TY - JOUR
T1 - Diagnostic analysis of future climate scenarios applied to urban flooding in the Chicago metropolitan area
AU - Markus, Momcilo
AU - Wuebbles, Donald J.
AU - Liang, Xin Zhong
AU - Hayhoe, Katharine
AU - Kristovich, David A.R.
N1 - Funding Information:
Acknowledgments This research has been partially funded by the University of Illinois’ Environmental Change Institute, University of Illinois at Urbana-Champaign, and by the United States Environmental Protection Agency Science to Achieve Results (STAR) award EPA RD-83337301-0. We would also like to thank Vern Knapp, Bill Saylor, Mustafa Rahim, Erin Bauer, Lisa Sheppard, Sara Olson, all from Illinois State Water Survey, and Ibraheem Khan, research assistant at Department for Atmospheric Science, University of Illinois, for help in their field of expertise in various stages of this research.
PY - 2012/4
Y1 - 2012/4
N2 - Past heavy precipitation events in the Chicago metropolitan area have caused significant flood-related economic and environmental damages. A key component in flood management policies and actions is determining flood magnitudes for specified return periods. This is a particularly difficult task in areas with a complex and changing climate and land-use, such as the Chicago metropolitan area. The standard design storm methodology based on the NOAA Atlas 14 and ISWS Bulletin 70 has been used in the past to estimate flood hydrographs with variable return periods in this region. In a changing climate, however, these publications may not be accurate. This study presents and illustrates a methodology for diagnostic analysis of future climate scenarios in the framework of urban flooding, and assesses the corresponding uncertainties. First, the design storms are calculated using data downscaled by a regional climate model (RCM) at 30-km spacing for the present and 2050s under the IPCC A1Fi (high) and B1 (low) emissions scenarios. Next, the corresponding flood discharges at six watersheds in suburban Chicago are estimated using a hydrologic event model. The resulting scenarios in flood frequency were first assessed through a set of diagnostic tests for precipitation timing and frequency. The study did not reveal any significant changes in the 2050s in the average timing of heavy storms, but their regularity decreased. The average timing did not exhibit any significant spatial variability throughout the region. The precipitation frequency analysis revealed distinct differences between the northern and southeastern subregions of the Chicago metropolitan area. The quantiles in the northern subregion averaged for 2-year, 5-year, and 10-year return periods exhibited a 20% and 16% increase in daily precipitation for scenarios B1 and A1Fi, respectively. The southeastern subregion, however, exhibited a decrease of 12% for scenario B1 and a minor increase of 3% for scenario A1Fi. The hydrologic effects of changing precipitation on the flood quantiles were illustrated using six small watersheds in the region. The relative increases or decreases in precipitation translated into even larger relative increases or decreases in flood peaks, due to the nonlinear nature of the rainfall-runoff process. Simulations using multiple climate models, for longer periods, finer spatio-temporal resolution, and larger areal coverage could be used to more accurately account for numerous uncertainties in the precipitation and flood projections.
AB - Past heavy precipitation events in the Chicago metropolitan area have caused significant flood-related economic and environmental damages. A key component in flood management policies and actions is determining flood magnitudes for specified return periods. This is a particularly difficult task in areas with a complex and changing climate and land-use, such as the Chicago metropolitan area. The standard design storm methodology based on the NOAA Atlas 14 and ISWS Bulletin 70 has been used in the past to estimate flood hydrographs with variable return periods in this region. In a changing climate, however, these publications may not be accurate. This study presents and illustrates a methodology for diagnostic analysis of future climate scenarios in the framework of urban flooding, and assesses the corresponding uncertainties. First, the design storms are calculated using data downscaled by a regional climate model (RCM) at 30-km spacing for the present and 2050s under the IPCC A1Fi (high) and B1 (low) emissions scenarios. Next, the corresponding flood discharges at six watersheds in suburban Chicago are estimated using a hydrologic event model. The resulting scenarios in flood frequency were first assessed through a set of diagnostic tests for precipitation timing and frequency. The study did not reveal any significant changes in the 2050s in the average timing of heavy storms, but their regularity decreased. The average timing did not exhibit any significant spatial variability throughout the region. The precipitation frequency analysis revealed distinct differences between the northern and southeastern subregions of the Chicago metropolitan area. The quantiles in the northern subregion averaged for 2-year, 5-year, and 10-year return periods exhibited a 20% and 16% increase in daily precipitation for scenarios B1 and A1Fi, respectively. The southeastern subregion, however, exhibited a decrease of 12% for scenario B1 and a minor increase of 3% for scenario A1Fi. The hydrologic effects of changing precipitation on the flood quantiles were illustrated using six small watersheds in the region. The relative increases or decreases in precipitation translated into even larger relative increases or decreases in flood peaks, due to the nonlinear nature of the rainfall-runoff process. Simulations using multiple climate models, for longer periods, finer spatio-temporal resolution, and larger areal coverage could be used to more accurately account for numerous uncertainties in the precipitation and flood projections.
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U2 - 10.1007/s10584-011-0172-z
DO - 10.1007/s10584-011-0172-z
M3 - Article
AN - SCOPUS:84857924519
SN - 0165-0009
VL - 111
SP - 879
EP - 902
JO - Climatic Change
JF - Climatic Change
IS - 3
ER -