Magnitude and Frequency of Floods on 

Nontidal Streams in Delaware

By Kernell G. Ries III and Jonathan J.A. Dillow

Prepared in cooperation with the

Delaware Department of Transportation 

and the 

Delaware Geological Survey

Scientific Investigations Report 2006-5146

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2006

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U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Ries, K.G., III, and Dillow, J.J.A., 2006, Magnitude and frequency of floods on nontidal streams in Delaware: 

U.S. Geological Survey Scientific Investigations Report 2006-5146, 59 p.
iii

Contents

Abstract............................................................................................................................................................. 1

Introduction....................................................................................................................................................... 1

Physical Setting................................................................................................................................................ 2

Methods for Estimating the Magnitude and Frequency of Floods .......................................................... 2

Flood-Frequency Analysis at Streamgaging Stations ...................................................................... 4

Analysis of and Adjustments for Trends in Annual Peak-Flow Time Series ........................ 12

Regional Skew Analysis ............................................................................................................... 15

Regional Flood-Frequency Relations................................................................................................... 17

Explanatory Variable Selection and Measurement ................................................................. 17

Development of Regression Equations ...................................................................................... 22

Accuracy and Limitations............................................................................................................. 24

Comparison of Results with Previous Study ............................................................................. 28

Application of the Methods............................................................................................................................ 30

Estimation for a Gaged Location .......................................................................................................... 30

Estimation for a Site Upstream or Downstream from a Gaged Location ...................................... 31

Estimation for a Site Between Gaged Locations............................................................................... 32

Effects of Urbanization on Floods ................................................................................................................. 33

StreamStats ...................................................................................................................................................... 35

Summary and Conclusions............................................................................................................................. 35

References........................................................................................................................................................ 36

Figures

1. Map showing study area and physiographic provinces in Delaware and 

surrounding states ......................................................................................................................... 3

2. Map showing location of streamgaging stations in Delaware and surrounding 

states for which flood-frequency estimates were computed................................................. 5

3. Example flood-frequency curve produced by the PEAKFQ program for Beaverdam 

Branch at Matthews, Maryland ................................................................................................... 11

4. Graph showing relation between 2000 housing density and 2001 impervious 

surface percentage for streamgaging stations in and within 25 miles of Delaware .......... 13

5. Time-series plot showing adjustment of annual-peak flows for Stockley Branch 

at Stockley, Delaware for an increasing trend with time......................................................... 13

6. Map showing skew ranges for streamgaging stations in Delaware and surrounding

states with 25 or more years of record ....................................................................................... 16

7. Graph showing relation between the new ArcHydro and the traditional 10/85 method 

for measuring main channel slope for stations used in the regression analysis ................ 21

8. Boxplot showing percent storage measured using the National Hydrography 

Dataset (NHD) and a combination of the 2001 National Land Cover Dataset (NLCD) 

and the 2002 Delaware Land-Use Dataset (DELU).................................................................... 22
iv

Tables

1. Summary of streamgaging stations in and near Delaware for which 

streamflow statistics were computed......................................................................................... 6

2. Description of treatment of stations with annual peak-flow time series that were

affected by trends........................................................................................................................... 14

3. Number of streamgaging stations included in the regression analyses by 

hydrologic region and state .......................................................................................................... 18

4. Summary of drainage area, number of streamgaging stations, and average years 

of record used in the regression analyses for Delaware ........................................................ 18

5. Basin characteristics considered for use in the regression analyses.................................. 19

6. Climatic characteristics for stations in and near Delaware that were considered 

for use in the regression analyses............................................................................................... 40

7. Basin characteristics for stations in and near Delaware that were considered 

for use in the regression analyses............................................................................................... 44

8. Flood-frequency statistics for stations in and near Delaware that were 

considered for use in the regression analyses ......................................................................... 52

9. Average standard errors of estimate and prediction and equivalent years of record 

for the best regression equations, by hydrologic region in Delaware .................................. 25

10. Values needed to determine 90-percent prediction intervals for the best regression

 equations, by hydrologic region in Delaware ........................................................................... 26

11. Ranges of basin characteristics used to develop the regression equations ....................... 28

12. Mean and median percent differences between peak-flow frequency statistics 

computed from the systematic records for streamgaging stations included in 

this study and the previous study ................................................................................................ 29

13. Matrix of correlations between the logarithms of flood-frequency estimates at 

the 2- and 100-year recurrence intervals and the logarithms of the indicators of 

urbanization ..................................................................................................................................... 34

14. Average standard errors of estimate and prediction and equivalent years of 

record for the urban regression equations ................................................................................ 34
v

Conversion Factors and Datum

Multiply By To obtain

 Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

 Area

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2) 

 Flow rate

cubic foot per second (ft3

/s) 0.02832 cubic meter per second (m3/s)

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to North American Vertical Datum of 1988 (NAVD 88).

Horizontal coordinate information is referenced to North American Datum of 1983 (NAD 83).

Altitude, as used in this report, refers to distance above the vertical datum.

Abstract

Reliable estimates of the magnitude and frequency of 

annual peak flows are required for the economical and safe 

design of transportation and water-conveyance structures. 

This report, done in cooperation with the Delaware Department of Transportation (DelDOT) and the Delaware Geological Survey (DGS), presents methods for estimating the magnitude and frequency of floods on nontidal streams in Delaware 

at locations where streamgaging stations monitor streamflow 

continuously and at ungaged sites. Methods are presented for 

estimating the magnitude of floods for return frequencies ranging from 2 through 500 years. These methods are applicable 

to watersheds exhibiting a full range of urban development 

conditions. The report also describes StreamStats, a web 

application that makes it easy to obtain flood-frequency estimates for user-selected locations on Delaware streams.

Flood-frequency estimates for ungaged sites are obtained 

through a process known as regionalization, using statistical 

regression analysis, where information determined for a group 

of streamgaging stations within a region forms the basis for 

estimates for ungaged sites within the region. One hundred 

and sixteen streamgaging stations in and near Delaware with 

at least 10 years of non-regulated annual peak-flow data available were used in the regional analysis. Estimates for gaged 

sites are obtained by combining the station peak-flow statistics 

(mean, standard deviation, and skew) and peak-flow estimates 

with regional estimates of skew and flood-frequency magnitudes. Example flood-frequency estimate calculations using 

the methods presented in the report are given for: (1) ungaged 

sites, (2) gaged locations, (3) sites upstream or downstream 

from a gaged location, and (4) sites between gaged locations.

Regional regression equations applicable to ungaged sites 

in the Piedmont and Coastal Plain Physiographic Provinces of 

Delaware are presented. The equations incorporate drainage 

area, forest cover, impervious area, basin storage, housing density, soil type A, and mean basin slope as explanatory variables, and have average standard errors of prediction 

ranging from 28 to 72 percent. Additional regression equations that incorporate drainage area and housing density as 

explanatory variables are presented for use in defining the 

effects of urbanization on peak-flow estimates throughout 

Delaware for the 2-year through 500-year recurrence intervals, 

along with suggestions for their appropriate use in predicting 

development-affected peak flows.

Additional topics associated with the analyses performed 

during the study are also discussed, including: (1) the availability and description of more than 30 basin and climatic 

characteristics considered during the development of the 

regional regression equations; (2) the treatment of increasing 

trends in the annual peak-flow series identified at 18 gaged 

sites, with respect to their relations with maximum 24-hour 

precipitation and housing density, and their use in the regional 

analysis; (3) calculation of the 90-percent confidence interval 

associated with peak-flow estimates from the regional regression equations; and (4) a comparison of flood-frequency 

estimates at gages used in a previous study, highlighting the 

effects of various improved analytical techniques.

Introduction

Reliable estimates of the magnitude and frequency of 

annual peak flows, generally referred to as flood-frequency 

estimates, are required for the economical design of transportation and water-conveyance structures such as roads, bridges, 

culverts, storm sewers, dams, and levees. These estimates are 

also needed for the effective planning and management of land 

use and water resources, to protect lives and property in floodprone areas, and to determine flood-insurance rates. 

Flood-frequency estimates are needed at locations where 

streamgaging stations monitor streamflow continuously and at 

ungaged sites, where no streamflow information is available 

for use as a basis for determining the estimates. Estimates for 

Magnitude and Frequency of Floods on 

Nontidal Streams in Delaware

By Kernell G. Ries III and Jonathan J.A. Dillow
ungaged sites usually are achieved through a process known as 

regionalization, where flood-frequency information determined for a group of streamgaging stations within a region 

forms the basis for estimates for ungaged sites within the 

region.

Methods for determining flood-frequency estimates 

for nontidal streams in Delaware have been provided previously in reports by: Tice (1968), Cushing, Kantrowitz, and 

Taylor (1973), Simmons and Carpenter (1978), and Dillow 

(1996). The regionalization methods described in those reports 

relied on fewer stations and shorter periods of record than the 

methods described in this report. An additional 14 years of 

record and improved regionalization techniques have become 

available since the analysis was done for the previous report 

by Dillow (1996).

The purpose of this report, done in cooperation with the 

Delaware Department of Transportation (DelDOT) and the 

Delaware Geological Survey (DGS), is to present methods for 

estimating the magnitude and frequency of floods on nontidal 

streams in Delaware. The report (1) describes methods used to 

estimate the magnitude and frequency of floods for streamgaging stations; (2) presents estimates of the magnitude of floods 

at the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence 

intervals determined for 116 streamgaging stations in and near 

Delaware; (3) describes methods used to develop regression 

equations for use in estimating the magnitude of floods at 

the same recurrence intervals for ungaged sites in Delaware; 

(4) describes the accuracy and limitations of the equations; 

(5) presents example applications of the methods; and (6) 

describes the StreamStats web application so that estimates 

can be easily obtained when needed.

Physical Setting

The study area, comprised of the State of Delaware, is 

in the Mid-Atlantic coastal region of the United States. The 

State lies between 38°27 ́ and 39°51 ́ north latitude and 75°04 ́ 

and 75°48 ́ west longitude, and is bordered on the north by 

the State of Pennsylvania, on the west and south by the State 

of Maryland, and on the east by Delaware Bay (Dillow, 1996) 

(fig. 1). The State of New Jersey is on the eastern shore of 

Delaware River and Delaware Bay. Delaware has a land area 

of 1,954 mi2

 (square miles) and a 2003 population of about 

817,000 (FedStats, 2005).

The climate in the study area is temperate. The mean 

annual temperature is about 54° F (degrees Fahrenheit), with 

monthly averages ranging from 31° F in January to 76° F in 

July (National Oceanographic and Atmospheric Administration, 2005). Mean annual precipitation is about 44 inches 

(Carpenter and Hayes, 1996). The precipitation is distributed 

fairly evenly throughout the year. Annual peak flows in the 

State arise from a mix of frontal storms with rain and melting 

snow in the spring, thunderstorms in the summer, and tropical 

storms and hurricanes in the summer and fall.

The study area is in two major physiographic provinces, 

the Coastal Plain and the Piedmont (Fenneman, 1938). The 

Fall Line, which crosses from the northeast corner of Delaware through about 5 mi (miles) south of the northwest corner 

of the State, forms the divide between the two provinces. The 

Piedmont Province, northwest of the Fall Line, consists of 

gently rolling landscape with maximum elevations generally 

less than 400 ft (feet) above sea level. Delaware streams in this 

province have fairly steep gradients, and drain to the Delaware 

River and Delaware Bay (Dillow, 1996). The Coastal Plain 

Province, southeast of the Fall Line, consists of an area of low 

relief adjacent to the Chesapeake and Delaware Bays, with 

elevations ranging from sea level to less than 100 ft. Streams 

in the Coastal Plain are often affected by tides for substantial 

distances above their mouths. The Fall Line is named as such 

because numerous waterfalls occur where rivers drop from the 

Piedmont onto the Coastal Plain.

Methods for Estimating the Magnitude 

and Frequency of Floods

This report describes separate methods for estimating 

the magnitude and frequency of floods, hereafter referred to 

as flood-frequency estimates, for streamgaging stations and 

for ungaged sites. The general process normally followed to 

determine flood-frequency estimates for ungaged sites in a 

given region requires:

Selecting a group of streamgaging stations in and around 

the region with at least 10 years of annual peak-flow data 

and streamflow conditions that are generally representative of the area as a whole; 

Computing initial flood-frequency estimates by weighting 

the station skews with generalized-skew values taken from 

“Guidelines For Determining Flood Flow Frequency” 

(Bulletin 17B) by the Interagency Advisory Committee on 

Water Data (IACWD, 1982); 

Computing physical and climatic characteristics, 

hereafter termed basin characteristics, that have a 

conceptual relation to the generation of flood peaks for 

the drainage basins associated with the stations;

Analyzing the initial station-skew coefficients to 

determine new generalized-skew values for the region;

Re-computing the flood-frequency estimates for the 

stations by weighting the station skews with the new 

generalized-skew values;

Analyzing to determine if relations between floodfrequency estimates and basin characteristics are 

homogenous throughout the region or if the region should 

be divided into sub-regions; 

1.

2.

3.

4.

5.

6.

 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
A

T

L

A

N

T

I

C

O

C

E

A

N

D E L A W A R E

B A Y

DELAWARE RIVER

POTOMAC RIVER

C & D

C

H

E

S

A

P

E

A

K

E

B

A

Y

H A R F O R D

L A N C A S T E R

C H E S T E R

D E L A W A R E

S A L E M

C U M B E R L A N D

C A P E

M A Y

G L O U C E S T E R

M O N T G O M E R Y B U C K S

BURLINGTON

ATLANTIC

CAMDEN

C E C I L

K E N T

T A L B O T

Q U E E N

A N N E S

C A R O L I N E

D O R C H E S T E R

W I C O M I C O

W O R C E S T E R

S O M E R S E T

N E W

C A S T L E

K E N T

S U S S E X

Y O R K

PENNSYLVANIA

MARYLAND

DELAWARE

MARYLAND

MARYLAND

VIRGINIA

NEW JERSEY

CANAL

Creek

Cr.

Chester

River

EASTERN

BAY

Choptank River

Patapsco River

L. Choptank R.

Chincoteague Bay

Nanticoke

River

Pocomoke

River

Fishing

Bay

Rehoboth

Bay

Indian River

Bay

Broad Creek

Wicomico R.

Nassawango

Creek

Manokin

River

Choptank

River

St. Jones R.

Murderkill River

Marshyho ep

Creek

Tuckahoe

Elk

River

River

Leipsic River

Unicorn Br.

Smyrna

River

Sassafras

Schuylkill

River

Salem River

Raccoon Cr.

Mantua Cr.

Great

Egg

Harbor

R.

Rancocas Cr.

Cohansey River

Maurice

R.

West

Br.

Br.

Brandywine

East

Christina River

L. Elk Cr.

SUSQUEHANNA

RIVER Conowingo

Cr.

Octoraro Cr.

East Br.

West Br.

Annapolis

Elkton

Chestertown

Centreville

Denton

Easton

Cambridge

Salisbury

Princess

Anne Snow Hill

Wilmington

Dover

Georgetown

Lancaster

West Chester

Media Philadelphia

P I E D M O N T

C O A S T A L P L A I N

FALL

GENERALIZED

LINE

76° 75°

40°

39°

38°

0

0

10

10 20 KILOMETERS

20 MILES

Figure 1. Study area and physiographic provinces in Delaware and surrounding states.

Methods for Estimating the Magnitude and Frequency of Floods 
Using regression analysis to develop equations for use in 

estimating flood frequencies at ungaged sites in the region 

or sub-regions; and 

Assessing and describing the accuracy associated with 

estimating flood frequencies for ungaged sites.

Streamgaging stations in Delaware and stations in 

adjacent states having drainage-basin centroids within 25 mi 

of the Delaware border were investigated for possible use in 

the regional analysis. Stations within this region were not used 

in the analysis if less than 10 years of annual peak-flow data 

were available, or if peak flows at the stations were substantially affected by dam regulations or flood-retarding reservoirs. 

Use of these criteria resulted in the initial selection of 116 stations for inclusion in the regional analysis (fig. 2, table 1).

The number of stations within the region was insufficient 

to develop separate regression equations for rural and urban 

basins. In addition, DelDOT was specifically interested in 

understanding how development can affect flood-frequency 

estimates. As a result, the stations were not screened based on 

the degree of urbanization.

Flood-Frequency Analysis at Streamgaging 

Stations

Flood-frequency estimates provided later in this report 

for 116 unregulated streamgaging stations in the study area 

were computed from annual series of peak-flow data for the 

stations according to methods recommended in Bulletin 17B. 

The estimates are reported as T-year discharges, where T is a 

recurrence interval that indicates the average number of years 

between occurrences of peak discharges of the same or greater 

magnitude. Flood-frequency estimates can also be expressed 

as exceedance probabilities, which are the reciprocal of the 

recurrence interval. In other words, the probability that the 

T-year flood will be exceeded is 1/T in every year. For 

example, the 100-year flood has a 1 in 100 (1 percent) chance 

of being equaled or exceeded in any given year.

The IACWD recommends fitting the logarithms of the 

annual peak flows to a log-Pearson, Type III frequency distribution. Fitting the distribution requires calculating the logarithms of the mean, standard deviation, and skew coefficient 

of the annual peak-flow series, which describe the mid-point, 

slope, and curvature of the peak-flow frequency curve, respectively. Estimates of the T-year flood peaks are computed by 

inserting the three statistics of the frequency distribution into 

the equation: 

QT = X + KS (1)

where

QT is the logarithm of the magnitude of the 

T-year recurrence interval discharge, in ft3/s 

(cubic feet per second); 

X is the mean of the logarithms of the annual 

peak streamflows; 

7.

8.

K is a factor based on the skew coefficient 

and the given recurrence interval, which can be 

obtained from a table in Bulletin 17B; and 

S is the standard deviation of the logarithms of 

the annual peak streamflows, which is a measure 

of the degree of variation of the annual values 

about the mean value.

The skew coefficient measures the symmetry of the 

frequency distribution and is strongly influenced by the 

presence of high or low outliers, annual peaks that are substantially higher or lower than other peaks in the series. The 

skew is positive when the mean of the annual series exceeds 

the median and negative when the mean is less than the 

median. Large positive skews are typically the result of high 

outliers, and large negative skews are typically the result of 

low outliers.

The U.S. Geological Survey (USGS) computer program 

PEAKFQ was used to compute the flood-frequency statistics 

for streamgaging stations presented in this report. PEAKFQ 

automates many of the analysis procedures recommended in 

Bulletin 17B, including identifying and adjusting for high and 

low outliers and historical periods, weighting of station skews 

with a generalized skew based on the skews of other stations 

within the region, and fitting a log-Pearson, Type III distribution to the streamflow data. The PEAKFQ program and 

associated documentation can be downloaded from the web 

free of charge at http://water.usgs.gov/software/peakfq.html.

In conjunction with PEAKFQ, the USGS software programs 

ANNIE, IOWDM (Flynn and others, 1995), and SWSTAT 

were used for binary database management, for input and 

output of data to the database, and for testing annual peakflow series for trends, respectively. The ANNIE program and 

accompanying documentation can be downloaded at http://

water.usgs.gov/software/annie.html. The IOWDM program 

and accompanying documentation can be downloaded at 

http://water.usgs.gov/software/iowdm.html. The SWSTAT 

program and accompanying documentation can be downloaded at http://water.usgs.gov/software/swstat.html.

The process generally followed when computing floodfrequency estimates for streamgaging stations consisted of the 

following steps:

Retrieve the annual time series of peak flows for the 

station from the USGS NWIS-Web on-line database at 

http://nwis.waterdata.usgs.gov/usa/nwis/peak;

Compare the time series for the station to time series for 

upstream and downstream stations, and for stations in 

adjacent basins to determine if the records for the other 

stations can be used as the basis for a historical 

adjustment;

Consult the USGS data-collection manager for the State 

in which the station is located, do a literature search, or 

both, to obtain any information that can be used as the 

basis for historical adjustments;

1.

2.

3.

 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
A

T

L

A

N

T

I

C

O

C

E

A

N

D E L A W A R E

B A Y

DELAWARE RIVER

C & D

H A R F O R D

L A N C A S T E R

C H E S T E R D E L A W A R E

S A L E M

C U M B E R L A N D

C A P E

M A Y

GLOUCESTER

M O N T G O M E R Y B U C K S

BURLINGTON

ATLANTIC

CAMDEN

C E C I L

K E N T

T A L B O T

C A R O L I N E

D O R C H E S T E R

W I C O M I C O

W O R C E S T E R

S O M E R S E T

N E W

C A S T L E

K E N T

S U S S E X

Y O R K

PENNSYLVANIA

MARYLAND

DELAWARE

MARYLAND

MARYLAND

VIRGINIA

NEW JERSEY

CANAL

POTOMAC RIVER

C

H

E

S 

A

P

E

A

K

E

B A

Y

Q U E E N

A N N E S Creek

Chester

River

EASTERN

BAY

Choptank

River

Patapsco River

L. Choptank R.

Chincoteague Bay

Nanticoke

River

Pocomoke R.

Fishing

Bay

Rehoboth

Bay

Indian River

Bay

Broad Creek

Wicomico R.

Nassawango

Creek

Manokin

River

Choptank

River

St. Jones R.

Murderkill River

Marshyho ep

Creek

Tuckahoe

Elk

River

River

Leipsic River

Unicorn Br.

Smyrna

River

Sassafras

Schuylkill

River

Salem River

Mantua Cr.

Great

Egg

Harbor

R.

Rancocas Cr.

Cohansey River

Maurice

R.

West

Br.

Br.

Brandywine Cr.

East

L. Elk Cr.

SUSQUEHANNA RIVER

Conowingo

Cr.

Octoraro Cr.

East Br.

West Br.

Raccoon Cr.

Annapolis

Elkton

Chestertown

Centreville

Denton

Easton

Cambridge

Salisbury

Princess

Anne Snow Hill

Dover

Georgetown

Lancaster

West Chester

Media

Philadelphia

01490000

01492050

01489000

01487500 01484550

01484500

01484270

01484300

01486980

01484525

01485500 01486000

01485000

01486100

01488000

01493000

01494000

01483700

01483720

01483500

01483290

01483400

01483200

01484000

01484002

01484050

01490600

01491010

01491000

01490800

01491050

01492500

01492550

01492000

01487000

01488500

01484100

01493500

01411500

01412500

01483000

01412800

01477800

01477120 01477110

01482500

01477500 01477480

01481500

01481450

01479000

01480015

01480100

01478650

01478000

01478040

01482310

01478500

01578500

01579000 01578800

01578200

01578400

01478200

01496200

01496000

01496080

01495000

01495500

01480000

01479950

01479200

01476480

01476500

01477000

01476000

01475550

01467081

01467150

01467160

01467180

01467317

01467130

01467351

01467330

01475019

01475000

01411456

01467305

01474000

01467086

01467045 01467043

01467089

01475530

01467087

01480500

01480870

01481000

01479820 01481200

01480800

01476435

01480300

01480675

01480700

01472157

01472174

01480680

01480610

01480617 01475510

01475850

01475300

01473169

01473470

0

0

10

10 20 KILOMETERS

20 MILES

EXPLANATION

01486000 STREAMGAGING STATION AND

U.S. GEOLOGICAL SURVEY

IDENTIFICATION NUMBER

76° 75°

40°

39°

38°

Figure 2. Location of streamgaging stations in Delaware and surrounding states for which 

flood-frequency estimates were computed.

Methods for Estimating the Magnitude and Frequency of Floods 
Table 1. Summary of streamgaging stations in and near Delaware for which streamflow statistics were computed.

