Draft
Analysis of
Storm Event Characteristics
for Selected Rainfall Gages
Thoughout The United States
by
Eugene D. Driscoll
Gary E. Palhegyi
Eric W. Strecker
and
Philip E. Shelley
November 1989
Prepared for
U.S. Environmental Protection Agency
Washington DC
Woodward-Clyde Consultants
0148B 1100 500 12th Street, Suite 100, Oakland, CA 94607- 4014
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DISCLAIMER
The information in this document has been funded wholly by the United States Environmental
Protection Agency. It has been subjected to the Agency's peer and administrative review, and
it has been approved for publication as an EPA document. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
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TABLE OF CONTENTS
1. Introduction Page
1.1 Background 1
1.2 Objective and Scope 1
2. Technical Approach 3
2.1 General 3
2.2 SYNOP - Statistical Rainfall Analysis Program 3
2.3 Sensitivity Analysis of SYNOP 6
2.3.1 Inter-event Time 6
2.3.2 Test for Independence of Storm Events 9
2.3.3 Minimum Storm Volume requirement 13
2.3.4 Wet Season Statistics 13
3. Results 18
3.1 Summary of Storm Event Statistics in the United States 18
3.2 Summary of Storm Event Statistics in North Carolina 37
4. References 43
m
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LIST OF FIGURES
Figure - page
1. Storm event characterization of a rainfall record. 4
2. Effect of minimum inter-event time on the COV of DELTA for three rainfall gages. 8
3. Test for independence of storm events using a 6 hour minimum inter-event time. 10
4. Correlagram showing autocorrelations for various inter-event times. 11
5. Effect of minimum storm volume on storm event statistics. 15
6. Map showing the location of selected rainfall gages. 19
7. Rainfall zones of the United States. 30
8. Nationwide contour map of the number of storms per year. 32
9. Nationwide contour map of the duration of storms. 33
10. Nationwide contour map of the intensity of storms. 34
11. Nationwide contour map of the volume of storms. 35
12. Nationwide contour map of North Carolina and average storm event statistics. 39
LIST OF TABLES
Table Number Page
1. Effect of minimum inter-event time on storm event statistics. 7
2. Effect of minimum storm volume on storm event statistics. 14
3. Comparison between wet season and calendar year statistics. 16
4. Listing of selected rainfall gages used in the analysis. 20
5. Storm event statistics on the national scale. 22
6. Typical values of storm event statistics for rain zones. 31
7. Examples of the effect of local rainfall variation and length of record on storm
event statistics. 38
8. Listing of selected rainfall gages in North Carolina. 40
9. Storm event statistics for North Carolina. 41
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1. Introduction
1.1 Background
Precipitation is the driving force that mobilizes and transports pollutants from a nonpoint
source (NFS) to receiving waters. Relevant information on the precipitation characteristics of an
area is essential to address issues such as the estimation of NFS pollutant loads, the water quality
impacts they produce, and the assessment of control strategies.
There is a growing tendency to apply probabilistic analysis techniques to the evaluation of a
variety of water quality issues, particularly those associated with the intermittent and variable NFS
load-generating process. Rainfall is a key input for many of the methodologies, and this requires
an appropriate definition of the statistical characteristics of storm events. The Environmental
Protection Agency (EPA) supported the development of a statistical rainfall analysis program
SYNOP (EPA, 1976), which has seen considerable use during the past decade and has been
adopted for use by the U.S. Geological Survey (USGS), Federal Highway Administration
(FHWA), and others. Further, statistical summaries of rainfall properties for a considerable
number of gages in different areas of the country have been assembled and reproduced in a number
of reports for use as general reference material.
Currently, summaries of rainfall statistics are available, but much of the information is
based on records that reach only to 1973. Also, some of the results were assembled from diverse
sources and their reliability is uncertain. Furthermore, there have been changes in the format of the
original source files provided by the US Weather Service, which have introduced output errors
when the original SYNOP program was applied to a record having these new formats. In addition,
a simplified rain zone map, developed some time ago for preliminary screening and based on
SYNOP results available at the time, has found relatively wide circulation. For the foregoing
reasons, it was considered appropriate to update the information on rainfall statistics.
1.2 Objective and Scope
The objective of this study was to develop an updated and expanded summary of storm
event statistics for locations throughout the country, and to make this information available for use
by probabilistic analysis procedures used for NFS investigations.
This report presents a summary of storm event statistics for 160 (mostly urban) locations
spatially distributed throughout the country. The summary tables are organized into groupings of
gage locations (or rain zones) having comparable storm event characteristics, which are also
delineated on a map. Regional differences in pertinent storm event parameters are illustrated by
contour maps showing the overall pattern by which individual parameters vary with location. In
addition to this national scale, a similar analysis is applied for a single state for illustrative
purposes, to examine results on a smaller spatial scale.
Chapter 2 describes the important features of the technical approach employed in
developing the rainfall event statistics for the selected rain gages. It provides a brief description of
the nature of the computations performed by the SYNOP statistical rainfall analysis program and
identifies the additional features that were added during this study effort to improve its reliability
and usefulness. This chapter also presents the results and conclusions from sensitivity analyses
that were performed to examine several important issues relating to the application of the program.
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Chapter 3 presents and discusses the analysis results for the nationwide array of gages and
for the higher spatial density gage network within a single state. The results are summarized in
tables and maps, in a format that is designed to make them suitable for use as reference material.
An appendix is provided under a separate cover, which provides a complete summary oi
the rainfall statistics generated for each gage. It is noted that even this expanded listing represents
only a small part of the complete statistical output that can be generated by the SYNOP program.
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2. TECHNICAL APPROACH
2.1 General
Hourly rainfall records for rain gages in the United States are available from the National
Climatic Data Center (NCDC) of the US Weather Service in Asheville, North Carolina. The
records that were analyzed for this study were taken from commercially available optical laser
disks, which provided a compact record of the data originally provided by NCDC. These disks
can be obtained from commercial sources.
Each particular record is identified by a unique 6-digit number, consisting of a 2-digit state
code followed by a 4-digit gage number. In the tabulated results presented later, each state is
identified by its standard abbreviation, rather than the state code. The information in a gage record
includes the location name, latitude and longitude, elevation of the measurement site, and the depth
of hourly rainfall recorded (inl/100 inches). The date and hour are recorded for each depth in the
record. The records examined cover the entire period of record for each of the gages selected for
analysis. In all but a few cases, these records begin in mid-1948, and for most of the selected
gages extend through mid-1988.
We attempted to utilize a common period of record (1949-1987) for all gages to be included
in the analysis. We further attempted to limit the selection to include only gages with high degrees
of completeness, because it is not uncommon for a gage record to have considerable stretches of
incomplete data. Both of these items of information were provided by a summary listing
identifying the gages contained on the optical disks. Even so, during our analysis there was a
number of cases where the selected records were found to be incomplete. In such cases, the data
were re-analyzed using only that part of the record that was not defective or, in a number of cases,
substituting a gage that was different than the original selection. While it was generally possible to
meet the gage selection objectives, shorter periods of record have been accepted in some cases in
order to provide the desired spatial distribution of gage locations.
2.2 SYNOP - Statistical Rainfall Analysis Program
Rainfall data provided in the NCDC hourly records may be viewed, as illustrated by Figure
l(a), as a series of hours with either no precipitation, or an intensity recorded by the gage for that
hour. This pattern is simplified by grouping the hours with rainfall into a set of separate "storm
events" and representing each event as a uniform, rectangular hyetograph as in sketch (b). Each
event may then be characterized by its duration (d), volume (v), average intensity (i), and the time
interval between the midpoints of successive events (d).
The rainfall volume in a particular hour is assigned to an event in progress, or as the start of
a subsequent independent event, on the basis of an assigned minimum inter-event time (EET), the
number of dry hours beyond which the occurrence of rainfall marks the beginning of a new event.
The IET is selected such that the resulting storm events are independent and occur randomly. The
selection of the EET to meet the independence requirement is discussed below.
The SYNOP program, developed about a decade ago for EPA reads an hourly precipitation
record, organizes data for the wet (rainfall) hours into events, and computes the statistics of the
storm event parameters (EPA, 1976). When a complete hourly record has been organized into a
sequence of individual storm events, the mean and standard deviation may be determined for each
of the event parameters. In the summaries presented, the coefficient of variation (COV), which is
the ratio of the standard deviation to the mean, is presented rather than the standard deviation.
3
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CO
c
CD
CO
"c
'co
DC
(a) Hourly Rainfall Variation
(b) Storm Event Variation
Time
w
c
CD
E
o
-t—>
CO
V
I
w/.
Time
Storm Event
Statistic
Volume
Duration
Average intensity
Interval between
event midpoint
PARAMETER
For each
V
d
i
8
storm event
(inches)
(hours)
(inches/hour)
(hours)
For all
Mean
V
D
1
A
storm events
Coef. Var.
CVV
cvd
CVj
CV5
Figure 1. Storm event characterization of a rainfall record.
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The analyses were performed on Apple Macintosh and IBM-PC (or compatible)
microcomputers, using SYNOP II, a microcomputer version of the original SYNOP program.
SYNOP II, prepared by Woodward-Clyde Consultants, continues to utilize the basic code and
computations of the original, but incorporates some important new features, which are described
below.
There have been format changes in the NCDC records at different points in time, resulting
in differences between one part of a long record and another. Although these changes are minor,
they can produce anomalous results at isolated parts of the record which can significantly distort
the statistics generated. SYNOP II eliminates this potential for error.
The following computational features have been added or modified to improve the
applicability of this program to different situations, and to make it easy for the user to select the
specific options that will apply for an analysis.
• The user may select the beginning and ending year for an analysis, to permit developing
statistics for different periods of time.
• The user may select beginning and ending months. This allows annual statistics to be
generated on either a calendar year basis, or on a water year basis for ease of comparison
with stream flow records. This feature also permits the development of rainfall statistics
for selected seasons, an important consideration in western US. areas having pronounced
wet and dry seasons.
• The user may select a minimum storm volume for events to be included in the analysis.
Since very small storm volumes (usually a significant fraction of the total number of
storms, but not annual volumes) do not result in runoff, the statistical characteristics of
runoff-producing events can be generated.
• The user may select the "inter-event time" (IET), minimum number of dry hours used to
assign an hourly rainfall volume to the current event, or to a new one. Alternatively, the
program will make successive iterations using a pair of user-selected lETs and then
interpolate to estimate a value that will result in storm intervals (times between storm mid-
points) that are approximately exponentially distributed.
• The user may select any or all of a variety of output summaries that provide different
degrees of detail or different organizations of results. For example, summary statistics
stratified by month and by year are generated, as well as results for the entire storm
sequence for the total period of record analyzed.
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2.3 SENSITIVITY ANALYSIS OF SYNOP
Before begining the statistical analysis, a sensitivity analysis was performed i.o identify a
set of uniform parameters to be assigned to each of the rainfall gages. The following sections
discuss the evaluation of inter-event time, independence of storm arrival time, mir'-num storm
volume, and wet season characteristics.
2.3.1 INTER-EVENT TIME
An underlying assumption necessary for the manipulation of probability density functions,
is that the events must be independent. One of the requirements associated with storm event
analysis is selecting an appropriate inter-event time (IET) such that the arrival time of storm events
are independent. Several authors have discussed methods for choosing an appropriate IET
(Heaney et al., 1977; Hydroscience, 1979; and Restrepo-Posada et al., 1982).
A common approach for the separation of precipitation records into statistically independent
events was discussed by Restrepo-Posada and Eagleson (1982). They consider the arrival time of
storm events to be random and to conform to a Poisson process. If the events are independent the
intervals between Poisson arrival times are distributed exponentially. They note that the Poisson
process describes the random arrival time of storms as point or instantaneous occurrences with
durations of zero, but conclude that the Poisson process can adequately describe the arrival of
independent storm events when the mean duration is much smaller than the mean arrival time.
Precipitation data has this characteristic.
The exponential distribution is a special case of the gamma, and results when the coefficient
of variation is 1. Rainfall event parameters have been shown to be well represented by a gamma
distribution (Hydroscience, 1979). It has also been shown by these authors and by this study, that
the COV of arrival times changes in a consistent way with IET, and that by the assignment of an
appropriate IET, storm event statistics can be developed that are based on exponential (and hence
independent) arrival times. As Restrepo-Posada et al (1892) suggest, this will also result in the
independence of other event parameters (durations, volumes, intensities).
