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Climate Change and Hydrological Response in the Trans-State Oologah Lake Watershed–Evaluating Dynamically Downscaled NARCCAP and Statistically Downscaled CMIP3 Simulations with VIC Model

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Abstract

Statistically and dynamically downscaled climate projections are the two important data sources for evaluation of climate change and its impact on water availability, water quality and ecosystems. Though bias correction helps to adjust the climate model output to behave more similarly to observations, the hydrologic response still can be biased. This study uses Variable Infiltration Capacity (VIC) model to evaluate the hydrologic response of the trans-state Oologah Lake watershed to climate change by using both statistically and dynamically downscaled multiple climate projections. Simulated historical and projected climate data from the North American Regional Climate Change Assessment Program (NARCCAP) and Bias-Corrected and Spatially Downscaled–Coupled Model Intercomparison Phase 3 (BCSD-CMIP3) forced the hydrologic model. In addition, different river network upscaling methods are also compared for a higher VIC model performance. Evaluation and comparison shows the following the results. (1) From the hydrologic point of view, the dynamically downscaled NARCCAP projection performed better, most likely in capturing a larger portion of mesoscale-driven convective rainfall than the statistically downscaled CMIP3 projections; hence, the VIC model generated higher seasonal streamflow amplitudes that are closer to observations. Additionally, the statistically downscaled GCMs are less likely to capture the hydrological simulation probably due to missing integration of climate variables of wind, solar radiation and others, even though their precipitation and temperature are bias corrected to be more favorably than the NARCCAP simulations. (2) Future water availability (precipitation, runoff, and baseflow) in the watershed would increase annually by 3–4 %, suggested by both NARCCAP and BCSD-CMIP3. Temperature increases (2.5–3 °C) are much more consistent between the two types of climate projections both seasonally and annually. However, NARCCAP suggested 2–3 times higher seasonal variability of precipitation and other water fluxes than the BCSD-CMIP3 models. (3) The hydrologic performance could be used as a potential metric to comparatively differentiate climate models, since the land surface and atmosphere processes are considered integrally.

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Acknowledgments

This research was funded by the Responses to Climate Change program, U.S. Army Corps of Engineers Institute for Water Resources and the South Central Climate Science Center, U.S. Geological Survey. We wish to thank the North American Regional Climate Change Assessment Program (NARCCAP) for providing the data used in this paper. “Bias Corrected and Downscaled WCRP CMIP3 Climate Projections” archive at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/.

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Authors and Affiliations

  1. School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA

    Lei Qiao, Yang Hong & Sheng Chen

  2. Advanced Radar Research Center, University of Oklahoma, Norman, OK, USA

    Lei Qiao, Yang Hong & Sheng Chen

  3. Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK, USA

    Lei Qiao

  4. Oklahoma Climatological Survey and Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA

    Renee McPherson & Mark Shafer

  5. U.S. Army Corps of Engineers, Tulsa District, OK, USA

    David Gade, David Williams & Douglas Lilly

  6. Department of Hydraulic Engineering, Tsinghua University, Beijing, China

    Yang Hong

  7. Hydrometeorology and Remote Sensing Lab (hydro.ou.edu), National Weather Center Advanced Radar Research Center Suite 4610, 120 David L. Boren Blvd., Norman, OK, 73072-7303, USA

    Yang Hong

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  1. Lei Qiao
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Correspondence to Yang Hong.

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Qiao, L., Hong, Y., McPherson, R. et al. Climate Change and Hydrological Response in the Trans-State Oologah Lake Watershed–Evaluating Dynamically Downscaled NARCCAP and Statistically Downscaled CMIP3 Simulations with VIC Model. Water Resour Manage 28, 3291–3305 (2014). https://doi.org/10.1007/s11269-014-0678-z

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