Technical Papers
Jun 3, 2013

Critical Examination of Area Reduction Factors

Publication: Journal of Hydrologic Engineering
Volume 19, Issue 4

Abstract

Area reduction factors (ARFs), which are used to convert estimates of extreme point rainfall to estimates of extreme area-averaged rainfall, are central to conventional flood risk assessment. Errors in the estimation of ARFs can result in large errors in subsequent estimates of design rainfall and discharge. This paper presents a critical examination of commonly used ARFs, particularly those from the U.S. Weather Bureau TP-29, demonstrating that they do not adequately represent the true properties of extreme rainfall. This lack of representativeness is due mainly to formulations that mix rainfall observations from different storms and different storm types. Storm catalogs developed from a 10-year high-resolution radar rainfall data are used set to estimate storm-centered ARFs for Charlotte, North Carolina. Storms are classified as either tropical or nontropical to demonstrate that storm type strongly influences spatial rainfall structure. While there appears to be some relationship between ARF structure and areal rain rate, basin-specific ARFs for the five largest storms from 2001 to 2010 in Little Sugar Creek in Charlotte do not show any systematic deviation from the larger population of storms. Given the challenges presented in this paper as well as other difficulties associated with ARF estimation, the authors suggest that research and practice should shift toward more robust methods, such as stochastic storm transposition, that incorporate realistic representations of the spatial and temporal structure and variability of extreme rainfall and its interactions with watershed surface, subsurface, and drainage network properties into flood risk estimation.

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Acknowledgments

This paper was partially funded by the Willis Research Network, the NOAA Cooperative Institute for Climate Sciences (Grant NOAA CICS NA08OAR4320752), the Dept. of the Interior under the USGS (Award G11AP20215), and the National Science Foundation (Grant CBET-1058027). The authors acknowledge the helpful comments of the three anonymous reviewers.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 19Issue 4April 2014
Pages: 769 - 776

History

Received: Feb 17, 2013
Accepted: May 30, 2013
Published online: Jun 3, 2013
Discussion open until: Nov 3, 2013
Published in print: Apr 1, 2014

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Authors

Affiliations

Daniel B. Wright, Ph.D. [email protected]
M.ASCE
Disaster Risk Management Analyst, Latin America and Caribbean Region Disaster Risk Management and Urban Development Unit, World Bank, 1818 H St. NW, Washington, DC 20433; formerly, Doctoral Candidate, Dept. of Civil and Environmental Engineering, Princeton Univ., E-209A Engineering Quad, Princeton, NJ 08544 (corresponding author). E-mail: [email protected]
James A. Smith, Ph.D.
Chair and Professor, Dept. of Civil and Environmental Engineering, Princeton Univ., E-209A Engineering Quad, Princeton, NJ 08544.
Mary Lynn Baeck, Ph.D.
Hydrometeorology Programmer, Dept. of Civil and Environmental Engineering, Princeton Univ., E-209A Engineering Quad, Princeton, NJ 08544.

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