[USGS, U.S. Geological Survey, CP, Coastal Plain Physiographic Province; PD, Piedmont Coastal Plain Physiographic Province; °  ́  ̋, degrees, 

minutes, seconds; N, years of record]

USGS 

station 

number

Name Latitude 

° ‘ ‘’

Longitude 

° ‘ ‘’ Region Peak-flow period N

01411456 Little Ease Run near Clayton, NJ 39 39 32 75 04 03 CP 1988-2004 17

01411500 Maurice River at Norma, NJ 39 29 44 75 04 37 CP 1933-2004h 72

01412500 West Branch Cohansey River at Seeley, NJ 39 29 06 75 15 32 CP 1952-73,

1974-79,

1980-2004

51

01412800 Cohansey River at Seeley NJ 39 28 21 75 15 20 CP 1978-95,

2003-4

20

01467043 Stream ‘A’ at Philadelphia, PA 40 05 27 75 03 50 PD 1965-80 16

01467045 Pennypack Creek below Veree Road at Philadelphia, PA 40 05 04 75 03 34 PD 1964-80 18

01467081 South Branch Pennsauken Creek at Cherry Hill, NJ 39 56 30 75 00 04 CP 1968-76,

1978-2004

36

01467086 Tacony Creek at County Line, Philadelphia, PA 40 02 47 75 06 40 PD 1966-86 21

01467087 Frankford Creek at Castor Ave., Philadelphia, PA 40 00 57 75 05 50 PD 1966-2004a 39

01467089 Frankford Creek at Torresdale Ave., Philadelphia, PA 40 00 25 75 05 33 PD 1966-81b 16

01467130 Cooper River at Kirkwood, NJ 39 50 11 75 00 05 CP 1963-80,

2004

18

01467150 Cooper River at Haddonfield, NJ 39 54 11 75 01 17 CP 1963-2003h 41

01467160 North Branch Cooper River near Marlton, NJ 39 53 20 74 58 07 CP 1964-78,

2004bh

26

01467180 North Branch Cooper River at Ellisburg, NJ 39 54 27 75 00 41 CP 1964-75,

2004

13

01467305 Newton Creek at Collingswood, NJ 39 54 30 75 03 12 CP 1964-75,

1977-2004

40

01467317 South Branch Newton Creek at Haddon Heights, NJ 39 52 45 75 04 25 CP 1964-2004c 41

01467330 South Branch Big Timber Creek at Blackwood, NJ 39 48 17 75 04 32 CP 1964-84h 21

01467351 North Branch Big Timber Creek at Laurel Rd, 

Laurel Springs, NJ

39 49 07 75 00 55 CP 1975-88 14

01472157 French Creek near Phoenixville, PA 40 09 05 75 36 06 PD 1969-2004 36

01472174 Pickering Creek near Chester Springs, PA 40 05 22 75 37 50 PD 1967-83 17

01473169 Valley Creek at PA Turnpike Bridge near 

Valley Forge, PA

40 04 45 75 27 40 PD 1983-2004ch 22

01473470 Stony Creek at Sterigere Street at Norristown, PA 40 07 38 75 20 43 PD 1971,

1975-94

21

01474000 Wissahickon Creek at mouth, Philadelphia, PA 40 00 55 75 12 26 PD 1966-2004h 39

01475000 Mantua Creek at Pitman, NJ 39 44 13 75 06 48 CP 1940,

1942-94,

1999,

2003-4ch

57

01475019 Mantua Creek at Salina, NJ 39 46 13 75 07 58 CP 1975-1988 14

 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 1. Summary of streamgaging stations in and near Delaware for which streamflow statistics were computed.—Continued

[USGS, U.S. Geological Survey, CP, Coastal Plain Physiographic Province; PD, Piedmont Coastal Plain Physiographic Province; °  ́  ̋, degrees, 

minutes, seconds; N, years of record]

USGS 

station 

number

Name Latitude 

° ‘ ‘’

Longitude 

° ‘ ‘’ Region Peak-flow period N

01475300 Darby Creek at Waterloo Mills near Devon, PA 40 01 21 75 25 20 PD 1972-97,

1999h

27

01475510 Darby Creek near Darby, PA 39 55 44 75 16 22 PD 1964-90 27

01475530 Cobbs Creek at U.S. Highway No. 1 at Philadelphia, PA 39 58 29 75 16 49 PD 1965-81h 17

01475550 Cobbs Creek at Darby, PA 39 55 02 75 14 52 PD 1964-90 27

01475850 Crum Creek near Newtown Square, PA 39 58 35 75 26 13 PD 1977-2004 28

01476000 Crum Creek at Woodlyn, PA 39 52 45 75 21 00 PD 1932-37,

1975-86

18

01476435 Ridley Creek at Dutton Mill near West Chester, PA 39 58 50 75 31 00 PD 1975-86 12

01476480 Ridley Creek at Media, PA 39 54 58 75 24 13 PD 1932-55,

1978-2004d

48

01476500 Ridley Creek at Moylan, PA 39 54 10 75 23 35 PD 1932-55,

1978-80,

1984-85bh

31

01477000 Chester Creek near Chester, PA 39 52 08 75 24 31 PD 1932-2004 73

01477110 Raccoon Creek at Mullica Hill, NJ 39 44 10 75 13 29 CP 1940,

1978-95,

1999h

20

01477120 Raccoon Creek near Swedesboro, NJ 39 44 26 75 15 33 CP 1967-2004h 38

01477480 Oldmans Creek near Harrisonville, NJ 39 41 20 75 18 37 CP 1975-95 21

01477500 Oldmans Creek near Woodstown, NJ 39 41 27 75 19 04 CP 1932-40,1967h 10

01477800 Shellpot Creek at Wilmington, DE 39 45 39.5 75 31 07.3 PD 1945-2004ch 60

01478000 Christina River at Coochs Bridge, DE 39 38 14.6 75 43 40.4 PD 1943-2004 62

01478040 Christina River near Bear, DE 39 38 12 75 40 53 PD 1979-83,

1985-91h

12

01478200 Middle Branch White Clay Creek near Landenberg, PA 39 46 54 75 48 03 PD 1960-1991,

1995

32

01478500 White Clay Creek above Newark, DE 39 42 50 75 45 35 PD 1953-59,

1963-80,

1989,

1994-2004ceh

37

01478650 White Clay Creek at Newark, DE 39 41 21.2 75 44 55.5 PD 1994-2003b 10

01479000 White Clay Creek near Newark, DE 39 41 57.2 75 40 30.1 PD 1932-36,

1943-57,

1960-2004h

65

01479200 Mill Creek at Hockessin, DE 39 46 31 75 41 26 PD 1966-75 10

Methods for Estimating the Magnitude and Frequency of Floods 
Table 1. Summary of streamgaging stations in and near Delaware for which streamflow statistics were computed.—Continued

[USGS, U.S. Geological Survey, CP, Coastal Plain Physiographic Province; PD, Piedmont Coastal Plain Physiographic Province; °  ́  ̋, degrees, 

minutes, seconds; N, years of record]

USGS 

station 

number

Name Latitude 

° ‘ ‘’

Longitude 

° ‘ ‘’ Region Peak-flow period N

01479820 Red Clay Creek near Kennett Square, PA 39 49 00 75 41 31 PD 1988-2004h 17

01479950 Red Clay Creek Tributary near Yorklyn, DE 39 47 50 75 39 33 PD 1966-75 10

01480000 Red Clay Creek at Wooddale, DE 39 45 46.1 75 38 11.4 PD 1943-2004h 62

01480015 Red Clay Creek near Stanton, DE 39 42 56.7 75 38 23.8 PD 1989-2004h 16

01480100 Little Mill Creek at Elsmere, DE 39 44 05 75 35 14 PD 1964-80,1989 18

01480300 West Branch Brandywine Creek near 

Honey Brook, PA

40 04 22 75 51 40 PD 1960-2004 45

01480500 West Branch Brandywine Creek at Coatesville, PA 39 59 08 75 49 40 PD 1942,1944-50,

1970-2004h

44

01480610 Sucker Run near Coatesville, PA 39 58 20 75 51 03 PD 1964-2004 41

01480617 West Branch Brandywine Creek at Modena, PA 39 57 42 75 48 06 PD 1970-2004b 35

01480675 Marsh Creek near Glenmoore, PA 40 05 52 75 44 31 PD 1967-2004b 38

01480680 Marsh Creek near Lyndell, PA 40 03 58 75 43 38 PD 1960-71b 12

01480700 East Branch Brandywine Creek near 

Downingtown, PA

40 02 05 75 42 32 PD 1966-2004h 39

01480800 East Branch Brandywine Creek at Downingtown, PA 40 00 20 75 42 20 PD 1942,

1958-68bh

12

01480870 East Branch Brandywine Creek below 

Downingtown, PA

39 58 07 75 40 25 PD 1972-2004fh 33

01481000 Brandywine Creek at Chadds Ford, PA 39 52 11 75 35 37 PD 1912-53,

1954-5,

1963-2004bh

85

01481200 Brandywine Creek tributary near Centerville, DE 39 50 08 75 35 57 PD 1966-75 10

01481450 Willow Run at Rockland, DE 39 47 32 75 33 16 PD 1966-75 10

01481500 Brandywine Creek at Wilmington, DE 39 46 09.9 75 34 25.0 PD 1912-2004g 93

01482310 Doll Run at Red Lion, DE 39 35 53 75 39 43 CP 1966-75b 10

01482500 Salem River at Woodstown, NJ 39 38 36 75 19 51 CP 1940-95,

2003-4h

58

01483000 Alloway Creek at Alloway, NJ 39 33 56 75 21 38 CP 1953-72 20

01483200 Blackbird Creek at Blackbird, DE 39 21 58.6 75 40 09.8 CP 1952-2004 52

01483290 Paw Paw Branch tributary near Clayton, DE 39 18 41 75 40 08 CP 1966-75h 10

01483400 Sawmill Branch tributary near Blackbird, DE 39 20 57 75 38 31 CP 1966-75 10

01483500 Leipsic River near Cheswold, DE 39 13 58 75 37 57 CP 1943-75 33

01483700 St. Jones River at Dover, DE 39 09 49.4 75 31 08.7 CP 1958-2004 47

01483720 Puncheon Branch at Dover, DE 39 08 25 75 32 20 CP 1966-75 10

 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 1. Summary of streamgaging stations in and near Delaware for which streamflow statistics were computed.—Continued

[USGS, U.S. Geological Survey, CP, Coastal Plain Physiographic Province; PD, Piedmont Coastal Plain Physiographic Province; °  ́  ̋, degrees, 

minutes, seconds; N, years of record.]

USGS 

station 

number

Name Latitude 

° ‘ ‘’

Longitude 

° ‘ ‘’ Region Peak-flow period N

01484000 Murderkill River near Felton, DE 38 58 33 75 34 03 CP 1932-3,

1960-85,

1997-99h

31

01484002 Murderkill River tributary near Felton, DE 38 58 19 75 33 31 CP 1966-75h 10

01484050 Pratt Branch near Felton, DE 39 00 37 75 31 46 CP 1966-75h 10

01484100 Beaverdam Branch at Houston, DE 38 54 20.8 75 30 45.9 CP 1958-2004 47

01484270 Beaverdam Creek near Milton, DE 38 45 41 75 16 03 CP 1966-80, 

2002-3bh

18

01484300 Sowbridge Branch near Milton, DE 38 48 51 75 19 39 CP 1957-78 22

01484500 Stockley Branch at Stockley, DE 38 38 19.9 75 20 31.1 CP 1943-2004c 62

01484525 Millsboro Pond outlet at Millsboro, DE 38 35 40.4 75 17 27.7 CP 1987-8,

1992-2004

15

01484550 Pepper Creek at Dagsboro, DE 38 32 50 75 14 40 CP 1960-75b 16

01485000 Pocomoke River near Willards, MD 38 23 20.0 75 19 28.0 CP 1950-2004ch 55

01485500 Nassawango Creek near Snow Hill, MD 38 13 44.1 75 28 17.2 CP 1950-2004c 55

01486000 Manokin Branch near Princess Anne, MD 38 12 50.0 75 40 17.0 CP 1951-71,

1975-2004

50

01486100 Andrews Branch near Delmar, MD 38 26 15 75 31 46 CP 1967-76 10

01486980 Toms Dam Branch near Greenwood, DE 38 48 04 75 33 28 CP 1966-75 10

01487000 Nanticoke River near Bridgeville, DE 38 43 42.0 75 33 42.7 CP 1943-2004ch 62

01487500 Trap Pond outlet near Laurel, DE 38 31 40.4 75 28 56.7 CP 1952-75,

2001-4

27

01488000 Holly Ditch near Laurel, DE 38 32 20 75 35 55 CP 1951-56,

1959-61, 

1967-75

18

01488500 Marshyhope Creek near Adamsville, DE 38 50 58.9 75 40 23.2 CP 1943-68,

1973-2003ch

59

01489000 Faulkner Branch at Federalsburg, MD 38 42 44 75 47 34 CP 1950-91bh 42

01490000 Chicamacomico River near Salem, MD 38 30 42.0 75 52 47.7 CP 1951-80,

2003h

31

01490600 Meredith Branch near Sandtown, DE 39 02 23 75 41 52 CP 1966-75h 10

01490800 Oldtown Branch at Goldsboro, MD 39 01 23 75 47 16 CP 1967-76h 10

01491000 Choptank River near Greensboro, MD 38 59 49.9 75 47 08.9 CP 1948-2004h 57

01491010 Sangston Prong near Whiteleysburg, DE 38 58 25 75 43 32 CP 1966-75h 10

01491050 Spring Branch near Greensboro, MD 38 56 34 75 47 25 CP 1967-76h 10

Methods for Estimating the Magnitude and Frequency of Floods 
Table 1. Summary of streamgaging stations in and near Delaware for which streamflow statistics were computed.—Continued

[USGS, U.S. Geological Survey, CP, Coastal Plain Physiographic Province; PD, Piedmont Coastal Plain Physiographic Province; °  ́  ̋, degrees, 

minutes, seconds; N, years of record]

USGS 

station 

number

Name Latitude 

° ‘ ‘’

Longitude 

° ‘ ‘’ Region Peak-flow period N

01492000 Beaverdam Branch at Matthews, MD 38 48 41 75 58 15 CP 1950-81h 32

01492050 Gravel Run at Beulah, MD 38 40 54 75 53 53 CP 1966-76h 11

01492500 Sallie Harris Creek near Carmichael, MD 38 57 53.6 76 06 31.8 CP 1952-81,

2001-4

34

01492550 Mill Creek near Skipton, MD 38 55 00 76 03 42 CP 1966-76h 11

01493000 Unicorn Branch near Millington, MD 39 14 58.9 75 51 40.7 CP 1948-2003c 56

01493500 Morgan Creek near Kennedyville, MD 39 16 48.1 76 00 52.4 CP 1951-2004h 54

01494000 Southeast Creek at Church Hill, MD 39 07 57 75 58 51 CP 1952-59,

1961-65

13

01495000 Big Elk Creek at Elk Mills, MD 39 39 25.4 75 49 20.5 PD 1884,

1932-2004h

73

01495500 Little Elk Creek at Childs, MD 39 38 30 75 52 00 PD 1949-58, 

1989,1999

12

01496000 Northeast Creek at Leslie, MD 39 37 40 75 56 40 PD 1949-84,

1999h

37

01496080 Northeast River tributary near Charlestown, MD 39 35 53 75 58 37 PD 1967-75 10

01496200 Principio Creek near Principio Furnace, MD 39 37 34 76 02 27 PD 1967-92,

1999h

27

01578200 Conowingo Creek near Buck, PA 39 50 35 76 11 45 PD 1963-89, 

1991-2004

41

01578400 Bowery Run near Quarryville, PA 39 53 41 76 06 50 PD 1963-81 19

01578500 Octoraro Creek near Rising Sun, MD 39 41 24 76 07 43 PD 1884,1918,

1932-58, 

1963,

1965-77, 

1999h

44

01578800 Basin Run at West Nottingham, MD 39 39 23 76 04 30 PD 1967-76 10

01579000 Basin Run at Liberty Grove, MD 39 39 30 76 06 10 PD 1949-76,

1999bh

23

a

 1966-1981 estimated based on record for station 01467089.

b

 Station not used in regression analysis.

c

 Peak-flow record adjusted for trends.

d

 1932-55,1978-80,1984-85 estimated based on record for station 01476480.

e

 1994-2004 estimated based on records for stations 01478245, 01478650, and 01479000.

f

 1958-68 estimated based on records for station 01480800, 1969-71 estimated based on records for 

 stations 01480800 and 01481000, historical period based on records for station 01481500.

g

 1912-46 estimated based on records from station 01481000.

h

 Peak-flow record adjusted for historical period.

10 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Plot the annual time series to look for unusual 

observations that will require further investigation and 

to visually detect monotonic or step trends;

Run SWSTAT to perform a Kendall’s tau test on the time 

series to determine if monotonic trends are statistically 

significant (Helsel and Hirsch, 1992);

If necessary, adjust the time series for trends or eliminate 

the station from further analysis;

Run PEAKFQ, applying any necessary historical adjustments, to obtain initial flood-frequency estimates for the 

station, using the default generalized-skew values provided by the program, which are derived from the Bulletin 

17B skew map;

Plot the initial flood-frequency curve to determine if it 

adequately fits the data or if low- or high-outlier thresholds or other adjustments need to be made for the curve to 

better fit the data (fig. 2); and

If necessary, re-run PEAKFQ to apply any adjustments to 

obtain a satisfactory flood-frequency curve.

4.

5.

6.

7.

8.

9.

Completion of the steps described above resulted in 

flood-frequency estimates that were based on weighting of 

the station skew and the Bulletin 17B generalized skew. The 

station skews from these initial analyses were used to develop 

an improved method for computing generalized-skew values 

for the stations used in the study. PEAKFQ was then rerun for 

each station with the new generalized-skew values replacing 

the Bulletin 17B skew values to obtain the final floodfrequency estimates for the stations. The following two 

sections describe methods for handling stations with trends 

and developing new generalized-skew values, respectively.

Simmons and Carpenter (1978) previously determined 

flood-frequency statistics for 21 of the stations used in this 

study by weighting estimates determined from the systematic records for the stations with estimates determined from 

a rainfall-runoff model. The rainfall-runoff model simulated 

a longer period of record than the one actually available for 

the stations. The weighted flood-frequency estimates were 

also used in the previous regression analysis done by Dillow 

(1996). Although none of the stations had additional record 

since either of the two previous reports were published, the 

weighted flood-frequency estimates were not used in this 

ANNUAL PEAK DISCHARGE,

IN CUBIC FEET PER SECOND

ANNUAL EXCEEDANCE PROBABILITY, IN PERCENT

Station 01492000 - Beaverdam Branch at Matthews, MD

104

Bulletin 17-B frequency

Systematic peaks

Systematic frequency

Historical adjusted

Confidence limits

99.5 98 95 90 80 70 50 30 20 10 5 2 1 0.5 0.2

103

102

10

Figure 3. Example flood-frequency curve produced by the PEAKFQ program for Beaverdam Branch at Matthews, 

Maryland.

Methods for Estimating the Magnitude and Frequency of Floods 11
analysis because the previous estimates were not determined 

using the revised generalized-skew values determined for this 

report.

Analysis of and Adjustments for Trends in Annual 

Peak-Flow Time Series

Trends in the annual peak flows at a station can affect the 

reliability and interpretation of the flood-frequency estimates. 

Plots of the peak-flow time series for a station can show 

evidence of (1) gradual upward or downward trends, known 

as monotonic trends; (2) sudden jumps from one condition 

to another, known as step trends; or (3) trends with more 

complex patterns. Visual inspection of the plots indicated 

no stations with step trends or obvious complex patterns, but 

monotonic trends were evident for several stations.

Kendall’s tau tests for monotonic trends (Helsel and 

Hirsch, 1992) were done on the annual series of peak flows for 

all stations considered for use in this study. The two primary 

outputs from the test are the tau value and the probability 

(p-value) associated with accepting the null hypothesis that 

there is no trend when, in fact, a trend exists. The tau value 

measures the strength of the correlation between the annual 

peak-flow values and time. Positive values of tau indicate 

increasing trends and negative values indicate decreasing 

trends. Trends are considered to be significant when the 

p-value is less than or equal to 0.05. At this p-value, there is a 

5-percent likelihood that the test will detect a significant trend 

when there is no actual trend present.

Usually only a small percentage of stations considered 

for use in similar regional flood-frequency studies are found to 

have trends. Because of this, any stations with trends usually 

are excluded from further analysis to avoid the effort required 

to treat the trends and to avoid confusion over how to interpret 

the resulting de-trended statistics. Usually, there are plenty of 

stations left over to use for regression analyses after the 

stations with trends are excluded.

The trend tests done for this study identified 18 stations 

with statistically significant trends (p-values <= 0.05). All 

stations with significant trends had positive tau values, indicating that peak flows were increasing with time. About half of 

the trend-affected stations were in and around southern 

Delaware. The remaining trend-affected stations were 

distributed throughout the region of study. Removal of the 

stations with trends from the regional analysis would leave an 

inadequate dataset to define regional peak-flow frequencies in 

southern Delaware. As a result, the annual-peak-flow records 

for stations with trends were further analyzed to determine if 

climate, land use, or other data could be used as the basis for 

de-trending the peak-flow data.

First, relations between annual series of peak flows 

and maximum 24-hour precipitation were examined for the 

trend-affected stations. Annual series of maximum 24-hour 

precipitation were obtained for 11 precipitation stations in and 

around Delaware from the National Oceanic and Atmospheric 

Administration web site at http://hdsc.nws.noaa.gov/hdsc/pfds/

pfds_series.html (Bonnin and others, 2004), and Kendall’s tau 

trend tests were performed using these data. Tau values for 9 

of the 11 precipitation stations were negative, in contrast to the 

positive tau values for the trend-affected streamgaging stations 

during the same time period, but no precipitation trends were 

statistically significant. From this analysis, it was concluded 

that the increasing trends in the streamflow data were not 

related to similar increasing trends in maximum 

24-hour rainfall. 

Second, relations between annual series of peak flows 

and housing density were examined for the trend-affected 

streamgaging stations. Geographic Information System (GIS) 

coverages of housing-density data for 1960, 1970, 1980, 

1990, and 2000 were obtained from The Nature Conservancy 

(Theobald, 2001). These data were derived from U.S. Census 

Bureau (2001) data. Average housing density, in homes per 

acre, was determined for each station for each decadal sample 

by using GIS to overlay drainage boundaries for the stations 

on the housing data. Linear interpolation between years of 

known housing density was then used to estimate average 

housing density for each year between 1960 and 2000 for 

each station. Values for 2001 through 2004 were extrapolated 

based on the rate of change between 1990 and 2000. The 

annual series of average housing density was related to the 

annual series of peak flows for each of the 18 streamgaging 

stations with significant trends in the peak-flow series using 

scatterplots and regression analyses. The regression analyses 

indicated statistically significant relations between the two 

time series for 8 of the 18 trend-affected stations.

As further described in the Explanatory Variable 

Selection and Measurement section, several GIS datasets were 

available to indicate the degree of urbanization in the study 

area. Housing density and population data were the only data 

that were readily available in 10-year snapshots, enabling 

interpolation to annual time series and relation to the annual 

peak-flow time series. The housing density data were considered superior to the population data for use as an indicator 

of urbanization in Delaware because of the large concentration of vacation homes in coastal areas. Housing density 

was considered more likely to reflect the existence of these 

vacation homes and their effect on peak flows than population 

density, which was not measured for this study. The housing 

density data are strongly related to the percentage of impervious surfaces, as determined from the impervious cover dataset 

developed by the USGS as part of the 2001 National Land 

Cover Dataset (NLCD) (Yang and others, 2003). The impervious data can be downloaded from the web at http://gisdata.

usgs.net/website/MRLC/.

 The relation between 2000 housing density and 2001 

impervious area percentage determined for the streamgaging 

stations used in this study is shown in figure 4. A polynomial 

equation fit through the data has an R2

 value of 0.9144. The 

dependent y variable in the equation in figure 4 is 2000 housing density in homes per acre, and the explanatory x variable 

is 2001 impervious percentage. The R2 value, known as the 

12    Magnitude and Frequency of Floods on Nontidal Streams in Delaware
squares, with a dashed baseline equal to the 2004 value from 

the smoothed trend curve.

Information for stations that were affected by trends is 

provided in table 2. For the 11 stations that were treated for 

trends, table 2 provides the 2- through 500-year floodfrequency estimates, means, standard deviations, and skew 

values of the logarithms of the annual peak flows before and 

after the time series for the stations were treated for trends. In 

addition, the table provides the change per year for the last 

10 years of the trend, in cubic feet per second and in percent, 

the base discharge used in the analysis, and the percentage 

change in housing density during the period of record at the 

station or from 1960 to the end of record for stations with 

record that precedes 1960. The base discharge is the 2004 

value from the smoothed curve through the annual peak-flow 

values for all stations except station 01488500, where record 

ended in 2002. The change-per-year values were determined 

by fitting a regression line through the last 10 values of the 

time series. These values are useful for evaluating the future 

reliability of the flood-frequency estimates for the trendadjusted stations. The time series for 7 of the 18 stations with 

trends were not adjusted for various reasons. A description of 

how the seven stations that were not adjusted for trends were 

treated is also provided in table 2. Asterisks in front of the 

period-of-record housing density change percentages for 8 of 

the 18 stations indicate that the relation between the unadjusted annual peak flows and housing density is statistically 

significant at the 95-percent probability (p-value <= 0.05) for 

those stations.

In all 11 cases where the time series were adjusted for 

trends, the adjustments resulted in larger means and smaller 

standard deviations of the logarithms of the annual-peak 

flows. The skews were smaller in absolute value for 4 of the 

YEAR 2000 HOMES PER ACRE

YEAR 2001 IMPERVIOUS SURFACE PERCENTAGE

8

7

6

5

4

3

2

1

0

0 10 20 30 40 50

y = 0.0033x + 0.0361x + 0.0881

R = 0.9144

2

2

Figure 4. Relation between 2000 housing density and 2001 

impervious surface percentage for streamgaging stations in 

and within 25 miles of Delaware.

coefficient of determination, indicates the proportion of the 

variation in the dependent variable that is explained by the 

explanatory variable. The standard error of estimate of this 

relation is 0.38 homes per acre, meaning that two thirds of the 

estimated homes per acre determined from the equation for 

stations used in the analysis were within the given standard 

error of the measured homes per acre for the stations.

Use of the relations between the annual series of peak 

flows and housing density to de-trend the peak-flow time 

series would give unsatisfactory results for the stations where 

the relations were not significant. Although it was not tried, it 

is also possible that use of only the housing density data to detrend the peak-flow data would not result in complete removal 

of the peak-flow trends for these stations. Resources to further 

investigate other possible physical or climatic mechanisms for 

the trends were not available.

The peak-flow time series for 11 of the trend-affected 

stations were adjusted on the basis of time alone. Trendadjusted peaks were determined for each year by (1) fitting a 

curve through the actual annual values by use of a LOWESS, 

or Locally-Weighted Scatterplot Smoothing, algorithm (Helsel 

and Hirsch, 1992), (2) computing the differences between the 

actual peaks and the corresponding values from the curve, 

and (3) subtracting the difference for each year from the 2004 

value from the smoothed curve. The adjusted values were 

then subjected to the standard Bulletin 17B flood-frequency 

analysis to obtain de-trended estimates of flood frequencies 

and magnitudes for the trend-affected stations.

An example scatterplot that illustrates the treatment of 

trends for station 01484500 is shown in figure 5. The original annual time series of peak-flow values are shown as open 

circles. A solid line is fit through the data by use of the LOWESS algorithm. The trend-adjusted peaks are shown as black 

Figure 5. Time-series plot showing adjustment of annualpeak flows for Stockley Branch at Stockley, Delaware for 

an increasing trend with time.

Figure 5. Time-series plot showing adjustment of annualpeak flows for Stockley Branch at Stockley, Delaware

for an increasing trend with time. DISCHARGE, IN CUBIC FEET PER SECOND

YEAR

Station 01484500 - Stockley Branch at Stockley, DE 350

300

250

200

150

100

50

Initial discharge

LOWESS fit

2004 fit value

Adjusted discharge

0

1930 1940 1950 1960 1970 1980 1990 2000 2010

Methods for Estimating the Magnitude and Frequency of Floods 13
Table 2. Description of treatment of stations with annual peak-flow time series that were affected by trends.

