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This data set covers the Anaktuvuk River fire site and maps drained lake basins in this area as described by Jones et al (2015). The data set is derived from airborne Light Detection and Ranging (LiDAR) data acquired in 2009 and 2014. The classification of drained lake basins is based on digital terrain models (DTMs) created from the classified LiDAR data and using the a topographic position index (TPI). The TPI output was manually categorized relative to existing surficial geology maps and refined into the following terrain units: (1) drained lake basins, (2) yedoma uplands, (3) rocky uplands, (4) glaciated upland, (5) river floodplain and (6) tundra stream gulches. The drained lake basin class is the subject of this data set publication. Jones, B., Grosse, G., Arp, C. et al. Recent Arctic tundra fire initiates widespread thermokarst development. Sci Rep 5, 15865 (2015). https://doi.org/10.1038/srep15865
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This content will become publicly available on June 1, 2026
Impacts of geographic variability and geologic history on the distribution of post-settlement alluvium (PSA) across the upper Midwest, USA
Accelerated floodplain sedimentation related to agricultural development of uplands has produced postsettlement alluvium (PSA) along rivers throughout the upper Midwest, U.S.A. Landscape characteristics, surficial sediments, and soils in the region vary geographically in relation to differences in geologic history, yet the extent to which this geographic variability influences PSA accumulation remains unexplored. This study uses existing data to assess how non-dimensional PSA thickness varies with landscape characteristics, surficial sediments, soils and climate. Geographic variability is associated with three subregions: 1) areas glaciated during the Late Wisconsin Episode (LWE), 2) areas glaciated during Pre-Illinois and Illinois Episodes (PI&IE), and 3) the Paleozoic Plateau (PP), an area where evidence of Quaternary glaciation is highly localized and does not influence geomorphic characteristics of the landscape. These subregions differ significantly in average geomorphic characteristics, including mean watershed slope (WS), mean local relief (LR), fraction of non-contributing area (NCA), pre-settlement drainage density (DD), and mean normalized river steepness (KSN). Native vegetation type also differs systematically between the subregions, creating significant differences in the frequency of alfisols (Alfi) and molisols (Mol). Thickness of last glacial loess (Loess) also varies across the region, although not systematically between the subregions identified. Non-dimensional PSA thickness differs significantly among the subregions, increasing systematically with landscape age, reflecting faster upland erosion rates and stronger connectivity of uplands to river corridors in older landscapes relative to more recently glaciated landscapes. Nondimensional PSA thickness is significantly positively correlated with LR, KSN, WS, Loess, Alfi, and Mol and significantly negatively correlated with NCA. Non-visibly distinct PSA is present in some LWE watersheds characterized by significantly lower KSN and WS relative to other LWE watersheds in which PSA is visibly distinct. PSA thickness and visibility reflect catchment-wide landscape characteristics and watershed-scale river steepness, which emphasize the importance of geographic setting, geological history, and landscape geomorphic characteristics for understanding historical river sediment dynamics. Spatial variability in PSA thickness also serves as an indicator of river system sensitivity to land-use change, providing insight into the relative impact of humans on rivers within different geographic settings.
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- Award ID(s):
- 2012850
- PAR ID:
- 10630770
- Editor(s):
- NA
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- CATENA
- Volume:
- 254
- Issue:
- C
- ISSN:
- 0341-8162
- Page Range / eLocation ID:
- 108939
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This data set covers the Anaktuvuk River fire site and maps drained lake basins in this area as described by Jones et al (2015). The data set is derived from airborne Light Detection and Ranging (LiDAR) data acquired in 2009 and 2014. The classification of drained lake basins is based on digital terrain models (DTMs) created from the classified LiDAR data and using the a topographic position index (TPI). The TPI output was manually categorized relative to existing surficial geology maps and refined into the following terrain units: (1) drained lake basins, (2) yedoma uplands, (3) rocky uplands, (4) glaciated upland, (5) river floodplain and (6) tundra stream gulches. The drained lake basin class is the subject of this data set publication. Jones, B., Grosse, G., Arp, C. et al. Recent Arctic tundra fire initiates widespread thermokarst development. Sci Rep 5, 15865 (2015). https://doi.org/10.1038/srep15865more » « less
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