Proglacial river stage, discharge, and temperature datasets from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008–2011
- 1Department of Geography, Rutgers, The State University of New Jersey, 54 Joyce Kilmer Avenue, Piscataway, NJ 08854-8045, USA
- 2Department of Geography, University of California, Los Angeles, 1255 Bunche Hall, P.O. Box 951524, Los Angeles, CA 90095-1524, USA
- 3Department of Geography, University of Utah, 260 S. Central Campus Dr., Salt Lake City, UT 84112, USA
- 4Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210-1361, USA
- 5Environment and Natural Resources Institute, University of Alaska Anchorage, 3211 Providence Drive, Anchorage, AK 99508, USA
Abstract. 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.