To use this approach, trial values of LET are chosen until a coefficient of variation of
approximately 1 is obtained for the arrival times. In the analysis performed by SYNOP, the arrival
time is computed as the time interval between storm midpoints, designated DELTA in the summary
tables.
Restrepo-Posada et al (1982) suggest that a coefficient of variation equal to 1, although less
sufficient than a chi-square test, provides a convenient test for the exponential distribution. The
rainfall data analyses reported by Hydroscience (1979) also indicated that when the COV of delta is
approximately 1, the actual distribution of deltas is closely described by an exponential
distribution. The poisson assumption has proved to be both convenient and realistic. Therefore,
assigning an IET such that the resulting COV of delta is about 1, is considered to provide a
sufficient indication of the independence of storm events.
Sensitivity analyses to examine the effect of IET on the resulting storm event statistics were
conducted. The analysis was performed on three arbitrary locations in the eastern, middle and
western part of the country. These results are listed in Table 1 and shown graphically in Figures 2.
The results for the three sample locations indicate the substantial differences in IET required to
produce a COV of 1 for storm intervals (DELTA'S). IET values of about 6 hours are found to be
suitable for locations in the eastern part of the country but are seen to increase as the gage location
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TABLE 1. Effect of Minimum Inter-event Time (IET) on Storm Event Statistics
ain Gage Location
EAST COAST
Charlottesburg
Reservoir
NEW JERSEY
Gagetf 1582
IET
hrs
1
2
3
4
5
6
9
12
15
24
36
48
DELTA
Avg COV
45
61
72
81
88
92
102
110
116
131
146
167
1.70
1.40
1.24
1.12
1.06
1.02
0.92
0.87
.0.82
0.73
0.65
0.59
Duration
Avg COV
1.8
2.8
3.6
4.5
5.1
5.6
7.0
8.1
9.2
12.7
17.4
25.8
1
1
1
1
1
1
1
1
1
1
1
1
.09
.21
.22
.23
.19
.21
.17
.13
.12
.15
.17
.22
Intensity
Avg COV
0.130
0.127
0.124
0.122
0.118
0.116
0.111
0.105
0.100
0.093
0.085
0.075
0
0
0
0
0
0
0
0
0
0
.61
.66
.71
.76
.76
.78
.81
.83
.80
.88
0.93
0
.92
Volume
Avg COV
0.30
0.40
0.47
0.53
0.57
0.59
0.66
0.71
0.74
0.84
0.93
1.07
1.92
1.75
1.65
1.57
1.53
1.51
1.44
1.49
1.46
1.41
1.35
1.28
MID COUNTRY
Ferris
TEXAS
Gage #3133
2
3
4
5
6
7
8
9
10
14
18
22
110
124
134
141
146
153
156
161
164
176
185
194
1
1
1
1
1
1
1
1
1
1
1
0
.49
.36
.29
.24
.20
.17
.14
.12
.10
.05
.01
.97
4.5
5.3
5.9
6.4
6.8
7.3
7.6
8.0
8.3
9.5
10.7
12.0
0
0
0
0
1
1
1
1
1
1
1
1
.96
.96
.96
.99
.02
.03
.04
.05
.05
.10
.13
.21
0.094
0.096
0.096
0.096
0.097
0.095
0.095
0.094
0.094
0.092
0.090
0.088
1
1
1
1
1
1
1
1
1
1
1
1
.20
.14
.14
.15
.15
.14
.12
.12
.13
.15
.17
.19
0.45
0.51
0.54
0.57
0.59
0.61
0.62
0.64
0.65
0.69
0.72
0.76
1.53
1.45
1.40
1.38
1.37
1.36
1.35
1.34
1.34
1.34
1.32
1.32
WEST COAST
Los Angeles
Airport
CALIFORNIA
Gage# 5114
6
10
15
18
24
30
50
75
100
150
200
250
300
536
584
633
650
685
717
818
946
1025
1198
1367
1694
1878
2.17
2.09
1.99
1.95
1.89
1.83
1.68
1.53
1.47
1.32
1.12
1.09
1.01
11.7
15.1
18.7
20.0
23.9
27.1
37.9
58.7
75.5
119,2
185.3
283.5
366.8
0.84
0.99
1.04
1.09
1.12
1.16
1.14
1.19
1.28
1.27
1.27
1.27
1.27
0.063
0.059
0.054
0.053
0.049
0.048
0.041
0.036
0.034
0.028
0.024
0.020
0.020
0.73
0.75
0.79
0.80
0.85
0.88
0.92
1.08
1.15
1.29
1.40
1.36
1.34
0.67
0.75
0.82
0.84
0.89
0.93
1.06
1.23
1.33
1.54
1.81
2.18
2.43
1.16
1.17
1.17
1.23
1.27
1.28
1.27
1.30
1.34
1.32
1.33
1.33
1.34
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co
1.8-
1.7-
1.6-
1.5-
1.4-
1.3-
1.2.
1.1 -
1.0
0.9-
0.8-
0.7-
0.6-
0.5-
0.4-
15 20 25 30 35
Inter-Event Time (hours)
40 45
1.5
50
ti
o
>
O
o
1.3-
8
1.0- -
0.9
Forris. TX I
10 15 20
inter-Event Time (hours)
25
30
50 100 150 200 250 300 350 400
inter-Event Time (nours)
Figure 2, Effect of inter-event time on the COV of DELTA for three rainfall gages
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moves to the west. IET values of about 20 hours are required in mid-country and become
extremely high (300 hours) for west coast sites where rainfall has a pronounced seasonal
distribution (Figure 2). The vary high lETs on the west coast result in abnormally high storm
volumes and durations followed by low intensities.
We concluded that while the method for assigning IET based on the COV for DELTA
provides a basis for assuring that the events are independent, for some locations the resulting
event statistics are not meaningful for the types of NFS analyses for which the rainfall statistics
will most commonly be applied. A similar determination was made by the authors of a study of
sites in Saudi Arabia and the western US. (Restreop-Posada and Eagleson, 1982).
We selected an LET of 6 dry hours as being a reasonable value to use for two reasons; 1) so
that the statistics for rain gages throughout the country would have a common basis, and 2) event
statistical parameters would relate more meaningfully for evaluating NFS water quality issues.
This choice is consistent with conclusions by other investigators (Hydroscience, Inc., 1979).
Analyses of selected gages performed during this study indicate that a 6 hour IET is sufficient to
produce event arrival times that are independent. The results presented below illustrate a test for
independence for an east coast and a west coast gage, by examining the degree of correlation
between paired values of the interval between successive events.
2.3.2 TEST FOR INDEPENDENCE OF STORM EVENTS
An analysis of the influence of the assigned IET on the independence of storm arrival times
was performed by investigating the autocorrelation of the set of individual values for DELTA (time
between storm midpoints) produced when the hourly record was sorted into storm events using
different values for IET. This analysis included a determination of the statistical significance of the
resulting correlation coefficients.
Separate SYNOP analyses of this record, using ffiTs of 2, 4, 6, 12 and 24 hours, resulted in
different sets of DELTAs. Autocorrelation was tested by creating paired values consisting of the
DELTA for an event and the DELTA for a subsequent event as defined by a specified lag period.
Separate determinations were made using lags of 1 through 10. For example, lag 1 used the values
for an event and the one immediately following, lag 2 for an event value paired with that for the
second event later, and so forth. A standard linear correlation test was then performed using the
paired sets that were produced and the correlation coefficient (r) was computed. Figure 3 presents
the correlation plots of such paired values for gages on the east and west coasts. For both, the
results shown are for a single gage, an ffiT of 6 hours, and a lag interval of 1.
Figure 4, based on Los Angeles rainfall gage #5114, presents a correlagram summarizing the
the relationship between the computed autocorrelation coefficients and the lag interval, for a set of
lETs. The upper plot (a) illustrates the pattern over a range of IET values; plot (b) isolates results
for the 6 hour IET that was selected to be uniformly applied to all gages in the study.
If a correlagram curve were to decrease gradually from r=l to r=0 as a function of the lag
interval, it would suggest a lack of independence in the arrival time of successive storms. A curve
that falls to zero (or near zero) at the first lag of the data suggests that the arrival times of
successive storms are independent. Differences in the observed pattern for the individual lETs
would indicate the influence of IET on the independence of storm events. The relationships shown
by Figure 4 suggest that for any of the lETs examined, the arrival times of successive storms are
either independent, or at most only very weakly correlated.
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600
200 400 600
DELTA (d)
800
Lag I correlation plot for Charlottesburg, N.J. gage * 1582.
(a)
5000
4000-
3000-p
2000
1000
1000 2000 3000 4000 5000
DELTA (d)
Lag I correlation plot for Los Angeles, CA. gage * 51 14
(b)
Figure 3. Test for independence of storm events using a 6 hour
minimum Inter-event time.
10
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inter-Event Times
2 hrs
• 4 hrs
12 hrs
24 hrs
-0.2
Lag
(a) Plot showing a variety of inter-event times.
Inter-Event Time
-—D— 6 hrs
xy 0.4-
-0.2
Lag
(b) Plot showing the 6 hour inter-event time.
Figure 4 Correlagram showing autocorrelations for various lET's
11
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To evaluate the statistical significance of the correlation coefficients obtained, a hypothesis
test was conducted to determine whether the computed correlation coefficients are significantly
different from zero. A procedure to test the hypothesis that the correlation coefficient i;
significantly different from zero is described by Sokal and Rohlf (1969). The null hypothesis is:
Ho: r = 0 (1)
This implies that the paired data is uncorrelated, or independent. The hypothesis is testec
with the Student's t-test using n-2 degrees of freedom:
t = r«SQRT((n-2V(l-r2)) (2)
Using Equation 2 and the common Student "t-tables", the hypothesis can be tested
Alternatively, by solving Equation 2 for r a critical value of the correlation coefficient can \x
computed and compared to those computed from the raw data. Thus:
r = SQRT(t2/(t2 + n-2)) (3)
As a result, given a confidence level (e.g. 99%) and the number of data points (n), a critical
value of r can be computed. When the computed value of r is less than the "critical r", the
correlation is not significantly different from zero.
For the gage records examined, the number of DELTA s computed using a 6 hour inter-
event time and .10 inches as a minimum storm volume are 653 for the west coast gage and 858 foi
the east coast gage. Given a 99% confidence level (Student's t = 2.576), the following critical
values of r are computed as:
west coast gage n = 653 r = 0.100
east coast gage n = 858 r = 0. 088
Thus, for a computed correlation coefficient less than the critical value, one would conclude
that the correlation coefficient is not significantly different from zero, and as a result, the paired
data are independent
The results of this analysis indicate that the lag 1 correlation coefficient is not significantly
different from zero for the east coast gage (r=.032), and a 6 hour DET results in independent storm
events. For the west coast location (r=0.146), the correlation is significantly different from zero.
However, the critical value is quite small because of the very large number of data pairs (n), and
while statistically not zero, the degree of correlation is quite small. For this and similar locations,
although events cannot be considered completely independent at a 99% confidence level, the degree
of independence is considered high enough for the purposees of this study.
On this basis, a uniform dry hour storm event separation period (IET) of 6 hours was applied
uniformly for the analysis of all of the rain gages examined in this study.
12
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2.3.3 MINIMUM STORM VOLUME
Since the smallest volume reported in any hour is generally 0.01 inch (some gages only
report rainfall to the nearest 0.10 inch), this value (or zero), assigned as a minimum storm volume
when the SYNOP program is run, results in all measured precipitation being included in the
statistics. Higher values for the minimum storm volume can be used to estimate statistics for only
those events that would be expected to produce runoff. Such minimum storm volumes are
estimated to be in the order of 0.08 to 0.12 inches (Schueler, 1987).
A minimum storm volume of 0.10 inches was specified for the analyses that were
performed, so that the analysis would produce statistics of "runoff-producing" events. This choice
was made because an important current use of the type of information developed will be for the
examination of NFS issues, where the principal use of the rainfall data is to provide estimates of
runoff quantities.
The user should note that these statistics for "runoff producing events" will differ from
those for "all precipitation events". The effect on the storm event statistics is indicated by the
sensitivity test results for 3 gages summarized in Table 2 and shown graphically in Figure 5.
Because the Charlottesburg, NJ gage used in the previous analysis only recorded rainfall to the
nearest. 1 inches it was replaced with the Newark, NJ gage for this analysis.