[Recurrence intervals, changes per year, and base discharges are in cubic feet per second; station statistics are in logarithms, base 10; std. dev. is standard deviation; base discharge is trend line value for 2004 except 01488500, which is value for 2002; POR HD change is period-of-record housing density change, in percent; * development-related trend]

Station 

number Scenario

Recurrence interval Station statistics Change

per 

year

Percent

per 

year

Base 

discharge POR HD change 2 5 10 25 50 100 200 500 Mean Std. dev. Skew

Stations for which trends were adjusted before use in the regression analysis 

01467317 Initial 69 147 217 327 425 537 665 859 1.836 0.393 -0.193

Adjusted 210 259 294 342 379 419 460 520 2.329 0.115 0.115 8.67 4.09 212 *6.5

01473169 Initial 1,230 1,930 2,510 3,360 4,100 4,930 5,870 7,310 3.115 0.240 0.803

Adjusted 2,040 2,620 3,050 3,650 4,150 4,680 5,260 6,110 3.317 0.165 0.504 73.9 3.56 2,078 69.7

01475000 Initial 114 220 331 537 755 1,050 1,430 2,140 2.090 0.282 0.423

Adjusted 211 291 353 444 521 607 703 848 2.347 0.164 1.044 7.49 3.64 206 619

01477800 Initial 1,590 2,710 3,670 5,160 6,510 8,070 9,890 12,800 3.220 0.261 0.533

Adjusted 2,440 3,480 4,320 5,560 6,650 7,880 9,280 11,400 3.402 0.182 0.618 37.6 1.56 2,397 36.4

01478500 Initial 3,450 5,720 7,550 10,200 12,500 15,100 18,000 22,200 3.523 0.278 -0.583

Adjusted 4,830 6,710 8,190 10,400 12,200 14,300 16,600 20,100 3.655 0.246 -1.820 17.9 0.38 4,757 *227

01484500 Initial 70 115 151 207 256 312 375 472 1.862 0.242 0.465

Adjusted 120 160 190 231 264 299 338 393 2.093 0.140 0.722 2.54 2.12 120 *290

01485000 Initial 711 1,020 1,270 1,640 1,970 2,330 2,740 3,370 2.869 0.193 0.399

Adjusted 832 1,130 1,360 1,700 1,980 2,300 2,650 3,180 2.935 0.163 0.510 3.32 0.40 831 *200

01485500 Initial 584 966 1,250 1,640 1,960 2,290 2,640 3,130 2.763 0.262 -0.166

Adjusted 827 1,180 1,430 1,770 2,040 2,330 2,640 3,070 2.925 0.176 0.274 11.3 1.38 818 *340

01487000 Initial 630 1,100 1,500 2,100 2,630 3,240 3,930 4,990 2.811 0.278 0.269

Adjusted 1,000 1,440 1,780 2,290 2,720 3,200 3,740 4,550 3.019 0.177 0.802 21.4 2.17 989 120

01488500 Initial 1,040 1,940 2,630 3,560 4,290 5,050 5,820 6,880 2.992 0.334 -0.555

Adjusted 2,160 2,830 3,260 3,780 4,160 4,540 4,900 5,390 3.330 0.135 -0.251 38.7 1.82 2,131 *100

01493000 Initial 334 627 878 1,260 1,600 1,990 2,440 3,110 2.529 0.320 0.076

Adjusted 622 879 1,080 1,390 1,650 1,940 2,280 2,790 2.805 0.189 -0.007 18.3 2.93 625 230

Stations with trends that were not used in the regression analysis and reasons for not using them

01467089 Combined with upstream station 01467087; 1966-80 peaks at station 01467087 estimated based on flow per unit area at station 01467089. 1.6

01467160 No record since 1988 to indicate if trend adjustment is still appropriate. 609

01482310 Development-related trend with no record since 1975 to indicate if trend adjustment is still appropriate. 97.0

01484270 Large break in record results in uncertainty in appropriateness of trend adjustment. *345

01484550 Development-related trend with no record since 1975 to indicate if trend adjustment is still appropriate. *35.0

01489000 No record since 1991 to indicate if trend adjustment is still appropriate. 100

01579000 Large break in record and no record since 1999 to indicate if trend adjustment is still appropriate. 113

14  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
11 stations after adjustment. The trend-adjusted floodfrequency estimates were all higher in discharge for recurrence 

intervals of 2 years or less and lower in discharge for the 200- 

and 500-year recurrence intervals than the non-trend-adjusted 

estimates. Trend-adjusted flood-frequency estimates for 

recurrence intervals between 5 and 100 years were sometimes 

lower and sometimes higher in discharge than those for the 

non-trend-adjusted estimates. 

Housing density increased from 1960 to 2000 for all 

116 stations considered for use in this study except for 

2 stations, where housing density was constant. The average 

increase in housing density, over the period of record for the 

stations or between 1960 and the end of the period of record 

for stations with record prior to 1960, was 121 percent. The 

maximum increase was 619 percent at station 01475000, 

and the standard deviation was 130 percent. Interestingly, 

the relation between the unadjusted annual peak flows and 

housing density was not statistically significant at station 

01475000, but the relation was statistically significant at station 01467317, which had an increase in housing density of 

only 6.5 percent.

Several other investigators have hypothesized a strong 

relation between the magnitude of peak flows and the degree 

of urbanization (for example, Beighley and Moglen, 2003; 

National Resources Conservation Service, 1986; and Sauer 

and others, 1983), so it is somewhat surprising that only 17 of 

the 116 stations considered for use in this study had statistically significant trends in annual peak flows, and that only 8 

of those trends could be attributed to urbanization. Numerous other USGS peak-flow studies have found similarly small 

numbers of stations with trends in annual peak-flow time 

series, however. For instance, recent flood-frequency studies 

for Illinois (Soong and others, 2004), Ohio (Koltun, 2003), 

Vermont (Olson, 2002), and West Virginia (Wiley and others, 

2000) found 50 of 288 stations, 34 of 305 stations, 0 of 138 

stations, and 10 of 160 stations affected by positive trends, 

respectively. Although the other studies did not compare the 

annual peak-flow time series to annual time series of housing density or other indicators of development, the generally 

very small percentage of stations with trends may indicate 

that either better methods are needed to detect trends that are 

actually present or the relation between the magnitude of peak 

flows and the degree of urbanization needs further investigation.

Regional Skew Analysis

As mentioned previously, the skew coefficient describes 

the curvature of the peak-flow frequency curve used to 

describe the annual peak-flow series from a streamgaging 

station. The value of skew is highly influenced by large 

events, and the addition of a single large value to the annual 

peak-flow time series for a station with a short record length 

can have a large influence on the skew. Also, a localized large 

event can have a large influence on the skew for an individual 

station. This causes large variations in skew between stations. 

Because of this, it is advantageous to improve the accuracy of 

the skew coefficient for any station by considering not only 

data from that station, but also information from other nearby 

stations. For the purpose of discussion, the station skew is 

defined as the skew calculated using the annual peak-flow 

series from that station alone. The generalized skew is defined 

as a skew coefficient associated with a defined region, calculated using the station skews from all stations in the region. A 

weighted skew, calculated using the station skew and a generalized skew, is used to calculate the flood-frequency statistics 

used in regression analyses to produce the peak-flow estimation equations for ungaged sites presented in this report.

The calculations of the station skew and the weighted 

skew are performed using the peak-flow series for an individual station and the equations and methods given in Bulletin 

17B. Generalized skew can also be obtained from a national 

map of generalized-skew values included in Bulletin 17B; 

however, that map was prepared at a national scale using 

data and methods that are now more than 30 years old. It is 

generally preferable for regional studies of flood frequency to 

include a regional analysis of station skews to either confirm 

the reasonableness of using the Bulletin 17B skew map or to 

generate more accurate generalized-skew values using the latest available station skews (Interagency Advisory Committee 

on Water Data, 1982, Plate 1). Bulletin 17B provides the following recommendations with regard to the data and methods 

to be used for a generalized-skew analysis:

Data from at least 40 stations, or all stations within a 

100-mi radius of the study region should be used in the 

analysis;

Each station providing data for the analysis should have at 

least 25 years of peak-flow record;

The recognized analytical methods for calculating generalized skew, in order of preference, are (a) development of 

skew isolines, (b) development of skew prediction equations, and (c) calculation of the mean station-skew value. 

A generalized-skew analysis using these guidelines was 

performed as part of the study. The steps followed, as well as 

the results, are discussed below.

From the dataset of 116 stations considered for use in 

this flood-frequency study, 53 of them had 25 or more years of 

peak-flow record and were suitable for use in the initial skew 

analysis. Graphical analysis indicated that the station-skew 

data associated with these sites is unbiased and approximately 

normally distributed.

The station skews for the 53 stations were plotted on a 

map (fig. 6), which was visually inspected for spatial patterns in the skew values. To create the map, the stations were 

separated into six bins based on the magnitude of the skew 

value. The three bins with the smallest skew values were 

shown on the map with circular symbols in shades of red, with 

the size of the circle and the intensity of the color increasing 

as the skew value decreased. The three bins with the largest 

skew values were shown on the map with circular symbols 

1.

2.

3.

Methods for Estimating the Magnitude and Frequency of Floods 15
A

T

L

A

N

T

I

C

O

C

E

A

N

D E L A W A R E

B A Y

DELAWARE RIVER

POTOMAC RIVER

C & D

C

H

E

S

A

P

E

A

K

E

B

A

Y

H A R F O R D

L A N C A S T E R

C H E S T E R D E L A W A R E

S A L E M

C U M B E R L A N D

C A P E

M A Y

G L O U C E S T E R

M O N T G O M E R Y B U C K S

BURLINGTON

ATLANTIC

CAMDEN

C E C I L

K E N T

T A L B O T

C A R O L I N E

D O R C H E S T E R

W I C O M I C O

W O R C E S T E R

S O M E R S E T

N E W

C A S T L E

K E N T

S U S S E X

Y O R K

PENNSYLVANIA

MARYLAND

DELAWARE

MARYLAND

MARYLAND

VIRGINIA

NEW JERSEY

CANAL

Q U E E N

A N N E S Creek

Cr.

Chester

River

EASTERN

BAY

Choptank River

Patapsco River

L. Choptank R.

Chincoteague Bay

Nanticoke

River

Pocomoke

River

Fishing

Bay

Rehoboth

Bay

Indian River

Bay

Broad Creek

Wicomico R.

Nassawango

Creek

Manokin

River

Choptank

River

St. Jones R.

Murderkill

River

Marshyho ep

Creek

Tuckahoe

Elk

River

River

Leipsic River Unicorn Br.

Smyrna

River

Sassafras

Schuylkill

River

Salem River

Mantua Cr.

Great

Egg

Harbor

R.

Rancocas Cr.

Cohansey R.

Maurice

R.

West

Br.

Br.

Brandywine

East

Christina River

L. Elk Cr.

SUSQUEHANNA

RIVER Conowingo

Cr.

Octoraro Cr.

East Br.

West Br.

Raccoon Cr.

Annapolis

Elkton

Chestertown

Centreville

Denton

Easton

Cambridge

Salisbury

Princess

Anne Snow Hill

Wilmington

Dover

Georgetown

Lancaster

West Chester

Media

Philadelphia

0

0

10

10 20 KILOMETERS

20 MILES

EXPLANATION

-1.820 to -0.451

SKEW RANGE

-0.409 to -0.073

-0.007 to 0.198

0.207 to 0.373

0.382 to 0.776

0.793 to 1.385

76° 75°

40°

39°

38°

Figure 6. Skew ranges for streamgaging stations in Delaware and surrounding states with 25 

or more years of record.

16  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
in shades of green, with the size of the circle and the intensity of the color increasing as the skew value increased. As 

a result, the more extreme values of skew, in either direction, 

had larger, darker circles, and appeared more prominently on 

the map. An examination of the map indicated that the skew 

values in the northern part of the study area were, on average, 

higher than the values in the southern part of the study area. 

The variation between sites was too large to allow the development of meaningful skew isolines, however. Consequently, 

an attempt was then made to develop prediction equations for 

station skew.

Weighted least-squares (WLS) regressions were 

performed using station skew as the response variable. All 

available basin-characteristic and climatic variables (Peter 

Steeves, USGS, written commun., 2005) were tested as 

explanatory variables. The weighting scheme used in the 

WLS analysis was the one proposed by Stedinger and Tasker 

(1986). The explanatory variables found to have the strongest 

linear relations with station skew were storage and development intensity; however, the coefficients of determination (R2

) 

for both relations were less than 0.03, indicating that each 

relation explained less than 3 percent of the variation in station 

skew. No relations were statistically significant at the 

95-percent confidence level, the level generally considered to 

be the minimum acceptable for statistical estimation. Neither 

of the identified relations predicted the value of station skew 

with enough accuracy to be useful in calculating the 

generalized skew.

When isolines and regression equations do not prove 

useful as means of developing generalized skews, as was the 

case for this study, Bulletin 17B recommends determining the 

generalized skew by computing the mean and variance of the 

station skews for all stations in the region having 25 or more 

years of record. As resources were not available to attempt 

more sophisticated techniques, the Bulletin 17B recommendations were followed. The mean and variance of the station 

skews for 53 stations in the study region were determined to 

obtain initial generalized skew and variance values for 

Delaware of 0.156 and 0.327, respectively. 

Previous studies performed in this region have found 

that physiography was a significant factor in estimating flood 

frequency, so this issue was considered in the regional skew 

analysis as well. The dataset was split initially by physiographic province to determine whether physiography was a 

significant factor in determining station skew. Of the 53 sites 

used, 27 were in the Coastal Plain subset and 26 were in the 

Piedmont subset. The mean and variance of the station skews 

for the Piedmont were 0.107 and 0.348, whereas the mean 

and variance for the Coastal Plain were 0.204 and 0.314, 

respectively. The means of the Coastal Plain and Piedmont 

station-skew subsets were each compared to the mean station 

skew for the entire data set using t-tests. The means of the two 

subsets were also compared to each other directly. Results 

from all comparisons indicate that neither subset has a mean 

that is significantly different from the whole dataset, nor were 

the two subsets significantly different from each other at the 

95-percent confidence level.

A further test was done to determine if use of separate 

mean skews for each region would result in improved accuracy 

of the generalized-skew estimates over use of a single mean 

skew value for the entire study area. Variances were computed 

for each region using the mean skew value determined from all 

53 stations rather than using the regional means, as described 

above. The resulting variances were 0.350 for the Piedmont and 0.317 for the Coastal Plain. Because the variances 

determined using the regional means are lower than those 

determined using the mean skew of all 53 sites, the accuracy 

of the generalized-skew estimate will be greater if the estimate is made based on the physiographic subsets. Therefore, 

generalized-skew values used in the flood-frequency analyses 

done for this study were based on the mean skews for each 

physiographic region, 0.107 for the Piedmont and 0.204 for 

the Coastal Plain.

Regional Flood-Frequency Relations

Regression analysis was used to develop separate sets of 

equations for use in estimating the magnitude and frequency 

of floods for unregulated, ungaged sites in two hydrologic 

regions of Delaware. The hydrologic regions correspond to 

the Coastal Plain and Piedmont physiographic regions, as 

discussed below. The equations statistically relate the 2-, 5-, 

10-, 25-, 50-, 100-, 200-, and 500-year floods computed from 

available records for data-collection stations (streamgaging 

and peak-flow partial-record stations) in each of the regions to 

measured physical and climatic characteristics of the drainage 

basins for the stations. A database for the regional analysis 

was developed using active and discontinued streamgaging 

stations, and populated with flood-frequency estimates for 

selected recurrence intervals for the streamgaging stations 

and the hydrologic characteristics of the basins upstream from 

each station. The total number of stations included in the 

regression analyses by hydrologic region and state, and the 

number of stations with 25 years or more of record for each 

grouping are shown in table 3. The number of stations and the 

average years of record for given ranges of drainage area, by 

hydrologic region and for all stations, are listed in table 4.

Explanatory Variable Selection and 

Measurement

Basin characteristics were selected for use as potential 

explanatory variables in the regression analyses on the basis 

of their theoretical relation to flood flows, results of previous 

studies in similar hydrologic regions, and the ability to measure the basin characteristics using digital datasets and GIS 

technology. The ability to measure the basin characteristics by 

use of a GIS was important to facilitate eventual automation of 

the process for measuring the basin characteristics and solving 

the regression equations for ungaged sites. The automation 

Methods for Estimating the Magnitude and Frequency of Floods 17
Table 3. Number of streamgaging stations included in the regression analyses by 

hydrologic region and state.

[POR, period of record; >=, greater than or equal to; DE, Delaware; MD, Maryland; 

NJ, New Jersey; PA, Pennsylvania]

Region

State

DE MD NJ PA Total

Coastal Plain

Total stations 20 15 20 0 55

POR >= 25 9 9 9 0 27

Piedmont

Total stations 13 7 0 27 47

POR >= 25 6 4 0 16 26

All

Total stations 33 22 20 27 102

POR >= 25 15 13 9 16 53

Table 4. Summary of drainage area, number of streamgaging stations, and average years of record used in the 

regression analyses for Delaware.

[--, not applicable]

Drainage area

(square miles)

Number of streamgaging stations Average years of observed record

Coastal 

Plain Piedmont Total Coastal Plain Piedmont Total

0 - 1 3 2 5 20.3 10.0 16.2

1 - 2 2 4 6 25.0 11.5 16.0

2 - 5 12 3 15 24.1 22.7 23.8

5 - 10 13 8 21 27.4 27.6 27.5

10 - 20 14 4 18 29.2 31.5 29.7

20 - 50 6 15 21 40.0 31.1 33.6

50 - 10 3 9 12 44.0 45.7 45.3

100 - 200 2 1 3 64.5 44.0 57.7

200 - 500 0 1 1 -- 93.0 93.0

 Total 55 47 102 30.3 31.8 31.0

process is described later in the StreamStats section. The 

name, units of measure, method of measurement, and source 

data for each measured basin characteristic are listed in 

table 5. The climatic and basin characteristics measured for 

each station considered for use in the regression analyses are 

listed in tables 6 and 7, respectively, at the back of the report.

Drainage-basin boundaries were needed for each station 

before their basin characteristics could be measured. A GIS 

and a Digital Elevation Model (DEM) can be used to measure basin boundaries; however, boundaries determined from 

DEMs can sometimes be inaccurate, especially in low-lying 

coastal areas, such as those in much of Delaware. To improve 

boundary delineations and to facilitate implementation of the 

StreamStats web application (discussed on page 35) for areas 

in or that drain into Delaware, processing was done to make 

the 10-meter resolution National Elevation Dataset (NED) 

(U.S. Geological Survey, 1999a) DEM conform to the streams 

in the National Hydrography Dataset (NHD) (U.S. Geological 

18  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Name Units Method Source data

24-hour, 2-, 5-, 10-, 25-, 

50-, 100-, 200-, and 

500-year maximum 

precipitation

Inches Area average U.S. National Oceanographic and Atmospheric Administration Atlas 14, Volume 

2 (http://hdsc.nws.noaa.gov/hdsc/pfds/index.html)

Average soil permeability Inches per hour Area average of maximum and 

minimum values of permeability of the surface soil layer

State Soil Geographic (STATSGO) Data 

(http://www.ncgc.nrcs.usda.gov/products/

datasets/statsgo/)

Basin relief Feet Maximum - minimum basin 

elevation

National Elevation Dataset elevation grid, 

10- and 30-meter resolution (http://ned.

usgs.gov/)

Basin shape factor Dimension-less Main channel length squared 

divided by drainage area

National Hydrography Dataset, 1:24,000 

scale (http://nhd.usgs.gov/), and National 

Elevation Dataset, 10- and 30-meter 

resolution (http://ned.usgs.gov/)

Development intensity Percent ((.10*A21+.25*A22+.65*A23+.

90*A24)/ drainage area)*100, 

where A21 through A24 are 

land-use classes defined at 

http://www.mrlc.gov/nlcd_definitions.asp

National Land-Cover Dataset 2001 (http://

www.mrlc.gov/mrlc2k_nlcd.asp) and 

Delaware Land-Use Cover 2003 (http://

datamil.delaware.gov)

Drainage area Square miles ArcHydro method National Elevation Dataset elevation grid, 

conditioned to conform with National 

Hydrography Dataset streams, 1:24,000 

scale (http://nhd.usgs.gov/), and 

Watershed Boundary Dataset drainage 

boundaries (http://www.ncgc.nrcs.usda.

gov/products/datasets/watershed/)

Station elevation Feet Point elevation from grid at the 

streamgaging station

National Elevation Dataset elevation grid, 

30-meter resolution (http://ned.usgs.gov/)

Housing density Homes per acre Area average for centroid year 

of record

Derived from Theobald, 2001

Hydrologic soil type A Percent (Area of type A soil/drainage 

area)*100; type A is high 

infiltration-rate soils

State Soil Geographic (STATSGO) Data 

(http://www.ncgc.nrcs.usda.gov/products/ 

datasets/statsgo/index.html)

Hydrologic soil type D Percent (Area of type D soil/drainage 

area)*100; type D is very slow 

infiltration-rate soils

State Soil Geographic (STATSGO) Data 

(http://www.ncgc.nrcs.usda.gov/products/ 

datasets/statsgo/index.html)

Main channel length Miles ArcHydro method using longest 

flow path extended to basin 

divide

National Hydrography Dataset, 1:24,000 

scale (http://nhd.usgs.gov/)

Mean annual precipitation Inches Area average DAYMET (http://www.daymet.org/)

Mean basin elevation Feet Area average National Elevation Dataset, 10-meter resolution (http://ned.usgs.gov/)

Mean basin slope Percent Mean of slope grid values within 

the drainage area

National Elevation Dataset slope grid, 10-

meter resolution (http://ned.usgs.gov/)

Table 5. Basin characteristics considered for use in the regression analyses.

Methods for Estimating the Magnitude and Frequency of Floods 19
Name Units Method Source data

Mean stream slope Feet per mile ArcHydro method for computing 

the mean of the slope grid values for all cells that intersect 

the stream channel from the 

site to the basin divide

National Hydrography Dataset, 1:24,000 

scale (http://nhd.usgs.gov/), and National 

Elevation Dataset slope grid, 10- and 30-

meter resolution (http://ned.usgs.gov/)

Percent developed Percent (Sum of areas of classes A21-

A24/drainage area)*100, 

where land-use classes are 

defined at http://www.mrlc.

gov/nlcd_definitions.asp

National Land-Cover Dataset 2001 (http://

www.mrlc.gov/mrlc2k_nlcd.asp) and 

Delaware Land-Use Cover 2003 (http://

datamil.delaware.gov)

Percent forest Percent (Sum of areas of classes A42-

A43, A92, A93/drainage 

area)*100, where land-use 

classes are defined at http://

www.mrlc.gov/nlcd_definitions.asp

National Land-Cover Dataset 2001 (http://

www.mrlc.gov/mrlc2k_nlcd.asp) and 

Delaware Land-Use Cover 2003 (http://

datamil.delaware.gov)

Percent impervious Percent (Impervious area/drainage 

area)*100

National Land-Cover Dataset 2001 Imperviousness (http://www.mrlc.gov/mrlc2k_

nlcd.asp)

Percent storage NHD Percent (Sum of areas of wetlands and 

open water/drainage area)*100

National Hydrography Dataset, 1:24,000 

scale (http://nhd.usgs.gov/)

Percent storage NLCD/DE Percent (Sum of areas of classes A10, 

A91-A99/drainage area)*100, 

where land-use classes are 

defined at http://www.mrlc.

gov/nlcd_definitions.asp

National Land-Cover Dataset 2001 (http://

www.mrlc.gov/mrlc2k_nlcd.asp) and 

Delaware Land-Use Cover 2003 (http://

datamil.delaware.gov)

Stream slope, 10/85 method Feet per mile ArcHydro method of computing stream slope from points 

10- and 85-percent of the 

distance from the site to the 

basin divide

National Hydrography Dataset, 1:24,000 

scale (http://nhd.usgs.gov/), and National 

Elevation Dataset elevation grid, 10- and 

30-meter resolution (http://ned.usgs.gov/)

Table 5. Basin characteristics considered for use in the regression analyses.—Continued

Survey, 1999b) and to watershed boundaries in the Watershed 

Boundary Dataset (WBD) (Natural Resources Conservation 

Service, 2004). This process was developed by Peter Steeves 

(2002), and was done using the ArcHydro Tools (Environmental Systems Research Institute, Inc., 2005). The resulting 

conditioned DEM was used only for basin-boundary delineations. The original DEM was used to measure all other basin 

characteristics for the study that required elevation information.

As a means of quality assurance, the drainage areas 

computed by use of the GIS and the conditioned DEM were 

compared to the previously published drainage areas for the 

stations and to Digital Raster Graphics (DRG) scanned images 

of USGS topographic maps for the area of interest (U.S. Geological Survey, 2005). The measured and published drainage 

areas agreed closely for most stations, but several differences 

of greater than 5 percent were found. In most of these cases, 

the published drainage areas were determined from older 

topographic maps with 10-ft contour intervals, whereas the 

conditioned 10-m (meter) NED from which the boundaries 

were determined using a GIS was derived from newer topographic maps with 5-ft contours. In all cases, the boundaries 

determined from the GIS were considered superior in accuracy 

to the previously published figures. The drainage areas shown 

in table 7 are those determined for this study by use of the 

GIS. Asterisks appear in table 7 beside the drainage areas for 

several stations. The official drainage areas for these stations 

have been revised to agree with the GIS measurements.

For stations with drainage areas that were entirely outside 

of Delaware, the 30-m resolution NED was used to determine 

elevation-dependent basin characteristics. Digital drainage 

boundaries for these stations were determined by USGS personnel from the offices for the states where the stations were 

located, and provided for use in this study.

20 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Four basin characteristics were measured for this study as 

possible indicators of urbanization: (1) housing density, 

(2) percent developed, (3) development intensity, and 

(4) percent imperviousness. The methods and source data 

used to measure these characteristics are presented in table 5. 

As mentioned above, annual series of housing density were 

determined for each station by interpolation from GIS coverages of housing density for 1960, 1970, 1980, 1990, and 2000 

(Theobald, 2001). In addition, housing density was computed 

for the centroids of the periods of record for each station from 

the annual values. A few stations had centroids of their periods of record that were before 1960. The 1960 values were 

used for those stations.

Development intensity is a surrogate measurement of the 

percentage of impervious surfaces in a basin that is derived 

from the NLCD land-cover dataset rather than from the NLCD 

impervious-cover dataset. Development intensity was computed by multiplying the area of each NLCD land-cover class 

for developed land (classes 21-24 at http://www.mrlc.gov/

nlcd_definitions.asp) within a basin by the average proportion 

of impervious surfaces attributed to the class by Bird and others (2002), summing these amounts, dividing the sum by the 

drainage area, and then multiplying the result by 100 to obtain 

percentages.

