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Keywords:

  • Bayesian statistics;
  • climate impacts;
  • computational hydrology;
  • hydrologic scaling;
  • modeling;
  • uncertainty assessment

For regional managers trying to make long-term investments in hydrological infrastructure, having a reliable forecast of how their watershed may evolve in a changing climate is a significant boon. To make a projection of the regional effects of climate change, researchers often use the calculations of a global general circulation model to determine a set of initial conditions—for either historical or future climes—which can then be used to run a regional hydrological model. Using this approach, uncertainty can arise from a number of sources, including from the difficulties of projecting climate change, from errors within either the general circulation model or the hydrological model, from uncertainty surrounding modeled parameterizations, or from data sampling errors.