In the companion paper, Seidou et al. ( 2011 , submitted) have shown that when adequate meteorological data are available to calibrate rainfall-runoff models, using a non-stationary GEV model with the simulated flows can provide a better description of flood peaks distributions than directly using the simulated peaks. Their methodology is extended in this paper to improve future flood peaks simulation under a changing climate. In this case, the rainfall-runoff model is forced with the downscaled outputs of the Canadian General Circulation Model CGCM3. Special attention is paid to the statistical downscaling of precipitations, as the choice of the transfer function has a significant influence on the performance of non-stationary GEV model. Stepwise regression was initially used to describe precipitation occurrence and intensity, but the patterns of the simulated hydrographs were found to be unsatisfactory. After precipitation occurrence model was successfully replaced with an ensemble of regression trees, the non-stationary GEV model was shown to provide a better description of flood peaks in the observation period. The non-stationary GEV model shows that exceedance probabilities on the Kemptville Creek will gradually rise up to 34% above current levels in 2100 for a 20-year service life.
%0 Journal Article
%1 springerlink:10.1007/s11069-011-0047-7
%A Seidou, Ousmane
%A Ramsay, Andrea
%A Nistor, Ioan
%D 2011
%I Springer Netherlands
%J Natural Hazards
%K ClimateChange Extremes Hydrology Nonstationarity flood
%P 1-12
%R 10.1007/s11069-011-0047-7
%T Climate change impacts on extreme floods II: improving flood future peaks simulation using non-stationary frequency analysis
%U http://dx.doi.org/10.1007/s11069-011-0047-7
%X In the companion paper, Seidou et al. ( 2011 , submitted) have shown that when adequate meteorological data are available to calibrate rainfall-runoff models, using a non-stationary GEV model with the simulated flows can provide a better description of flood peaks distributions than directly using the simulated peaks. Their methodology is extended in this paper to improve future flood peaks simulation under a changing climate. In this case, the rainfall-runoff model is forced with the downscaled outputs of the Canadian General Circulation Model CGCM3. Special attention is paid to the statistical downscaling of precipitations, as the choice of the transfer function has a significant influence on the performance of non-stationary GEV model. Stepwise regression was initially used to describe precipitation occurrence and intensity, but the patterns of the simulated hydrographs were found to be unsatisfactory. After precipitation occurrence model was successfully replaced with an ensemble of regression trees, the non-stationary GEV model was shown to provide a better description of flood peaks in the observation period. The non-stationary GEV model shows that exceedance probabilities on the Kemptville Creek will gradually rise up to 34% above current levels in 2100 for a 20-year service life.
@article{springerlink:10.1007/s11069-011-0047-7,
abstract = {In the companion paper, Seidou et al. ( 2011 , submitted) have shown that when adequate meteorological data are available to calibrate rainfall-runoff models, using a non-stationary GEV model with the simulated flows can provide a better description of flood peaks distributions than directly using the simulated peaks. Their methodology is extended in this paper to improve future flood peaks simulation under a changing climate. In this case, the rainfall-runoff model is forced with the downscaled outputs of the Canadian General Circulation Model CGCM3. Special attention is paid to the statistical downscaling of precipitations, as the choice of the transfer function has a significant influence on the performance of non-stationary GEV model. Stepwise regression was initially used to describe precipitation occurrence and intensity, but the patterns of the simulated hydrographs were found to be unsatisfactory. After precipitation occurrence model was successfully replaced with an ensemble of regression trees, the non-stationary GEV model was shown to provide a better description of flood peaks in the observation period. The non-stationary GEV model shows that exceedance probabilities on the Kemptville Creek will gradually rise up to 34% above current levels in 2100 for a 20-year service life.},
added-at = {2011-12-06T10:03:47.000+0100},
affiliation = {Department of Civil Engineering, University of Ottawa, 161 Louis Pasteur Office A113, Ottawa, ON K1N6N5, Canada},
author = {Seidou, Ousmane and Ramsay, Andrea and Nistor, Ioan},
biburl = {https://www.bibsonomy.org/bibtex/2c848189b59625c8b9d5ca5840af89509/marsianus},
description = {SpringerLink - Natural Hazards, Online First™},
doi = {10.1007/s11069-011-0047-7},
interhash = {1ead1486b8c43460cdacf02f7e58ad52},
intrahash = {c848189b59625c8b9d5ca5840af89509},
issn = {0921-030X},
journal = {Natural Hazards},
keyword = {Biomedical and Life Sciences},
keywords = {ClimateChange Extremes Hydrology Nonstationarity flood},
pages = {1-12},
publisher = {Springer Netherlands},
timestamp = {2013-01-09T14:02:10.000+0100},
title = {Climate change impacts on extreme floods II: improving flood future peaks simulation using non-stationary frequency analysis},
url = {http://dx.doi.org/10.1007/s11069-011-0047-7},
year = 2011
}