The ArcHydro Tools were used to measure main channel 

lengths and slopes. The ArcHydro Tools method for measuring main channel length uses the longest flow path from the 

NHD stream network, and then extends the flow path from the 

upstream end of the NHD stream to the highest elevation that 

contributes drainage to the main channel. Two methods were 

used to measure main channel slope. One method determines 

the distances for points at 10 and 85 percent of the distance 

along the main channel from the NHD and the corresponding elevations from the DEM, and then divides the difference 

in elevation between the two points by 0.75 times the main 

channel length. This is the ArcHydro Tools implementation 

of the traditional channel slope method recommended by the 

Interagency Advisory Committee on Water Data (1977), often 

referred to as the 10/85 method. 

The other method for measuring main channel slope 

takes the average value of slopes computed for each grid cell 

in the DEM that has spatial correspondence with the NHD 

main stream channel. This new method in the ArcHydro Tools 

should be a more accurate measure of main channel slope than 

the method recommended by the Interagency Advisory Committee on Water Data (1977) because the slope is determined 

from an average of the elevations along the stream rather than 

from only two points along the stream channel. On average, 

926 elevations were used to determine main channel slope for 

the stations used in this study.

The two methods for measuring main channel slope 

gave results that were highly correlated. A graph of the 

relation between the results of the two slope-measurement 

methods, with a regression line fit through the data is shown 

in figure 7. The R2

 value for the relation is 0.938. The exponent of the 10/85 slope (the x variable) in the equation in 

figure 7 is nearly one, thus the ArcHydro slope can be reasonably approximated from the 10/85 slope by adding 19 percent 

to the 10/85 slope value. Tests in other areas would be needed 

to determine if this relation between the two methods is consistent everywhere. Overall, however, this relation indicates 

that the traditional 10/85 slope method yields results for 

most stations in and around Delaware that are very similar to 

those obtained from the much more data-intensive ArcHydro 

method.

The land-use variables development intensity, percent 

developed, percent forest, and percent storage were measured 

using a dataset that combined the 2001 NLCD in areas outside 

of Delaware and a land-use dataset that was developed for 

Delaware from 2002 aerial photography. Metadata for the 

Delaware land-use dataset is available online at http://maps.

udel.edu/metadata/full_metadata.jsp?docId=%7BDEA492B3-

17AA-4AD3-957F-3CA3F384A0AF%7D&loggedIn=false.

For comparative purposes, percent storage was also 

measured using the NHD. Differences between percent storage measured from the combined land-use dataset (NLCD.

DELU) and from the NHD were substantial. Percent storage 

determined from the NHD reflects all areas of lakes, ponds, 

reservoirs, wide rivers, and wetlands, as shown on USGS 

1:24,000-scale topographic maps. Percent storage determined 

from the NLCD.DELU dataset reflects all areas of open water 

and wetland land-use categories. Except for one station, storMAIN CHANNEL SLOPE, 10/85 METHOD,

IN FEET PER MILE

MAIN CHANNEL SLOPE, ARCHYDRO METHOD,

IN FEET PER MILE

1,000

100

10

1

1 10 100 1,000

y = 1.1918x

R = 0.938

1.007

2

Figure 7. Relation between the new ArcHydro and the traditional 

10/85 method for measuring main channel slope for stations used 

in the regression analysis.

Methods for Estimating the Magnitude and Frequency of Floods 21
age values determined from NLCD.DELU were larger than 

those from the NHD.

Boxplots of the two storage measurements are shown 

in figure 8. The boxplots show how the data are distributed 

(Tukey, 1977). The horizontal line inside the box shows the 

location of the median value. The top and bottom of the box 

indicate the quartiles, which are the values that are exceeded 

75 and 25 percent of the time. The vertical lines extending 

upward and downward from the box are known as the whiskers. They encompass all values that are within 1.5 times the 

length of the box (1.5 times the interquartile range). Values 

that are within the upper and lower whiskers are indicated in 

the explanation as within the upper and lower adjacent regions 

of the boxplots, respectively. Values that are outside the 

whiskers are shown individually. Values shown with an “x” 

in the boxplot are referred to as outside values. These values 

are within 3 times the interquartile range in either direction 

from the median. The values shown with an “o” in the boxplot 

are referred to as detached values. These values are more 

than 3 times the interquartile range in either direction from 

the median. The boxplots show that the 75th percentile of the 

NHD values is approximately equal to the 25th percentile of 

the NLCD.DELU values.

Percent storage values from the NLCD.DELU were 

much more highly correlated with flood frequencies than the 

values from the NHD, indicating that NLCD.DELU storage 

is a better individual predictor of flood frequencies than NHD 

storage. As discussed in the next section, however, when used 

in conjunction with other explanatory variables, the inclusion of NHD storage provided regression equations with the 

greater accuracy in predicting flood magnitudes of specified 

frequency. Correlation coefficients between the logarithms of 

NLCD.DELU values and the logarithms of the T-year floods 

ranged from -0.338 for the 2-year flood to -0.396 for the 

500-year flood. Correlation coefficients for the NHD values 

ranged from 0.003 for the 10-year flood to -0.039 for the 

500-year flood.

Much of the land area of southern Delaware has been 

ditched to provide drainage for agriculture. One issue of concern for DelDOT was that the NHD representation of streams 

would inadequately capture the ditches that are actually 

present on the landscape, and there would be errors in drainage boundaries and basin characteristics determined for some 

selected streams because of this. Consequently, a GIS was 

used to compare the NHD streams to county-mapped ditches, 

and to determine if incorporation of the ditches into the NHD 

would be necessary. The comparison indicated that the NHD 

incorporated the great majority of the ditches. Some areas 

had ditches that were not included in the NHD, and drainage 

boundaries determined for these areas could be in error. In 

general, however, the affected areas are small (less than 1 mi2

). 

It was determined that adding all missing ditches into the 

NHD would be too large a task for inclusion in this study, and 

it would generally provide little benefit.

Development of Regression Equations

Regression equations were developed for use in 

estimating peak flows associated with the 2- through 500-year 

recurrence intervals at both ungaged and gaged locations for 

the two hydrologic regions in Delaware. All response (T-year 

peak flows) and explanatory variables (basin characteristics) 

were transformed to logarithms, base 10, prior to the regression analyses to obtain linear relations between the response 

variables and the explanatory variables, and to achieve equal 

variance about the regression line. A one (1) was added to all 

basin characteristics given as percentages to facilitate 

transformation to logarithms.

Equation development was done in three phases. The 

first phase used weighted all-possible-subsets (APS) regression methods to identify possible optimal combinations of 

explanatory variables. The second phase used WLS regression to test the adequacy of candidate explanatory variable 

subsets for violations of regression analysis assumptions and 

to determine if separate sets of equations were needed for each 

physiographic region. The third phase used EstimatedGeneralized-Least-Squares (EGLS) regression methods to 

determine the final regression equations.

EXPLANATION

75th PERCENTILE (75 percent of the

data values are less than this value.)

MEDIAN

INTERQUARTILE

RANGE (IQR)

25th PERCENTILE (25 percent of the

data values are less than this value.)

MINIMUM VALUE

MAXIMUM VALUE

DETACHED VALUE (greater than 3

times the IQR outside the quartile)

OUTSIDE VALUE (less than or equal

to 3 times and greater than 1.5 times

the IQR outside the quartile)

X

X

X

X

X

X

X

X

XX

PERCENT STORAGE

40

30

20

10

0

NHD NLCD.DELU

Figure 8. Percent storage measured using the National 

Hydrography Dataset (NHD) and a combination of the 2001 

National Land Cover Dataset (NLCD) and the 2002 Delaware 

Land-Use Dataset (DELU).

22 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
In APS regression (Neter and others, 1985, p. 421-429), 

all possible combinations of explanatory variables were 

tested to identify a small set of possible best combinations of 

explanatory variables for further testing with WLS regression 

methods. Weighting was applied in the APS regressions to 

correct for differences in record length by dividing the number 

of years of systematic data available for each station by the 

mean record length for all stations. As a result, stations with 

longer records were given greater weight in the analysis than 

stations with shorter records. The Mallow’s Cp criterion was 

used for selecting best subset combinations (Neter and others, 

1985, p. 426-428). 

The WLS analyses were used for detailed testing of 

candidate models identified through the APS analyses. 

Weights used in the WLS analyses were the same as those 

used for the APS analyses. WLS results were examined to 

identify potential undesirable statistical characteristics, and to 

select the final combinations of variables to be included in the 

EGLS analysis. Possible undesirable statistical characteristics 

that could lead to elimination of a set of candidate explanatory variables included (1) geographic bias of the potential 

equations, (2) extreme influence of flood-frequency values or 

high leverage of the basin characteristics for individual stations, (3) high correlation (multicollinearity) among potential 

explanatory variables, or (4) lack of statistical significance of 

the explanatory variables at the 95-percent probability level. 

The WLS analyses indicated that developing separate sets 

of regression equations for the Coastal Plain and Piedmont 

hydrologic regions would result in more accurate relations 

than developing a single set of equations for the entire State.

EGLS was used to determine the final regression 

equations because the EGLS algorithm is able to assign 

weights to the stations used in the analysis to adjust not only 

for differences in record length, as in WLS, but also for crosscorrelation of the annual time series on which the peak-flow 

statistics for the stations are based, and for spatial correlation 

among the stations (Stedinger and Tasker, 1985). Because the 

WLS and EGLS weighting schemes were not the same, it was 

necessary to test several combinations of explanatory variables 

identified through the APS/WLS process to determine the best 

EGLS equations for the 2- through 500-year recurrence intervals in each of the two hydrologic regions. The combinations 

of explanatory variables that met all requirements with regard 

to leverage, influence, and multicollinearity while also providing the lowest estimation error for each recurrence interval in 

each region, were selected for inclusion in the final regression 

equations.

The results of the analyses described above are separate 

sets of the best regression equations for the Piedmont and 

Coastal Plain regions, which can be used to estimate peak 

flows of known accuracy with recurrence intervals between 

2 and 500 years for gaged and ungaged streams in Delaware. 

The final equations were developed for the Piedmont using 

47 stations, and for the Coastal Plain using 55 stations. Fourteen sites that were considered for use were excluded from 

regression equation development—7 with unadjustable trends 

in their annual peak-flow series, 5 that are in close proximity on the same stream to sites that were included, and 2 that 

exerted undue leverage on the form of the regression equations caused by basin characteristic values that are atypical of 

streams in Delaware. The best equations are as follows:

Piedmont region

PK2 = 1,320DRNAREA0.684(FOREST+1)-0.540(SOILA+1)-0.219

(IMPNLCD01+1)0.101 (2)

PK5 = 3,080DRNAREA 0.662(FOREST +1)-0.568(SOILA+1)-0.224 (3)

PK10 = 2,190DRNAREA 0.674(FOREST +1)-0.447(STORNHD+1)-0.346 (4)

PK25 = 2,580DRNAREA 0.675(FOREST +1)-0.391(STORNHD+1)-0.445 (5)

PK50 = 2,840DRNAREA 0.679(FOREST +1)-0.353(STORNHD+1)-0.520 (6)

PK100 = 3,090DRNAREA 0.684(FOREST +1)-0.316(STORNHD+1)-0.594 (7)

PK200 = 3,310DRNAREA 0.689(FOREST +1)-0.282(STORNHD+1)-0.668 (8)

PK500 = 3,600DRNAREA 0.698(FOREST +1)-0.239(STORNHD+1)-0.765 (9)

Coastal Plain region

PK2 = 92.8DRNAREA 0.710BSLDEM10M 0.303(SOILA+1)-0.301 (10)

PK5 = 157DRNAREA 0.710BSLDEM10M 0.292(SOILA+1)-0.310 (11)

PK10 = 210DRNAREA 0.709BSLDEM10M 0.289(SOILA+1)-0.316 (12)

PK25 = 288DRNAREA 0.711BSLDEM10M0.292(SOILA+1)-0.323 (13)

PK50 = 353DRNAREA 0.712BSLDEM10M0.297(SOILA+1)-0.328 (14)

PK100 = 425DRNAREA 0.715BSLDEM10M0.303(SOILA+1)-0.332 (15)

PK200= 505DRNAREA 0.717BSLDEM10M0.310(SOILA+1)-0.337 (16)

PK500 = 623DRNAREA 0.720BSLDEM10M0.320(SOILA+1)-0.344 (17)

Methods for Estimating the Magnitude and Frequency of Floods 23
where

PK2, PK5,..., PK500 are the peak discharges for 

floods with recurrence intervals of 2 years, 

5 years,..., 500 years, in ft3/s;

DRNAREA is the drainage area, in mi2;

FOREST is percent forest;

IMPNLCD01 is percent impervious determined 

from the 2001 NLCD impervious dataset;

STORNHD is percent storage from NHD, in 

percent;

BSLDEM10M is mean basin slope determined 

from a 10-m DEM, in percent, and;

SOILA is hydrologic soil type A, in percent, high 

infiltration-rate soils.

The methods and source data used to calculate the 

variables in equations (2) through (17) are identified in 

table 5. Discharge estimates calculated by use of the 

equations are in units of cubic feet per second, but they may 

be converted to other measurement systems by applying the 

appropriate conversion factor. Systematic record, regression equation, and weighted estimates of the flood-frequency 

statistics for each station considered for use in the regression 

analyses are shown in table 8. The method for determining the 

weighted estimates is described below.

Normally, allowing the equation for each recurrence 

interval to contain the best variables for estimating flood 

discharge for that interval without regard to variables used for 

other recurrence intervals improves the accuracy of the equations. The drawback to this approach, however, is that equations that contain different variables for successive recurrence 

intervals may provide estimated discharge magnitudes that do 

not increase with increasing recurrence interval. The 2-year 

recurrence interval flood discharge estimate for a particular 

site may be larger than the 5-year estimate for the same site, 

for example.

The initial set of best equations developed for each region 

had explanatory variables that differed among the recurrence 

intervals. Tests of these equations indicated a high incidence 

of estimated flood flows that did not increase with increasing 

recurrence interval. To avoid these irregularities, the housing 

density explanatory variable that was found significant for the 

2-, 5-, and 10-year recurrence intervals for the Coastal Plain 

was replaced by the mean basin slope explanatory variable for 

these recurrence intervals to avoid reductions in flow between 

the 10- and 25-year recurrence intervals when housing density 

was included in the equations. Dropping of housing density 

from the Coastal Plain equations lowered the accuracy of the 

affected equations somewhat, but eliminated irregularities in 

estimated flows with increasing recurrence intervals.

The percent storage explanatory variable was allowed 

to remain in the equation for estimating the 10-year peak 

discharge for the Piedmont, and the percent forest explanatory 

variable was allowed to remain in the equation for estimating the 500-year peak discharge for the Piedmont region even 

though their statistical significance in the relations did not 

meet the standard criterion used for variable selection. These 

substitutions of variables reduced irregularities in the 

estimated flows with increasing recurrence intervals, but some 

irregularities can still occur between flow estimates for the 

5- and 10-year recurrence intervals when the percent forest for 

an ungaged site is less than about 15 percent.

Accuracy and Limitations

The accuracy of a regression equation depends on the 

model error and the sampling error. Model error measures the 

ability of a set of explanatory variables to estimate the values 

of peak-flow characteristics calculated from the station records 

used to develop the equation. Sampling error measures the 

ability of a finite number of stations with a finite number of 

recorded annual peak flows to describe the true peak-flow 

characteristics of the entire peak-flow record for a station. 

Model error depends on the number and predictive power of 

the explanatory variables in a regression equation. Sampling 

error depends on the number and record length of stations used 

in the analysis, and decreases as the number of stations and 

record lengths increases.

Traditional measures of the accuracy of peak-discharge 

regression equations are the standard errors of estimate and 

prediction, and the equivalent years of record. The standard 

error of estimate is derived from the model error, and is a 

measure of how well the estimated peak discharges generated 

using an equation agree with the peak-flow statistics generated from station records that were used to create the equation. 

Approximately two thirds of the estimates obtained from the 

equations for the stations used in the regression analysis have 

errors less than the noted standard errors of estimate. The 

standard error of prediction is derived from the sum of the 

model error and the sampling error, and is a measure of how 

accurately the estimated peak discharges generated using an 

equation will be able to predict the true value of peak discharge for the selected recurrence interval. Approximately 

two thirds of the estimates obtained from the equations for 

ungaged sites will have errors less than than the noted standard errors of prediction. The equivalent years of record is an 

estimate of the number of years of station record that would 

be needed at a given ungaged site to produce peak-discharge 

estimates with an accuracy equal to that of the associated 

regression equation. The equivalent years of record is derived 

from a relation between the standard error of estimate and the 

measure of variability of the observed peak discharges used 

to develop an equation. Average standard errors of estimate 

and prediction and equivalent years of record associated with 

equations (2) through (17) are shown in table 9.

Prediction intervals are another useful indicator of the 

uncertainty inherent in use of the regression equations when 

applied to ungaged sites. A prediction interval is given as a 

24  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
minimum and maximum value within which there is a stated 

probability that the true value of the response variable exists. 

As an example, the minimum and maximum values given in 

a 90-percent prediction interval for the 100-year peak for an 

ungaged site should be interpreted to mean that there is 

90-percent confidence that the true value of the 100-year peak 

is within the prediction interval.

Tasker and Driver (1988) have shown that a 100(1- α) 

prediction interval for the true value of a streamflow statistic 

obtained for an ungaged site from a regression equation can be 

computed by

 Q/T < Q < TQ (18)

where 

Q is the streamflow statistic for the site and T 

is computed as:

 (19)

In equation (19), t

(α / 2,n-p) is the critical value from the 

students t-distribution at alpha-level α (α = 0.10 for 90-percent 

prediction intervals); n-p is the degrees of freedom with n stations (n=55 for the Coastal Plain and n=47 for the Piedmont) 

used in the regression analysis and p parameters in the equation (the number of basin characteristics plus one); and Si

 is 

computed from equation (20) below. Critical values from the 

students t-distribution are contained in many introductory statistics textbooks. Other prediction intervals can be calculated 

by changing α to obtain the desired percentage.

The value of Si

 is computed using the equation

 (20)

where 

γ2 is the model error variance; 

xi is a row vector of the logarithms of the basin 

characteristics for site i, augmented by a 1 as the 

first element; 

U is the covariance matrix for the regression 

coefficients; and 

xi ́ is the transpose of xi (Ludwig and Tasker, 

1993). 

The values of t

(α / 2,n-p) ,γ2

, and U needed to determine 

prediction intervals for estimates obtained from the regression 

equations are presented in table 10.

The procedure necessary to obtain the estimates is 

explained below with an example computation of the 50-year 

peak discharge for a hypothetical ungaged site on the Christina 

River near Newark, Delaware. First, the necessary basin characteristics for the site are measured from the various GIS data 

layers. Values for drainage area, percent forest, and percent 

storage are 8.00 mi2, 30.00 percent, and 0.60 percent, respectively. Substituting these values into equation (6) to predict 

the 50-year peak discharge yields

PK50 = 2,840(8.00)0.679(30.00+1)-0.353(0.60+1)-0.520=2,720 ft3/s.

Table 9. Average standard errors of estimate and prediction and equivalent years of record for 

the best regression equations, by hydrologic region in Delaware.

Recurrence 

interval 

(years)

Piedmont Coastal Plain

Average standard errors Equivalent 

years of 

record 

(years)

Average standard errors Equivalent 

years of 

record 

(years)

Estimate 

(percent)

Prediction 

(percent)

Estimate 

(percent)

Prediction 

(percent)

2 26.6 28.9 4.1 64.3 67.4 0.8

5 26.0 28.1 6.7 57.1 60.1 1.6

10 27.4 29.9 8.4 55.3 58.5 2.4

25 28.3 31.0 11.3 55.5 59.0 3.5

50 29.8 32.7 12.7 57.0 60.8 4.2

100 31.8 35.1 13.5 59.3 63.4 4.8

200 34.4 38.0 13.8 62.4 66.9 5.2

500 38.2 48.3 13.7 67.3 72.3 5.6

  > @ipn St T  ,2/ 10 D

5.0 2

»1⁄4

o «¬a c i  UxxS ii J

Methods for Estimating the Magnitude and Frequency of Floods  25
Table 10. Values needed to determine 90-percent prediction intervals for the best regression equations, by hydrologic region in 

Delaware.

[t, the critical value from the Student’s t distribution used in equation 19; 2, the regression model error variance used in equation 20; U, the covariance matrix 

used in equation 20]

Piedmont 

Recurrence 

interval 

(years)

t γ2 U

2 1.682 0.0129 0.032399 0.000256 -0.015862 -0.008039 -0.006372

0.000256 0.001094 -0.000897 -0.000551 -0.000209

-0.015862 -0.000897 0.009974 0.002040 0.002671

-0.008039 -0.000551 0.002040 0.007052 0.001515

-0.006372 -0.000209 0.002671 0.001515 0.002657

5 1.681 0.0123 0.018606 -0.000293 -0.010122 -0.004813

-0.000293 0.001139 -0.000715 -0.000458

-0.010122 -0.000715 0.007731 0.000596

-0.004813 -0.000458 0.000596 0.006605

10 1.681 0.0137 0.020045 -0.001710 -0.013381 0.008815

-0.001710 0.001841 0.000092 -0.004745

-0.013381 0.000092 0.010790 -0.008049

0.008815 -0.004745 -0.008049 0.042291

25 1.681 0.0145 0.023753 -0.001963 -0.015881 0.010301

-0.001963 0.002131 0.000089 -0.005454

-0.015881 0.000089 0.012815 -0.009442

0.010301 -0.005454 -0.009442 0.048422

50 1.681 0.0160 0.027642 -0.002241 -0.018531 0.011950

-0.002241 0.002448 0.000097 -0.006257

-0.018531 0.000097 0.014957 -0.010975

0.011950 -0.006257 -0.010975 0.055508

100 1.681 0.0182 0.032334 -0.002587 -0.021740 0.013985

-0.002587 0.002836 0.000116 -0.007254

-0.021740 0.000116 0.017545 -0.012862

0.013985 -0.007254 -0.012862 0.064376

200 1.681 0.0211 0.037763 -0.002997 -0.025458 0.016371

-0.002997 0.003289 0.000146 -0.008428

-0.025458 0.000146 0.020538 -0.015074

0.016371 -0.008428 -0.015074 0.074865

500 1.681 0.0257 0.045988 -0.003629 -0.031101 0.020027

-0.003629 0.003980 0.000202 -0.010230

-0.031101 0.000202 0.025073 -0.018465

0.020027 -0.010230 -0.018465 0.091042

26  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 10. Values needed to determine 90-percent prediction intervals for the best regression equations, by hydrologic region in 

Delaware.—Continued

[t, the critical value from the Student’s t distribution used in equation 19; 2, the regression model error variance used in equation 20; U, the covariance matrix 

used in equation 20]

Coastal Plain

Recurrence 

interval 

(years)

t γ2 U

2 1.675 0.0652 0.014305 -0.004551 -0.004712 -0.008147

-0.004551 0.004659 0.000261 -0.000044

-0.004712 0.000261 0.017005 0.004016

-0.008147 -0.000044 0.004016 0.008181

5 1.675 0.0532 0.012706 -0.004072 -0.004172 -0.006940

-0.004072 0.004069 0.000284 -0.000062

-0.004172 0.000284 0.015025 0.003457

-0.006940 -0.000062 0.003457 0.007005

10 1.675 0.0504 0.012851 -0.004115 -0.004178 -0.006867

-0.004115 0.004068 0.000294 -0.000086

-0.004178 0.000294 0.015252 0.003446

-0.006867 -0.000086 0.003446 0.006968

25 1.675 0.0507 0.013878 -0.004422 -0.007297 -0.004438

-0.004422 0.004344 -0.000127 0.000296

-0.007297 -0.000127 0.007454 0.003690

-0.004438 0.000296 0.003690 0.016605

50 1.675 0.0531 0.015112 -0.004793 -0.007900 -0.004777

-0.004793 0.004705 -0.000163 0.000297

-0.007900 -0.000163 0.008105 0.004010

-0.004777 0.000297 0.004010 0.018187

100 1.675 0.0569 0.016674 -0.005268 -0.008696 -0.005222

-0.005268 0.005176 -0.000203 0.000300

-0.008696 -0.000203 0.008952 0.004426

-0.005222 0.000300 0.004426 0.020161

200 1.675 0.0620 0.018532 -0.005839 -0.009660 -0.005764

-0.005839 0.005746 -0.000247 0.000307

-0.009660 -0.000247 0.009972 0.004926

-0.005764 0.000307 0.004926 0.022483

500 1.675 0.0704 0.021407 -0.006729 -0.011172 -0.006618

-0.006729 0.006640 -0.000311 0.000323

-0.011172 -0.000311 0.011562 0.005705

-0.006618 0.000323 0.005705 0.026044

Methods for Estimating the Magnitude and Frequency of Floods  27
To determine a 90-percent prediction interval for this 

estimate, the xi vector is

xi = {1, log10(8.00). log10(31.00), log10(1.60)}

the model error variance from table 10 is γ2 = 0.0160, and the 

covariance matrix, U, for the 50-year peak discharge in the 

Piedmont hydrologic region is

The standard error of prediction computed using 

equation (20) is Si=(0.0160+0.00205)^0.5=0.1344, and T 

computed from equation (19) is T=10^(1.681*0.1344)=1.682. 

The 90-percent prediction interval is estimated from equation (18) as (2,720/1.682)< PK50<(2,720*1.682), or, 1,620< 

PK50< 4,580.

The regression equations can be used to estimate peakflow frequencies for ungaged sites with natural flow conditions in Delaware. The equations should not be applied to 

streams with substantial flood-retention storage upstream from 

sites of interest.

The accuracy of the equations is known only within the 

range of the basin characteristics used to develop the equations. The equations can be applied for ungaged sites with 

basin characteristics that are not within the ranges of applicability, but the accuracy of the estimates will be unknown. 

Also, it is possible that discharge estimates for lower-recurrence-interval floods can be larger than discharge estimates 

for higher-recurrence-interval floods when basin characteristics for an ungaged site are substantially beyond the ranges 

of applicability. The ranges of basin characteristics used to 

develop the equations are provided in table 11.

