Nonlinear scaling of climate change impacts in headwater catchments

Lauren Foster, Ohio Supercomputer Center

Usage Details

One in 10 Americans source water from the Colorado River, and 85% of that streamflow is gnerated in Rocky Mountain headwater catchments, which have been shown to be especially sensitive to a changing climate. Despite their importance, global climate models and regional hydrologic models are known to perform poorly in these regions, casting doubt on water supply forecasts for the next century. Here we develop relationships across scales to better model climate change impacts on headwater hydrology. First, we describe a new method to parameterize high and hyper-resolution models where traditional calibrations are infeasible. Second, we demonstrate that high resolution simulations show more sensitivity to climate changes, indicating that the coarse resolution models used now may over predict future water supply. Finally we compare extensive remote-sensing, point, and field observations to modeling predictions of snowpack, allowing for cross validation across spatial and temporal scales.