Critical examination of area reduction factors

Daniel B. Wright, James A. Smith, Mary Lynn Baeck

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)769-776
Number of pages8
JournalJournal of Hydrologic Engineering
Volume19
Issue number4
DOIs
StatePublished - Jan 1 2014

All Science Journal Classification (ASJC) codes

  • Environmental Chemistry
  • Civil and Structural Engineering
  • Water Science and Technology
  • Environmental Science(all)

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