Water sample analysis and satellite imagery of a thermo-erosion gully and its surroundings in Adventdalen, Svalbard.

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数据集说明 本数据集隶属于Parmentier等人2024年发表的论文《Rapid Ice-Wedge Collapse and Permafrost Carbon Loss Triggered by Increased Snow Depth and Surface Runoff》（快速冰楔崩塌与雪深及地表径流增加引发的冻土（permafrost）碳流失）的补充材料。数据集包含对斯瓦尔巴（Svalbard）高北极群岛一处热侵蚀沟壑（thermo-erosion gully）及其周边水域的水质分析，以及三张卫星影像，用于展示该沟壑周边区域在雪栅栏试验（Cooper et al. 2011）背景下的整体概况。更多细节可参见Parmentier等人2024年的研究。 研究背景 冻土区积雪厚度增加会导致活动层加深及冻融沉陷，改变局地水文状况，并可能加剧土壤碳流失。然而，积雪覆盖与地表径流变化对冻土碳活化的潜在影响仍缺乏定量研究。本数据集对应的研究表明，在高北极斯瓦尔巴开展的雪栅栏试验意外引发了升温驱动的地表沉陷，以及因地表径流增加导致的大规模下游侵蚀。在人工提升积雪深度后的十年内，多处冰楔发生崩塌，在地表形成了一条长50米、深1.5米的热侵蚀沟壑。经估算，该沟壑侵蚀流失的碳量可达1.1至3.3吨，同时也是活化水生碳处理的热点区域。本研究证实，积雪、径流与冻土冻融之间的相互作用是土壤碳流失的重要驱动因素。 水样分析 以下数据文件包含2017年8月5日至6日在斯瓦尔巴一处热侵蚀沟壑及其周边采集的多组水样的分析结果。分析指标包括溶解有机碳（dissolved organic carbon, DOC）、颗粒有机碳（particulate organic carbon, POC）、颗粒氮（particulate nitrogen, PN）含量，以及稳定碳同位素比值δ¹³C-DOC与δ¹³C-POC。此外，采样当日在野外同步测定了水样的温度、pH值、溶解氧及电导率。相关数据存储于以下Excel文件中，该文件同时包含各采样点的经纬度信息： Parmentier et al - 2024 - Water Sample Analysis.xlsx 样品分析方法 本部分完整重复了关联论文（Parmentier et al. 2024）补充材料中的分析流程。水样采集当日即通过孔径0.7μm的预灼烧玻璃纤维滤膜（Whatman GF/F级）进行过滤。过滤完成后，将滤膜用铝箔包裹并冷冻保存，用于后续颗粒物分析。从滤液中采集约50ml的三份样品，立即冷冻以待运输。 过滤后的水样将用于溶解有机碳（DOC）含量与稳定碳同位素比值δ¹³C-DOC的分析。该联合分析在比利时鲁汶大学（UCLouvain）实验室完成，使用OI Analytical公司生产的Aurora 1030W总有机碳分析仪，与Thermo delta V Advantage型同位素比值质谱仪（isotope ratio mass spectrometer, IRMS）联用。在Aurora 1030W中，先用磷酸（H₃PO₄）吹扫水样以去除溶解无机碳（dissolved inorganic carbon, DIC），随后向加热至97℃的样品中加入过硫酸钠（Na₂S₂O₈），将所有DOC氧化为二氧化碳（CO₂）。以氮气（N₂）作为载气，将CO₂传输至分析单元，检测CO₂的总浓度与δ¹³C-DOC。δ¹³C-DOC的校准采用标准物质IAEA-CH-6（δ¹³C = -10.449 ± 0.033 ‰ VPDB）与内部蔗糖标准（δ¹³C = -26.99 ± 0.04 ‰）。DOC浓度的校准采用浓度梯度（n=8）的同一套标准物质（Morana et al., 2015）。 滤膜上截留的颗粒物将用于分析颗粒有机碳（POC）、颗粒氮（PN）浓度以及δ¹³C-POC。将玻璃纤维滤膜分装至预灼烧的银胶囊中，反复用1.5M盐酸（HCl）酸化以去除碳酸盐。分析工作在加州大学戴维斯分校稳定同位素实验室完成，使用Elementar Vario EL Cube元素分析仪（德国Elementar分析系统公司）与PDZ Europa 20-20型同位素比值质谱仪（英国Sercon有限公司，柴郡）联用完成。δ¹³C同位素比值均相对于国际标准VPDB（维也纳佩德北箭石，Vienna PeeDee Belemnite）报告。 卫星影像 为展示热侵蚀沟壑随时间的演化过程，本数据集提供三张来自Digital Globe卫星星座的高分辨率影像。影像覆盖范围包含斯瓦尔巴Adventdalen山谷内的全部雪栅栏试验区域。三张影像分别由WorldView-2、GeoEye-1与WorldView-3卫星于2011年8月5日、2013年8月30日及2015年7月9日采集。影像以GeoTIFF格式提供，投影坐标系为UTM 33X： 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 每个文件包含以下波段： 波段1：蓝光 波段2：绿光 波段3：红光 波段4：近红外 此外，影像被裁剪至以下UTM 33X坐标系范围： xmin, xmax: 523740, 524825 ymin, ymax: 8677150, 8678100 关于这些卫星产品的完整细节，请参考DigitalGlobe/Maxar官方说明。 影像处理流程 卫星影像按照DigitalGlobe的指南与校准系数调整因子进行处理。首先将经过辐射校正的原始影像转换为大气层顶光谱辐亮度，随后进一步转换为大气层顶反射率。完成上述处理后，使用QGIS 2.18的Orfeo工具箱中的RCS算法，结合双三次插值对影像的各色彩波段进行全色锐化（pansharpened）处理，将空间分辨率提升至约50cm。为减少雾霾影响，通过暗物体减法（对蓝色波段取最低1%分位数作为暗基准）对每个波段分别进行校正，随后将处理后出现的负值全部置零。 致谢 本研究由挪威研究理事会（Research Council of Norway, RCN；资助协议号230970）与FRAM陆地旗舰项目（资助协议号362255与642018）资助。F.J.W.P.与S.W.额外获得了RCN的资助（资助协议号323945）。高分辨率卫星影像由DigitalGlobe基金会提供。感谢比利时鲁汶大学与加州大学戴维斯分校协助完成样品分析工作。 参考文献 1. Cooper, E. J., Dullinger, S., & Semenchuk, P. (2011). 高北极地区晚融雪延迟植物发育并降低繁殖成功率. 植物科学, 180(1), 157–167. https://doi.org/10.1016/j.plantsci.2010.09.005 2. Morana, C., Darchambeau, F., Roland, F. A. E., Borges, A. V., Muvundja, F., Kelemen, Z., et al. (2015). 大型深水热带湖泊的生物地球化学特征——基于年度循环的稳定同位素研究. 生物地球科学, 12(16), 4953–4963. https://doi.org/10.5194/bg-12-4953-2015 3. Parmentier, F. J. W., Nilsen, L, Tømmervik, H., Meisel, O. H., Bröder, L., Vonk, J. E., Westermann, S., Semenchuk, P. R., Cooper, E. J. 快速冰楔崩塌与雪深及地表径流增加引发的冻土碳流失. 地球物理研究通讯, 已录用.