Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois

Over, Thomas; Saito, Riki; Veilleux, Andrea; Sharpe, Jennifer; Soong, David; Ishii, Audrey

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https://hdl.handle.net/2142/91029 Copy

Description

Title

Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois

Author(s)

• Over, Thomas
• Saito, Riki
• Veilleux, Andrea
• Sharpe, Jennifer
• Soong, David
• Ishii, Audrey

Issue Date

2016-06

Keyword(s)

• floods
• flood frequency
• urbanization
• peak discharge estimation
• peak discharge
• streamflow statistics
• basin characteristics
• regionalization
• regression
• Web application
• StreamStats

Geographic Coverage

Northeastern Illinois

Abstract

This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions. The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, generalized skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter. This report also provides: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant. The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web-based application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted peak discharge records by streamgage are provided at http://dx.doi.org/10.3133/sir20165050 for download.

Publisher

Illinois Center for Transportation/Illinois Department of Transportation

Series/Report Name or Number

Illinois Center for Transportation Series No. 16-014; Research Report No. FHWA-ICT-16-013

ISSN

0197-9191

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/91029

Sponsor(s)/Grant Number(s)

Illinois Department of Transportation, R27-144

Copyright and License Information

No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161

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