As the results indicate, the average number of storms per year may be reduced by as much
as 25 to 45 percent, but these small storm events account for only a small percent of the annual
precipitation volume. Increasing the value for the minimum volume assigned, results in a
significant increase in the average value, and a decrease in the COV of each parameter.
2.3.4 WET SEASON CHARACTERISTICS
The results presented in the report analyzed the entire calendar year (months 1-12) for all
gages. As a result, for those locations having distinct wet and dry seasons, the statistics include
conditions with extended periods with little or no rainfall. A sensitivity analysis was performed to
examine the extent to which the precipitation statistics might be distorted by the presence of long
dry periods. For selected gage locations in the west, an additional analysis was performed, using
the full period of record, but including in the analysis only those months assigned to the wet
season. The wet season was arbitrarily chosen as the months between October and March,
inclusive, and was based on the total precipitation volume computed for each month in the original
analysis. The results are summarized in Table 3, for a sample of six western locations. Results
are seen to vary appreciably for the different locations.
For Phoenix, AZ. and Las Vegas, NV., only about 60 percent of the storms and annual
precipitation volume occur in the winter months. For these sites, the average storm durations are
20-25 percent longer during the "wet" period, and the average interval between storms is
significantly shorter. Mean storm volumes are virtually identical, but the average storm intensity is
40 percent lower during the winter period.
In contrast, the Los Angeles and Oakland CA statistics show the effect of the strong seasonal
rainfall pattern in these areas. Approximately 85 percent of the total rainfall and number of
independent storm events occur during the 6 month period assigned as the wet season. As a result
of this period containing most of the storms, the individual event statistics for storm durations,
volumes and intensities are essentially the same. The interval between storms is naturally much
shorter, since the average is not influenced by the very long intervals during the summer months.
13
-------
TABLE 2 Effect of Minimum Storm Volume on Storm Event Statistics
Inter-event Time (IET) = 6 hours
Rain Gage
Location
min
Vol
Avg No
Storms
Avg
Volume
EAST COAST
Newark
NEW JERSEY
1975-1985
Gage# 6062
0.01
0.02
0.03
0.04
0.05
0.06
0.08
0.10
0.12
pet change .01/.10
101
94
87
84
76
74
70
65
62
-36
47.4
47.3
47.2
47.1
46.7
46.6
46.4
45.9
45.6
-3.2
DELTA
Avg COV
87
94
102
105
117
119
126
137
144
0.90
0.87
0.87
0.87
0.86
0.85
0.85
0.86
0.87
Duration
Avg COV
8.1
8.7
9.2
9.5
10.1
10.2
10.6
11.1
11.4
1.02
0.96
0.92
0.90
0.85
0.84
0.83
0.80
0.78
Intensity
Avg COV
0.057
0.060
0.064
0.066
0.070
0.071
0.074
0.078
0.080
1.22
1.17
1.12
1.11
1.07
1.06
1.04
1.01
1.00
Volume
Avg C(
0.47 1 .'
0.50 1.'
0.54 1.
0.56 1.
0.62 1.
0.63 1.
0.66 1.'
0.71 1.(
0.74 1.(
56
37
-22
37
-17
51
MID COUNTRY
Ferris
TEXAS
Gage #31 33
0.01
0.02
0.03
0.04
0.05
0.06
0.08
0.10
0.12
54
53
52
50
46
46
44
40
39
32.0
32.0
32.0
31.9
31.7
31.7
31.6
31.2
31.1
146
149
153
159
174
176
184
203
210
1.20
1.20
1.19
1.18
1.15
1.15
1.15
1.14
1.15
6.8
6.9
7.0
7.2
7.6
7.7
7.9
8.4
8.5
1.02
1.01
0.99
0.97
0.93
0.93
0.92
0.88
0.88
0.097
0.098
0.101
0.104
0.111
0.112
0.115
0.121
0.124
1.15
1.13
1.12
1.09
1.05
1.04
1.02
0.99
0.98
0.59
0.60
0.61
0.63
0.68
0.69
0.72
0.78
0.79
1.
1.
1.
1.2
1.2
1.2
1.1
1.1
1.C
pet change .01/.10
-26
-2.4
39
24
-14
25
-14
32
WEST COAST
Los Angeles
Airport
CALIFORNIA
Gage# 5114
0.01
0.02
0.03
0.04
0.05
0.06
0.08
0.10
0.12
30
26
24
23
21
20
19
17
17
12.1
12.1
12.1
12.0
11.9
11.9
11.8
11.7
11.6
299
342
371
390
442
448
480
531
550
1.94
2.02
2.01
2.00
2.20
2.18
2.27
2.21
2.17
8.0
8.9
9.5
9.8
10.6
10.7
11.2
11.8
12.0
1.15
1.05
1.00
0.98
0.93
0.92
0.90
0.87
0.86
0.044
0.049
0.052
0.052
0.058
0.058
0.060
0.063
0.064
0.93
0.85
0.81
0.79
0.75
0.74
0.73
0.70
0.69
0.41
0.47
0.51
0.53
0.59
0.59
0.63
0.68
0.70
1.6
1.5
1.4
1.3
1.2
1.2
1.2
1.1
1.1
pet change .01/.10
-43
-3.3
78
14
48
-24
43
-25
66
14
-------
N«wark,NswJ»f»«y
Forrjl. Taxas
Lot Angalt*. Calriomia
E
0.00 002
0.06 0.08 0.10
Mln. Vol.(In)
0.12 0.14
0.80
0.73
0.70
0.63-
0.60
0.33
0.30
0.43
0.40
Fern's, Taxas
Los Angelas. Cailornia
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14
Mln. Vol. (In)
14
13-
12-
11 -
i .:
Nvwaifc. NawJ»re«y
F0fria. Taxa*
Los Ang»k«, CaHorria
0.00 0.02 0.04 0.06 O.OS 0.10 0.12 0.14
Mir. Vcl. (Ir)
600
H
300-
Newarfc. New Jars«y
Fsffis. Taxas
LomAngalse, CaBfomia
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14
Uln. Vol. (In)
Figure 5. Effect of minimum strom volume on storm event statistics.
15
-------
TABLE 3. Comparison Between Wet Season and Calendar Year Statistics
Plain Gage
CALIFORNIA
Annual Statistics
No. Storms/yr
Avg COV
Los Angeles, gage #5114
Total Year 1 7
Wet period 1 5
Wet - % of Total I 88 I
0.39
0.38
Precip in/yr
Avq COV
11.65
10.30
0.45
0.52
Independent Storm Event Statistics
Duration (hh Intensity (in/hh Volume l\n) DELTA (hr)
Avg COV Avg COV Avg COV Avg COV
11.7 0.84
12.0 0.85
0.063 0.73
0.065 0.73
0.67 1.16
0.71 1.16
536 2.17
232 1.32
Oakland, gage #6335
Total Year
Wet period
Wet - % of Total
30 0.22
25 0.35
17.06
14.91
0.32
0.42
13.3 0.79
13.8 0.79
0.048 0.69
0.049 0.68
0.57 1.01
0.60 0.99
295 2.28
148 1.30
Redding, gage #7295
Total Year
Wet period
Wet - % of Total
30 0.34
23 0.35
26.59
22.69
0.40
0.43
14.5 0.90
16.5 0.84
0.072 0.94
0.063 0.64
0.88 1.08
0.98 1.05
248 2.13
136 1.36
CFEGCN
Medford, gage #5429
Total Year
Wet period
Wet - % of Total
40 0.17
29 0.25
17.71
14.07
0.26
0.36
12.9 0.77
14.0 0.75
0.040 0.98
0.037 0.65
0.44
0.49
1.14
1.14
222 1.63
139 1.12
NEVADA
Las Vegas, gage #4436
Total Year 10 0.45
Wet period 6 0.59
Wet - % of Total I 60 I
3.63
2.05
0.51
0.68
8.8
10.9
0.75
0.62
0.064 1.09
0.038 0.66
0.37 0.82
0.36 0.73
967 1.49
491 1.25
ARIZONA
Phoenix, gage #6481
Total Year
Wet period
Wet - % of Total
16 0.29
9 0.46
8.1
10.4
0.92
0.80
0.085
0.053
1.23
0.84
0.42
0.42
35
0.15
579
369
1.46
1.15
16
-------
A pattern that is intermediate between those described above is shown by the Medford OR
and Redding CA sites. Here, a relatively strong seasonal distribution of precipitation is shown by
the fact that 75 percent of the storm events, and 80-85 percent of the annual volume, occur during
' the wet period. The individual event statistics also exhibit intermediate differences. As with the
other sites, the average interval between storms is shorter. Durations are longer and intensities
lower, but the difference is only about 10 percent. The average event volume is about 10 percent
higher.
The seasonal comparison presented here provides some general information that will assist a
user in determining how seasonal patterns might influence different rainfall parameters that are
relevant to a particular NFS study. It was not considered feasible to attempt a regional
generalization of wet/dry seasonal effects, because of the differences indicated by the sample
locations examined.
17
-------
3 RESULTS
3.1 Summary of Storm Event Statistics in the United States
This section presents a summary of the storm event statistics developed from a statistical
analysis of a national cross-section of rain gage locations. The geographical distribution of the
gages selected is shown on the map presented in Figure 6. Table 4 lists the gage name, number,
elevation, latitude and longitude, together with information on the length of the record. It also
presents the period of record analyzed for each gage. Appendix provides a summary sheet for each
gage analyzed, with a more complete set of statistics. It was not practical to include a complete
output of all of the summaries due to the large output that can be generated by the SYNOP
program.
There were a number of guidelines applied in selecting the gages to be analyzed. Because
of current emphasis on urban nonpoint source issues, the locations sought were those either in or
near large metropolitan areas. Project resources allowed the analysis of 163 gages at various
location throughout the US. Our guideline included selecting 2 gages per state, with a larger
number selected where the size of the state or climatic variation within the state argued for more,
and a smaller number where the state was small or population centers were few. The guidelines
resulted in a denser spatial matrix in the east where most of the population is located, and therefor a
relatively good delineation. To compensate for the relatively sparse spatial matrix in the western
regions that resulted from the emphasis on population centers, additional gages were analyzed to
fill in spatial gaps.
The statistical characteristics of storm events computed using an IET of 6 hours and a
minimum storm volume of 0.10 inches are summarized for the national matrix of rain gages. As
addressed in the following section, for one state (North Carolina) a dense statewide matrix of 30
gages was analyzed. The national summary incorporates only 7 of these gages, to avoid
introducing a bias to the grouping analysis discussed below, and to permit an evaluation of how
well a small number of gages can represent an entire state.
Table 5 presents results for both annual precipitation characteristics, and for the statistics of
individual storm events.
• Annual Statistics: The analysis program counts the number of independent storm events
and the total volume of precipitation for each year analyzed, and averages the annual
values obtained. The COV measures the variability of the event counts and annual
volumes obtained for the separate years.
Independent Storm Event Statistics: Individual event values for duration, volume,
average intensity and DELTA are computed for each of the storm events in the period of
record. The arithmetic average of the individual values is listed as the "Avg". The
standard deviation of the individual values is also computed. This value is divided by the
average to compute the coefficient of variation listed under the column heading COV.
Accordingly, the listing provides the parameter magnitude for the mean storm and a
measure of the event-to-event variability of the parameter, based on all storms in the
record analyzed.
18
-------
Figure 6. Map showing the location of selected rainfall gages.
(Gages for Hawaii and Alaska not shown)
-------
State Location
AK
AL
AL
AR
AR
AZ
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
CA
CO
CO
CO
CO
CT
CT
DE
a
a
a
a
a
GA
GA
HI
IA
IA
IA
ID
ID
IL
IL
IN
IN
KS
KS
KY
KY
LA
LA
LA
MA
MA
MO
ME
Ml
Ml
MN
MN
MO
MO
MO
MS
MT
MT
MT
MT
NC
NC
NC
NC
NC
NC
NC
ND
ND
NE
NE
NH
BIRMINGHAM FAAAP
MONTGOMERY WSO AP
FORT SMITH
LITTLE ROCK FAA AP
PETRIFIED FOREST
PHOENIX WSFO AP
TUCSON WSO AP
FRESNO WSOAP
BAKERSFIELD WSO AP
BLYTHE
LOS ANGELES WSO AP
OAKLAND WSO AP
REDDING 5 SSE
SACRAMENTO FAA AP
SAN DIEGO WSOAP
SAN FRANCISCO V\
DENVER WSFO AP
GRAND JUNCTIOI
PUEBLO WSO AP
FORT COLLINS
HARTFORD BRAII
BRIDGEPORT WSO AP
WILMINGTON WSOAP
JACKSONVILLE W:
MIAMI WSCMOAP
ORLANDO WSO AP
ST PETERSBURG
TALLAHASSEE WSOAP
COLUMBUS WSO AP
ATLANTA WSOAP
HONOLULU WSFO
DES MOINES WSFO AP
DUBUQUE WSO AP
SIOUX CENTER 2 SE
BOISE WSFO AP
POCATELLO WSFO AP
CHICAGO MIDWAY AP:
SPRINGFIELD WSOAP
FORT WAYNE WSOAP
INDIANAPOLIS WSFO
COLBY 1 SW
EMPORIA
LEXINGTON WSOAP
LOUISVILLE WSFO
NEWORLEAr.