Comparison of Results with Previous Study

A comparison was made between estimates obtained 

from the systematic records and the regression equations in 

this report and those from the previous Delaware floodfrequency report (Dillow, 1996) for stations that were used in 

both reports. Mean and median percent differences between 

the flood-frequency estimates obtained from the systematic 

record from the previous study and from this study were computed for all stations and by region, and are shown in table 12. 

Differences for the 200-year recurrence interval are not shown 

in the table because discharges for this recurrence interval 

were not computed for the previous study.

Estimates determined from the systematic record for this 

study are, on average, larger in discharge than those from the 

previous study for the lowest recurrence intervals, and they 

are smaller than those from the previous study for the highest recurrence intervals when all stations are considered as a 

group. Mean differences in percent range from positive 

9.9 percent for the 2-year recurrence interval to negative 

18.5 percent for the 500-year recurrence interval. Median 

Table 11. Ranges of basin characteristics used to develop the regression equations.

[NHD, National Hydrography Dataset]

Piedmont region Coastal Plain region

Basin characteristic Minimum Maximum Minimum Maximum

Drainage area 

(square miles)

0.31 319 0.51 117

Forest cover 

(percent)

4.07 84.9 -- --

Impervious area 

(percent)

0.10 38.3 -- --

Storage (NHD) 

(percent)

0.00 2.92 -- --

Housing density 

(homes/acre)

0.06 6.84 0.01 3.42

Hydrologic soil type A 

(percent)

0.00 7.22 0.53 60.0

Mean basin slope 

(percent)

-- -- 0.30 3.69

0.027642 -0.002241 -0.018531 0.011950

U = -0.002241 0.002448 0.000097 -0.006257

-0.018531 0.000097 0.014957 -0.010975

0.011950 -0.006257 -0.010975 0.055508

28  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
differences in percent range from positive 2.9 percent for the 

2-year recurrence interval to negative 22.3 percent for the 500-

year recurrence interval. Many stations within the study area 

experienced major flooding since completion of the previous 

study, which could lead to the expectation that flood-frequency 

estimates would increase rather than decrease. The decrease 

in the higher recurrence-interval estimates, however, can 

mostly be explained by (1) additional record for many of the 

stations, (2) the improved generalized-skew values used for 

this study, which are substantially lower than the previous values taken from Bulletin 17B, and account for lowering of the 

100-year peaks by an average of about 4 percent, (3) the use 

of more historical adjustments than were used for the previous 

study, and (4) adjustments for trends in the annual peak-flow 

time series at some stations. 

As indicated in table 12, differences between the 

estimates from the previous and current studies vary substantially depending on the region and whether or not additional 

data were collected. When all stations are considered, percent 

differences generally are much larger in the Coastal Plain than 

in the Piedmont, and stations with no record since the previous 

study have very small positive mean changes for smaller peaks 

and large negative mean changes for larger peaks, whereas stations with additional record since the previous study have large 

positive mean changes for smaller peaks and small negative 

mean changes for larger peaks. For the Coastal Plain, stations 

with no additional record have small negative mean changes 

for smaller peaks and large negative mean changes for larger 

peaks, whereas stations with additional record have large 

positive mean changes for smaller peaks and large 

Table 12. Mean and median percent differences between peak-flow frequency statistics computed from the 

systematic records for streamgaging stations included in this study and the previous study (Dillow, 1996).

Recurrence 

interval

All stations Coastal Plain Piedmont

Mean 

percent 

difference

Median 

percent 

difference

Mean 

percent 

difference

Median 

percent 

difference

Mean 

percent 

difference

Median 

percent 

difference

All stations 

2 9.9 2.9 16.0 2.9 4.7 2.8

5 3.5 1.4 3.4 -0.7 3.7 1.9

10 -0.9 -1.5 -3.8 -6.5 1.9 -1.0

25 -5.9 -5.9 -11.2 -8.4 -0.6 -4.7

50 -9.5 -9.3 -16.2 -14.0 -2.6 -8.3

100 -12.6 -13.6 -20.5 -18.6 -4.5 -13.1

500 -18.5 -22.3 -28.8 -30.1 -8.0 -20.5

Stations with no record since last study

2 0.9 2.9 -2.4 -2.1 4.2 3.2

5 -4.7 1.4 -11.1 -10.5 1.8 0.7

10 -9.1 -1.5 -16.8 -12.4 -1.5 -2.4

25 -14.6 -5.9 -23.0 -17.7 -6.2 -6.3

50 -18.9 -9.3 -27.3 -23.6 -10.6 -9.8

100 -22.8 -13.6 -31.0 -29.7 -14.5 -14.0

500 -31.0 -22.3 -38.5 -41.4 -23.4 -22.3

Stations with additional record since last study

2 24.3 6.7 48.1 13.4 5.7 2.3

5 14.6 7.8 27.0 13.4 4.9 5.4

10 9.5 6.6 16.6 11.5 4.0 2.7

25 4.5 2.7 6.5 7.6 2.9 -1.7

50 1.4 -3.3 0.0 -3.3 2.5 -5.2

100 -1.1 -8.8 -5.3 -8.8 2.2 -9.0

500 -4.9 -17.4 -15.2 -20.1 3.2 -17.4

Methods for Estimating the Magnitude and Frequency of Floods  29
negative mean changes for larger peaks. For the Piedmont, 

stations with no additional record have small positive mean 

changes for smaller peaks and large negative mean changes 

for larger peaks, whereas stations with additional record have 

small positive mean changes for all peaks.

Adjustments for trends for some stations also 

contribute to increasing the low recurrence-interval 

estimates and decreasing the high recurrence-interval estimates. Because the annual peak flows tend to be smaller for 

the trend-affected stations during earlier parts of the periods of 

record than during later parts, the trend adjustments generally have the effect of increasing the lower flows more than 

the higher flows, and lowering the standard deviations of the 

annual series. This results in higher discharge estimates for 

the lower recurrence intervals and lower discharge estimates 

for the higher recurrence intervals.

Errors associated with the regression equations cannot 

be directly compared between the two studies because the 

same stations and explanatory variables were not used; however, some comparison is justified to understand differences 

between the results. Average standard errors of prediction 

associated with the regression equations for the Piedmont are 

somewhat larger for this study (28 to 48 percent) than for the 

previous study (23 to 45 percent). Average standard errors 

of prediction associated with the regression equations for the 

Coastal Plain are substantially larger for this study (58 to 

72 percent) than for the previous study (38 to 43 percent).

The large differences in error between the two studies 

were not expected and they cannot be fully explained, but it is 

likely that the new average standard errors of prediction give 

a more precise indication of the true errors associated with 

estimates from the regression equations than the average standard errors of prediction given for the previous equations. The 

regression methods used in the two studies were essentially 

the same. The peak-flow statistics for the stations used in this 

study are considered more precise than those used in the previous study because of (1) improved generalized-skew values, 

(2) longer periods of record for many stations, and (3) corrections for trends that were not made previously. In addition, 

the basin characteristics used as explanatory variables in the 

equations were generally measured with more precision than 

those from the previous study.

A possible explanation for the increased error in the equations is that many of the long-term streamgaging stations used 

in the analysis have experienced large peaks since the previous 

study was completed. These large peaks may have increased 

the uncertainty in systematic flood-frequency estimates used 

as the dependent variables in the regression analyses. Percent 

differences in discharge between estimates obtained from 

the previous study and this study, as shown in table 12, are 

larger for the Coastal Plain, where average standard errors of 

estimate have increased the most, than for the Piedmont. The 

Coastal Plain also has the largest differences between the percent changes for stations with and without additional record. 

The pattern of changes for the Coastal Plain stations with and 

without new record is substantially different, indicating that 

more recent events are causing the differences in the changes.

This study included 21 stations in the Coastal Plain of 

southern New Jersey that were not included in the previous study. There was some concern that differences in the 

physiography of southern New Jersey and the Coastal Plain 

in Delaware were large enough that the addition of the New 

Jersey stations was causing the increased errors. A test set of 

regression analyses was run excluding the New Jersey stations. 

Average prediction errors decreased a few percentage points 

when this was done, but the decision was made to include the 

New Jersey stations in the final analyses to extend the range of 

applicability of the resulting regression equations.

Application of the Methods

The best estimates of flood frequencies for a site are 

often obtained through a weighted combination of estimates 

produced from more than one method. Tasker (1975) demonstrated that if two independent estimates of a streamflow 

statistic are available, a properly weighted average of the 

independent estimates will provide an estimate that is more 

accurate than either of the independent estimates. Improved 

flood-frequency estimates can be determined for Delaware 

streamgaging stations by weighting estimates determined from 

the systematic peak-flow record at the station with estimates 

obtained from the regression equations provided in this report. 

Improved estimates can be determined for ungaged sites in 

Delaware by weighting the estimates obtained from the regression equations with estimates determined based on the flow 

per unit area of an upstream or downstream streamgaging 

station.

The sections below describe the weighting process for 

streamgaging stations and ungaged sites in more detail, and 

provide example calculations. The methods presented are 

those incorporated into the USGS National Flood Frequency 

Program (NFF) (Ries and Crouse, 2002), a computer program 

that can be used to solve all of the USGS flood-frequency 

equations in the Nation, including those from this report, given 

user input of basin characteristics. NFF can be downloaded 

from the web at http://water.usgs.gov/software/nff.html, along 

with complete documentation on how to use it. NFF can also 

be used to perform the weighting functions described below 

for estimation at a gaged location and for an ungaged site 

upstream or downstream from a gaged location, but not for 

an ungaged site between gaged locations. The StreamStats 

program (described later in the StreamStats section) does not 

currently (2006) include the weighting functionality that is in 

NFF.

30 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Estimation for a Gaged Location

The Interagency Advisory Committee on Water Data 

(1982) recommends that the best estimates of flood-frequency statistics for a streamgaging station can be obtained 

by combining the estimates determined from log-Pearson 

type III analysis of the systematic annual peaks with estimates 

obtained for the station from regression equations. Note that 

the symbols used to explain this method in the source publication have been preserved in the discussion below, and that the 

equivalent expressions used in this report are identified in the 

variable definitions that accompany each equation.

Weighting is based on the years of record for the estimates obtained from the station records and on the equivalent 

years of record for the regression estimates. If the two different estimates are assumed to be independent, weighted floodfrequency estimates can be computed as

 

 (21)

where

QT(G)w is the weighted estimate of flood-peak 

discharge for any recurrence interval (PK2, PK5,

...,PK500) at the streamgaging station,

QT(G)s is the estimate of (PK2, PK5,..., PK500) 

derived from the systematic flood peaks,

QT(G)r is the estimate of (PK2, PK5,..., PK500) 

derived from the regression equation,

N is the number of years of gaged record, and

EQ is the equivalent years of record determined 

for the regression equation.

The accuracy of the weighted estimate, in equivalent 

years of record, EQT(G)w, is equal to the N + EQ. No other indicators of accuracy are available for these weighted estimates.

An example of the application of the procedure described 

above is the computation of the weighted 100-year flood-peak 

discharge for the site on Little Mill Creek at Elsmere, 

Delaware (station number 01480100):

1. Obtain the estimate of the 100-year discharge at the 

site based on the systematic flood peaks from table 8; 

PK100(G)s = 6,370 ft3/s,

2. Obtain drainage area, percent forest, and percent storage 

from table 7, and the number of years of gaged record 

from table 1; DRNAREA=6.67 mi2

, FOREST= 

13.76 percent, STORNHD=0.35 percent, and N=18 years,

3. Compute PK100 (G)r = 3,090(6.67)

0.684(13.76+1)-0.316 

(0.35+1)-0.594 =4,040 ft3/s,

4. Obtain the equivalent years of record for the 100-year 

peak-discharge regression equation for the Piedmont 

region from table 9; EQ=13.5 years, and

5. Compute the weighted 100-year flood-peak discharge for 

the site;

 log PK100 (G)w=((18)(log6,370)+(13.5)(log4,040))/

(18+13.5)=3.7194, and PK100 (G)w=5,240 ft3/s.

Estimation for a Site Upstream or Downstream 

from a Gaged Location

Guimaraes and Bohman (1992) and Stamey and Hess 

(1993) presented the following method to improve floodfrequency estimates for an ungaged site with a drainage 

area that is between 0.5 and 1.5 times the drainage area of a 

streamgaging station that is on the same stream. As in the 

previous section, the symbols used to explain this method in 

the source publications have been preserved in the discussion below, and the equivalent expressions used in this report 

are identified in the variable definitions that accompany each 

equation.

To obtain a weighted peak-flow estimate (QT(U)w)for 

recurrence interval T at the ungaged site, the weighted flow 

estimate for an upstream or downstream streamgaging station 

(QT(G)w) must first be determined using the equation provided 

in the previous section. The weighted streamgaging station 

estimate is then used to obtain an estimate for the ungaged site 

that is based on the flow per unit area at the streamgaging 

station (QT(U)g) by use of the equation

 (22)

where

Au is the drainage area (DRNAREAu) for the 

ungaged site,

Ag is the drainage area (DRNAREAg) for the 

upstream or downstream streamgaging station, 

and 

b is 0.60 in the Piedmont and 0.70 in the 

Coastal Plain, as determined by computing the 

mean of the drainage-area exponents for all 

recurrence intervals from regressions of floodfrequencies against drainage area as the only 

explanatory variable, and where the equation 

constant is forced to be zero. 

The weighted estimate for the ungaged site (QT(U)w) is then 

computed as

 (23)

EQN

QEQQN Q sGT rGT

wGT 

 )( )(

)(

log log log

wGT

b

gUT Q Ag

Au Q )(  ̧ )(  ̧

1

·

 ̈

 ̈

©

§ 

gUT

g

rUT

g

wUT Q A

A Q AA Q )( )( )(

2 1 2

 ̈

 ̈

©

§

 ̧

 ̧

1

' ·



' 

Application of the Methods  31
where

∆A is the absolute value of the difference 

between the drainage areas of the streamgaging 

station and the ungaged site, |DRNAREAg - 

DRNAREAu|, and

QT(U)ris the peak-flow estimate for recurrence 

interval (PK2, PK5,...,PK500) at the ungaged 

site derived from the applicable regional equation 

given above.

Use of the equations above gives full weight to the 

regression estimates when the drainage area for the ungaged 

site is less than 0.5 or greater than 1.5 times the drainage area 

for the streamgaging station, and increasing weight to the 

streamgaging-station-based estimates as the drainage area 

ratio approaches 1. The weighting procedure should not be 

applied when the drainage area ratio for the ungaged site and 

streamgaging station is less than 0.5 or greater than 1.5.

The equivalent years of record for the weighted 

estimate for an ungaged site, EQT(U)w, can be computed. This 

is done by first substituting the equivalent years of record for 

the weighted estimate of peak discharge at the streamgaging 

station, EQT(G)w, in place of QT(G)w in equation (22) above to 

obtain an estimate of the weighted equivalent years of record 

for the streamgaging station that is adjusted to the drainage 

area for the ungaged site, EQT(U)g. As noted above, EQT(G)w

is equal to N + EQ from equation (21). The area-adjusted 

equivalent years of record based on the gaged site, EQT(U)g, is 

then substituted for QT(U)g, and the equivalent years of record 

for the ungaged site based on the regression equation, EQT(U)r, 

is substituted for QT(U)r in equation (23) to compute the final 

weighted equivalent years of record for the ungaged site, 

EQT(U)w. No other indicators of accuracy are available for these 

estimates. In theory, the standard errors for these estimates 

should be at least as small as those for the estimates derived 

from the regression equations alone.

An example of the application of the procedure described 

above is the computation of the weighted 100-year flood-peak 

discharge, and its associated equivalent years of record, for a 

hypothetical site on Little Mill Creek located above the USGS 

station at Elsmere, Delaware (station number 01480100) cited 

in the previous section:

Calculate the value of PK100(G)w (see example in previous 

section); PK100 (G)w=5,240 ft3/s,

Obtain the drainage areas for both the gaged and ungaged 

sites; DRNAREAg =6.67 mi2, and DRNAREAu=4.44 mi2,

Use equation (22) and b=0.6 for stations in the Piedmont, 

to calculate the 100-year peak discharge based on station 

data; PK100 (U)g = (4.44/6.67)0.6(5,240) = 4,100 ft3

/s,

Compute ∆A, where ∆A=6.67-4.44=2.23 mi2,

Compute PK100(U)r for the ungaged site using equation 

(7) with FOREST= 8.00 percent and STORNHD= 

1.

2.

3.

4.

5.

0.10 percent; PK100(U)r =3,090(4.44)0.684(8.00+1)-0.316 

(0.10+1)-0.594=4,040 ft3/s,

Compute the weighted estimate for the ungaged site, 

QT(U)w, using equation (23);

PK100(U)w=[((2*2.23)/6.67)*4,040]+[(1-((2*2.23)/6.67))*

3,490]=3,860 ft3/s, and finally,

Compute the equivalent years of record for the weighted 

estimate of the 100-year peak discharge for the ungaged 

site using equations (22) and (23) and substituting EQT(G)w

in place of QT(G)w, EQT(U)g, in place of QT(U)g, EQT(U)r in 

place of QT(U)r, and EQT(U)w in place of QT(U)w; giving:

From equation (22), EQ100(U)g=(4.44/6.67)0.6(31.5)=

 24.7 years, 

From table 9, EQ100(U)r=13.5 years, and

From equation (23), EQ100(U)w=[((2*2.23)/6.67)*13.5]+

[(1-((2*2.23)/6.67))*18]=15.0 years.

Estimation for a Site Between Gaged Locations

In the case where a flood-frequency estimate is needed 

for a site that is located between two gaged locations on a 

stream, the estimate may be obtained by use of the procedure 

presented above for calculating weighted estimates for a gaged 

location, with the following procedural alteration. For consistency, the symbology used below is the same as that used 

in the previous section, and the equivalent expressions used 

elsewhere in this report are identified in the variable definitions that accompany each equation.

Because the site is ungaged, a direct determination of 

the flow at the site for the selected recurrence interval is not 

possible. An interpolated value can be obtained by use of the 

equation:

 

 (24)

where

Au is the drainage area (DRNAREAu) for the 

ungaged site,

Agu is the drainage area (DRNAREAgu) for the 

upstream gaged location,

Agd is the drainage area (DRNAREAgd) for the 

downstream gaged location,

QTu is the discharge at the T-year recurrence 

interval (PK2, PK5,..., PK500) for the ungaged 

site,

QTgu is the discharge at the T-year recurrence 

interval (PK2, PK5,..., PK500) for the upstream 

gaged location, and 

6.

7.

8.

u

gu

Tgu

gu

Tgu

gd

Tgd

gd gu

guu

Tu A

A

Q

A

Q

A

Q

AA

AA

Q [ *  *]  ̧

 ̧

1

·   ̈

 ̈

©

§



 

32  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
QTgd is the discharge at the T-year recurrence 

interval (PK2, PK5,..., PK500) for the 

downstream gaged locations. 

The value of QTu from equation (24) may be used in 

equation (21) in place of QT(G)s.

The value of N for use in equation (21) may be calculated 

by determining the arithmetically weighted average of the 

number of years of record for the upstream and downstream 

gaged locations, using the difference in the two drainage areas 

as the weighting factor. The calculation can be done using the 

equation:

 (25)

where, 

Au

, Agu, and Agd are as defined immediately above, and 

Nu, Ngu, and Ngd are the number of years of record for the 

ungaged site and the upstream and downstream 

gaged locations, respectively. 

The value determined for Nu from equation (25) may be 

inserted in place of the value of N in equation (21) to solve 

that equation, thus obtaining a weighted estimate of the T-year 

flood for the ungaged site located between an upstream and 

downstream gaged location.

An example of the application of the procedure described 

above is the computation of the weighted 5-year flood-peak 

discharge, and its associated equivalent years of record, for a 

hypothetical site on Brandywine Creek, with a drainage area 

of 300 mi2, percent forest of 31.60 percent and percent hydrologic soil type A of 5.00, located between the USGS gages at 

Chadds Ford, Pennsylvania (station number 01481000) and 

Wilmington, Delaware (station number 01481500):

Use equation (24) to calculate PK5u with the 

information given above, gaged drainage areas 

associated with the two stations from table 7, and 

the appropriate discharge characteristics from table 8; 

DRNAREAu

=300 mi2, DRNAREAgu=288 mi2, 

DRNAREAgd=319 mi2, PK5gu= 11,000 ft3/s, 

and PK5gd=12,400 ft3/s, so PK5u={[(300-

288)/(319-288)]*[(12,400/319)-(11,000/288)]+ 

(11,000/288)}*300=11,500 ft3/s,

Use equation (25) to calculate Nu, with drainage areas as 

defined in the previous step and the years of record for 

the upstream (station number 01481000) and downstream 

(station number 01481500) gages as given in table 1; 

Ngu=84 years, and Ngd=93 years, so Nu

 =(93*(300.00-

288.17)+84*(318.54-300.00))/(318.54-288.17)=

87.5 years,

1.

2.

After computing the regression equation estimate for the 

ungaged site and determining the associated equivalent 

years of record from table 9, calculate the weighted peak 

discharge estimate of the ungaged site using equation (21) 

with PK5(G)s=11,500 ft3

/s, PK5(G)r=12,400 ft3/s, N=87.5 

years, and EQ=6.7 years, so log PK5 (G)w=((87.5)

(log11,500)+(6.7)(log12,400))/(87.5+ .7)=4.0630, and 

PK5 (G)w=11,600 ft3/s.

Effects of Urbanization on Floods

The design of structures that can withstand future floods 

and protection of life and property in floodplains in urbanizing 

basins requires an understanding of the effects of urbanization 

on flood peaks. Engineers and planners often need to consider 

the potential effects on streamflow of full-build-out scenarios 

in their design and planning efforts. The section above on the 

Analysis of and Adjustments for Trends in Annual Peak-Flow 

Time Series presents some findings on the effects of urbanization on annual flood peaks at streamgaging stations in and near 

Delaware. This section describes an analysis that was done to 

develop regression equations that could be used to estimate the 

effects of future development on flood frequencies.

A matrix of correlations between the logarithms of floodfrequency estimates at the 2- and 100-year recurrence intervals 

and the logarithms of drainage area and the measured indicators of urbanization for stations used in the regression analyses 

is presented in table 13. Correlations among the indicators of 

urbanization were very high. In addition, note that the correlations between the indicators of urbanization and the 2-year 

peak flow were higher than those for the 100-year peak flow. 

Although only the 2- and 100-year peak flows are shown in 

the correlation matrix for simplicity, additional tests showed 

that correlations with the indicators of urbanization decreased 

consistently with increasing recurrence interval.

Development intensity was computed for this study 

primarily as a basis for comparing how closely this measure 

of impervious surface percentage agrees with impervious 

percentage obtained directly from the 2001 NLCD imperviousness dataset. The matrix indicates that the correlation of 

peak flows with development intensity is less than half of the 

correlation with percent impervious, which has the highest 

individual correlation with the peak flows of the urbanization indicators. In addition, development intensity actually 

had slightly lower correlations with peak flows than percent 

developed. Development intensity was derived by applying 

weights to the same land-use categories as those used to compute percent developed. This indicates that the application of 

weights to the land-use categories was actually counterproductive when attempting to explain more of the variation in peak 

flows.

Regressions of peak flows against the individual 

urbanization indicators had very high average standard errors 

of prediction. As a result, regressions that also included 

3.

gd gu

guugd ugdgu

u AA

AANAAN

N 

 )()(

Effects of Urbanization on Floods  33
drainage area as an explanatory variable were done to increase 

the accuracy of the equations. The combination of drainage 

area and centroid housing density provided the regression 

equations with the lowest errors. Regressions that included 

an indicator variable to differentiate between the Piedmont 

and the Coastal Plain were also tested, but the indicators were 

statistically insignificant. The equations that are most useful 

for developing scenarios of the effects of future urbanization 

on flood-frequency relations are:

UPK2 = 51.4DRNAREA0.798(HOMEDENS+1)1.09 (26)

UPK5 = 91.8DRNAREA0.783(HOMEDENS+1)0.950 (27)

UPK10 = 126DRNAREA0.775(HOMEDENS+1)0.870 (28)

UPK25 = 179DRNAREA0.767(HOMEDENS+1)0.780 (29)

UPK50 = 225DRNAREA0.762(HOMEDENS+1)0.719 (30)

UPK100 = 277DRNAREA0.758(HOMEDENS+1)0.663 (31)

UPK200 = 334DRNAREA0.754(HOMEDENS+1)0.611 (32)

UPK500 = 420DRNAREA0.751(HOMEDENS+1)0.546 (33)

where 

UPK2 through UPK500 are the estimates of urban flood 

frequency for the 2- through 500-year recurrence intervals, 

in cubic feet per second, and HOMEDENS is the housing 

density, in homes per acre. Housing-density values used in 

the analysis were those associated with the centroid of the 

period of record for each station. The average standard errors 

of estimate and prediction and the equivalent years of record 

associated with the urban equations above are presented 

in table 14. The ranges of applicability for equations (26) 

through (33) are equivalent to the combined ranges for both 

regions given in table 11.

Table 13. Matrix of correlations between the logarithms of flood-frequency estimates at the 2- and 100-year recurrence 

intervals and the logarithms of the indicators of urbanization.

2-year 

peak flow

100-year 

peak flow

Drainage 

area

2000 

Housing 

density

Centroid 

year 

housing 

density

Percent 

impervious

Percent 

developed

2-year peak flow 1

100-year peak flow 0.952 1

Drainage area 0.769 0.738 1

2000 housing density 0.423 0.314 0.057 1

Centroid year housing 

density 0.352 0.291 0.038 0.704 1

Percent impervious 0.431 0.315 0.130 0.900 0.651 1

Percent developed 0.212 0.095 -0.013 0.822 0.512 0.817 1

Development intensity 0.194 0.076 -0.025 0.807 0.467 0.823 0.989

Table 14. Average standard errors of estimate and prediction and 

equivalent years of record for the urban regression equations.

