Dataset for: A comparison of supraglacial meltwater features throughout contrasting melt seasons: Southwest Greenland

Supraglacial Meltwater Features Dataset – Southwest Greenland (2018 & 2019) This dataset accompanies the publication:Glen, E., Leeson, A., Banwell, A. F., Maddalena, J., Corr, D., Atkins, O., Noël, B., and McMillan, M.A comparison of supraglacial meltwater features throughout contrasting melt seasons: Southwest Greenland.The Cryosphere, 19, 1047–1066, 2025. https://doi.org/10.5194/tc-19-1047-2025© Author(s) 2025. Licensed under CC BY 4.0. 1. About This Dataset This dataset provides spatial polygon shapefiles of supraglacial meltwater features across the Russell–Leverett Glacier catchment in southwest Greenland, captured during two contrasting melt seasons: 2018 – a relatively low melt year 2019 – a high melt year The mapped features include: Supraglacial lakes (large and small) Slush fields Supraglacial channels (rivers) This dataset enables spatiotemporal analysis of surface hydrology in a warming climate and highlights the often-overlooked role of small lakes and slush in supraglacial meltwater dynamics. 2. Folder Structure Each year contains subdirectories grouping shapefiles by feature type and satellite image date: Meltwater_Features_V3/ 2018/ Large_Lakes/ # Supraglacial lakes > 0.0495 km² Small_Lakes/ # Supraglacial lakes 0.0018–0.0495 km² Slush/ # Slush fields Rivers/ # Supraglacial channels 2019/ Large_Lakes/ Small_Lakes/ Slush/ Rivers/ 3. Shapefile Naming Convention Each shapefile follows the naming pattern: [SENSOR]_[YYYYMMDD]_[TYPE].shp For example:S2_20190824_Small_Lakes.shp refers to small lakes mapped from Sentinel-2 imagery acquired on 24 August 2019. SENSOR → S2 (Sentinel-2) or L8 (Landsat 8) YYYYMMDD → date of image acquisition TYPE → Large_Lakes, Small_Lakes, Slush, or Rivers 4. Satellite Data Overview Sensor Resolution Notes Sentinel-2 10 m Primary source (MSI sensor) Landsat 8 15–30 m Supplemented coverage (OLI sensor, pan-sharpened) Temporal coverage: 2018: 1 May – 30 September (~5-day revisit) 2019: 1 May – 30 September (~2-day revisit) 5. Attribute Information Each shapefile contains a minimal set of retained attributes specific to the meltwater feature type. Feature Type Attribute Units Description Large Lakes Area km² Polygon area Volume m³ Estimated water volume Small Lakes Area km² Polygon area Volume m³ Estimated water volume Slush Fields Area km² Polygon area Supraglacial Channels Area km² Polygon area of vectorised mask 6. Feature Classification Summary Feature Type Methodology Large Lakes NDWI/NDWI_ice thresholding with size filtering (> 0.0495 km²) Small Lakes NDWI/NDWI_ice thresholding with size filtering (0.0018–0.0495 km²) Channels Gabor filtering + connectivity metrics (after Yang et al., 2015) Slush Fields Adapted NDWI thresholds (Bell et al., 2017) with iterative tuning 7. Recommended Tools This dataset can be used with: GIS software: QGIS, ArcGIS Pro (recommended for visual inspection) Python: geopandas, shapely, matplotlib MATLAB: Compatible with FASTER lake tracking tools 8. Contact Emily [e-mail] Environment CentreLancaster University, UK 9. Citation If using this dataset, please cite both the paper and the data archive: PaperGlen, E., Leeson, A., Banwell, A. F., Maddalena, J., Corr, D., Atkins, O., Noël, B., and McMillan, M.:A comparison of supraglacial meltwater features throughout contrasting melt seasons: Southwest Greenland,The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, 2025. DatasetGlen, E. (2024): Supraglacial Meltwater Features in Southwest Greenland (2018–2019), Zenodo, https://doi.org/10.5281/zenodo.11645884