ALEXANDRIA
SHREVEPORT WSOAP
BOSTON WSO AP
WORCESTER WSO AP
BALTIMORE WSOAP
PORTLAND WSMOAP
DETROIT METRO \
LANSING WSOAP
MINN-ST PAUL WSO AP
DULUTH
ST LOUIS WSCMOAP
SPRINGFIELD WSOAP
KANSAS CITY UofMO
JACKSON WSFO AP
GREAT FALLS WS(
BILLINGS WSO AP
BUTTE 8S
GLASGOW WSO AP
CAPE HATTERAS WSO
CHARLOTTE WSO AP
DALTON
ELIZABETH CITY
ASHFORD
RALEIGH DURHA
WILMINGTON WSO AP
FARGO WSO AP
BISMARCK WSFOAP
LINCOLN WSO AP
NORTH PLATTE V
CONCORD WSOAP
Table 4. Ustlng of Selected Rainfall Gages Used In the Analysis
Gage No.
;MOAP 280
AP 831
SOAP 5550
2574
AP 4248
5TN.P. 6468
P 6481
8820
3257
;O AP 442
925
iOAP 5114
3 6335
7295
AAP 7630
AP 7740
WSO AP 7769
P 2220
J WSO AP 3488
6740
3005
JARD FLD 3451
OAP 806
D AP 9595
'SOAP 4358
1 5663
P 6638
7886
SO AP 8758
AP 2166
' 451
)703AP 1919
:O AP 2203
P 2367
: SE 7700
1022
OAP 7211
YAP3SW 1577
OAP 8179
OAP 3037
5FO 4259
1699
2543
AP 4746
D 4954
'SCMOAP 6660
98
5OAP 8440
770
OAP 9923
AP 465
DAP 6905
WSOAP 2103
' 4641
SOAP 5435
2248
)AP 7455
OAP 7976
)f MO 4379
\P 4472
ICMOAP 3751
5 807
1309
AP 3558
WSO 1458
JAP 1690
2230
2719
312
dWSFOAP 7069
0 AP 9457
2859
AP 819
4795
/VSOAP 6065
\P 1683
Latitude
61:10:00
33:34:00
32:18:00
35:20:00
34:44:00
34:49:00
33:26:00
32:08:00
36:46:00
35:25:00
33:37:00
33:56:00
37:45:00
4030:00
38:31 :00
32:44:00
37:37:00
39;46;00
39:06:00
38:17:00
40:35:00
41:44:00
41:10:00
39:40:00
30:30:00
25:48:00
28:33:00
27:46:00
30:23:00
3231 :00
33:39:00
2120:00
41:32:00
4224:00
43:03:00
4334:00
42:55:00
41:44:00
39:51 .-00
41 :00:00
39:44:00
3923:00
38:20:00
38:02:00
38:11:00
29:59:00
31:19:00
3228:00
42:22:00
42:16:00
39:11:00
4339:00
42:14:00
42:46:00
44:53:00
46:50:00
38:45:00
37:14:00
37:02:00
32:19:00
4729:00
45:48:00
4554:00
48:13:00
35:16:00
35:13:00
36:18:00
36:19:00
35:53:00
35:52:00
34:16:00
46:54:00
46:46:00
40:51:00
41 .-08:00
43:12:00
Longitude
.150:01:00
086:45:00
086:24:00
194:22:00
092:14:00
109:53:00
112:01:00
110:57:00
119:43:00
119:03:00
114:43:00
118:24:00
122:12:00
122:22:00
121:30:00
117:10:00
12223:00
104;52;00
108:33:00
104:31:00
105:05:00
072:39:00
073:08:00
075:36:00
081:42:00
080:18:00
081:20:00
082:38:00
084:22:00
084:57:00
084:26:00
15755:00
093:39:00
090:42:00
096:09:00
116:13:00
11236:00
087:46:00
089:41:00
085:12:00
086:16:00
101:04:00
096:11:00
084:36:00
085:44:00
090:15:00
092:28:00
093:49:00
071:02:00
071:52:00
076:40:00
070:19:00
083:20:00
084:36:00
093:13:00
092:11:00
090:22:00
093:23:00
9435:00
090:05:00
111:22:00
108:32:00
11233:00
106:37:00
075:33:00
080:56:00
080:24:00
076:12:00
081:57:00
078:47:00
077:54:00
096:48:00
100:46:00
096:45:00
100:41:00
071 :30:00
Elevation
110
630
220
450
260
5450
1110
2580
330
500
390
110
10
430
20
10
10
5280
4850
4640
5000
20
10
80
30
10
110
10
60
450
1010
10
960
1070
1360
2840
4450
620
590
800
790
3170
1210
970
480
0
90
250
20
990
200
60
630
840
830
1430
540
1270
850
330
3660
3570
5700
2280
10
700
1010
10
1760
380
70
900
1650
1190
2780
350
Beginning
Year
1963
1949
1949
1949
1949
1949
1949
1949
1949
1949
1954
1949
1949
1959
1949
1949
1949
1949
1949
1955
1949
1949
1949
1949
1950
1949
1949
1949
1949
1949
1949
1963
1949
1951
1949
1949
1949
1949
1949
1949
. 1949
1951
1951
1949
1949
1954
1949
1949
1949
1949
1949
1949
1960
1949
1949
1949
1949
1949
1949
1964
1949
1949
1954
1958
1958
1949
1949
1955
1949
1949
1950
1949
1949
1949
1949
1949
Ending
Year
1987
1987
1987
1987
1975
1987
1987
1987
1987
1987
1987
1987
1984
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1983
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1973
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1969
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
Total
Years
25
39
39
39
27
39
39
39
39
39
34
39
36
29
39
39
39
39
39
33
39
39
39
39
38
39
35
39
39
39
39
25
39
37
39
39
39
39
39
39
39
37
23
39
39
34
39
39
39
39
39
39
28
39
39
39
39
39
21
24
39
39
34
30
30
39
39
33
39
39
38
39
39
39
39
39
?n
-------
Table 4. Listing of Selected Rainfall Gages Used In the Analysis
Slate Location
NJ ATLANTIC CITY WSO AP
NJ NEWARK WSO AP
NM ALBUQUERQUE WSFO AP
NM ROSWELL WSO AP
NV LAS VEGAS WSO AP
NV RENO WSFO AP
NV ELKOFAA AP
NV SMOKEY VALLEY
NY BUFFALO WSFO AP
NY NEW YORK CENTRAL PARK
NY ROCHESTER WB AP
NY SYRACUSE WB AP
OH COLUMBUS WSO AP
OH YOUNGSTOWN WSO AP
OK OKLAHOMA CITY WS FO AP
OR MEDFORD WSO AP
OR PORTLAND WSFO A P
OR SALEM WSO AP
OR LAKEVIEW 2 NNW
OR PENDELTON WSO AP
PA ERIE WSO AP
PA PHILADELPHIA WSCMO AP
PA PITTSBURGH WSCMO2 AP
SC CHARLESTON WSO Cl
SC COLUMBIA WSFO AP
SD RAPID CITY WSO AP
SD MOBRIDGE
SD SIOUX FALLS WSFO AP
TN BRISTOL WSO AP
TN CHATTANOOGA WSO AP
TN KNOXVILLEWSOAP
TN MEMPHIS FAA-AP
TN NASHVILLE WSO AP
TX BROWNSVILLE WSO AP
TX ABILENE WSO AP
TX CORPUS CHRISTI WSO AP
TX AMARILLOWSOAP
TX DALLAS FAA AP
TX a PASO WSO AP
TX FT WORTH MEACH WSO AP
TX AUSTIN WSO AP
TX HOUSTON-ALIEF
TX HOUSTON-SATSUMA
TX LUBBOCKWSFOAP
TX MIDLAND/ODESSA WSO AP
TX SAN ANTONIO WSFO
UT SALT LAKE CITY NWSFO AP
UT GREEN RIVER
UT ST GEORGE
VA LYNCHBURGWSOAP
VA NORTHFOLKWSOAP
VA WASH NATL WSCMO AP
VT BURLINGTON WSO AP
WA SEATTLE TAG WSCMO AP
WA SPOKANE WSO AP
WA YAKIMAWSOAP
Wl GREEN BAY WSO AP
Wl MADISON WSO AP
Wl MILWAUKEE WSO AP
WV CHARLESTON WFSO AP
WY CASPER WSO AP
WY MUD SPRINGS
WY PATHFINDER DAM
Gage No.
311
6026
234
7609
4436
6779
2573
7620
1012
5801
7167
8383
1786
9406
6661
5429
6751
7500
4670
6546
2682
6889
6993
1549
1939
6937
5691
7667
1094
1656
4950
5954
6402
1136
16
2015
211
2244
2797
3284
428
4311
4329
5411
5890
7945
7598
3418
7516
5120
6139
8906
1081
7473
7938
9465
3269
4961
5479
1570
1570
6597
7105
Latitude
39:27:00
40:42:00
35:03:00
33:24:00
36:05:00
39:30:00
40:50:00
38:47:00
42:56:00
40:47:00
43;07;00
43:07:00
40:00:00
41:15:00
35:24:00
42:23:00
45:36:00
44:55:00
42:13:00
45:41 :00
42:05:00
39:53:00
40:30:00
32:47:00
33:57:00
44:03:00
45:34:00
43:34:00
36:29:00
35:02:00
35:48:00
35:03:00
36:07:00
25:54:00
3226:00
27:46:00
35:14:00
32:51 :00
31 :48:00
32:49:00
30:18:00
29:43:00
29:56:00
33:39:00
31 :57:00
29:32:00
40:47:00
39:00:00
37:07:00
3750:00
36:54:00
38:51:00
4428:00
47:27:00
47:38:00
4634:00
44:29:00
43:08:00
42:57:00
3822:00
42:55:00
41:19:00
4228:00
Longitude
074:34:00
074:10:00
106:37:00
104:32:00
115:10:00
119:47:00
115:47:00
117:10:00
078:44:00
073:58:00
077;40;00
076:07:00
082:53:00
080:40:00
097:36:00
122:53:00
122:36:00
123:01:00
120:22:00
118:51:00
080:11:00
075:14:00
080:13:00
079:56:00
081 :07:00
103:04:00
10027:00
096:44:00
082:24:00
085:12:00
084:00:00
090:00:00
086:41:00
097:26:00
099:41 :00
097:30:00
101:42:00
096:51:00
10624:00
09721:00
097:42:00
095:36:00
095:38:00
101:49:00
102:11:00
09828:00
11157:00
110:10:00
113:34:00
079:12:00
074:12:00
077:02:00
073:09:00
122:18:00
117:32:00
12032:00
088:08:00
089:20:00
08754:00
08136;00
10628:00
108:55:00
106:51:00
Elevation
140
30
5310
3640
2160
4400
5080
5630
710
130
550
420
810
1180
1280
1300
20
200
4780
1490
730
10
1150
10
210
3160
1700
1420
1530
680
950
270
580
20
1760
40
3590
440
3920
670
600
70
120
3250
2860
790
4220
4070
2760
920
20
70
330
450
2360
1060
680
860
670
1020
5340
6740
5930
Beginning
Year
1959
1949
1949
1948
1950
1949
1949
1954
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1950
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1976
1954
1949
Ending
Year
1987
1987
1987
1972
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1986
1987
1987
Total
Years
29
39
39
25
38
39
39
34
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
38
39
39
39
39
39
39
39
39
39
39
39
39
11
34
39
21
-------
TABLE 5. Storm Event Statistics on the National Scale
Annual Statistics
Rain Gage
Location
NORTH EAST
VT BURLINGTON
NH CONCORD
CT HARTFORD
NY ROCHESTER
NY SYRACUSE
NY BUFFALO
OH COLUMBUS
OH YOUNGSTOWN
PA ERIE
PA PITTSBURGH
WV CHARLESTON
Gage
No.
