Climate downscaling using regional regression and physically based watershed models
A typical approach to projecting climate change impacts on water resources systems involves statistically downscaling general circulation model (GCM) or regional climate model (RCM) outputs and forcing a watershed model to evaluate hydrologic impacts. Challenges associated with this approach include properly calibrating and verifying the watershed model and maintaining a consistent energy budget between the two models. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to directly predict selected streamflow quantiles from regional regression equations that include physical basin characteristics as well as meteorological variables output by climate models (Fennessey 2011). We compare the two approaches for Maumee River basin in Ohio, Indiana, and Michigan, using readily available downscaled outputs from the Coupled Model Intercomparison Project (CMIP3) as inputs to the Large Basin Runoff Model (LBRM) and Ordinary Least Square (OLS) regional regression models. © ASCE 2012.
World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress
Climate downscaling using regional regression and physically based watershed models.
World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress, 1806-1815.
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