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The Effects of Downscaling Method on the Variability of Simulated Watershed Response to Climate Change in Five U.S. Basins

D. M. NoverScience and Technology Policy Fellow, American Association for the Advancement of Science, U.S. Agency for International Development, Ghana, West Africa

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J. W. WittOak Ridge Institution for Science and Education Fellow, Office of Research and Development, U.S. Environmental Protection Agency, Washington, D.C.

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J. B. ButcherTetra Tech, Inc., Research Triangle Park, North Carolina

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T. E. JohnsonOffice of Research and Development, U.S. Environmental Protection Agency, Washington, D.C.

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C. P. WeaverOffice of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina

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Print Publication:
01 Apr 2016
DOI:
https://doi.org/10.1175/EI-D-15-0024.1
Page(s):
1–27
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Abstract

Simulations of future climate change impacts on water resources are subject to multiple and cascading uncertainties associated with different modeling and methodological choices. A key facet of this uncertainty is the coarse spatial resolution of GCM output compared to the finer-resolution information needed by water managers. To address this issue, it is now common practice to apply spatial downscaling techniques, using either higher-resolution regional climate models or statistical approaches applied to GCM output, to develop finer-resolution information. Downscaling, however, can also introduce its own uncertainties into water resources’ impact assessments. This study uses watershed simulations in five U.S. basins to quantify the sources of variability in streamflow, nitrogen, phosphorus, and sediment loads associated with the underlying GCM compared to the choice of downscaling method (both statistically and dynamically downscaled GCM output). This study also assesses the specific, incremental effects of downscaling by comparing watershed simulations based on downscaled and nondownscaled GCM model output. Results show that the underlying GCM and the downscaling method each contribute to the variability of simulated watershed responses. The relative contribution of GCM and downscaling method to the variability of simulated responses varies by watershed and season of the year. Results illustrate the potential implications of one key methodological choice in conducting climate change impact assessments for water—the selection of downscaled climate change information.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/EI-D-15-0024.s1.

Corresponding author address: D. M. Nover, AAAS Science and Technology Policy Fellow, U.S. Agency for International Development, Ghana, West Africa. E-mail address: dmnover@gmail.com

Abstract

Simulations of future climate change impacts on water resources are subject to multiple and cascading uncertainties associated with different modeling and methodological choices. A key facet of this uncertainty is the coarse spatial resolution of GCM output compared to the finer-resolution information needed by water managers. To address this issue, it is now common practice to apply spatial downscaling techniques, using either higher-resolution regional climate models or statistical approaches applied to GCM output, to develop finer-resolution information. Downscaling, however, can also introduce its own uncertainties into water resources’ impact assessments. This study uses watershed simulations in five U.S. basins to quantify the sources of variability in streamflow, nitrogen, phosphorus, and sediment loads associated with the underlying GCM compared to the choice of downscaling method (both statistically and dynamically downscaled GCM output). This study also assesses the specific, incremental effects of downscaling by comparing watershed simulations based on downscaled and nondownscaled GCM model output. Results show that the underlying GCM and the downscaling method each contribute to the variability of simulated watershed responses. The relative contribution of GCM and downscaling method to the variability of simulated responses varies by watershed and season of the year. Results illustrate the potential implications of one key methodological choice in conducting climate change impact assessments for water—the selection of downscaled climate change information.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/EI-D-15-0024.s1.

Corresponding author address: D. M. Nover, AAAS Science and Technology Policy Fellow, U.S. Agency for International Development, Ghana, West Africa. E-mail address: dmnover@gmail.com

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