1081
1683
3451
7167
8383
1012
1786
9406
2682
6993
1570
AVG =
COV =
No. Storms/yr
Avq
69
62
55
67
75
75
70
74
77
70
77
70
0.10
cov
0.11
0.09
0.23
0.11
0.11
0.10
0.11
0.10
0.17
0.18
0.11
0.13
0.34
Precip in/yr
Avq
31.42
35.17
36.10
28.62
35.34
34.86
34.93
34.54
37.05
32.77
39.95
34.61
0.09
COV
0.17
0.18
0.22
0.15
0.22
0.14
0.15
0.15
0.23
0.20
0.17
0.18
0.18
Duration (M
Avq
11.5
12.0
10.9
11.2
12.2
12.0
10.0
10.4
11.0
11.0
10.9
11.2
0.06
COV
0.77
0.74
0.78
0.83
0.83
0.81
0.82
0.81
0.83
0.81
0.85
0.81
0.04
Intensity fin/hh
Avq
0.059
0.061
0.076
0.059
0.062
0.059
0.078
0.073
0.067
0.067
0.076
0.067
0.11
COV
1.20
1.18
1.06
1.21
1.41
1.26
1.25
1.25
1.20
1.23
1.31
1.23
0.07
Volume (in^
Avg
0.45
0.56
0.65
0.43
0.47
0.47
0.50
0.47
0.48
0.47
0.52
0.50
0.12
COV
0.89
0.95
0.98
0.93
0.97
0.99
0.94
0.93
1.01
0.90
0.95
0.95
0.04
I2EUA fhrt
Avg
128
143
147
133
118
119
127
121
112
126
115
126.1
0.09
COV
0.90
0.86
0.92
0.97
0.89
0.92
0.97
0.93
0.93
1.13
0.92
0.94
0.08
NORTH EAST - COASTAL
ME PORTLAND
MA BOSTON
MA WORCESTER
CT BRIDGEPORT
NY NEW YORK CITY
NJ NEWARK
6905
770
9923
806
5801
6026
AVG =
COV =
64
62
65
62
63
63
63
0.02
0.11
0.11
0.12
0.11
0.13
0.12
0.12
0.07
41.77
41.49
45.07
39.35
42.67
38.25
41.43
0.06
0.20
0.21
0.20
0.24
0.22
0.20
0.21
0.08
12.6
12.3
12.7
10.5
11.0
11.1
11.7
0.08
0.76
0.79
0.80
0.73
0.76
0.77
0.77
0.03
0.065
0.066
0.070
0.076
0.079
0.072
0.071
0.07
1.06
0.94
1.06
1.03
1.10
1.10
1.05
0.06
0.65
0.67
0.69
0.64
0.67
0.61
0.66
0.04
1.04
1.08
1.00
1.03
1.06
0.94
1.03
0.05
139
144
134
143
140
139
140
0.03
0.83
0.85
0.80
0.91
0.92
0.91
0.87
0.06
-------
Annual Statistics
Independent Storm Event Statistics
Rain Gage
Location
MID ATLANTIC
NJ ATLANTIC CITY
PA PHILADELPHIA
DE WILMINGTON
MD BALTIMORE
VA LYNCHBURG
VA WASHINGTON DC
VA NORFOLK
NC ASHFORD
NC CHARLOTTE
NC RALEIGH-DURHAM
NC DALTON
NC ELIZABETH CITY
EAST GULF
FL ORLANDO
FL ST PETERSBURG
FL MIAMI
FL TALLAHASSEE
LA ALEXANDRIA
LA NEW ORLEANS
Gage
No.
311
6889
9595
465
5120
8906
6139
312
1690
7069
2230
2719
AVG =
COV =
6638
7886
5663
8758
98
6660
AVG =
COV =
Precip in/yr
Avq
60
62
59
60
62
61
63
58
63
62
55
56
60
0.04
69
59
78
72
57
70
68
0.12
cov
0.13
0.12
0.17
0.11
0.13
0.12
0.15
0.26
0.13
0.12
0.20
0.18
0.15
0.29
0.22
0.20
0.16
0.12
0.18
0.14
0.17
0.22
Avq
38.80
39.68
38.24
39.41
38.26
37.46
42.28
40.9
40.79
40.12
38.1
41.3
39.61
0.04
47.15
46.86
55.17
62.95
51.43
58.70
53.71
0.12
COV
0.16
0.16
0.23
0.19
0.20
0.18
0.28
0.29
0.16
0.12
0.24
0.21
0.20
0.25
0.26
0.25
0.23
0.25
0.18
0.21
0.23
0.13
Duration (hrt
Avg
10.0
10.3
10.6
10.6
10.9
10.0
9.9
9.9
9.5
9.6
7.8
7.7
9.7
0.10
5.9
5.5
6.0
7.1
6.5
7.3
6.4
0.11
COV
0.76
0.76
0.74
0.84
0.83
0.83
0.87
0.90
0.91
0.86
0.88
0.89
0.84
0.07
1.16
1.06
1.06
1.00
1.01
0.99
1.05
0.06
Intensity fin/hr)
Avg
0.087
0.085
0.083
0.088
0.085
0.094
0.098
0.101
0.098
0.099
0.127
0.130
0.098
0.16
0.169
0.209
0.163
0.172
0.190
0.165
0.178
0.10
COV
1.11
1.19
1.13
1.22
1.16
1.25
1.17
1.16
1.11
1.10
1.10
1.13
1.15
0.04
1.12
0.98
1.02
1.03
0.92
1.11
1.03
0.07
Volume (in)
Avg
0.65
0.64
0.64
0.65
0.62
0.62
0.67
0.69
0.65
0.65
0.69
0.73
0.66
0.05
0.69
0.80
0.71
0.87
0.91
0.83
0.80
0.11
COV
0.99
0.98
0.96
1.04
0.98
1.00
1.11
1.05
1.01
0.94
1.08
1.08
1.02
0.05
1.25
1.12
1.33
1.17
1.10
1.14
1.19
0.07
DELTA (hrt
Avg
-
149
144
146
149
142
148
138
141
141
144
147
145
144
0.02
126
145
115
119
151
126
130
0.11
COV
0.87
0.96
0.90
0.96
0.95
0.97
0.90
1.56
1.01
0.94
1.12
1.03
1.01
0.18
1.32
1.39
1.56
1.11
1.06
1.08
1.25
0.16
-------
TABLE 5. Storm Event Statistics on the National Scale (continued)
Annual Statistics
Rain Gage
Location
SOUTHEAST
GA COLUMBUS
GA ATLANTA
AL BIRMINGHAM
AL MONTGOMERY
FL JACKSONVILLE
SC CHARLESTON
SC COLUMBIA
NC CAPE HATTERAS
NC WILMINGTON
TN CHATTANOOGA
LA SHREVEPORT
MS JACKSON
AR LITTLE ROCK
TN MEMPHIS
EAST TEXAS
OK OKLAHOMA CITY
TX BROWNSVILLE
TX CORPUS CHRISTI
TX DALLAS
TX FT WORTH
TX AUSTIN
TX SAN ANTONIO
TX HOUSTON-ALIEF
TX HOUSTON-SATS
Gage
No.
2166
451
831
5550
4358
1549
1939
1458
9457
1656
8440
4472
4248
5954
AVG =
COV =
6661
1136
2015
2244
3284
/a45
4311
4329
AVG =
rnv -
Precip in/yr
Avg
68
67
69
65
69
63
61
67
69
71
54
67
60
64
65
0.07
44
35
38
40
38
45
39
46
46
41
n m
cov
0.12
0.12
0.18
0.12
0.13
0.12
0.21
0.17
0.11
0.11
0.22
0.12
0.16
0.16
0.15
0.25
0.17
0.22
0.24
0.28
0.23
0.14
0.22
0.26
0.26
0.22
n ">r\
Avq
48.79
46.87
50.71
49.05
50.02
44.57
45.50
52.33
51.79
50.90
42.27
55.01
48.36
50.28
49.03
0.07
31.39
24.73
28.85
31.32
28.31
31 .46
28.57
39.26
37.08
31.22
n -\A
COV
0.18
0.15
0.22
0.20
0.18
0.18
0.28
0.22
0.13
0.18
0.27
0.23
0.21
0.20
0.20
0.20
0.24
0.30
0.30
0.32
0.28
0.20
0.31
0.33
0.30
0.29
n 1/1
Duration (hr)
Avg
8.0
9.3
8.4
8.0
7.4
8.2
9.1
9.2
8.8
10.0
8.8
8.2
9.4
9.2
8.7
0.08
8.3
8.2
8.2
7.6
6.8
8.4
8.9
7.7
7.7
8.0
n no
COV
0.93
0.89
0.89
0.91
1.04
0.91
0.93
0.90
0.90
0.85
0.94
0.95
0.88
0.90
0.9
0.05
0.87
1.05
1.06
1.00
0.96
0.91
0.95
1.00
0.97
0.97
n nc
Intensity (in/hr)
Avq
0.131
0.112
0.121
0.135
0.142
0.123
0.121
0.108
0.119
0.099
0.124
0.140
0.117
0.123
0.122
0.10
0.123
0.135
0.141
0.148
0.155
0.119
0.125
0.144
0.139
0.137
n nn
COV
1.08
1.09
1.04
1.02
1.10
1.33
1.21
0.96
1.18
1.04
1.01
1.02
1.08
1.10
1.09
0.09
1.05
1.20
1.14
1.05
1.04
1.01
1.10
1.11
1.04
1.08
ft f\C
I I fc— » *_»! 11 V^ IUI IO LIVv?
Volume (in)
Avg
0,72
0.70
0.73
0.76
0.73
0.71
0.74
0.79
0.75
0.72
0.79
0.82
0.80
0.79
0.75
0.05
0.71
0.71
0.77
0.78
0.74
0.70
0.73
0.86
0.80
0.76
n r\-r
COV
1.06
0.99
1.10
1.07
1.27
1.17
1.05
1.21
1.19
1.05
1.07
1.09
1.05
1.02
1.10
0.07
1.07
1.44
1.39
1.07
1.00
1.13
1.16
1.17
1.17
1.18
/% -4 n
EELIA. flirt
Avg
131
133
124
137
130
141
140
130
129
125
161
133
147
138
136
0.07
206
262
241
213
223
200
230
169
170
213
r\ -4 A
COV
1.10
1.00
1.01
1.01
1.22
1.08
1.04
0.95
0.98
0.96
1.03
1.00
1.02
0.97
1.03
0.07
1.29
1.44
1.40
1.20
1.27
1.33
1.32
1.14
1.11
1.28
ft f*r\
-------
Annual Statistics
Independent Storm Event Statistics
Rain Gage
Location
CENTRAL
KY LEXINGTON
KY LOUISVILLE
TN BRISTOL
TN KNOXVILLE
TN NASHVILLE
MO SPRINGFIELD
AR FORT SMITH
NORTH CENTRAL
ND FARGO
SD SIOUX FALLS
MN MINN-ST PAUL
IA DESMOINES
IA DUBUQUE
NE LINCOLN
KS EMPORIA
MOST LOUIS
MO KANSAS CITY
Ml DETROIT
Ml LANSING
IN FORT WAYNE
IN INDIANAPOLIS
IL CHICAGO
IL SPRINGFIELD
MN DULUTH
Wl GREEN BAY
Wl MADISON
Wl MILWAUKEE
Gage
No.