Recurrence 

interval

(years)

Average standard errors of Equivalent 

years of 

record 

(years)

Estimate 

(percent)

Prediction 

(percent)

2 88.6 90.6 0.54

5 88.8 91.1 0.85

10 89.5 91.9 1.19

25 91.0 93.6 1.68

50 92.6 95.4 2.06

100 94.7 97.6 2.42

200 97.2 100 2.76

500 101 105 3.17

34  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Because the errors associated with the urban equations are much higher than those for the best equations, it is 

recommended that the urban equations be applied only for 

the purpose of evaluating the effects of increased urbanization on peak flows. First, the best estimates of peak flows for 

a site should be determined using equations (2) through (17). 

Next, housing density should be determined under different 

land-use conditions and the different values of housing density 

should be applied using equations (26) through (33) to obtain 

estimates of peak flows for the different land-use scenarios. 

Finally, the percentage change between the peak-flow estimates for the different scenarios should be applied to the estimates obtained from equations (3) through (17) to obtain the 

best estimates of peak flows for the scenarios. These scenarios 

can be computed easily by using the NFF program, which 

includes both the best and the urban equations. Because the 

2-year best equation for the Piedmont (equation 2) already 

contains the percent of impervious surfaces as a variable it is 

preferable to do build-out scenarios with the best equation for 

the 2-year recurrence interval for the Piedmont region rather 

than using equation 26 above. The urban equations can be 

incorporated into the methods used to develop build-out 

scenarios in the Coastal Plain region.

StreamStats

StreamStats is a map-based USGS web application that 

makes it easy for users to obtain streamflow statistics and 

basin characteristics for USGS streamflow data-collection 

stations and ungaged sites of interest. It uses digital map data 

and a GIS to automatically determine the basin characteristics 

for ungaged sites. Ries and others (2004) provide a detailed 

description of the application. Although it is designed to eventually be a national application, Streamstats is being implemented on a state-by-state basis, usually through cooperative 

funding agreements between the USGS and local partners.

StreamStats has been developed for Delaware. Users can 

access all of the flood-frequency statistics and basin characteristics published in this report for the stations used in this 

study by selecting a station location on the map shown in the 

StreamStats user interface. Users can also obtain estimates for 

ungaged sites in Delaware by selecting the location of a site of 

interest on the map.

Complete instructions for using StreamStats are provided 

through links on the StreamStats web site at http://streamstats.

usgs.gov. The web site also provides links to (1) general 

limitations of the application, (2) other State applications, 

(3) definitions of terms, (4) answers to frequently asked questions, (5) downloadable talks and other technical information 

about the application, (6) information that can be accessed 

only by USGS employees, and (7) contact information.

Due to software limitations, the StreamStats implementation for Delaware does not include the ability to solve the 

urban equations presented above for ungaged sites. 

Readers who are interested in using the urban equations can 

use StreamStats to obtain the basin characteristics needed to 

solve both the best equations and the urban equations, and they 

can get flood-frequency estimates based on the best 

equations. The basin characteristics obtained from StreamStats can then be used in the NFF program to obtain urban 

estimates for different development scenarios. StreamStats 

measures housing density for ungaged sites from the 2000 

housing-density dataset (Theobald, 2001). Users will need 

to determine the appropriate housing-density values for other 

times.

Summary and Conclusions

This study was done by the U.S. Geological Survey in 

cooperation with the Delaware Geological Survey and the 

Delaware Department of Transportation. The report presents 

estimates of flood-frequency statistics and basin characteristics for 116 stations in and within 25 miles of Delaware. It 

also describes methods for estimating flood frequencies for 

streamgaging stations and for ungaged sites in Delaware.

Statistically significant upward trends were found in the 

annual time series of peak flows for 18 of the 116 streamgaging stations analyzed for this study. Additional analyses were 

done to determine if these trends were related to corresponding increases in annual maximum precipitation or housing 

density, or both. The analyses revealed that annual maximum 

precipitation has not been increasing in the study area, but statistically significant relations were found between annual peak 

flows and corresponding annual values of housing density for 

8 of the 18 stations.

Adjustments for trends in the annual peak-flow time 

series were made on the basis of time only for 11 of the 

18 stations with significant trends before final flood-frequency 

analyses were completed for the stations. When compared to 

the original flood-frequency estimates for the trend-adjusted 

stations, the adjustments had the effect of increasing the 

magnitude of peak discharges for floods at recurrence intervals 

of up to 2 years, and decreasing the peak discharges for the 

200- and 500-year recurrence intervals for all of the stations. 

Results varied for recurrence intervals between 5 and 

100 years. For various reasons, the time series for seven of the 

trend-affected stations were not adjusted. These stations were 

not used in the regional flood-frequency analyses.

An analysis of station skews resulted in new generalized-skew values defined for each of two hydrologic regions 

in Delaware -- the Piedmont and Coastal Plain regions. The 

Piedmont includes the area north of the Fall Line, in northern 

Delaware, and the Coastal Plain includes the area to the south. 

The new generalized skew values are 0.107 for the Piedmont 

and 0.204 for the Coastal Plain, and are substantially lower 

than skew values taken from Bulletin 17B for the previous 

flood-frequency study. These new generalized-skew values 

were used to determine the flood-frequency values from the 

Summary and Conclusions  35
systematic records for the streamgaging stations presented in 

this report.

Discharge estimates determined from the systematic 

record for this study were, on average, larger than those from 

the previous study for the lowest recurrence intervals, and 

they were smaller than those from the previous study for the 

highest recurrence intervals when all stations are considered 

as a group. The changes are much larger in the Coastal Plain 

than in the Piedmont. The changes are due in large part to the 

longer periods of record and the improved generalized-skew 

values used for this study, and the adjustment of annual time 

series for some stations to eliminate trends.

Two sets of regression equations are presented for 

estimating flood discharges at the 2-, 5-, 10-, 25-, 50-, 100-, 

200-, and 500-year recurrence intervals at ungaged sites in 

Delaware. One set of equations is the best set of regression 

equations that could be developed for estimating flood discharges in the study area. Separate sets of best equations were 

developed for the Coastal Plain and the Piedmont hydrologic 

regions. A second set of equations was developed for use in 

estimating the effects of urbanization on flood discharges. 

The explanatory variables in the best equations for the Coastal 

Plain include drainage area, percent of drainage basin covered 

by soil type A, and mean basin slope. The explanatory variables in the best equations for the Piedmont include drainage 

area, percent of basin covered by forest, percent of basin covered by impervious surfaces (2-year recurrence interval only), 

percent of basin covered by hydrologic soil type A (2-year and 

5-year recurrence intervals), and percent storage (areas of wetlands and waterbodies) determined from the National Hydrography Dataset (10- to 500-year recurrence intervals). The 

explanatory variables used in the urban equations included 

drainage area and housing density. The report presents the 

equations, indicators of the errors associated with use of the 

equations, and a discussion of the limitations for their use.

Average standard errors of prediction for the best 

regression equations ranged from 28 to 48 percent for the 

Piedmont, and from 58 to 72 percent for the Coastal Plain. 

Although they are not directly comparable because of 

differences in the stations used and their lengths of record, 

the errors associated with the new equations are higher than 

those presented in the previous report, which ranged from 23 

to 45 percent for the Piedmont, and from 38 to 43 percent for 

the Coastal Plain. The differences in error cannot be fully 

explained, but it is likely that the new average standard errors 

of prediction give a more precise indication of the true errors 

associated with estimates from the regression equations than 

the average standard errors of prediction given for the previous 

equations. A possible explanation for the increased error in 

the equations is that many of the long-term streamgaging stations used in the analysis have experienced large peaks since 

the previous study was completed. These large peaks lead to 

greater uncertainty in the flood-frequency estimates for the 

streamgaging stations used in the study.

Estimates of housing density under different land-use 

scenarios can be used with the urban equations to evaluate 

the changes in flood magnitude as a result of the land-use 

changes. The average standard errors of prediction for the 

urban equations range from 91 to 105 percent. Consequently, 

these equations should be used only to compute the percentage 

change for different scenarios.

The best equations and the urban equations developed 

during this study have been incorporated into the National 

Flood Frequency (NFF) and StreamStats programs of the 

USGS. The National Flood Frequency program is a desktop 

program that solves regression equations for all states in the 

Nation, and requires user input of the basin characteristics. 

The StreamStats program is a web application that can provide 

the streamflow statistics and basin characteristics published in 

this report for streamgaging stations when users select a station location in the user interface. StreamStats can also compute basin characteristics and provide estimates of streamflow 

statistics for ungaged sites when users select the location of a 

site along any stream in Delaware.

This report describes methods for obtaining improved 

flood-frequency estimates for streamgaging stations and 

ungaged sites. Improved estimates for streamgaging stations 

are obtained by computing the weighted average of the estimates obtained from the systematic record and the estimates 

obtained from the regression equations, with weighting based 

on the years of systematic record and the equivalent years of 

record for the regression estimates. Improved estimates for 

ungaged sites can be obtained by combining the estimates 

from regression equations with estimates determined by 

applying the flow per unit area for an upstream or downstream 

streamgaging station to the drainage area for the ungaged 

site, and weighting the estimates according to the difference 

in drainage area between the ungaged site and the streamgaging station. The NFF program can be used to obtain these 

improved estimates.

References

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peak discharges from an urbanizing watershed to reflect a 

stationary land use signal: Water Resources Research, 

vol. 39, no. 4, p. 4-1 to 4-11.

Bird, S., Harrison, J., Exum, L., Alberty, S., and Perkins, C., 

2002, Screening to identify and prevent urban storm water 

problems: Estimating impervious area accurately and inexpensively, in Proceedings of the 2002 National Conference 

of the National Water Quality Monitoring Council, May 

20-23, Madison, Wisconsin, 16 p., accessed January 6, 2006 

at http://www.nwqmc.org/NWQMC-Proceedings/PapersAlphabetical%20by%20First%20Name/Jim%20HarrisonScreening.pdf.

36    Magnitude and Frequency of Floods on Nontidal Streams in Delaware
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estimating magnitude and frequency of floods for ungaged 

sites: U.S. Geological Survey Water-Resources Investigations Report 02-4168, 42 p.

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Stewart, D.W., 2004, StreamStats: A U.S. Geological 

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References    37
Sauer, V.B., Thomas, W.O., Jr., Stricker, V.A., and Wilson, 

K.V., 1983, Flood characteristics of urban watersheds in the 

United States: U.S. Geological Survey Water-Supply Paper 

2207, 63 p.

Simmons, R.H., and Carpenter, D.H., 1978, Technique for 

estimating magnitude and frequency of floods in Delaware: 

U.S. Geological Survey Water-Resources Investigations 

Report 78-93, 69 p.

Soong, D.T., Ishii, A.L., Sharpe, J.B., and Avery, C.F., 2004, 

Estimating flood-peak discharge magnitudes and frequencies for rural streams in Illinois: U.S. Geological Survey 

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magnitude and frequency of floods in rural basins of Georgia: U.S. Geological Survey Water-Resources Investigations 

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Paper 1672, 585 p.

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38    Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Tables 6 through 8

Tables 6 through 8  39
Table 6. Climatic characteristics for stations in and near Delaware that were considered for use in the regression analyses.

[USGS, U.S. Geological Survey]

USGS 

station 

number

Mean annual 

precipitation 

(inches)

Recurrence interval of 24-hour maximum precipitation (inches)

2-

year

5-

year

10-

year

25-

year

50-

year

100-

year

200-

year

500-

year

01411456 46.59 3.30 4.28 5.13 6.41 7.54 8.79 10.21 12.37

01411500 46.06 3.29 4.27 5.12 6.41 7.54 8.81 10.23 12.42

01412500 45.27 3.26 4.24 5.08 6.36 7.48 8.75 10.18 12.35

01412800 45.53 3.27 4.24 5.08 6.37 7.49 8.76 10.18 12.35

01467043 50.86 3.31 4.20 4.95 6.07 7.04 8.09 9.25 10.98

01467045 50.11 3.30 4.17 4.90 5.98 6.92 7.90 9.00 10.62

01467081 47.36 3.33 4.24 5.01 6.15 7.15 8.22 9.42 11.19

01467086 50.56 3.30 4.17 4.90 5.97 6.89 7.87 8.96 10.57

01467087 49.96 3.30 4.16 4.89 5.96 6.87 7.85 8.93 10.52

01467130 47.17 3.31 4.24 5.04 6.24 7.28 8.43 9.71 11.63

01467150 47.12 3.30 4.23 5.02 6.21 7.23 8.36 9.61 11.50

01467160 47.34 3.32 4.24 5.03 6.21 7.23 8.35 9.60 11.46

01467180 47.22 3.32 4.24 5.02 6.18 7.19 8.30 9.52 11.35

01467305 46.63 3.29 4.21 4.98 6.14 7.15 8.24 9.47 11.29

01467317 46.27 3.29 4.20 4.98 6.15 7.17 8.27 9.51 11.37

01467330 46.78 3.30 4.26 5.08 6.32 7.42 8.62 9.98 12.04

01467351 47.24 3.30 4.25 5.05 6.27 7.34 8.51 9.82 11.80

01472157 47.23 3.23 4.05 4.72 5.70 6.52 7.40 8.35 9.74

01472174 46.81 3.24 4.06 4.73 5.72 6.53 7.42 8.37 9.75

01473169 47.05 3.23 4.05 4.73 5.72 6.54 7.43 8.39 9.78

01473470 47.48 3.25 4.08 4.77 5.76 6.60 7.49 8.46 9.87

01474000 48.61 3.28 4.12 4.82 5.84 6.71 7.63 8.65 10.12

01475000 46.72 3.30 4.27 5.10 6.37 7.48 8.72 10.11 12.23

01475019 46.66 3.29 4.24 5.07 6.31 7.42 8.61 9.97 12.04

01475300 48.16 3.25 4.08 4.77 5.77 6.62 7.52 8.50 9.93

01475510 48.12 3.26 4.10 4.80 5.81 6.67 7.59 8.59 10.05

01475530 49.21 3.27 4.11 4.81 5.82 6.67 7.59 8.58 10.03

01475550 48.02 3.26 4.10 4.80 5.81 6.66 7.58 8.57 10.02

01475850 47.97 3.25 4.08 4.77 5.78 6.63 7.53 8.52 9.96

01476000 47.72 3.25 4.09 4.79 5.82 6.68 7.61 8.62 10.11

01476435 47.56 3.25 4.07 4.76 5.76 6.60 7.49 8.47 9.89

01476480 47.42 3.25 4.09 4.79 5.81 6.68 7.60 8.62 10.10

01477000 47.12 3.25 4.10 4.81 5.85 6.73 7.68 8.72 10.24

01477110 46.52 3.27 4.21 5.02 6.24 7.33 8.49 9.82 11.83

01477120 46.37 3.26 4.20 5.01 6.22 7.29 8.45 9.76 11.75

01477480 46.18 3.26 4.21 5.02 6.24 7.32 8.50 9.84 11.86

40 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 6. Climatic characteristics for stations in and near Delaware that were considered for use in the regression 

analyses.—Continued

[USGS, U.S. Geological Survey]

USGS 

station 

number

Mean annual 

precipitation 

(inches)

Recurrence interval of 24-hour maximum precipitation (inches)

2-

year

5-

year

10-

year

25-

year

50-

year

100-

year

200-

year

500-

year

01477500 46.07 3.26 4.21 5.02 6.24 7.31 8.50 9.83 11.84

01477800 46.77 3.27 4.13 4.84 5.89 6.77 7.73 8.77 10.30

01478000 45.86 3.25 4.07 4.77 5.78 6.62 7.53 8.52 9.96

01478040 45.08 3.24 4.08 4.78 5.80 6.67 7.59 8.61 10.08

01478200 47.83 3.25 4.08 4.77 5.76 6.60 7.50 8.47 9.88

01478500 47.39 3.26 4.08 4.77 5.77 6.61 7.51 8.48 9.89

01479000 46.97 3.26 4.08 4.77 5.78 6.62 7.52 8.49 9.91

01479200 48.07 3.27 4.10 4.79 5.80 6.64 7.55 8.53 9.96

01479820 47.68 3.27 4.10 4.79 5.79 6.63 7.53 8.50 9.91

01479950 47.47 3.27 4.11 4.80 5.81 6.66 7.57 8.56 9.99

01480000 47.69 3.27 4.10 4.80 5.80 6.64 7.55 8.52 9.94

01480015 47.53 3.27 4.10 4.80 5.80 6.65 7.55 8.53 9.95

01480100 45.84 3.27 4.12 4.81 5.83 6.68 7.60 8.60 10.05

01480300 47.81 3.21 4.02 4.70 5.68 6.49 7.37 8.32 9.70

01480500 47.76 3.22 4.03 4.71 5.69 6.51 7.39 8.34 9.72

01480610 47.25 3.24 4.05 4.73 5.72 6.54 7.43 8.38 9.77

01480675 47.58 3.24 4.06 4.74 5.72 6.54 7.42 8.38 9.77

01480680 47.29 3.24 4.06 4.74 5.72 6.54 7.43 8.38 9.77

01480700 47.24 3.24 4.05 4.73 5.71 6.53 7.42 8.37 9.75

01480870 47.11 3.24 4.06 4.74 5.72 6.54 7.42 8.38 9.76

01481000 47.25 3.25 4.07 4.75 5.74 6.56 7.45 8.41 9.80

01481200 47.94 3.28 4.12 4.82 5.83 6.68 7.60 8.59 10.02

01481450 47.62 3.28 4.13 4.84 5.87 6.73 7.67 8.70 10.18

01481500 47.29 3.25 4.07 4.75 5.74 6.57 7.46 8.43 9.83

01482310 43.93 3.22 4.10 4.83 5.92 6.88 7.88 9.01 10.68

01482500 46.06 3.26 4.22 5.04 6.29 7.39 8.60 9.97 12.05

01483000 45.48 3.26 4.23 5.06 6.32 7.42 8.65 10.05 12.16

01483200 44.41 3.20 4.14 4.94 6.17 7.24 8.43 9.77 11.81

01483290 44.55 3.21 4.15 4.96 6.19 7.27 8.47 9.82 11.88

01483400 44.34 3.20 4.14 4.95 6.18 7.25 8.45 9.80 11.85

01483500 44.51 3.25 4.22 5.05 6.32 7.43 8.67 10.07 12.21

01483700 44.62 3.27 4.25 5.10 6.39 7.53 8.79 10.23 12.42

01483720 44.56 3.30 4.29 5.14 6.45 7.60 8.88 10.35 12.57

01484000 44.86 3.31 4.30 5.16 6.47 7.63 8.92 10.38 12.60

01484002 44.83 3.33 4.33 5.20 6.52 7.68 8.98 10.46 12.70

01484050 44.80 3.33 4.33 5.19 6.51 7.67 8.97 10.44 12.69

01484100 44.94 3.35 4.36 5.23 6.56 7.73 9.04 10.51 12.77

01484270 45.37 3.41 4.43 5.32 6.67 7.86 9.19 10.70 13.00

Tables 6 through 8  41
Table 6. Climatic characteristics for stations in and near Delaware that were considered for use in the regression 

analyses.—Continued

[USGS, U.S. Geological Survey]

USGS 

station 

number

Mean annual 

precipitation 

(inches)

Recurrence interval of 24-hour maximum precipitation (inches)

2-

year

5-

year

10-

year

25-

year

50-

year

100-

year

200-

year

500-

year

01477500 46.07 3.26 4.21 5.02 6.24 7.31 8.50 9.83 11.84

01477800 46.77 3.27 4.13 4.84 5.89 6.77 7.73 8.77 10.30

01478000 45.86 3.25 4.07 4.77 5.78 6.62 7.53 8.52 9.96

01478040 45.08 3.24 4.08 4.78 5.80 6.67 7.59 8.61 10.08

01478200 47.83 3.25 4.08 4.77 5.76 6.60 7.50 8.47 9.88

01478500 47.39 3.26 4.08 4.77 5.77 6.61 7.51 8.48 9.89

01479000 46.97 3.26 4.08 4.77 5.78 6.62 7.52 8.49 9.91

01479200 48.07 3.27 4.10 4.79 5.80 6.64 7.55 8.53 9.96

01479820 47.68 3.27 4.10 4.79 5.79 6.63 7.53 8.50 9.91

01479950 47.47 3.27 4.11 4.80 5.81 6.66 7.57 8.56 9.99

01480000 47.69 3.27 4.10 4.80 5.80 6.64 7.55 8.52 9.94

01480015 47.53 3.27 4.10 4.80 5.80 6.65 7.55 8.53 9.95

01480100 45.84 3.27 4.12 4.81 5.83 6.68 7.60 8.60 10.05

01480300 47.81 3.21 4.02 4.70 5.68 6.49 7.37 8.32 9.70

01480500 47.76 3.22 4.03 4.71 5.69 6.51 7.39 8.34 9.72

01480610 47.25 3.24 4.05 4.73 5.72 6.54 7.43 8.38 9.77

01480675 47.58 3.24 4.06 4.74 5.72 6.54 7.42 8.38 9.77

01480680 47.29 3.24 4.06 4.74 5.72 6.54 7.43 8.38 9.77

01480700 47.24 3.24 4.05 4.73 5.71 6.53 7.42 8.37 9.75

01480870 47.11 3.24 4.06 4.74 5.72 6.54 7.42 8.38 9.76

01481000 47.25 3.25 4.07 4.75 5.74 6.56 7.45 8.41 9.80

01481200 47.94 3.28 4.12 4.82 5.83 6.68 7.60 8.59 10.02

01481450 47.62 3.28 4.13 4.84 5.87 6.73 7.67 8.70 10.18

01481500 47.29 3.25 4.07 4.75 5.74 6.57 7.46 8.43 9.83

01482310 43.93 3.22 4.10 4.83 5.92 6.88 7.88 9.01 10.68

01482500 46.06 3.26 4.22 5.04 6.29 7.39 8.60 9.97 12.05

01483000 45.48 3.26 4.23 5.06 6.32 7.42 8.65 10.05 12.16

01483200 44.41 3.20 4.14 4.94 6.17 7.24 8.43 9.77 11.81

01483290 44.55 3.21 4.15 4.96 6.19 7.27 8.47 9.82 11.88

01483400 44.34 3.20 4.14 4.95 6.18 7.25 8.45 9.80 11.85

01483500 44.51 3.25 4.22 5.05 6.32 7.43 8.67 10.07 12.21

01483700 44.62 3.27 4.25 5.10 6.39 7.53 8.79 10.23 12.42

01483720 44.56 3.30 4.29 5.14 6.45 7.60 8.88 10.35 12.57

01484000 44.86 3.31 4.30 5.16 6.47 7.63 8.92 10.38 12.60

01484002 44.83 3.33 4.33 5.20 6.52 7.68 8.98 10.46 12.70

01484050 44.80 3.33 4.33 5.19 6.51 7.67 8.97 10.44 12.69

01484100 44.94 3.35 4.36 5.23 6.56 7.73 9.04 10.51 12.77

01484270 45.37 3.41 4.43 5.32 6.67 7.86 9.19 10.70 13.00

01484300 45.11 3.39 4.40 5.29 6.62 7.80 9.12 10.62 12.90

42  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 6. Climatic characteristics for stations in and near Delaware that were considered for use in the regression 

analyses.—Continued

[USGS, U.S. Geological Survey]

USGS 

station 

number

Mean annual 

precipitation 

(inches)

Recurrence interval of 24-hour maximum precipitation (inches)

2-

year

5-

year

10-

year

25-

year

50-

year

100-

year

200-

year

500-

year

01484500 45.61 3.42 4.45 5.34 6.69 7.88 9.22 10.73 13.03

01484525 45.52 3.42 4.45 5.34 6.69 7.88 9.22 10.73 13.03

01484550 45.65 3.42 4.44 5.33 6.68 7.86 9.20 10.71 13.00

01485000 45.49 3.44 4.47 5.37 6.73 7.93 9.27 10.79 13.11

01485500 45.33 3.47 4.51 5.41 6.79 7.99 9.35 10.89 13.22

01486000 44.90 3.35 4.35 5.22 6.54 7.71 9.02 10.49 12.74

01486100 45.38 3.45 4.49 5.39 6.75 7.95 9.30 10.82 13.15

01486980 44.98 3.36 4.37 5.25 6.58 7.76 9.07 10.55 12.81

01487000 44.98 3.36 4.37 5.25 6.58 7.75 9.06 10.54 12.80

01487500 45.35 3.44 4.47 5.36 6.72 7.91 9.25 10.77 13.08

01488000 44.67 3.42 4.45 5.34 6.69 7.88 9.22 10.73 13.03

Tables 6 through 8  43
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

USGS 

station 

number

Drainage 

area 

(mi2

)

Mean 

stream 

slope 

(ft/mi)

10/85

stream 

slope 

(ft/mi)

Mean 

basin 

slope 

(percent)

Storage 

(NHD) 

(percent)

Storage 

(NLCD.DE) 

(percent)

Forest 

cover 

(percent)

Main 

channel 

length 

(mi)

Basin 

shape 

factor

Hydrologic 

soil 

type A 

(percent)

