Record Russian river discharge in 2007 and the limits of analysis

• Main Authors: Shiklomanov, Alexander I., Lammers, Richard B.
• Format: Text
• Language: unknown
• Published: University of New Hampshire Scholars' Repository 2009
• Subjects: Arctic; Arctic Ocean; Yenisey; Climate change; Sea ice
• Online Access: https://scholars.unh.edu/faculty_pubs/320; https://scholars.unh.edu/cgi/viewcontent.cgi?article=1319&context=faculty_pubs

The Arctic water cycle has experienced an unprecedented degree of change which may have planetary-scale impacts. The year 2007 in particular not only was unique in terms of minimum sea ice extent in the Arctic Ocean but also was a record breaking year for Eurasian river inflow to the Arctic Ocean. Over the observational period from 1936 to 2006, the mean annual river discharge for the six largest Russian rivers was 1796 km3 y−1, with the previous record high being 2080 km3 y−1, in 2002. The year 2007 showed a massive flux of fresh water from these six drainage basins of 2254 km3 y−1. We investigated the hydroclimatological conditions for such extreme river discharge and found that while that year's flow was unusually high, the overall spatial patterns were consistent with the hydroclimatic trends since 1980, indicating that 2007 was not an aberration but a part of the general trend. We wanted to extend our hydroclimatological analysis of river discharge anomalies to seasonal and monthly time steps; however, there were limits to such analyses due to the direct human impact on the river systems. Using reconstructions of the naturalized hydrographs over the Yenisey basin we defined the limits to analysis due to the effect of reservoirs on river discharge. For annual time steps the trends are less impacted by dam construction, whereas for seasonal and monthly time steps these data are confounded by the two sources of change, and the climate change signals were overwhelmed by the human-induced river impoundments. We offer two solutions to this problem; first, we recommend wider use of algorithms to 'naturalize' the river discharge data and, second, we suggest the identification of a network of existing and stable river monitoring sites to be used for climate change analysis.