4.7 Article

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

Journal

WATER RESOURCES RESEARCH
Volume 54, Issue 1, Pages 132-149

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2017WR020471

Keywords

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Funding

  1. Los Alamos National Lab's LDRD program
  2. U.S. National Science Foundation (NSF) Science, Engineering and Education for Sustainability (SEES) Post-Doctoral Fellowship program [1216037]
  3. NSF [1462086]
  4. Divn Of Social and Economic Sciences [1462086] Funding Source: National Science Foundation

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The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

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