Contribution of environmental forcings to US runoff changes for the period 1950-2010

Whitney L. Forbes, Jiafu Mao, Mingzhou Jin, Shih Chieh Kao, Wenting Fu, Xiaoying Shi, Daniel M. Riccuito, Peter E. Thornton, Aurélien Ribes, Yutao Wang, Shilong Piao, Tianbao Zhao, Christopher R. Schwalm, Forrest M. Hoffman, Joshua B. Fisher, Akihiko Ito, Ben Poulter, Yuanyuan Fang, Hanqin Tian, Atul K. JainDaniel J. Hayes

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive), winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. We also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.

Original languageEnglish
Article number054023
JournalEnvironmental Research Letters
Volume13
Issue number5
DOIs
StatePublished - May 2018

Funding

This work is supported by the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA) project funded through the Terrestrial Ecosystem Science Program, partially supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA) project funded through the Regional and Global Climate Modeling Program, and partially supported by the Energy Exascale Earth System Model (E3SM) project funded through the Earth System Modeling Program, in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the US Department of Energy Office of Science. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725. JBF contributed to this from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. JBF was supported in part by NASA SUSMAP, INCA, IDS, and CARBON programs. Atul K Jain is funded by the US National Science Foundation (NSF-AGS-12-43071).

Keywords

  • MsTMIP
  • US runoff
  • detection and attribution

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