SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Assessment of climate change impacts on extreme high and low flows: An improved bottom-up approach 
Authors:Alodah, A. and O. Seidou 
Volume (Issue):11(6) 
Article ID:1236 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate change 
Secondary Application Category:weather generator effects/processes 
Watershed Description:4,000 km^2 South Nation River, located in southeast Ontario, Canada. 
Calibration Summary: 
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General Comments: 
Abstract:A quantitative assessment of the likelihood of all possible future states is lacking in both the traditional top-down and the alternative bottom-up approaches to the assessment of climate change impacts. The issue is tackled herein by generating a large number of representative climate projections using weather generators calibrated with the outputs of regional climate models. A case study was performed on the South Nation River Watershed located in Eastern Ontario, Canada, using climate projections generated by four climate models and forced with medium- to high-emission scenarios (RCP4.5 and RCP8.5) for the future 30-year period (2071–2100). These raw projections were corrected using two downscaling techniques. Large ensembles of future series were created by perturbing downscaled data with a stochastic weather generator, then used as inputs to a hydrological model that was calibrated using observed data. Risk indices calculated with the simulated streamflow data were converted into probability distributions using Kernel Density Estimations. The results are dimensional joint probability distributions of risk-relevant indices that provide estimates of the likelihood of unwanted events under a given watershed configuration and management policy. The proposed approach offers a more complete vision of the impacts of climate change and opens the door to a more objective assessment of adaptation strategies. 
Keywords:hydrological risk assessment; extreme hydrologic events; climate change impacts; downscaling; uncertainty; ensembles; water resource systems