Proglacial river stage, discharge, and temperature datasets from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008–2011

Pressing scientific questions concerning the Greenland ice sheet's climatic sensitivity, hydrology, and contributions to current and future sea level rise require hydrological datasets to resolve. While direct observations of ice sheet meltwater losses can be obtained in terrestrial rivers drai...

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Bibliographic Details
Published in:Earth System Science Data
Main Authors: A. K. Rennermalm, L. C. Smith, V. W. Chu, R. R. Forster, J. E. Box, B. Hagedorn
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2012
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Online Access:https://doi.org/10.5194/essd-4-1-2012
https://doaj.org/article/16d264b24b224dc68c618dff0fa6ec4e
Description
Summary:Pressing scientific questions concerning the Greenland ice sheet's climatic sensitivity, hydrology, and contributions to current and future sea level rise require hydrological datasets to resolve. While direct observations of ice sheet meltwater losses can be obtained in terrestrial rivers draining the ice sheet and from lake levels, few such datasets exist. We present a new hydrologic dataset from previously unmonitored sites in the vicinity of Kangerlussuaq, Southwest Greenland. This dataset contains measurements of river stage and discharge for three sites along the Akuliarusiarsuup Kuua (Watson) River's northern tributary, with 30 min temporal resolution between June 2008 and July 2011. Additional data of water temperature, air pressure, and lake stage are also provided. Flow velocity and depth measurements were collected at sites with incised bedrock or structurally reinforced channels to maximize data quality. However, like most proglacial rivers, high turbulence and bedload transport introduce considerable uncertainty to the derived discharge estimates. Eleven propagating error sources were quantified, and reveal that largest uncertainties are associated with flow depth observations. Mean discharge uncertainties (approximately the 68% confidence interval) are two to four times larger (±19% to ±43%) than previously published estimates for Greenland rivers. Despite these uncertainties, this dataset offers a rare collection of direct measurements of ice sheet runoff to the global ocean and is freely available for scientific use at http://dx.doi.org/10.1594/PANGAEA.762818 .