HR: 0800h
AN: B41G-0401 Poster
TI: The impact of climate, CO2, nitrogen deposition and land use change on contemporary global river flow
AU: *Shi, X
EM: shix@ornl.gov
AF: ORNL, Oak Ridge, TN, USA
AU: Mao, J
EM: maoj@ornl.gov
AF: ORNL, Oak Ridge, TN, USA
AU: Thornton, P E
EM: thorntonpe@ornl.gov
AF: ORNL, Oak Ridge, TN, USA
AU: Hoffman, F M
EM: forrest@climatemodeling.org
AF: ORNL, Oak Ridge, TN, USA
AB: We investigated how climate change, rising atmospheric CO2 concentration, nitrogen deposition, and land use change influenced the continental river flow during 1948-2004 using CLM-CN model with coupled river transfer model (RTM), global river routing scheme. At the global scale, the total change trend in river flow is -0.0123 0.00444 km3 yr-1, and climate change, atmospheric CO2, nitrogen deposition, and land cover change account for -0.0174 0.00439 km3 yr-1, 0.0064 0.00015 km3 yr-1, -0.0006 0.00002 km3 yr-1, and -0.0003 0.00009 km3 yr-1 of the change trend in river flow, respectively. The results indicate that climate change likely functions as dominant controller, then atmospheric CO2, nitrogen deposition and land use change in turn for the global river flow change trend during the study period. However, the relative role of each driving factor is not constant across global continent. The change trend in river flow in Amazon River basin region is primarily explained by atmospheric CO2, and land use change plays more important role than nitrogen deposition for Yangtze and Danube river basin regions. To better understand the change trends of river flow, it is not only needed to take into account the climate change, but also needed to consider atmospheric composition, carbon-nitrogen interaction and land cover change, particularly for regional scales.
DE: [0414] BIOGEOSCIENCES / Biogeochemical cycles, processes, and modeling
SC: Biogeosciences (B)
MN: 2010 Fall Meeting

Acknowledgements
Research partially sponsored by the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research (OBER), U.S. Department of Energy Office of Science (SC). This research used resources of the National Center for Computational Science (NCCS) at Oak Ridge National Laboratory (ORNL) which is managed by UT-Battelle, LLC, for the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.