Dissolved-gas concentrations, physical and chemical properties of 41 ponds as well as key meteorological parameters in the Lena River Delta, Siberia

• Main Authors: Rehder, Zoé, Zaplavnova, Anna, Kutzbach, Lars
• Format: Dataset
• Language: English
• Published: PANGAEA 2020
• Subjects: 3D-UA; 3D ultrasonic anemometer; Arctic peatlands; Area; AWI Arctic Land Expedition; Calculated based on geographical coordinates; Campbell Scientific NR-LITE2 Net Radiometer; Carbon; organic; Carbon dioxide; dissolved; CLICCS; Cluster of Excellence: Climate; Climatic Change; and Society; Date; DEPTH; water; Event label; Handheld GPS; Garmin; Headspace gas chromatography; Lake/Pond; LATITUDE; Lena 2019; Lena-2019_1; Lena-2019_10; Lena-2019_11; Lena-2019_12; Lena-2019_13; Lena-2019_14; Lena-2019_15; Lena-2019_16; Lena-2019_17; Lena-2019_19; Lena-2019_2; Lena-2019_20; Lena-2019_21; Lena-2019_22; Lena-2019_24; Lena-2019_25; Lena-2019_26; Lena-2019_27; Lena-2019_28; Lena-2019_29; Lena-2019_3; Lena-2019_30; Lena-2019_31; Lena-2019_32; Lena-2019_33; lena river; Tundra; Siberia
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.922399; https://doi.org/10.1594/PANGAEA.922399

Ponds emit more methane per area than larger lakes. However, methane concentrations in and methane emissions from ponds show more spatial variability than larger waterbodies. A better understanding of this variability is needed to improve upscaling estimates of freshwater methane emissions. To this end, we studied 41 polygonal-tundra ponds on the islands Samoylov and Kurungakh in the Lena River Delta, northeast Siberia. The ponds fall into three geomorphological types with distinct differences in drivers of methane concentrations: polygonal-center ponds, ice-wedge ponds and larger merged-polygonal ponds. We collected water samples at different locations and depths in each pond and determined methane concentrations using gas chromatography. Additionally, we collected information on the geomorphology, vegetation cover as well as on key physical and chemical properties of the ponds and combined them with meteorological data to identify drivers of surface-water methane concentrations.