01411456 9.78 8.84 8.07 0.72 12.3 18.8 59.9 5.40 2.98 12.5

01411500 112 6.16 4.84 0.99 9.27 11.7 50.8 19.7 3.46 13.6

01412500 2.55 25.0 22.6 2.09 0.06 1.39 4.87 3.36 4.43 0.53

01412800 28.0 11.6 11.2 1.93 1.27 4.53 16.3 8.58 2.63 4.55

01467043 1.20 71.8 67.1 4.39 0.00 0.57 13.4 2.13 3.80 6.25

01467045 43.1 20.4 16.7 4.75 0.47 0.96 19.1 14.7 5.02 2.82

01467081 8.98 12.2 9.72 1.88 0.31 5.81 17.3 8.64 8.31 5.39

01467086 16.2 38.3 26.9 5.23 0.33 1.49 13.5 9.40 5.46 5.98

01467087 30.0 31.8 21.8 4.41 0.36 1.29 9.43 12.9 5.57 6.31

01467089 33.8 30.9 20.8 4.11 0.33 1.20 8.44 13.8 5.59 6.56

01467130 5.03 32.5 20.0 2.71 2.47 11.2 44.2 4.11 3.36 30.0

01467150 17.1 18.3 11.2 2.69 1.25 7.58 29.9 9.92 5.75 11.7

01467160 5.32 24.0 12.8 2.57 0.34 8.22 29.8 6.16 7.13 3.22

01467180 10.5 18.9 11.1 2.64 0.33 9.55 32.1 9.18 8.01 3.64

01467305 1.33 41.8 30.3 1.21 0.31 3.49 21.1 2.31 4.04 6.00

01467317 0.62 43.5 45.5 1.51 0.28 2.38 11.0 1.46 3.44 6.00

01467330 20.8 20.6 20.4 3.19 3.80 7.91 31.2 8.44 3.42 5.17

01467351 7.16 24.8 27.3 3.69 2.66 6.81 36.7 5.63 4.43 35.3

01472157 59.0 36.1 25.1 9.53 0.73 2.44 53.1 19.0 6.08 5.43

01472174 5.98 73.4 38.6 8.00 0.48 2.01 30.7 4.74 3.77 6.25

01473169 20.8 47.3 29.7 8.72 0.37 3.60 29.8 9.93 4.73 1.97

01473470 20.8 35.6 28.1 4.39 0.24 0.24 16.3 7.87 2.97 0.00

01474000 63.7 64.3 13.3 5.45 0.57 1.17 24.0 25.4 10.1 1.26

01475000 6.05 17.7 19.2 2.07 2.58 5.23 19.2 4.50 3.35 4.03

01475019 14.1 17.3 17.9 2.59 2.42 5.87 23.4 8.02 4.56 2.66

01475300 5.18 56.2 36.8 5.59 0.36 1.01 30.5 4.08 3.21 3.47

01475510 37.6 28.2 21.0 6.90 0.46 1.00 24.7 18.3 8.94 6.21

01475530 4.78 63.7 61.7 4.42 0.15 1.26 11.2 4.71 4.64 6.46

01475550 21.8 35.4 32.2 4.08 0.27 1.17 8.17 11.8 6.34 7.36

01475850 15.8 43.6 32.0 6.56 0.43 1.74 36.8 8.67 4.75 1.95

01476000 33.7 27.6 22.0 7.77 2.30 3.92 35.1 20.1 12.0 3.25

01476435 9.71 40.8 32.7 5.54 0.56 1.31 24.9 6.42 4.24 3.16

01476480 30.2 29.3 23.4 7.79 0.58 0.93 41.1 16.8 9.35 1.74

01476500 31.6 28.4 22.3 7.88 0.59 0.96 40.8 18.2 10.4 1.94

01477000 60.7 27.9 22.7 7.67 0.92 1.80 32.2 20.9 7.19 3.35

01477110 14.6 14.4 15.1 2.65 2.17 5.42 29.6 8.17 4.57 7.32

01477120 25.9 13.4 14.8 2.84 1.77 5.70 29.5 10.3 4.10 5.19

44  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

Hydrologic 

soil 

type D 

(percent)

Average 

soil 

permeability 

(in/hr)

Impervious 

area 

(percent)

Basin 

relief 

(ft)

Mean 

basin 

eleva

tion 

(ft)

Gage 

elevation 

(ft)

Development 

intensity 

(percent)

Developed 

area 

(percent)

Centroid 

year 

housing 

density 

(homes/

acre)

2000 

Housing 

density 

(homes/

acre)

USGS 

station 

number

8.09 6.91 4.22 48.6 134 112 4.25 15.8 0.26 0.28 01411456

7.08 6.86 3.27 131 115 48.7 3.21 13.9 0.15 0.26 01411500

0.00 1.83 0.13 93.3 105 47.9 0.06 0.46 0.06 0.07 01412500

0.74 2.84 0.80 114 103 27.4 0.76 2.87 0.07 0.08 01412800

7.29 1.23 25.8 154 207 96.9 22.5 80.6 2.92 2.99 01467043

5.67 1.12 20.3 364 251 69.2 19.7 69.4 1.56 1.99 01467045

0.53 2.67 31.0 106 63.1 17.0 29.1 77.6 1.80 1.98 01467081

6.97 1.23 24.6 366 254 63.8 23.7 79.2 3.80 3.94 01467086

7.69 1.23 38.3 417 220 18.3 37.3 85.6 6.70 6.74 01467087

8.32 1.23 41.1 430 206 3.28 40.0 87.0 7.16 7.25 01467089

4.47 6.99 14.2 145 104 56.5 13.2 41.6 0.52 0.97 01467130

2.68 3.82 19.4 193 84.9 5.80 18.4 60.7 1.22 1.39 01467150

3.37 2.61 16.7 157 91.6 33.7 15.2 59.5 0.35 1.38 01467160

2.26 2.52 17.6 183 78.0 8.92 16.6 60.6 0.57 1.35 01467180

0.00 2.64 18.2 103 70.2 18.9 17.4 78.1 3.42 3.47 01467305

0.00 2.64 23.8 64.8 73.4 37.9 22.7 89.0 3.28 3.28 01467317

2.53 3.96 14.4 180 112 9.15 13.4 47.0 0.62 1.12 01467330

5.25 7.83 15.5 182 114 19.1 14.5 50.2 1.92 1.94 01467351

7.00 1.65 0.45 838 529 167 0.44 2.03 0.08 0.10 01472157

7.29 1.23 3.70 355 437 277 3.33 14.0 0.06 0.24 01472174

2.33 1.24 12.7 635 354 117 12.5 38.6 0.58 0.66 01473169

8.07 1.06 15.8 412 283 78.8 14.8 52.3 1.02 1.29 01473470

6.89 1.07 13.8 469 283 20.6 13.6 54.7 1.53 1.68 01474000

2.58 4.20 14.6 90.1 128 69.6 13.4 49.0 0.45 1.67 01475000

2.79 3.64 13.8 150 105 11.7 12.7 46.6 0.68 1.25 01475019

12.0 0.95 8.25 245 434 316 9.01 42.3 0.78 0.93 01475300

10.7 1.15 15.7 531 325 28.3 15.0 56.9 1.90 2.03 01475510

7.85 1.23 22.6 311 319 126 21.5 81.4 3.19 3.33 01475530

10.3 1.23 37.5 426 209 17.1 36.0 87.6 6.84 6.89 01475550

14.6 0.79 3.56 382 419 218 4.10 20.6 0.49 0.53 01475850

13.6 0.90 7.24 561 336 35.4 7.30 32.3 0.47 0.82 01476000

12.6 0.91 5.48 270 472 342 5.51 28.9 0.40 0.83 01476435

15.0 0.77 3.83 499 373 110 3.82 19.5 0.20 0.57 01476480

14.7 0.79 4.42 523 367 87.3 4.42 20.8 0.21 0.66 01476500

12.3 0.93 7.74 586 338 24.6 7.78 29.8 0.30 0.62 01477000

5.35 4.98 1.60 140 115 31.0 1.60 8.13 0.12 0.15 01477110

3.86 3.93 1.67 163 102 10.6 1.56 7.78 0.11 0.14 01477120

Tables 6 through 8  45
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

USGS 

station 

number

Drainage 

area 

(mi2

)

Mean 

stream 

slope 

(ft/mi)

10/85

stream 

slope 

(ft/mi)

Mean 

basin 

slope 

(percent)

Storage 

(NHD) 

(percent)

Storage 

(NLCD.DE) 

(percent)

Forest 

cover 

(percent)

Main 

channel 

length 

(mi)

Basin 

shape 

factor

Hydrologic 

soil 

type A 

(percent)

01477480 13.8 14.5 13.5 2.47 1.31 5.33 31.8 9.16 6.09 5.45

01477500 18.5 13.7 13.5 2.67 0.99 5.31 28.8 9.87 5.26 6.44

01477800 7.34 65.3 65.4 3.70 0.13 0.23 7.29 6.10 5.07 1.56

01478000 20.8 30.5 21.7 4.71 0.43 2.26 23.7 13.4 8.67 2.61

01478040 40.6 23.2 17.6 3.38 1.06 4.71 25.1 18.1 8.08 1.33

01478200 12.7 36.8 27.5 6.63 0.18 0.66 15.9 11.0 9.53 6.23

01478500 66.4 25.2 17.7 8.16 0.36 1.54 25.7 19.5 5.70 5.90

01478650 68.6 23.3 16.7 8.22 0.41 1.59 26.5 21.7 6.86 5.82

01479000 88.9 20.0 13.9 7.69 0.42 1.56 25.1 27.2 8.32 5.12

01479200 4.29 60.1 42.8 6.39 0.33 0.76 10.7 3.38 2.67 6.25

01479820 27.6 32.8 20.9 6.90 0.64 1.76 19.6 10.8 4.22 5.84

01479950 0.38 173 149 14.7 0.00 0.00 35.2 1.40 5.14 6.25

01480000 47.2 23.8 15.9 8.58 1.36 2.07 25.1 19.3 7.88 6.01

01480015 52.5 22.3 15.4 8.34 1.31 2.03 23.8 23.7 10.7 5.88

01480100 6.67 46.2 33.4 4.08 0.35 0.53 13.8 6.55 6.44 7.22

01480300 18.7 44.9 24.4 5.23 0.26 3.15 22.0 9.22 4.56 5.36

01480500 46.1 33.6 22.0 6.75 0.69 3.27 34.3 20.7 9.31 2.42

01480610 2.61 124 145 9.96 0.23 4.74 31.8 2.65 2.68 3.74

01480617 55.3 31.1 21.5 7.48 0.67 3.83 33.9 23.7 10.1 2.64

01480675 8.54 41.3 26.9 7.11 6.04 5.46 46.3 6.01 4.23 6.25

01480680 17.6 39.9 31.6 7.80 5.15 5.57 39.1 9.13 4.72 6.25

01480700 60.1 43.8 23.5 7.49 2.92 4.62 37.5 17.9 5.30 5.99

01480800 81.8 40.3 22.0 7.61 2.26 4.22 35.5 20.2 4.97 5.39

01480870 89.8 35.0 19.9 7.95 2.14 4.27 36.2 24.1 6.46 5.36

01481000 288 19.4 13.8 8.53 1.15 3.28 31.5 43.6 6.59 4.65

01481200 1.05* 142 134 15.2 0.19 0.26 48.2 1.93 3.53 6.25

01481450 0.31* 72.1 74.7 3.11 0.00 0.00 4.07 0.92 2.69 0.00

01481500 319 17.2 11.2 8.63 1.21 3.26 31.8 54.4 9.28 4.59

01482310 1.05 32.1 32.0 2.22 0.82 4.92 13.3 1.81 3.10 0.00

01482500 14.6 15.0 11.7 2.55 1.71 4.13 17.9 8.11 4.51 3.88

01483000 20.4 13.8 13.6 2.86 2.83 5.29 39.0 9.35 4.29 11.6

01483200 4.06* 14.4 14.8 1.76 4.39 17.7 30.7 4.19 4.33 3.07

01483290 1.2* 11.9 11.7 1.16 1.67 10.4 7.34 2.40 4.79 3.06

01483400 0.51* 30.3 28.2 1.70 2.59 18.0 7.44 1.08 2.3 3.06

01483500 9.15 9.04 8.22 1.46 0.89 11.3 9.40 5.86 3.75 3.6

01483700 31.0 4.87 4.95 1.06 4.28 16.1 14.0 13.7 6.04 3.71

01483720 2.54* 14.0 14.3 1.01 0.06 3.33 9.95 2.53 2.51 3.06

46  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses—

Continued.

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

Hydrologic 

soil 

type D 

(percent)

Average 

soil 

permeability 

(in/hr)

Impervious 

area 

(percent)

Basin 

relief 

(ft)

Mean 

basin 

elevation 

(ft)

Gage

elevation 

(ft)

Development 

intensity 

(percent)

Developed 

area 

(percent)

Centroid

year 

housing 

density 

(homes/

acre)

2000 

Housing 

density 

(homes/

acre)

USGS 

station 

number

23.8 4.06 0.33 148 109 17.2 0.34 1.76 0.05 0.05 01477480

19.4 4.34 0.31 150 105 13.0 0.31 1.57 0.02 0.05 01477500

19.1 0.66 18.6 400 275 21.9 31.5 90.7 1.74 1.87 01477800

7.98 1.25 11.0 412 191 28.6 16.3 40.0 0.50 0.74 01478000

6.61 1.38 11.6 423 135 17.0 20.5 47.4 0.59 0.80 01478040

7.27 1.23 1.03 414 452 235 1.09 6.18 0.10 0.16 01478200

6.88 1.23 1.64 582 376 70.4 2.19 9.79 0.12 0.20 01478500

6.92 1.23 1.84 597 369 55.5 2.54 10.7 0.21 0.21 01478650

7.19 1.23 5.10 636 324 16.2 8.06 23.1 0.15 0.50 01479000

7.29 1.23 8.22 226 313 214 23.7 76.8 0.20 0.72 01479200

6.81 1.23 3.75 361 370 190 3.83 15.8 0.30 0.31 01479820

7.29 1.23 0.56 269 305 147 8.94 37.8 0.15 0.42 01479950

7.01 1.23 2.55 467 336 84.7 5.82 24.8 0.18 0.29 01480000

7.08 1.23 3.90 536 320 15.7 8.09 30.7 0.37 0.38 01480015

14.2 1.13 22.6 304 155 49.7 34.1 83.0 1.64 1.67 01480100

6.3 1.47 1.35 463 726 590 1.24 4.33 0.10 0.15 01480300

11.5 1.10 1.47 743 663 306 1.31 5.95 0.09 0.20 01480500

5.86 1.17 4.38 331 543 354 4.17 20.7 0.33 0.38 01480610

10.5 1.12 3.82 783 632 266 3.56 11.3 0.30 0.35 01480617

7.29 1.23 0.60 381 598 452 0.57 2.79 0.06 0.08 01480675

7.29 1.23 1.33 494 557 336 1.21 6.53 0.03 0.12 01480680

6.98 1.31 1.66 795 558 261 1.48 6.42 0.12 0.19 01480700

6.53 1.32 3.08 826 531 228 2.82 11.6 0.07 0.32 01480800

6.48 1.31 3.71 855 516 199 3.47 13.2 0.27 0.35 01480870

7.79 1.21 3.38 901 489 154 3.23 12.4 0.11 0.34 01481000

7.29 1.23 0.40 282 327 157 8.57 34.5 0.07 0.11 01481200

18.0 0.59 23.7 70.7 355 312 34.8 95.9 1.51 1.51 01481450

8.11 1.19 3.45 987 472 67.3 3.91 14.4 0.19 0.34 01481500

2.15 1.76 5.57 58.8 58.1 21.4 13.8 25.7 0.08 0.21 01482310

4.47 3.03 0.89 133 110 31.0 0.99 4.34 0.04 0.06 01482500

3.79 3.29 0.13 151 82.2 10.1 0.14 0.92 0.03 0.04 01483000

3.05 2.87 0.05 63.1 62.8 19.8 2.25 9.91 0.03 0.04 01483200

3.06 2.87 0.14 34.6 64.0 45.6 2.99 13.4 0.02 0.06 01483290

3.06 2.87 0.94 33.8 52.9 36.2 13.6 29.1 0.02 0.06 01483400

3.06 2.98 0.56 56.1 58.7 20.0 3.31 14.9 0.02 0.07 01483500

2.70 2.78 5.30 67.7 51.4 12.6 11.0 31.4 0.22 0.31 01483700

3.06 2.87 12.4 36.0 45.3 24.1 22.2 36.6 0.33 0.64 01483720

Tables 6 through 8  47
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

USGS 

station 

number

Drainage 

area 

(mi2

)

Mean 

stream 

slope 

(ft/mi)

10/85

stream 

slope 

(ft/mi)

Mean 

basin 

slope 

(percent)

Storage 

(NHD) 

(percent)

Storage 

(NLCD.DE) 

(percent)

Forest 

cover 

(percent)

Main 

channel 

length 

(mi)

Basin 

shape 

factor

Hydrologic 

soil 

type A 

(percent)

01484000 12.9* 7.00 6.23 0.69 0.71 18.0 14.4 6.91 3.7 36.8

01484002 0.88* 13.9 14.6 1.00 0.19 3.91 10.3 2.29 5.92 60.0

01484050 2.91* 11.9 12.3 1.20 0.14 4.74 10.2 3.49 4.19 60.0

01484100 3.02* 6.40 4.42 0.48 0.95 17.9 21.5 3.15 3.29 49.8

01484270 6.85* 5.69 6.85 0.86 2.27 5.35 29.0 7.01 7.17 51.0

01484300 6.99 7.70 8.29 0.81 3.10 9.18 30.4 5.69 4.64 43.9

01484500 5.20 4.45 4.19 0.57 0.00 19.5 10.9 4.98 4.76 38.4

01484525 61.7* 4.45 4.62 0.66 2.30 14.1 27.9 12.2 2.42 45.7

01484550 8.31* 4.37 3.76 0.59 0.00 24.3 8.15 7.34 6.47 6.77

01485000 58.2 2.10 2.14 0.48 17.3 25.4 22.8 16.7 4.77 8.53

01485500 44.8 5.07 3.18 0.41 6.42 8.22 66.0 13.3 3.91 18.2

01486000 4.69 7.13 6.62 0.35 0.02 9.98 56.1 3.68 2.89 6.01

01486100 4.84* 8.63 7.24 0.57 0.00 1.11 57.1 4.88 4.93 7.17

01486980 6.48 2.27 1.41 0.36 0.10 25.2 26.3 4.47 3.08 17.6

01487000 74.0 2.81 2.60 0.53 1.59 17.9 16.8 15.1 3.07 17.9

01487500 16.0 4.62 5.14 0.43 1.38 16.2 40.1 9.00 5.06 46.2

01488000 2.89* 5.39 4.53 0.30 0.00 7.23 3.73 3.30 3.77 59.5

01488500 46.8* 3.03 2.49 0.53 0.02 27.7 8.3 12.3 3.21 8.55

01489000 7.33 6.84 5.56 1.20 0.00 1.64 19.8 6.06 5.01 4.70

01490000 15.3 6.09 4.75 0.63 0.00 4.22 33.6 7.87 4.05 6.8

01490600 8.90* 5.52 5.33 0.50 1.03 36.6 11.9 6.00 4.05 10.2

01490800 4.00 6.95 7.85 0.64 0.00 3.97 37.7 4.24 4.49 4.98

01491000 117 2.87 2.75 0.72 1.50 23.1 21.0 22.0 4.15 10.0

01491010 2.11* 4.42 4.22 0.55 0.00 16.7 11.9 3.33 5.24 27.9

01491050 3.51* 6.06 4.76 0.50 0.00 1.00 25.5 4.34 5.37 10.2

01492000 5.88 9.03 11.7 0.65 0.00 2.96 27.0 4.72 3.79 3.59

01492050 8.73 9.46 9.01 1.12 0.26 1.50 15.3 5.57 3.55 4.08

01492500 7.97 9.84 9.12 0.89 0.00 4.16 24.5 5.87 4.32 0.76

01492550 4.44 17.7 15.2 0.70 0.20 2.55 5.56 3.62 2.95 3.79

01493000 19.7 5.74 5.57 0.89 1.32 8.56 29.9 11.2 6.34 3.72

01493500 12.4 7.67 9.48 0.98 0.72 3.59 6.33 6.36 3.27 1.09

01494000 12.8 10.4 7.20 0.86 0.06 4.13 23.6 5.93 2.75 2.34

01495000 53.2 22.8 16.6 7.26 0.50 1.64 23.2 25.0 11.8 6.14

01495500 26.7 28.5 23.3 5.95 0.39 1.61 23.4 17.3 11.3 4.41

01496000 24.2 31.5 24.4 3.83 0.53 1.85 19.9 14.2 8.38 4.06

01496080 1.73 127 121 7.02 0.70 8.80 84.9 2.83 4.63 0.00

48  Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

Hydrologic 

soil 

type D 

(percent)

Average

soil 

permeability 

(in/hr)

Impervious 

area 

(percent)

Basin 

relief 

(ft)

Mean

basin

elevation 

(ft)

Gage

elevation 

(ft)

Development

intensity 

(percent)

Developed 

area 

(percent)

Centroid

year 

housing

density

(homes/

acre)

2000

Housing

density

(homes/

acre)

USGS 

station 

number

4.31 2.92 0.84 52.0 55.0 21.3 3.68 13.5 0.04 0.09 01484000

6.00 3.15 0.69 32.6 54.3 28.1 1.40 2.19 0.03 0.08 01484002

5.99 3.15 2.01 48.5 52.8 22.9 7.40 22.6 0.02 0.08 01484050

5.25 3.05 0.01 25.8 53.1 37.5 1.49 6.33 0.03 0.06 01484100

4.91 2.90 0.72 51.2 34.5 4.19 4.08 13.3 0.05 0.08 01484270

4.76 3.37 0.50 45.8 37.1 8.33 1.99 7.55 0.02 0.05 01484300

3.05 2.60 2.62 29.4 43.8 26.8 8.17 19.0 0.03 0.07 01484500

4.29 2.95 1.48 62.0 39.7 1.00 5.58 15.4 0.08 0.09 01484525

10.1 3.93 1.34 35.9 33.7 9.08 3.76 11.9 0.03 0.05 01484550

13.0 4.00 0.16 55.8 41.1 19.2 0.87 3.63 0.02 0.03 01485000

6.09 4.49 0.12 74.8 44.3 14.3 0.12 0.66 0.02 0.04 01485500

2.00 3.22 0.12 35.3 28.6 17.5 0.10 0.62 0.01 0.02 01486000

1.35 2.15 0.03 40.3 59.3 39.2 0.03 0.13 0.01 0.06 01486100

2.91 2.74 0.38 39.6 51.9 44.1 2.96 11.0 0.01 0.03 01486980

3.49 3.04 0.87 65.6 48.6 18.8 3.35 11.2 0.02 0.04 01487000

4.89 3.21 0.05 49.4 48.7 28.8 1.22 5.12 0.02 0.03 01487500

5.96 3.16 0.01 17.9 37.0 28.6 2.10 8.93 0.01 0.04 01488000

2.45 2.93 0.12 38.9 55.8 31.2 1.37 6.23 0.02 0.04 01488500

2.58 2.91 0.14 42.6 44.4 17.5 0.11 0.53 0.02 0.04 01489000

3.19 3.57 0.11 49.1 29.2 2.72 0.11 0.36 0.02 0.02 01490000

2.87 3.15 0.04 34.1 58.1 36.6 1.56 7.03 0.01 0.04 01490600

2.02 2.62 0.86 29.9 57.2 35.7 0.80 3.13 0.02 0.04 01490800

2.80 3.10 0.28 103 57.1 11.4 2.24 9.60 0.03 0.06 01491000

4.94 4.68 0.03 18.0 58.5 46.7 0.28 2.11 0.01 0.02 01491010

2.66 3.08 0.10 26.3 56.5 39.2 0.12 0.68 0.02 0.06 01491050

2.28 2.34 0.18 43.2 52.3 16.9 0.21 1.26 0.01 0.03 01492000

3.82 3.55 0.18 57.7 40.2 2.19 0.19 0.75 0.02 0.04 01492050

2.26 1.85 0.27 60.8 55.1 18.7 0.36 2.21 0.02 0.04 01492500

2.52 2.73 0.27 66.8 51.1 14.3 0.23 1.13 0.01 0.03 01492550

3.07 2.99 0.26 69.2 59.9 10.4 0.28 1.28 0.02 0.03 01493000

4.50 1.75 0.26 63.8 56.5 16.9 0.28 1.24 0.01 0.01 01493500

3.06 2.71 0.32 64.3 62.3 18.0 0.31 1.61 0.01 0.03 01494000

6.90 1.26 0.92 583 409 68.5 0.91 3.98 0.05 0.13 01495000

6.99 1.26 1.12 504 366 67.2 1.17 5.29 0.05 0.14 01495500

7.62 1.19 1.08 451 404 119 1.11 4.16 0.03 0.11 01496000

6.66 0.88 2.49 365 225 58.8 2.28 6.94 0.02 0.06 01496080

Tables 6 through 8  49
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

USGS 

station 

number

Drainage 

area 

(mi2

)

Mean 

stream 

slope 

(ft/mi)

10/85

stream 

slope 

(ft/mi)

Mean 

basin 

slope 

(percent)

Storage 

(NHD) 

(percent)

Storage 

(NLCD.DE) 

(percent)

Forest 

cover 

(percent)

Main 

channel 

length 

(mi)

Basin 

shape 

factor

Hydrologic 

soil 

type A 

(percent)

01496200 8.96 38.1 30.1 5.25 0.25 0.52 15.8 6.71 5.02 3.79

01578200 5.53 91.0 71.2 7.43 0.11 0.74 18.0 4.76 4.09 6.25

01578400 6.03 86.6 70.7 7.10 0.06 0.96 18.1 4.36 3.15 6.25

01578500 192 16.3 9.50 7.74 0.93 2.26 20.2 41.9 9.14 5.52

01578800 1.37* 66.7 71.2 3.87 0.78 1.54 13.0 1.76 2.27 5.89

01579000 5.26 52.8 45.2 4.90 0.48 1.79 20.5 3.87 2.85 5.33

*

 Indicates that drainage area has been revised as a result of this study.