4746
4954
1094
4950
6402
7976
2574
AVG =
COV =
2859
7667
5435
2203
2367
4795
2543
7455
4379
2103
4641
3037
4259
1577
8179
2248
3269
4961
5479
AVG =
COV =
Precip in/yr
Avg
72
69
74
74
70
60
55
68
0.11
37
42
52
53
58
48
46
60
46
63
58
66
67
59
60
55
55
56
58
55
0.15
cov
0.12
0.13
0.13
0.10
0.14
0:16
0.18
0.14
0.19
0.17
0.18
0.16
0.16
0.19
0.18
0.23
0.13
0.23
0.11
0.14
0.10
0.12
0.18
0.15
0.14
0.13
0.15
0.16
0.16
0.22
Avq
42.71
41.65
38.97
44.57
46.03
39.74
39.43
41.87
0.06
17.79
22.56
25.52
30.09
35.59
28.81
32.21
34.73
31.34
30.05
26.72
33.30
37.83
33.38
33.00
27.84
26.28
29.41
30.02
29.81
0.16
COV
0.18
0.18
0.15
0.16
0.20
0.23
0.22
0.19
0.16
0.25
0.24
0.25
0.23
0.28
0.25
0.31
0.22
0.27
0.16
0.18
0.18
0.15
0.22
0.17
0.20
0.18
0.17
0.20
0.22
0.21
Duration (hh
Avg
9.8
9.5
9.4
9.3
9.1
9.0
8.6
9.2
0.04
9.3
9.6
9.8
9.8
9.7
9.5
8.5
8.9
7.6
9.8
10.2
9.7
9.7
9.2
9.1
11.6
9.8
9.5
10.1
9.5
0.08
COV
0.83
0.85
0.83
0.84
0.88
0.85
0.85
0.85
0.02
0.91
0.90
0.85
0:84
0.83
0.87
0.80
0.85
0.84
0.79
0.80
0.80
0.82
0.84
0.86
0.85
0.81
0.79
0.80
0.83
0,04
Intensity (in/hr)
Avg
0.089
0.092
0.087
0.090
0.103
0.104
0.113
0.097
0.10
0.084
0.091
0.080
0.089
0.091
0.095
0.110
0.096
0.129
0.075
0.070
0.079
0.087
0.093
0.090
0.068
0.074
0.084
0.076
0.087
0.16
COV
1.09
1.13
1.24
1.04
1.06
1.07
0.99
1.09
0.07
1.26
1.20
1.34
1.25
1.09
1.15
1.17
1.14
1.09
1.27
1.22
1.17
1.20
1.19
1.15
1.26
1.18
1.24
1.22
1.20
0.05
Volume (in)
Avg
0.60
0.60
0.53
0.60
0.66
0.66
0.72
0.62
0.10
0.48
0.54
0.49
0.57
0.61
0.60
0.70
0.58
0.67
0.48
0.46
0.50
0.56
0.57
0.55
0.51
0.47
0.53
0.52
0.55
0.12
COV
0.97
1.02
0.91
0.98
1.04
1.04
1.07
1.00
0,05
1.18
1.02
1.09
1.02
1.07
1.03
1.06
1.01
1.00
0.94
0.94
0.91
0.99
1.05
1.05
1.03
0.92
0.99
0.97
1.01
0.06
DELTA fhr)
Avg
124
128
120
119
127
148
163
133
0.12
251
220
175
172
149
196
192
149
165
141
149
135
133
148
150
164
162
161
155
167
0.18
COV
0.97
0.95
0.92
0.92
0.97
1.10
1.09
0.99
0.08
1.44
1.42
1.31
1.24
1.11
1.40
1.39
1.10
1.20
0.97
1.03
0.96
1.02
1.05
1.08
1.13
1.12
1.14
1.07
1.17
0.13
-------
TABLE 5. Storm Event Statistics on the National Scale (continued)
Annual Statistics
Independent Storm Event Statistics
Rain Gage
Location
NORTH WEST INLAND
WA SPOKANE
WA YAKIMA
OR PENDLETON
ID BOISE
ID POCATELLO
UT SALT LAKE CITY
MT GREAT FALLS
MT BILLINGS
MT BUTTE
MT GLASGOW
SD RAPID CITY
SD MOBRIDGE
ND BISMARCK
NE N.PLATTEWSO
WY MUD SPRINGS
WY PATHFINDER DAM
WY CASPER
CO DENVER
CO FT COLLINS
WEST TEXAS
KS COLBY
TX LUBBOCK
TX MIDLAND/ODESSA
TX AMARILLO
TX ABILENE
Gage
No.
7938
9465
6546
1022
7211
7598
3751
807
1309
3558
6937
5691
819
6065
6597
7105
1570
2220
3005
AVG =
COV =
1699
5411
5890
-""I
16
AVG =
COV =
Precip in/yr
Avg
46
23
35
33
31
39
35
33
30
23
34
31
32
37
18
22
33
32
26
31
0.21
27
^1
..4
33
35
30
0.15
cov
0.18
0.28
0.16
0.20
0.27
0.24
0.20
0.19
0.31
0.18
0.16
0.23
0.17
0.20
0.40
0.26
0.20
0.21
0.32
0.23
0.28
0.39
0.25
0.29
0.23
0.18
0.27
0.29
Avg
14.57
6.73
9.88
9.92
9.07
14.13
13.26
12.72
10.32
8.88
14.27
13.64
13.66
18.34
5.21
7.19
11.66
13.74
11.25
11.50
0.28
14.44
17.67
13.32
18.33
22.66
17.28
0.21
COV
0.20
0.28
0.21
0.25
0.33
0.25
0.30
0.28
0.33
0.33
0.24
0.31
0.23
0.27
0.34
0.27
0.31
0.29
0.41
0.29
0.18
0.39
0.27
0.43
0.29
0.27
0.33
0.23
Duration (hr)
Avg
11.6
10.0
10.1
10.5
10.3
10.6
12.9
12.3
8.6
9.8
10.4
9.0
10.2
8.7
7.9
11.0
12.4
11.2
10.4
10.4
0.13
6.7
7.5
7.6
7.5
7.9
7.4
n.nfi
COV
0.70
0.65
0.71
0.72
0.74
0.71
0.81
0.87
0.96
0.90
0.94
0.87
0.91
0.95
0.81
0.74
0.82
0.89
0.84
0.82
0.12
0.86
1.00
1.07
0.98
0.98
0.98
nnn
Intensity (in/hr)
Avg
0.034
0.037
0.036
0.037
0.038
0.045
0.045
0.053
0.073
0.066
0.076
0.084
0.077
0.098
0.057
0.043
0.048
0.067
0.062
0.057
0.33
0.126
0.116
0.121
0.114
0.128
0.12
nns
COV
0.84
1.06
0.86
0.88
0.83
0.95
1.31
1.62
1.17
1.31
1.42
1.44
1.33
1.19
1.06
1.33
1.56
1.29
1.37
1.20
0.21
1.11
1.09
1.28
1.11
1.06
1.13
nna
Volume (in)
Avg
0.31
0.29
0.28
0.30
0.29
0.37
0.38
0.38
0.35
0.39
0.42
0.45
0.42
0.49
0.29
0.33
0.35
0.43
0.43
0.37
0.17
0.53
0.57
0.55
0.55
0.65
0.57
n nn
COV
0.73
0.74
0.76
0.76
0.76
0.81
1.25
0.99
0.80
1.11
1.02
1.00
0.93
0.97
0.80
1.00
1.06
1.06
1.17
0.93
0.17
0.97
1.10
1.10
1.14
1.04
1.07
n nfi
DELTA (hr)
Avg
190
383
251
269
289
231
261
277
311
417
275
271
290
249
506
399
274
290
340
304
0.25
312
296
369
275
261
302
n 1/1
COV
1.32
1.47
1.32
1.46
1.30
1.43
1.25
1.21
1.62
1.59
1.62
1.74
1.55
1.60
1.71
1.34
1.01
1.23
1.39
1.43
0.13
1.77
1.66
1.42
1.47
1.35
1.53
n 11
-------
Annual Statistics
Independent Storm Event Statistics
Rain Gage
Location
SOUTHWEST
TX EL PASO
NM ROSWELL
NM ALBUQUERQUE
UT GREEN RIVER
UT ST. GEORGE
CO GRAND JUNCTION
CO PUEBLO
AZ TUCSON
AZ PHOENIX
AZ PET. FOREST NP
WEST INLAND
NV LAS VEGAS
NV RENO
NV ELKO
NV SMOKEY VALLEY
CA BLYTHE
CA BAKERSFIELD
Gage
No.
2797
7609
234
3418
7516
3488
6740
8820
6481
6468
AVG =
COV =
4436
6779
2573
7620
925
442
AVG =
COV =
Precip in/yr
Avg
19
20
22
14
15
25
24
25
16
19
20
0.20
10
18
24
13
6
15.
14
0.44
cov
0.32
0.29
0.24
0.34
0.36
0.27
0.26
0.23
0.29
0.36
0.30
0.16
0.45
0.32
0.35
0.34
0.48
0.34
0.38
0.18
Avg
7.47
9.41
6.92
4.27
5.50
6.76
9.70
10.56
6.77
6.61
7.40
0.26
3.63
6.55
7.04
4.60
2.64
5.02
4.9133
0.34
COV
0.42
0.37
0.30
0.43
0.41
0.35
0,37
0.31
0.44
0.33
0.37
0.14
0.51
0.31
0.43
0.39
0.58
0.36
0.43
0.23
Duration (hr)
Avg
7.4
8.0
6.6
8.9
7.6
9.4
8.5
7.1
8.1
6.5
7.8
0.12
8.8
10.9
10.0
8.9
8.3
9.3
9.4
0.10
COV
0.97
1.07
0.84
0.75
0.83
0.73
0.92
0.90
0.92
0.87
0.88
0.11
0.75
0.78
0.72
0.78
0.77
0.71
0.75
0.04
Intensity (in/hr)
Avg
0.090
0.101
0.079
0.048
0.076
0.044
0.091
0.093
0.085
0.086
0.079
0.24
0.064
0.042
0.043
0.055
0.075
0.048
0.05468
0.23
COV
1.13
1.15
1.13
1.05
1.19
1.15
1.39
1.10
1.23
1.11
1.16
0.08
1.09
1.02
1.32
0.89
1.13
0.93
1.06
0.15
Volume (in)
Avg
0.40
0.46
0.31
0.30
0.36
0.28
0.41
0.42
0.42
0.35
0.37
0.16
0.37
0.36
0.30
0.36
0.45
0.34
0.36
0.14
COV
0.98
1.08
0.77
0.79
0.68
0.70
0.96
0.96
0.95
0.94
0.88
0.15
0.82
0.92
0.89
0.84
0.91
0.81
0.87
0.06
DELTA (hr)
Avg
500
458
419
634
579
370
386
359
579
447
473
0.20
967
498
382
670
1583
617
786
0.56
COV
1.56
1.58
1.38
1.35
1.51
1.21
1.46
1.56
1.46
1.53
1.46
0.08
1.49
1.40
1.49
1.43
1.56
1.89
1.54
0.12
-------
TABLE 5. Storm Event Statistics on the National Scale (continued)
Annual Statistics
Rain Gage
Location
PACIFIC NORTHWEST
WA SEATTLE
OR PORTLAND
OR SALEM
PACIFIC CENTRAL
OR MEDFORD
OR LAKEVIEW
CA REDDING
CA SACRAMENTO
CA OAKLAND
CA SAN FRANCISCO
PACIFIC SOUTHWEST
CA FRESNO
CA LOS ANGELES
CA SAN DIEGO
Gage
No.
7473
6751
7500
AVG =
COV =
5429
4670
7295
7630
6335
7769
AVG =
COV =
3257
5114
7740
AVG =
COV =
Precip in/yr
Avq
71
72
70
71
0.01
40
36
30
28
30
30
32
0.14
23
17
18
19
0.17
cov
0.17
0.14
0.13
0.15
0.14
0.17
0.23
0.34
0.26
0.22
0.25
0.25
0.23
0.27
0.39
0.41
0.36
0.21
Avg
34.31
34.60
38.27
35.73
0.06
17.71
13.06
26.59
16.72
17.06
19.22
18.39
0.24
10.07
11.65
8.97
10.23
0.13
COV
0.21
0.18
0.19
0.19
0.08
0.26
0.27
0.40
0.38
0.32
0.36
0.33
0.18
0.38
0.45
0.44
0.42
0.09
Duration (hrt
Avg
14.6
15.9
17.2
15.9
0.08
12.9
13.4
14.5
13.7
13.3
14.2
13.7
0.04
11.3
11.7
11.8
11.6
0.02
COV
0.78
0.77
0.86
0.80
0.06
0.77
0.73
0.90
0.79
0.79
0.81
0.80
0.07
0.74
0.84
0.75
0.78
0.07
Intensity (in/hrt
Avq
0.036
0.034
0.035
0.035
0.03
0.040
0.032
0.072
0.048
0.048
0.048
0.04797
0.28
0.046
0.063
0.052
0.05363
0.16
COV
0.66
0.80
0.73'
0.73
0.10
0.98
0.94
0.94
0.87
0.69
0.66 .
