Status on the Development of Methods for Determining ...€¦ · # of low outliers using MGBT: 6...
Transcript of Status on the Development of Methods for Determining ...€¦ · # of low outliers using MGBT: 6...
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U.S. Department of the Interior
U.S. Geological Survey
Status on the Development of Methods for
Determining Magnitude and Frequency of
Floods in California
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Annual Exceedance Probability (AEP)
AEP is probability that the discharge will
exceed a given discharge in any year.
AEP in percent is the reciprocal of the
recurrence interval times 100.
Example: For the 100-year flood, the AEP is
(1/100)*100 or 1% for any given year. There is a
1 in 100 chance each year that this discharge
will occur.
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http://pubs.usgs.gov/gip/106/
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History:
• 1967 Bulletin 15
• 1976 Bulletin 17
• 1977 Bulletin 17A
• 1982 Bulletin 17B
• 20?? Bulletin 17C
http://water.usgs.gov/osw/bulletin17b/bulletin_17B.html
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Annual peak-flow data for a gaged station
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http://pubs.usgs.gov/sir/2010/5260/
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Regional Skew for California
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Expected Moments Algorithm (EMA)
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Multiple Grubbs-Beck Test
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Regional Regression Analysis
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Regression equations for ungaged
sites outside of the desert
QAEP = aAbBcCd… ,
where
QAEP = flood discharge for specified AEP level
A,B,C = are the basin and climatological characteristics
a, b, c, d = the regression coefficients
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Basin Characteristics Drainage Area
Basin Perimeter
Relief
Mean Elevation
Maximum Elevation
Minimum Elevation
Percent Lake Area
High Elevation Index
Elevation of Outlet
Relative Relief
Distance to Coast
Average Basin Slope
Percent Impervious Area
Percent Forested Area
Mean Annual Precipitation
Average Maximum January Temperature
Average Minimum January Temperature
Longitude of the Basin Centroid
Latitude of the Basin Centroid
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Regression equations for regions outside
the desert take the form:
QAEP = a(DRNAREA)b (PRECIP)c
where:
QAEP is the annual exceedance probability
flow, in cubic feet per second
DRNAREA is drainage area, in square miles
ELEV is mean basin elevation, in feet
PRECIP is mean annual precipitation, in inches
a, b, and c are the regression coefficients
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For the Sierra-Nevada Region, the
regression equations take the form:
QAEP = a(DRNAREA)b(ELEV)c(PRECIP)d
where:
QAEP is the annual exceedance probability
flow, in cubic feet per second
DRNAREA is drainage area, in square miles
ELEV is mean basin elevation, in feet
PRECIP is mean annual precipitation, in inches
a, b, c, and d are the regression coefficients
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Updating Flood Frequency Estimates
in the Desert Region of California
• Unique to the western United States:
numerous zero flows/ low outliers
short annual peak-flow records
highly variable peak-flow data
• Standard LP3 fitting method doesn’t
work with the desert peak-flow data
• As recommended in B17B, flood-
frequency estimates are improved by
weighting at-site skew with a more
robust regional skew estimate
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Updating Flood Frequency Estimates
in the Desert Region of California
• Because of the problems of the at-site
peak flow data, the at-site standard
deviation and mean were also
weighted with regional estimates of
those parameters in the desert region
• In Gotvald and others (2012), in review,
regional standard deviation and mean
were developed for the desert region
of California
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Updating Flood Frequency Estimates
in the Desert Region of California
Regional standard deviation:
0.91
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Regional mean:
Updating Flood Frequency Estimates
in the Desert Region of California
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Updating Flood Frequency Estimates
in the Desert Region of California
Length of historical period: 14
# of peaks: 14
# of zero flows: 0
# of low outliers using MGBT: 0
At-site standard deviation: 0.31
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Updating Flood Frequency Estimates
in the Desert Region of California
Length of historical period: 14
# of peaks: 14
# of zero flows: 6
# of low outliers using MGBT: 6
At-site standard deviation: 1.81
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Updating Flood Frequency Estimates
in the Desert Region of California
• The average standard errors of prediction for these regression
equations range from 214.2 percent for the Q50% to 856.2
percent for the Q0.2% annual exceedance probabilities
• The large standard errors indicate the difficulty in accurately
predicting flood flows in this region of extreme flow variability
• These standard errors of prediction are smaller than comparable
errors reported for the prediction equations for the southwestern
United States by Thomas and others, 1997
Regional Prediction Equations:
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Anthony (Tony) Gotvald
Hydrologist
USGS
Atlanta, GA
(770) 903-9310
Questions ?
Nancy Barth
Hydrologist
USGS
Sacramento, CA
(916) 278-3171