Abstract
The present study proposes a statistical downscaling approach to the assessment of the climate change impacts on the estimation of design storms and the resulting runoff characteristics for a given urban watershed. The proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The proposed method was tested using simulations from two GCMs under the A2 scenario (HadCM3A2 and CGCM2A2) and annual maximum (AM) precipitation data available at the Dorval Airport raingage in Quebec (Canada). It was found that AM precipitations and design storm rainfall intensities downscaled from the HadCM3A2 displayed small decreasing trends in the future, while those values estimated from the CGCM2A2 indicated large increasing trends. Similar variations were found for the estimated runoff characteristics for several selected urban watersheds of different shapes, area sizes and imperviousness levels. Results of this illustrative application have indicated the feasibility of the proposed downscaling method.
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