0.85
0.16
0.74
0.73
0.82
0.76
0.06
Volume (\r\)
Avg
0.48
0.48
0.55
0.50
0.08
0.44
0.37
0.88
0.59
0.57
0.64
0.58
0.31
0.44
0.67
0.51
0.54
0.22
COV
1.07
1.06
1.15
1.09
0.05
1.14
0.93
1.08
1.06
1.01
1.07
1.05
0.07
0.88
1.16
0.89
0.98
0.16
DBJA fhrt
Avg
121
122
126
122.9
0.02
222
230
248
306
295
288
264.7
0.14
389
536
503
475.8
0.16
COV
1.38
1.51
1.61
1.50
0.08
1.63
1.67
2.13
2.00
228
2.26
2.00
0.14
209
2.17
2.00
2.09
0.04
-------
The important information produced by the analysis is represented by the set of parameter
statistics listed for each specific gage location. However, in the belief that the ability to assign
"typical" approximate values for relatively broad regions will be of value in situations where
areawide or regional assessments are desired, we have organized the summary of study results so
that gage locations are placed in a series of regional groups.
The results were arranged by geographical location and then the gages were grouped by
similarities in the overall set of statistical characteristics. A measure of how closely the individual
sites in a group compare (how reasonable are the assigned geographic rainfall zone) is provided by
inspection of the summary at the end of each group. The value of a parameter at a particular site
may be compared with the mean for the group to provide a sense of how well it fits. The
coefficient of variation (COV) for the group provides a measure of the variability in the values of a
parameter at all of the sites in the group.
An attempt was made to make the geographical area assigned to a group as large as
possible, though obviously a greater number of smaller groupings would improve the match within
a zone. The results appear to provide a geographic zone breakdown that will provide reasonable
estimates for broad-scale screening analyses, but the user should recognize that local deviations
could be significant in the western parts of the country. Mountains, deserts, and coastal patterns in
the west result in large differences over small distances. For this part of the country, data are
grouped as suggested by apparent similarities, but the user is cautioned that specific locations
within an apparent grouping might be quite different than the sites analyzed.
Figure 7 shows the selected rainfall "zones" for the continental United States, based on the
sample of rain gages that were analyzed in this study and the gage groupings assigned in Table 6.
This is presented to provide an overview of the number of appreciably different rainfall patterns (as
measured by storm event statistics) that are present, and as a way to graphically summarize the
study results. Table 6 summarizes the "typical" values for the storm event statistics for each of the
zones, which are taken as the group average presented previously in Table 5.
It is re-emphasized here that the required values should be used for screening purposes
only, especially for western states. The SYNOPII program should be used with a local gage for
more reliable results in areas where a local gage has not been analyzed.
The regional groupings presented above can be used as a guide for assessing regional
patterns. A group average may be used in the east to provide an estimate of the characteristics of
an ungaged site. In all cases, especially in the western part of the country, estimates will be best
made by inspecting the specific results for pertinent sites in the list. Obviously, wherever accurate
local estimates are important, the record for a local gage or gages should be analyzed directly.
An informative picture of regional patterns for the storm event parameters (event mean
durations, intensities, volumes, and interval between storms), is provided by a mapped display of
the long term averages. The number of storms per year is a direct reflection of the average interval
between storm events and has been presented instead. Figures 8 through 11 illustrate the national
patterns for each of these parameters, using smoothed contours to reflect broad patterns that ignore
smaller scale spatial variations and localized deviations.
29
-------
PACIFIC
NORTH
WEST
PACIFIC
SOUTHWEST
Figure 7. Rain zones of the United States.
-------
TABLE 6. Typical Vaules of Storm Event Statistics for Zones
Annual Statistics
Independent Storm Event Statistics
RAIN
ZONE
NORTH EAST
NORTH EAST - COASTAL
MIDATLANTIC
CENTRAL
NORTH CENTRAL
SOUTHEAST
EAST GULF
EAST TEXAS
WEST TEXAS
SOUTHWEST
WEST INLAND
PACIFIC SOUTH
NORTHWEST INLAND
PACIFIC CENTRAL
PACIFIC NORTHWEST
No. of Storms
Avq COV
70
63
62
68
55
65
68
41
30
20
14
19
31
32
71
0.13
0.12
0.13
0.14
0.16
0.15
0.17
0.22
0.27
0.30
0.38
0.36
0.23
0.25
0.15
Precip
Avq
34.6
41.4
39.5
41.9
29.8
49.0
53.7
31.2
17.3
7.4
4.9
10.2
11.5
18.4
35.7
in/yr
COV
0.18
0.21
0.18
0.19
0.22
0.20
0.23
0.29
0.33
0.37
0.43
0.42
0.29
0.33
0.19
Duration
Avq COV
11.2
11.7
10.1
9.2
9.5
8.7
6.4
8.0
7.4
7.8
9.4
11.6
10.4
13.7
15.9
0.81
0.77
0.84
0.85
0.83
0.92
1.05
0.97
0.98
0.88
0.75
0.78
0.82
0.80
0.80
Intensity
Avq COV
0.067
0.071
0.092
0.097 :
0.087
0.122
0.178
0.137
0.121
0.079
0.055
0.054
0.057
0.048
0.035
1.23
1.05
1.20
1.09
1.20
1.09
1.03
1.08
1.13
1.16
1.06
0.76
1.20
0.85
0.73
Volume
Avq COV
0.50
0.66
0.64
0.62
0.55
0.75
0.80
0.76
0.57
0.37
0.36
0.54
0.37
0.58
0.50
0.95
1.03
i.01
1.00
1.01
1.10
1.19
1.18
1.07
0.88
0.87
0.98
0.93
1.05
1.09
DELTA
Avq COV
126
140
143
133
167
136
130
213
302
473
786
476
304
265
123
0.94
0.87
0.97
0.99
1.17
1.03
1.25
1.28
1.53
1.46
1.54
2.09
1.43
2.00
1.50
-------
70
40
40
70
OJ
20
18
10
10
20
78
30 40
70
Figure 8. Annual average number of storms.
-------
16
CO
CO
12
10
8
Figure 9. Average storm event duration.
(hours)
-------
0.04
0.04
CO
.0
0.05 o.06
0.08
0.06
0.07
0.
0.06
0.07
0.13
0.14
Figure 10. Average Storm Event Intensity.
-------
0.60
0.60
0.50
0.50
0.60
0.70
0.80
Figure 11. Average Storm Event Volume.
(inches)
-------
The contours indicate a set of rather well defined patterns. Allowing for the modifying
influences of mountains and strong coastal effects, they may be generalized as follows.
• NUMBER OF STORMS (Figure 8) - There is a general east-west gradient for the
average number of storms per year, with an overlying north-south influence immediate!)
adjacent to the west coast. The greatest number of separate storm events per year occui
in the Pacific Northwest and along the Appalachian mountain chain in the east.
• STORM DURATION (Figure 9) - The average storm duration decreases from north tc
south, with a west to east decrease near the west coast.
• STORM INTENSITY (Figure 10) - The basic trend is increasing average intensity frorr
north to south in the eastern part of the country. The Rocky Mountains impose an east-
west influence, but the pattern returns partially to a north-south increasing gradient or
the Pacific coast
• STORM VOLUME (Figure 11) - The general pattern for the average storm volume
appears to be a gradient related to distance from a coast and the influence of mountains.
Both the Gulf and Atlantic influence the pattern in the eastern half of the country
producing a decreasing gradient that is roughly perpendicular to the coastline. In the
west, a coastal influence on the pattern is indicated, but is significantly modified by the
regional variations in climate and topography.
The presence of the differing national patterns for each of the storm event parameters
indicates the problem in identifying very large areas that can be assigned a common set of storm
event descriptors. In the northern half of the country and in the southwest, fairly large areas with
approximately similar rainfall event characteristics can be delineated. On the west coast, such areas
are much smaller.
Whenever possible, analysis of a local rainfall record is the preferred basis for
characterizing local rainfall for use in NPS water quality related assessments. For preliminary
estimates, or for more generalized assessments, one of the following approaches may be used.
• Use the contour plots of the specific event parameters (Figures 8 to 11), to estimate an
approximate value for each parameter. The average interval between storms (DELTA) is
related to the average annual number of storms (NST) as follows:
DELTA = 8760 hr/yr / NST
• Identify the appropriate rain zone from Figure 7, and select the event characteristics from
the average characteristics for the zone, from the list presented in Table 6. Use Table 5 to
examine the differences between specific gages within the zone. This listing arranges the
rain gages into regional groups that correspond to the zones shown on the map.
• Use the tables, elect one or more individual gages that are located near the area of concern.
Use these values to estimate the storm event parameters for the local area.
Even for cases where storm parameters for a local gage are determined by direct analysis of
the gage record, it will be useful to evaluate the results in the context of the data listed in this report
for nearby sites. This will provide a check against the possibility of a distortion in the results
obtained due to data gaps or other imperfections in the original record analyzed. It will also serve
another purpose. There will be situations where differences in rainfall statistics exist for gages that
are relatively close to each other, because of topography or other localized factors.
36
-------
This factor is illustrated by the information summarized in Table 7. Seven different Texas
rain gages, located within a radius of approximately 40 miles of Dallas-Ft. Worth, are compared.
Results are comparable, but exhibit individual differences for most parameters of plus/minus 10
percent of what would be the area average. A similar analysis is also shown for two gages near
Asheville, North Carolina. In this case there is a substantial difference in rainfall for the two
gages.
For four of the Texas gages, separate results are presented in Table 7 for two different
lengths of record to examine the possible effect of longer term trends. It is apparent that the recent
storms have been generally larger in intensity but shorter in duration. Storm volumes have
remained about the same. The summary at the bottom shows the percent difference in the storm
parameters that result from the analysis of different lengths of the available record.
3.2 Summary of Storm Event Statistics in North Carolina
This section presents a summary of the storm event statistics computed for a set of rain
gage locations in a single state. North Carolina was selected for this illustration because its ranges
in geographic features, from inland mountains to coastal shoreline areas, would be expected to
accentuate the variation in rainfall patterns in different parts of the state. The geographical
distribution of the sites selected is shown on the map presented in Figure 12. Table 8 lists the site
name, gage number, elevation, latitude and longitude, together with information on the length of
the record analyzed. The basic guideline applied in selecting the gages within this sample state was
to select gages which adequately represent the different geographic regions of the state (coastal,
piedmont and mountain).
The gages have been grouped as suggested by similarities in the set of statistical
characteristics. In this case the elevation, which correlates closely with distance inland from the
coast, proved to be an effective sorting variable. A measure of how closely the individual sites in a
group compare (how reasonable it is to define a geographic rainfall zone) is provided by inspection
of the mean and COV of all group values for each specific parameter.
Table 9 shows some interesting results regarding the grouped statistics. For example, the
average duration of storm events tends to increase with distance from the coastal zone.
Furthermore, the average event volume and intensity of a storm event tends to decrease with
distance from the coastal zone. In short, storm events appear to be shorter, more intense near the
coast and longer, less intense further inland.
Theoretically, a greater refinement of rainfall gages should produce less variability within
zones when compared to the variability within regional zones generated on a national scale. The
variability (COV) within the regional zones is shown in Table 5 and those for the North Carolina
zones are shown in Table 9. This comparison suggest that the variability within the more refined
North Carolina zones are generally equal to the Central, Mid Atlantic, and Southeastern zones
presented on the national scale.
The advantage of the state level discretization of rainfall statistics is that it provides localized
results allowing more frequent use of this study. State level contour maps can be developed for
each of the individual states, thereby providing greater reliability with the statistics on the localized
scale.
37
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TABLE 7. Examples of the Effect of Local Variation and Length of Record on Storm Event Statistics.