50 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 7. Basin characteristics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; mi2, square miles; ft/mi, NHD, National Hydrography Dataset; NLCD.DE, 2001 National Land Cover Dataset 

and 2003 Delaware land cover dataset combined; feet per mile; mi, miles; in/hr, inches per hour; ft, feet]

Hydrologic 

soil 

type D 

(percent)

Average 

soil 

permeability 

(in/hr)

Impervious 

area 

(percent)

Basin 

relief 

(ft)

Mean 

basin 

elevation 

(ft)

Gage 

elevation 

(ft)

Development 

intensity 

(percent)

Developed 

area (percent)

Centroid 

year 

housing 

density 

(homes/

acre)

2000 

Housing 

density 

(homes/

acre)

USGS 

station 

number

8.19 1.18 0.19 274 381 207 0.17 0.67 0.08 0.11 01496200

7.29 1.23 1.18 434 656 472 1.13 3.28 0.08 0.11 01578200

7.29 1.23 0.23 406 654 478 0.20 0.83 0.03 0.09 01578400

7.70 1.19 0.69 839 500 84.0 0.63 2.62 0.04 0.09 01578500

5.52 1.39 0.10 142 367 299 0.11 0.55 0.09 0.15 01578800

5.93 1.37 0.61 269 356 218 0.62 3.23 0.07 0.15 01579000

Tables 6 through 8  51
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

USGS 

station 

number

2-year

Recurrence interval

5-year

Recurrence interval

10-year

Recurrence interval

25-year

Recurrence interval

G R W G R W G R W G R W

01411456 70 194 76 113 321 130 143 423 175 182 571 243

01411500 504 1,180 509 820 1,930 837 1,100 2,540 1,130 1,540 3,440 1,610

01412500 109 198 110 237 332 240 356 441 360 548 605 552

01412800 424 721 434 868 1,190 892 1,260 1,570 1,300 1,880 2,140 1,920

01467043 290 321 296 475 490 480 608 749 656 786 1,030 882

01467045 2,830 3,490 2,940 4,010 5,000 4,260 4,850 6,310 5,280 5,970 8,510 6,850

01467081 550 306 541 768 504 751 936 665 911 1,180 904 1,140

01467086 2,420 1,900 2,330 3,400 2,750 3,220 4,010 3,910 3,980 4,760 5,230 4,920

01467087 6,290 3,590 5,940 8,370 4,950 7,680 9,660 6,820 9,020 11,200 8,940 10,600

01467089 6,750 4,090 6,090 8,510 5,620 7,530 9,580 7,800 8,930 10,800 10,200 10,500

01467130 150 141 150 244 228 243 317 298 315 422 400 419

01467150 779 438 769 1,230 715 1,200 1,610 939 1,560 2,200 1,270 2,100

01467160 225 327 228 330 434 335 414 572 426 538 782 562

01467180 469 417 465 677 688 679 825 908 839 1,020 1,240 1,070

01467305 180 67 177 221 111 215 248 147 240 281 199 273

01467317 210 42 204 259 70 247 294 92 276 342 125 316

01467330 424 659 431 732 1,080 753 1,020 1,420 1,060 1,510 1,940 1,570

01467351 284 190 279 424 305 411 518 398 500 637 535 617

01472157 2,440 1,730 2,350 4,430 3,130 4,170 6,120 4,740 5,810 8,730 6,660 8,150

01472174 669 528 636 1,330 906 1,190 1,870 1,360 1,670 2,660 1,870 2,300

01473169 2,040 1,700 1,970 2,620 2,570 2,620 3,050 3,270 3,120 3,650 4,550 3,970

01473470 5,410 3,010 4,960 9,470 4,550 8,100 12,700 4,390 9,310 17,400 5,960 11,900

01474000 3,690 4,380 3,760 5,770 6,440 5,870 7,580 7,290 7,520 10,400 9,900 10,300

01475000 211 256 211 291 422 294 353 558 360 444 759 459

01475019 398 549 406 530 907 561 612 1,200 677 711 1,640 844

01475300 709 572 687 1,240 922 1,160 1,670 1,270 1,560 2,330 1,770 2,140

01475510 2,920 2,360 2,840 4,070 3,450 3,940 4,830 5,170 4,910 5,800 7,070 6,150

01475530 769 887 790 1,400 1,340 1,380 1,970 1,950 1,970 2,900 2,620 2,790

01475550 2,520 2,990 2,570 3,540 4,180 3,660 4,230 5,950 4,570 5,080 7,800 5,740

01475850 1,140 1,130 1,140 1,890 1,910 1,900 2,500 2,450 2,480 3,380 3,430 3,400

01476000 1,000 1,910 1,130 1,550 2,980 1,860 1,930 3,110 2,220 2,430 4,000 2,890

01476435 588 958 674 761 1,590 1,010 865 2,020 1,250 985 2,750 1,660

01476480 1,320 1,710 1,350 2,400 2,820 2,450 3,390 3,510 3,410 5,020 4,900 5,000

01476500 1,060 1,750 1,120 1,690 2,850 1,850 2,240 3,600 2,480 3,120 5,020 3,630

01477000 2,990 2,990 2,990 5,320 4,590 5,250 7,420 5,800 7,220 10,900 7,840 10,400

52 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

50-year

Recurrence interval

100-year

Recurrence interval

200-year

Recurrence interval

500-year

Recurrence interval

USGS 

station 

number G R W G R W G R W G R W

211 694 298 240 827 355 270 973 415 309 1,190 497 01411456

1,960 4,200 2,050 2,460 5,050 2,580 3,050 5,980 3,210 4,020 7,370 4,220 01411500

724 745 725 929 901 926 1,170 1,080 1,160 1,540 1,340 1,510 01412500

2,430 2,630 2,470 3,060 3,170 3,080 3,780 3,780 3,780 4,870 4,700 4,830 01412800

922 1,260 1,060 1,060 1,500 1,250 1,200 1,770 1,450 1,400 2,160 1,730 01467043

6,850 10,400 8,140 7,770 12,400 9,510 8,730 14,700 11,000 10,100 18,100 13,000 01467045

1,380 1,110 1,340 1,600 1,330 1,560 1,850 1,580 1,810 2,220 1,960 2,170 01467081

5,290 6,320 5,670 5,800 7,500 6,440 6,300 8,790 7,220 6,950 10,700 8,280 01467086

12,300 10,700 11,800 13,400 12,500 13,100 14,400 14,600 14,400 15,700 17,500 16,200 01467087

11,700 12,100 11,900 12,500 14,300 13,300 13,400 16,400 14,700 14,400 19,800 16,700 01467089

508 487 505 603 583 600 706 688 703 856 843 854 01467130

2,730 1,560 2,580 3,350 1,880 3,140 4,080 2,230 3,790 5,220 2,760 4,810 01467150

645 958 682 765 1,160 816 901 1,380 968 1,110 1,710 1,200 01467160

1,180 1,520 1,260 1,340 1,840 1,470 1,510 2,200 1,690 1,740 2,730 2,020 01467180

306 242 299 331 289 326 356 341 354 391 417 394 01467305

379 152 348 419 181 384 460 214 423 520 261 479 01467317

1,990 2,390 2,050 2,590 2,890 2,640 3,340 3,450 3,360 4,620 4,300 4,550 01467330

725 652 709 813 782 806 901 925 907 1,020 1,140 1,050 01467351

11,000 8,340 10,200 13,700 10,300 12,600 16,700 12,400 15,300 21,400 15,700 19,600 01472157

3,320 2,310 2,820 4,030 2,780 3,390 4,800 3,300 4,020 5,900 4,070 4,950 01472174

4,150 5,660 4,710 4,680 6,900 5,520 5,260 8,290 6,400 6,110 10,400 7,670 01473169

21,400 7,300 14,100 25,800 8,780 16,700 30,500 10,400 19,700 37,500 12,900 24,300 01473470

13,100 12,100 12,800 16,200 14,600 15,800 20,000 17,300 19,200 26,000 21,400 24,600 01474000

521 931 544 607 1,120 639 703 1,330 745 848 1,650 904 01475000

782 2,020 979 851 2,440 1,120 918 2,920 1,270 1,000 3,640 1,470 01475019

2,910 2,190 2,640 3,560 2,660 3,200 4,300 3,170 3,840 5,420 3,930 4,820 01475300

6,510 8,710 7,160 7,230 10,500 8,210 7,950 12,500 9,300 8,920 15,600 10,800 01475510

3,770 3,160 3,500 4,800 3,750 4,310 6,040 4,390 5,250 8,040 5,300 6,700 01475530

5,720 9,300 6,640 6,350 10,900 7,560 6,990 12,600 8,480 7,840 15,200 9,710 01475550

4,120 4,280 4,180 4,950 5,230 5,060 5,860 6,290 6,030 7,210 7,900 7,480 01475850

2,810 4,690 3,410 3,190 5,400 3,920 3,580 6,130 4,430 4,100 7,130 5,110 01476000

1,070 3,350 1,980 1,150 4,010 2,300 1,220 4,720 2,610 1,320 5,750 3,010 01476435

6,570 6,100 6,460 8,440 7,460 8,190 10,700 8,980 10,300 14,400 11,300 13,600 01476480

3,930 6,240 4,610 4,890 7,660 5,740 6,040 9,150 7,030 7,900 11,500 9,060 01476500

14,100 9,560 13,200 17,900 11,500 16,600 22,600 13,500 20,700 30,200 16,600 27,300 01477000

Tables 6 through 8 53
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

USGS 

station 

number

2-year

Recurrence interval

5-year

Recurrence interval

10-year

Recurrence interval

25-year

Recurrence interval

G R W G R W G R W G R W

01477110 328 443 331 633 726 638 910 955 914 1,360 1,300 1,350

01477120 717 743 718 1,180 1,220 1,180 1,510 1,610 1,520 1,950 2,190 1,970

01477480 391 449 393 574 738 585 699 972 724 861 1,320 917

01477500 655 543 649 1,200 891 1,170 1,720 1,170 1,640 2,620 1,600 2,400

01477800 2,440 1,820 2,380 3,480 2,810 3,400 4,320 3,120 4,130 5,560 4,100 5,280

01478000 1,810 1,810 1,810 2,730 2,780 2,740 3,430 3,550 3,450 4,410 4,860 4,490

01478040 1,980 3,080 2,150 2,920 4,640 3,300 3,620 4,810 3,960 4,580 6,370 5,210

01478200 990 1,140 1,010 1,680 2,130 1,760 2,240 3,230 2,420 3,060 4,400 3,380

01478500 4,830 2,870 4,580 6,710 4,970 6,410 8,190 7,650 8,090 10,400 10,600 10,400

01478650 4,340 2,900 3,860 8,480 5,010 6,870 12,100 7,640 9,810 17,700 10,500 13,400

01479000 3,820 3,950 3,830 6,070 6,270 6,090 7,840 9,260 7,990 10,400 12,700 10,700

01479200 557 770 617 900 1,280 1,040 1,190 1,760 1,430 1,630 2,320 1,970

01479820 1,850 1,920 1,860 3,480 3,220 3,410 4,980 4,450 4,800 7,420 5,940 6,800

01479950 47 67 52 84 136 102 117 228 159 169 329 240

01480000 2,200 2,360 2,210 3,490 4,010 3,540 4,560 5,080 4,620 6,170 6,640 6,240

01480015 2,840 2,710 2,820 5,500 4,440 5,170 7,770 5,620 7,000 11,300 7,340 9,520

01480100 963 984 967 1,760 1,460 1,670 2,490 2,120 2,360 3,730 2,830 3,330

01480300 1,220 1,310 1,230 2,160 2,380 2,190 2,930 3,570 3,040 4,080 4,930 4,260

01480500 1,940 2,220 1,960 3,530 3,900 3,580 4,900 4,900 4,900 7,030 6,730 6,970

01480610 342 327 340 601 565 594 805 815 807 1,100 1,150 1,110

01480617 2,620 2,660 2,620 4,600 4,370 4,560 6,150 5,600 6,040 8,360 7,690 8,180

01480675 243 485 260 409 914 461 538 844 584 722 1,020 781

01480680 659 903 714 851 1,620 1,070 978 1,550 1,180 1,140 1,880 1,450

01480700 2,400 2,210 2,380 3,860 3,790 3,850 4,890 4,230 4,780 6,240 5,380 6,060

01480800 3,680 2,950 3,480 4,800 4,860 4,820 5,640 5,670 5,650 6,800 7,300 7,040

01480870 3,490 3,180 3,460 5,060 5,120 5,070 6,070 6,050 6,070 7,320 7,850 7,410

01481000 6,980 7,700 7,010 11,000 12,300 11,100 14,100 16,100 14,300 18,500 21,500 18,800

01481200 110 112 110 227 223 226 336 372 352 516 537 527

01481450 247 342 270 371 565 432 466 480 472 600 619 609

01481500 7,810 8,260 7,840 12,400 13,100 12,500 16,100 17,000 16,200 21,300 22,700 21,500

01482310 130 122 129 209 205 208 274 274 274 369 376 371

01482500 667 513 664 1,370 846 1,350 2,050 1,120 2,000 3,220 1,520 3,080

01483000 519 506 519 948 826 938 1,300 1,080 1,280 1,830 1,470 1,770

01483200 147 195 148 268 324 270 371 429 373 529 584 533

01483290 138 73 132 220 121 204 290 160 261 402 217 347

54 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

50-year

Recurrence interval

100-year

Recurrence interval

200-year

Recurrence interval

500-year

Recurrence interval

USGS 

station 

number G R W G R W G R W G R W

1,780 1,590 1,750 2,280 1,920 2,220 2,870 2,290 2,760 3,820 2,840 3,620 01477110

2,280 2,690 2,320 2,620 3,260 2,680 2,960 3,900 3,060 3,420 4,850 3,580 01477120

983 1,620 1,070 1,110 1,960 1,240 1,230 2,340 1,410 1,400 2,900 1,640 01477480

3,490 1,960 3,100 4,590 2,370 3,950 5,960 2,820 4,970 8,300 3,500 6,650 01477500

6,650 4,900 6,270 7,880 5,740 7,390 9,280 6,650 8,670 11,400 7,950 10,600 01477800

5,220 5,970 5,360 6,080 7,200 6,300 7,020 8,560 7,320 8,380 10,600 8,800 01478000

5,370 7,640 6,220 6,200 9,010 7,290 7,100 10,500 8,430 8,400 12,600 10,000 01478040

3,750 5,400 4,180 4,520 6,500 5,060 5,380 7,710 6,020 6,650 9,510 7,440 01478200

12,200 13,100 12,400 14,300 16,000 14,700 16,600 19,300 17,200 20,100 24,300 21,100 01478500

22,800 13,000 16,700 28,500 15,900 20,400 35,100 19,000 24,600 45,200 24,000 31,300 01478650

12,600 15,800 13,000 15,000 19,200 15,600 17,600 23,100 18,500 21,600 28,900 22,700 01479000

2,020 2,760 2,420 2,480 3,240 2,900 3,010 3,730 3,420 3,830 4,440 4,180 01479200

9,710 7,180 8,540 12,500 8,520 10,500 15,700 9,980 12,800 21,100 12,100 16,400 01479820

217 415 311 273 512 390 339 618 478 443 778 612 01479950

7,600 7,890 7,640 9,220 9,220 9,220 11,100 10,600 11,000 14,000 12,600 13,700 01480000

14,300 8,720 11,600 17,800 10,200 14,000 21,700 11,800 16,600 27,700 14,000 20,500 01480015

4,910 3,400 4,190 6,370 4,040 5,240 8,160 4,700 6,340 11,100 5,660 8,180 01480100

5,070 6,090 5,310 6,180 7,390 6,480 7,410 8,840 7,770 9,260 11,000 9,710 01480300

8,940 8,300 8,780 11,100 10,000 10,900 13,700 12,000 13,200 17,600 14,900 16,900 01480500

1,340 1,430 1,370 1,610 1,740 1,650 1,900 2,090 1,950 2,310 2,610 2,400 01480610

10,200 9,470 9,990 12,100 11,500 11,900 14,200 13,700 14,100 17,200 17,100 17,200 01480617

873 1,130 932 1,040 1,240 1,090 1,210 1,330 1,240 1,470 1,440 1,460 01480675

1,260 2,110 1,640 1,380 2,330 1,820 1,500 2,510 1,980 1,660 2,750 2,170 01480680

7,260 6,260 7,030 8,310 7,150 8,030 9,370 8,060 9,040 10,800 9,280 10,400 01480700

7,760 8,580 8,170 8,780 9,990 9,400 9,890 11,300 10,600 11,500 13,300 12,500 01480800

8,220 9,280 8,410 9,090 10,800 9,410 9,950 12,400 10,400 11,100 14,600 11,700 01480870

22,100 26,100 22,600 26,100 31,400 26,800 30,500 36,800 31,300 36,900 45,500 38,000 01481000

683 679 681 883 839 858 1,120 1,020 1,060 1,500 1,290 1,370 01481200

711 724 717 831 829 830 962 936 947 1,150 1,080 1,110 01481450

25,700 27,500 26,000 30,400 32,900 30,900 35,700 38,800 36,300 43,500 47,600 44,200 01481500

451 463 455 542 560 548 645 670 653 800 833 812 01482310

4,360 1,870 4,110 5,770 2,260 5,370 7,510 2,700 6,900 10,400 3,360 9,430 01482500

2,290 1,800 2,190 2,800 2,170 2,660 3,370 2,580 3,180 4,210 3,200 3,960 01483000

670 715 674 831 862 834 1,020 1,020 1,020 1,300 1,260 1,300 01483200

504 265 423 625 318 510 769 376 611 1,000 460 771 01483290

Tables 6 through 8 55
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

USGS 

station 

number

2-year

Recurrence interval

5-year

Recurrence interval

10-year

Recurrence interval

25-year

Recurrence interval

G R W G R W G R W G R W

01483400 24 44 25 32 74 36 38 97 45 46 132 58

01483500 217 317 219 415 526 420 606 695 612 937 946 938

01483700 517 680 520 856 1,130 866 1,100 1,500 1,120 1,420 2,040 1,460

01483720 145 118 143 270 198 259 375 262 351 533 356 482

01484000 307 171 302 575 280 555 790 367 749 1,100 491 1,020

01484002 19 25 19 32 40 33 44 52 46 66 70 67

01484050 63 61 63 112 99 110 157 129 152 233 172 217

01484100 51 50 51 81 82 81 103 107 103 133 143 134

01484270 36 106 38 55 173 60 69 226 79 91 302 111

01484300 36 110 37 56 180 60 72 236 81 97 315 114

01484500 120 84 119 160 137 160 190 180 189 231 241 231

01484525 562 482 555 970 786 939 1,300 1,030 1,240 1,800 1,380 1,670

01484550 269 192 265 402 321 394 495 423 485 616 574 608

01485000 832 676 829 1,130 1,130 1,130 1,360 1,490 1,370 1,700 2,010 1,720

01485500 827 434 818 1,180 719 1,160 1,430 946 1,400 1,770 1,270 1,730

01486000 142 113 142 246 189 243 326 251 321 438 339 431

01486100 97 128 99 144 213 152 178 281 194 222 380 255

01486980 39 107 42 60 177 69 74 234 93 93 314 127

01487000 1,000 673 995 1,440 1,110 1,430 1,780 1,460 1,770 2,290 1,970 2,270

01487500 208 162 206 332 266 327 425 348 417 554 465 541

01488000 9 40 10 25 66 27 42 86 46 74 114 79

01488500 2,160 597 2,120 2,830 992 2,740 3,260 1,310 3,130 3,780 1,770 3,600

01489000 471 239 465 724 397 708 930 524 901 1,240 714 1,190

01490000 232 302 233 376 502 381 488 664 499 651 899 672

01490600 221 172 217 315 286 311 394 377 390 512 509 511

01490800 177 127 173 278 212 268 352 280 337 452 380 432

01491000 1,850 1,200 1,840 3,310 1,980 3,250 4,450 2,620 4,340 6,070 3,540 5,860

01491010 63 48 61 130 79 121 204 104 180 354 139 281

01491050 63 89 65 105 148 110 144 195 153 212 263 224

01492000 266 181 263 504 303 492 728 402 698 1,110 546 1,030

01492050 88 275 96 143 456 167 190 604 236 262 820 349

01492500 222 330 225 462 556 466 690 740 694 1,080 1,010 1,070

01492550 113 150 115 184 251 192 250 332 263 361 451 381

01493000 622 466 619 879 776 876 1,080 1,030 1,080 1,390 1,400 1,390

01493500 377 441 378 856 740 852 1,390 985 1,370 2,420 1,350 2,330

56 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is estimated 

from the regression equation, and W is the weighted estimate]

50-year

Recurrence interval

100-year

Recurrence interval

200-year

Recurrence interval

500-year

Recurrence interval

USGS 

station 

number G R W G R W G R W G R W

51 162 69 57 194 80 63 229 92 70 281 109 01483400

1,260 1,160 1,250 1,680 1,400 1,640 2,190 1,660 2,110 3,080 2,050 2,890 01483500

1,660 2,500 1,730 1,910 3,010 2,010 2,160 3,580 2,300 2,510 4,420 2,700 01483700

670 435 591 822 521 712 993 616 846 1,250 756 1,050 01483720

1,360 594 1,240 1,640 706 1,470 1,940 826 1,720 2,380 1,000 2,090 01484000

87 84 86 114 99 109 147 115 137 205 138 181 01484002

306 208 275 395 246 343 504 287 421 687 347 546 01484050

157 172 158 182 203 184 208 236 211 245 283 249 01484100

109 364 137 128 433 165 151 506 198 184 609 245 01484270

119 381 143 144 452 176 172 529 214 217 639 270 01484300

264 290 266 299 343 303 338 401 343 393 483 400 01484500

2,230 1,670 2,030 2,700 1,990 2,420 3,240 2,330 2,860 4,040 2,840 3,510 01484525

708 696 705 802 833 809 898 981 918 1,030 1,190 1,070 01484550

1,980 2,450 2,020 2,300 2,930 2,350 2,650 3,460 2,730 3,180 4,240 3,280 01485000

2,040 1,550 2,000 2,330 1,840 2,280 2,640 2,160 2,580 3,070 2,630 3,020 01485500

530 411 519 629 488 614 734 572 716 885 694 863 01486000

257 462 306 292 550 359 329 647 415 380 787 494 01486100

108 379 156 123 449 187 139 524 218 160 632 261 01486980

2,720 2,400 2,690 3,200 2,860 3,170 3,740 3,370 3,700 4,550 4,110 4,500 01487000

659 561 643 772 664 752 892 774 869 1,060 933 1,040 01487500

106 137 111 147 161 149 197 186 195 283 222 269 01488000

4,160 2,160 3,960 4,540 2,590 4,320 4,900 3,050 4,690 5,390 3,740 5,190 01488500

1,510 870 1,440 1,820 1,050 1,720 2,170 1,240 2,040 2,710 1,520 2,530 01489000

787 1,100 818 936 1,310 979 1,100 1,540 1,160 1,340 1,890 1,410 01490000

618 618 618 739 735 738 880 863 874 1,100 1,050 1,080 01490600

531 462 510 614 552 593 701 650 683 823 793 812 01490800

7,400 4,330 7,090 8,830 5,200 8,420 10,400 6,150 9,850 12,600 7,570 11,900 01491000

523 167 380 761 198 503 1,100 231 660 1,760 277 936 01491010

277 319 289 359 379 366 462 444 456 640 538 602 01491050

1,480 666 1,340 1,930 797 1,720 2,490 941 2,170 3,420 1,150 2,910 01492000

327 1,000 452 403 1,210 569 491 1,430 702 630 1,760 904 01492050

1,440 1,240 1,420 1,890 1,500 1,830 2,430 1,780 2,320 3,320 2,200 3,120 01492500

467 550 489 598 658 616 761 776 765 1,040 949 1,000 01492550

1,650 1,710 1,660 1,940 2,060 1,960 2,280 2,440 2,290 2,790 3,010 2,810 01493000

3,560 1,650 3,340 5,110 2,000 4,690 7,220 2,380 6,460 11,200 2,940 9,700 01493500

Tables 6 through 8 57
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is estimated 

from the regression equation, and W is the weighted estimate]

USGS 

station 

number

2-year

Recurrence interval

5-year

Recurrence interval

10-year

Recurrence interval

25-year

Recurrence interval

G R W G R W G R W G R W

01494000 477 377 470 839 631 813 1,150 838 1,100 1,650 1,140 1,520

01495000 2,940 2,500 2,910 4,970 4,500 4,930 6,610 6,650 6,620 9,030 9,060 9,040

01495500 1,780 1,660 1,750 2,600 3,020 2,760 3,240 4,270 3,660 4,170 5,860 4,970

01496000 1,540 1,710 1,560 2,530 3,140 2,620 3,380 4,150 3,510 4,710 5,580 4,900

01496080 290 198 262 496 353 440 653 359 505 869 516 671

01496200 1,090 934 1,070 2,140 1,860 2,080 3,080 2,510 2,930 4,580 3,400 4,170

01578200 455 612 471 874 1,150 917 1,260 1,790 1,360 1,920 2,470 2,050

01578400 636 610 631 1,300 1,220 1,280 1,980 1,920 1,960 3,230 2,660 3,000

01578500 4,560 6,480 4,660 9,540 11,600 9,720 14,200 15,300 14,400 22,000 20,300 21,800

01578800 447 262 381 707 551 636 890 681 789 1,130 879 991

01579000 598 549 590 1,040 1,070 1,050 1,400 1,490 1,420 1,900 2,000 1,950

58 Magnitude and Frequency of Floods on Nontidal Streams in Delaware
Table 8. Flood-frequency statistics for stations in and near Delaware that were considered for use in the regression analyses.—

Continued

[USGS, U.S. Geological Survey; discharges are in cubic feet per second; G is estimated from the systematic record at the streamgaging station, R is 

estimated from the regression equation, and W is the weighted estimate]

50-year

Recurrence interval

100-year

Recurrence interval

200-year

Recurrence interval

500-year

Recurrence interval

USGS 

station 

number G R W G R W G R W G R W

2,110 1,400 1,900 2,640 1,680 2,330 3,270 2,000 2,820 4,260 2,460 3,590 01494000

11,100 11,100 11,100 13,400 13,400 13,400 16,000 15,900 16,000 19,800 19,700 19,800 01495000

4,960 7,210 6,080 5,830 8,720 7,310 6,810 10,400 8,660 8,290 12,900 10,600 01495500

5,910 6,780 6,120 7,310 8,090 7,520 8,960 9,520 9,110 11,600 11,600 11,600 01496000

1,040 651 815 1,230 801 975 1,420 967 1,150 1,690 1,210 1,410 01496080

5,940 4,140 5,250 7,520 4,950 6,480 9,350 5,840 7,900 12,200 7,140 10,100 01496200

2,540 3,040 2,670 3,290 3,680 3,400 4,210 4,380 4,260 5,730 5,430 5,640 01578200

4,520 3,300 3,960 6,220 4,000 5,130 8,410 4,790 6,560 12,300 5,960 8,960 01578400

29,400 24,400 28,500 38,200 28,900 36,400 48,800 33,800 45,800 65,900 41,100 60,600 01578500

1,310 1,030 1,150 1,500 1,180 1,310 1,680 1,330 1,470 1,940 1,540 1,700 01578800

2,320 2,420 2,380 2,780 2,890 2,840 3,270 3,370 3,330 3,990 4,080 4,040 01579000

Tables 6 through 8 59