13C-DOC. This combined analysis was carried out at the labs of UCLouvain, Belgium with an Aurora 1030W TOC Carbon Analyzer, from OI Analytical, coupled to an IRMS (Thermo delta V Advantage). In the Aurora 1030W, the water samples were purged with H3PO4(phosphoric acid) to remove any dissolved inorganic carbon (DIC). Afterwards, Na2S2O8 (sodium persulfate) was added to the heated sample (97 °C) to oxidize any DOC to CO2. With N2 as the carrier gas, the CO2 was transferred to the analyzing units where the total concentration and δ13C-DOC of the CO2 were detected. The δ13C-DOC samples were calibrated against the certified standard IAEA-CH-6 (-10.449 ± 0.033 ‰VPDB) and an internal sucrose standard (-26.99 +/- 0.04 ‰). The DOC measurements were calibrated against a concentration range (n=8) of the same standards (Morana et al., 2015).

 The particulate matter retained on the filters was analyzed for particulate organic carbon (POC) and particulate nitrogen (PN) concentrations, as well as δ13C-POC. The glass fiber filters were subsampled and repeatedly acidified with HCl (1.5 M) in pre-combusted Ag capsules to remove carbonates. Analyses were performed at the Stable Isotope Facility of the University of California in Davis using an Elementar Vario EL Cube (Elementar Analysensysteme GmbH, Hanau, Germany) connected to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK). Isotope ratios of δ13C are reported relative to the international standard VPDB (Vienna PeeDee Belemnite).

Satellite imagery

To show the development of the thermo-erosion gully over time, we provide three high resolution satellite images from the Digital Globe constellation of satellites. The areal extent of these images covers the entire snow fence experiment in the valley of Adventdalen on Svalbard. They were acquired on August 5th, 2011, August 30th, 2013, and July 9th, 2015 by the WorldView-2, GeoEye-1 and WorldView-3 satellites, respectively. These images are provided as GeoTiffs – projected in the UTM 33X coordinate system:



SnoEco_2011AUG05_WV2_MUL_Pansharpened_bco_rcs_dobj.tif

SnoEco_2013AUG30_GE1_MUL_Pansharpened_bco_rcs_dobj.tif

SnoEco_2015JUL09_WV3_MUL_Pansharpened_bco_rcs_dobj.tif


Each of these files includes the following color bands: 



Band 1: Blue

Band 2: Green

Band 3: Red

Band 4: Near Infrared


In addition, the images are clipped to the following coordinate bounds (in UTM 33X):





xmin, xmax: 523740, 524825




ymin, ymax: 8677150, 8678100



For full details on these satellite products, we refer to DigitalGlobe/Maxar. 

Image processing

The satellite imagery was processed according to DigitalGlobe guidelines and calibration coefficient adjustment factors. The radiometrically corrected source images were first converted to top-of-the-atmosphere spectral radiance, and thereafter to top-of-the-atmosphere reflectance. Following this processing, each color band of the image was pansharpened (using Bicubic interpolation) with the RCS algorithm in the Orfeo ToolBox of QGIS 2.18 to increase the horizontal resolution to ~50 cm. To reduce haze effects, the images were further corrected through a dark object subtraction (bottom 1 percentile of the blue band) which was applied to each band separately. Subsequent negative values were set to zero. 

Acknowledgments

This research was funded by the Research Council of Norway (RCN; grant agreement 230970), and the FRAM - Terrestrial flagship (362255 and 642018). F.J.W.P. and S.W. received additional funding from the RCN (grant agreement 323945). The high-resolution satellite imagery comes courtesy of the DigitalGlobe Foundation. We thank UCLouvain and the University of California, Davis for assisting in the sample analysis. 

References

Cooper, E. J., Dullinger, S., & Semenchuk, P. (2011). Late snowmelt delays plant development and results in lower reproductive success in the High Arctic. Plant Science, 180(1), 157–167. https://doi.org/10.1016/j.plantsci.2010.09.005

Morana, C., Darchambeau, F., Roland, F. A. E., Borges, A. V., Muvundja, F., Kelemen, Z., et al. (2015). Biogeochemistry of a large and deep tropical lake (Lake Kivu, East Africa: insights from a stable isotope study covering an annual cycle. Biogeosciences, 12(16), 4953–4963. https://doi.org/10.5194/bg-12-4953-2015

Parmentier, F. J. W., Nilsen, L, Tømmervik, H., Meisel, O. H., Bröder, L., Vonk, J. E., Westermann, S., Semenchuk, P. R., Cooper, E. J., Rapid Ice-Wedge Collapse and Permafrost Carbon Loss Triggered by Increased Snow Depth and Surface Runoff, Geophysical Research Letters, In press