Annual Statistics Event Statistics
Station
Location
TEXAS
Grapevine
Bardwell
Benbrook
Dallas
FWWSOAP
DFWWSC
Maypearl
record
years
76-87
50-87
76-87
66-87
76-87
41-87
76-87
41-87
54-73
75-87
48-80
No. of
Storms
37
38
35
40
40
39
41
41
44
43
37
Annual
Volume
27.84
28.71
28.69
31.24
28.99
28.08
33.13
31.73
31.80
29.94
29.12
Duration
Avq COV
5.8
6.5
5.3
6.7
7.5
7.7
5.6
7.9
8.6
7.5
7.8
0.90
0.91
0.87
0.92
0.88
0.92
0.89
0.96
0.94
0.88
0.90
Intensity
Avq COV
0.171
0.158
0.206
0.164
0.131
0.122
0.201
0.144
0.122
0.136
0.129
0.80
0.94
0.90
0.98
1.09
0.99
0.99
1.08
1.08
1.01
1.12
Volume
Avg COV
0.76
0.75
0.82
0.78
0.72
0.72
0.81
0.78
0.73
0.70
0.78
0.93
1.03
1.08
1.10
1.01
1.06
0.93
1.08
1.05
0.96
1.04
DELTA
Avg COV
231
220
228
210
209
212
211
209
204
207
196
1.20
1.28
1.49
1.35
1.04
1.22
1.18
1.20
1.12
1.26
1.15
NORTH CAROLINA
Asheville
#301
65-87
49-87
65
65
34.73
35.37
9.5
9.6
0.87
0.85
0.083
0.083
1.17
1.18
0.53
0.54
0.97
0.99
136
136
1.07
1.04
Asheville 65-87
#300
67 44.65
10.5 0.90
0.093 1.19
0..67 1.07
132 0.99
PERCENT DIFFERENCE BETWEEN THE LENGTH OF RECORD
TEXAS
Grapevine
Bardwell
Benbrook
Dallas
NORTH CAROLINA
Asheville 301
-2.6
-12.5
2.6
0.0
-3.0
-8.2
3.2
4.4
0.0 -1.8
-10.2 -1.1
-22.0 -5.4
-2.7 -4,3
-29.2 -7.3
-1.0 2.4
7.7 -15
25.1 -8.2
7.9 10.1
39.1 -8.3
0.0 -0.8
1.3 -9.7
5.1 -1.8
0.0 -4.7
3.8 -14
-1.9 -2.0
5.0 -6.3
8.6 10.4
-1.4 -15
1.0 -1.7
0.0 2.9
38
-------
West
West
central
East
West
Number of storms
Annual volume
Average duration
Average intensity
Average volume
Average DELTA
64
44
10.0
.099
.68
134
West
central
58
41
8.8
.118
.70
142
East
central
56
39
8.4
.121
.70
150
East
57
43
7.9
.132
.75
142
Figure 12. Rain zones of North Carolina and average storm event statistics
39
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Table 8. Location and Period of Record for Rain Gages Analyzed in North Carolina
State Location
Gage No.
NC BURLINGTON 3 NNE
NC CAPE HATTERAS WSO '
NC CHARLOTTE WSO AP *
NC DALTON '
NC DOBSON
NC ELIZABETH CITY *
NC ELIZABETHTOWN LOCK 2
NC ELKVILLE
NC ASHEVILLE WSO AP
NC ASHEVILLE
NC ASHFORD *
NC FRANKLINTON
NC GREENSBORO WSO AP
NC GREENVILLE
NC HOBUCKEN BRIDGE
NC BADIN
NC LAKE LURE 2
NC MOREHEAD CITY 2 WNW
NC MOUNT PLEASANT
NC NWILKESBORO 12SE
NC POLKTON 2 NE
NC RALEIGH DURHAM WSFO AP
NC ROARING GAP 1 NW
NC SHELBY 2
NC SNEADS FERRY 2 ENE
NC WILSON 3 SW
NC YADKINVILLE 6 E
NC WILMINGTON WSO AP *
NC MOORESVILE 2 WNW
NC LAURINBURG
These gages are used in the national summary
Latitude
Longitude
Elev Begin Year End Year Yrs
1241
1458
1690
2230
2388
2719
2732
2757
300
301
312
3232
3630
3638
4136
438
4764
5830
5945
6261
6867
7069
7324
7850
8037
9476
9675
9457
5814
4860
36:08:00
35:16:00
35:13:00
36:18:00
36:24:00
36:19:00
34:38:00
36:04:00
35:26:00
35:36:00
35:53:00
36:06:00
36:05:00
35:37:00
35:14:00
35:24:00
35:26:00
34:44:00
35:25:00
36:04:00
35:01:00
35:52:00
36:24:00
35:16:00
34:33:00
35:42:00
36:08:00
34:16:00
35:36:00
34:45:00
079:24:00
075:33:00
080:56:00
080:24:00
080:44:00
076:12:00
078:35:00
081:24:00
082:33:00
082:32:00
081:57:00
078:28:00
079:57:00
077:23:00
076:36:00
080:07:00
082:14:00
076:44:00
080:26:00
080:59:00
080:1 1 :00
078:47:00
081:00:00
081:33:00
077:24:00
077:57:00
080:31:00
077:54:00
080:50:00
079:27:00
640
10
700
1010
1250
10
60
1140
2140
2240
1760
380
890
30
10
530
1040
10
740
1000
310
380
2800
780
10
110
860
70
910
210
1952
1958
1949
1949
1949
1955
1949
1949
1965
1949
1949
1949
1949
1956
1961
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1949
1950
1950
1949
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987
1987 .
1987
1987
1987
36
30
39
39
39
33
39
39
23
39
39
39
39
32
27
39
39
39
39
39
39
39
39
39
39
39
39
38
38
39
40
-------
Annual Statistics
Independent Storm Event Statistics
Rain Gage Location
EAST
NC CAPE HATTERAS
NC ELIZABETH CITY
Gage Elev.
No. feet
1458 10
2719 10
NC HOBUCKEN BRIDGE 4136 10
NC MOREHEAD CITY
NC SNEADS FERRY
NC GREENVILLE
NC ELIZABETHTOWN
NC WILMINGTON
NC WILSON
EAST CENTRAL
NC POLKTON
NC FRANKLINTON
NC RALEIGH-DURHAM
NC BADIN
NC BURLINGTON
NC LAURINBURG
5830 10
8037 10
3638 30
2732 60
9457 70
9476 110
avg =
cov =
6867 310
3232 380
7069 380
438 530
1241 640
4860 210
avg =
cov =
No. of
Avg
67
56
53
56
54
48
54
69
58
57
0.12
57
56
62
59
49
54
56
0.08
Storms
COV
0.17
0.18
0.32
0.24
0.26
0.29
0.23
0.11
0.19
0.22
0.30
0.13
0.17
0.12
0.14
0.27
0.28
0.19
0.39
Precip in/yr
Avg
52.3
41.3
40.4
43.5
42.6
36.5
38.1
51.8
40.2
43.0
0.13
40.9
38.6
40.1
41.5
32.7
42.5
39.4
0.09
COV
0.22
0.21
0.29
0.25
0.26
0.31
0.23
0.13
0.21
0.23
0.22
0.18
0.18
0.12
0.17
0.28
0.63
0.26
0.73
Duration
Avg
9.2
7.7
6.4
7.5
8.7
7.0
7.5
8.8
8.1
7.9
0.12
8.6
7.6
9.6
8.1
8.6
7.9
8.4
0.08
COV
0.90
0.89
0.98
0.89
0.87
0.94
0.88
0.90
0.86
0.90
0.04
0.93
0.91
0.86
0.91
0.88
0.88
0.90
0.03
Intensity
Avg
0.108
0.130
0.170
0.132
0.116
0.150
0.136
0.119
0.125
0.132
0.14
0.121
0.126
0.099
0.124
0.118
0.140
0.121
0.11
COV
0.96
1.13
1.12
0.99
1.04
1.07
1.09
1.18
1.15
1.08
0.07
1.12
0.99
1.10
1.11
1.19
1.31
1.14
0.09
Volume DELTA
Avg
0.79
0.73
0.76
0.77
0.78
0.76
0.70
0.75
0.69
0.75
0.05
0.72
0.69
0.65
0.70
0.67
0.79
0.70
0.07
COV
1.21
1.08
1.14
1.22
1.18
1.03
1.01
1.19
1.00
1.12
0.08
1.00
0.95
0.94
0.99
0.98
1.90
1.13
0.34
Avg
130
145
133
143
149
151
149
129
146
142
0.06
148
152
144
147
159
149
150
0.03
COV
0.95
1.03
1.34
1.29
1.48
1.46
1.27
0.98
1.14
1.22
0.16
1.04
1.07
0.94
1.06
1.14
1.28
1.09
0.10
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TABLE 9. Storm Event Statistics for North Carolina
Annual Statistics
Independent Storm Event Statistics
Rain Gage Location
WEST CENTRAL
NC CHARLOTTE
NC MOUNT PLEASANT
NC SHELBY
NC YADKINVILLE
NC GREENSBORO
NC MOORESVILLE
NC N WILKESBORO
NC DALTON
NC LAKE LURE
NC ELKVILLE
NC DOBSON
WEST
NC ASHFORD
NC ASHEVILLE
NC ASHEVILLE
NC ROARING GAP
Gage Elev.
No. feet
1690 700
5945 740
7850 780
9675 860
3630 890
5814 910
6261 1000
2230 1010
4764 1040
2757 1140
2388 1250
avg =
cov =
312 1760
300 2140
301 2240
7324 2800
avg =
cov =
No. of
Avg
63
57
56
60
63
56
61
55
53
60
56
58
0.06
58
67
65
67
64
0.07
Storms
COV
0.13
0.19
0.16
0.14
0.11
0.20
0.23
0.20
0.34
0.18
0.20
0.19
0.33
0.26
0.12
0.11
0.16
0.16
0.42
Precip in/vr
Avg
40.8
38.5
40.9
40.1
40.8
39.5
45.6
38.1
42.0
44.3
40.1
41.0
0.06
40.3
44.7
35.4
53.6
43.5
0.18
COV
0.16
0.21
0.16
0.17
0.16
0.18
0.24
0.24
0.32
0.22
0.22
0.21
0.24
0.28
0.18
0.17
0.22
0.21
0.23
Duration
Avq
9.5
8.3
8.4
7.9
9.8
9.1
8.5
7.8
10.6
9.1
8.1
8.8
0.10
9.9
10.5
9.6
10.1
10.0
0.04
COV
0.91
0.94
0.94
0.89
0.85
0.90
0.95
0.88
0.96
0.94
0.90
0.91
0.04
0.90
0.90
0.85
0.94
0.90
0.04
Intensity
Avg
0.098
0.119
0.130
0.126
0.097
0.117
0.129
0.127
0.101
0.120
0.131
0.118
0.11
0.101
0.093
0.083
0.110
0.097
0.12
COV
1.11
1.07
1.12
1.03
1.15
1.57
1.01
1.10
1.07
1.05
1.15
1.13
0.14
1.16
1.19
1.18
1.11
1.16
0.03
Volume
Avg
0.65.
0.68
0.73
0.66
0.64
0.70
0.75
0.69
0.79
0.74
0.71
0.70
0.07
0.69
0.67
0.54
0.80
0.68
0.16
COV
1.01
0.98
0.98
1.00
1.02
1.06
1.07
1.08
1.15
1.08
0.99
1.04
0.05
1.05
1.07
0.99
1.16
1.07
0.07
DELTA
Avg
141
147
149
144
140
146
137
147
137
134
143
142
0.04
141
132
136
125
134
0.05
COV
1.01
1.10
1.03
1.01
1.02
1.14
1.10
1.12
1.29
1.04
1.13
1.09
0.08
1.56
0.99
1.04
1.02
1.15
0.24
-------
4. References
1. EPA, Areawide Assessment Procedures Manual. EPA-600/9-76-014, 3 volumes
(Cincinnati, Ohio: EPA, July et seq., 1976).
2. Heaney, J.P., W.C. Huber, M.A. Medina, M.P. Murphy, S.J. Nix, and S.M.
Hasan, Nationwide Evaluation of Combined Sewer Overflows and Urban
Stormwater Discharges - Vol. II: Cost Assessment and Impacts. EPA-600/2-77-
064(b) (NTIS PB-266005) (Cincinnati, Ohio: EPA, March 1977).
3. Hydroscience Inc., A Statistical method for Assessment of Urban Stormwater Loads
- Impacts - Controls. EPA-440/3-79-023 (Washington, D.C.: EPA, May 1979).
4. Restrepo-Posada, P.J., and Eagleson, P.S., Identification of Independent
Rainstorms. Journal of Hydrology, 55 (1982), 303-319.
5. Schueler, T.B., Controlling Urban Runoff: A Practical manual for Planning and
Designing Urban BMPs. Washington Metropolitan Water Resources Planning
Board (Washington D.C., July 1987).
43
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