U.S. Department of the Interior U.S. Geological Survey Scientific Investigations Report 2008-5102 In cooperation with the Federal Emergency Management Agency, the Pennsylvania State Association of Township Supervisors, and the Susquehanna River Basin Commission Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania
67
Embed
Regression Equations for Estimating Flood Flows at ... · 2 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania for ungaged streams in Pennsylvania.
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
U.S. Department of the InteriorU.S. Geological Survey
Scientific Investigations Report 2008-5102
In cooperation with the Federal Emergency Management Agency, the Pennsylvania State
Association of Township Supervisors, and the Susquehanna River Basin Commission
Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania
Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania
By Mark A. Roland and Marla H. Stuckey
In cooperation with the Federal Emergency Management Agency, the Pennsylvania State Association of Township Supervisors, and the Susquehanna River Basin Commission
Scientific Investigations Report 2008–5102
U.S. Department of the InteriorU.S. Geological Survey
U.S. Department of the InteriorDIRK KEMPTHORNE, Secretary
U.S. Geological SurveyMark D. Myers, Director
U.S. Geological Survey, Reston, Virginia: 2008
For product and ordering information: World Wide Web: http://www.usgs.gov/pubprod Telephone: 1-888-ASK-USGS
For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment: World Wide Web: http://www.usgs.gov Telephone: 1-888-ASK-USGS
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 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:Roland, M.A., and Stuckey, M.H., 2008, Regression equations for estimating flood flows at selected recurrence inter-vals for ungaged streams in Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2008-5102, 57 p.
Purpose and Scope ..............................................................................................................................1Previous Studies ...................................................................................................................................2
Development of Regression Equations ......................................................................................................2Selection of Streamflow-Gaging Stations ........................................................................................2Basin Characteristics ...........................................................................................................................4Regression Analysis .............................................................................................................................4
Flood-Flow Regression Equations ...............................................................................................................4Limitations of Regression Equations ........................................................................................................15Summary........................................................................................................................................................15Acknowledgments .......................................................................................................................................16References Cited..........................................................................................................................................16Appendix 1. Streamflow-gaging stations and basin characteristics used in development of
flood-flow regression equations for Pennsylvania streams ...................................................20Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from
observed streamflow-gaging data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis .................................30
Appendix 3. Flood-flow magnitudes for selected recurrence intervals for streamflow-gaging stations in Pennsylvania with drainage areas less than 2,000 square miles and streamflow substantially affected by upstream regulation .....................55
Figures 1-6. Maps showing
1. Streamflow-gaging stations used in development of flood-flow regression equations for Pennsylvania streams ..................................................................................3
2. Flood-flow regions and hydrologic unit code boundaries in Pennsylvania ..................7 3. Flood-flow region 1 in Pennsylvania ....................................................................................8 4. Flood-flow region 2 in Pennsylvania ....................................................................................9 5. Flood-flow region 3 in Pennsylvania ..................................................................................11 6. Flood-flow region 4 in Pennsylvania ..................................................................................12
iv
Tables 1. Basin characteristics selected for use in the development of regression equations
for flood-flow estimates ...............................................................................................................5 2. Number of streamflow-gaging stations and area in flood-flow regions in
Pennsylvania and surrounding states .....................................................................................10 3. Regression coefficients for use with flood-flow regression equations for
Pennsylvania streams ................................................................................................................13 4. Equivalent period of record for regression equations developed for estimating flood
magnitudes for selected recurrence intervals in Pennsylvania .........................................14 5. Summary of the variables used to develop the flood-flow regression equations for
inch (in.) 2.54 centimeter (cm)inch (in.) 25.4 millimeter (mm)foot (ft) 0.3048 meter (m)mile (mi) 1.609 kilometer (km)
Areasquare mile (mi2) 2.590 square kilometer (km2)
Flow ratecubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)inch per hour (in/h) 0.0254 meter per hour (m/h)
Hydraulic gradientfoot per mile (ft/mi) 0.1894 meter per kilometer (m/km)
Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88).
Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).
Altitude, as used in this report, refers to distance above the vertical datum.
vi
AbstractRegression equations were developed for estimat-
ing flood flows at selected recurrence intervals for ungaged streams in Pennsylvania with drainage areas less than 2,000 square miles. These equations were developed utilizing peak-flow data from 322 streamflow-gaging stations within Pennsylvania and surrounding states. All stations used in the development of the equations had 10 or more years of record and included active and discontinued continuous-record as well as crest-stage partial-record stations. The state was divided into four regions, and regional regression equations were developed to estimate the 2-, 5-, 10-, 50-, 100-, and 500-year recurrence-interval flood flows. The equations were developed by means of a regression analysis that utilized basin characteristics and flow data associated with the stations.
Significant explanatory variables at the 95-percent con-fidence level for one or more regression equations included the following basin characteristics: drainage area; mean basin elevation; and the percentages of carbonate bedrock, urban area, and storage within a basin. The regression equations can be used to predict the magnitude of flood flows for specified recurrence intervals for most streams in the state; however, they are not valid for streams with drainage areas generally greater than 2,000 square miles or with substantial regulation, diversion, or mining activity within the basin. Estimates of flood-flow magnitude and frequency for streamflow-gaging stations substantially affected by upstream regulation are also presented.
IntroductionInformation on the frequency and magnitude of floods is
essential for Flood Insurance Studies (FIS), flood-plain man-agement, and the design of bridges and flood-control struc-tures. Accurate and accessible methods that produce flood-flow statistics are important to engineers and planners working on such projects. Flood-flow statistics commonly used in flood-related projects include the magnitude of flood flows
occurring, on average, once in 2, 5, 10, 50, 100, and 500 years (Q2, Q5, Q10, Q50, Q100, and Q500, respectively). These flood flows are estimates based on statistical probabilities or frequencies, and the recurrence intervals associated with each flood flow refer to the average number of years between the floods (Dinicola, 1996). For example, the Q100 has a 1 in 100 chance (or 0.01 probability or frequency) that a flood of this magnitude will occur in any given year.
Regression equations for computing the magnitude and frequency of peak flows were last developed for Pennsylvania by the U.S. Geological Survey (USGS) by use of peak-flow data collected through 1997 (Stuckey and Reed, 2000). Flood-ing experienced in the northern and eastern parts of Penn-sylvania subsequent to 1997 prompted an analysis of flood-magnitude and flood-frequency data through the 2006 water year1 for streamflow-gaging stations with at least 25 years of record in the Delaware and Susquehanna River Basins in Pennsylvania (Roland and Stuckey, 2007). The results of that study, other recent flooding across the state, and advances in geospatially derived basin characteristics warranted updating the flood-flow regression equations for Pennsylvania.
The USGS, in cooperation with the Federal Emergency Management Agency (FEMA), the Pennsylvania State Asso-ciation of Township Supervisors (PSATS), and the Susque-hanna River Basin Commission (SRBC), developed updated flood-flow regression equations for use on ungaged streams in Pennsylvania. Regression equations were developed to esti-mate the Q2, Q5, Q10, Q50, Q100, and Q500 flood flows for streams without substantial regulation, diversion, or mining activity in the basin. This report discusses the methodology used and presents the results of the regression analysis.
Purpose and Scope
This report presents regression equations that describe the statistical relation between expected flood magnitudes and basin characteristics for selected recurrence intervals
1Water year is defined as a 12-month period beginning October 1 and end-ing September 30. The water year is designated by the calendar year in which it ends.
Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania
By Mark A. Roland and Marla H. Stuckey
2 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
for ungaged streams in Pennsylvania. Flood-flow regression equations were developed by use of peak-flow data from 277 continuous-record2 and 45 crest-stage partial-record3 stream-flow-gaging stations in Pennsylvania and surrounding states—New York, Ohio, Maryland, and West Virginia—with 10 or more years of record generally through the 2005 water year. Peak-flow data were used through the 2006 water year for 39 stations in the Delaware and North Branch Susquehanna River Basins that experienced severe flooding in June 2006. Flood-flow data are also presented for the Q2, Q5, Q10, Q50, Q100, and Q500 along with basin characteristics computed from the station data.
Previous Studies
Regression equations used to predict flood frequency-magnitude relations for ungaged streams in Pennsylvania were first published by Flippo in 1977 and were updated by Flippo in 1982. The equations published in 1982 were evaluated by Ehlke and Reed (1999) on the basis of a comparison between flood flows calculated from the regression equations and peak-flow data collected through the 1996 water year. Regression equations for estimating magnitude of flood flows in Penn-sylvania for selected recurrence intervals were last published in 2000 using data through the 1997 water year (Stuckey and Reed, 2000).
Development of Regression EquationsFlood flows for selected recurrence intervals were com-
puted using peak streamflow data from gaging stations with flow relatively unaffected by regulation, diversion, or mining. Methods used are described in Water Resource Council Bul-letin 17B (Water Resources Council, Hydrology Committee, 1981). These flood flows will be referred to as “observed” in this report. The terms ‘peak flows’ and ‘flood flows’ may be used interchangeably in common parlance; however, within this report, an attempt is made to maintain consistency with regard to usage. The use of ‘peak flows’ is associated with flows that are more or less measured at a streamflow-gaging station and are associated with a period of observation (year). The term ‘flood flow’ is reserved for a more extreme event typically not measured directly and that is associated with a recurrence interval.
Basin characteristics known to affect streamflow, such as land cover, were determined for the drainage basins upstream from the gaging stations. The observed flood flows (dependent
2Continuous-record station is a site where stage or streamflow is recorded at some interval on a continuous basis. The recording interval is usually 15 minutes but may be less or more frequent.
3Partial-record station is a site where discrete measurements of one or more hydrologic parameters are obtained over a period of time without continuous data being recorded or computed. A common example is a crest-stage gage partial-record station at which only peak stages and flows are recorded.
variable) were related to the basin characteristics (independent or explanatory variables) using regression techniques to obtain regression equations. These equations can be used to compute flood flows for selected recurrence intervals for streams where no gaging-station data are available. The flood flows com-puted from regression equations will be referred to as “pre-dicted” in this report.
Selection of Streamflow-Gaging Stations
Peak-flow data generally through the 2005 water year from 306 stations on streams in Pennsylvania, along with peak-flow data from stations in surrounding states, including 6 stations in New York, 5 in Ohio, 3 in Maryland, and 2 in West Virginia, with flow relatively unaffected by regulation, diversions, and mining were used in the development of the regression equations (fig. 1). In addition, peak-flow data for water year 2006 were used for 39 stations in the Delaware and North Branch Susquehanna River Basins that experienced severe flooding due to heavy rains occurring June 23, 2006, through June 29, 2006.
Stations included in the analysis had 10 or more years of record and drainage areas less than 2,000 mi2. The stations were selected on the basis of information about regulation, diversions, and mining published in the USGS Pennsylvania Water Resources Data Reports, Surface-Water-Supply Reports, and other scientific reports. In the event of regulation, diver-sion, or mining occurring within a basin during the period of record, only the period of record prior to the event was used in the analysis. For stations that had a gap in the operational his-tory, the total number of years the station was in actual opera-tion was used to determine the period of record. A list of the stations used in the development of the regression equations is provided in appendix 1.
Peak flows may be recorded outside of the streamflow-gaging station operational period (also referred to as the systematic period of record) to document major flood events. These peaks are termed “historical peaks” and may be used to supplement the period of record at a station. If historical peaks are used in the analysis, the period of record at the sta-tion is adjusted to include the total number of years from the historical peak to the operational period of record, which may include a period when the station was not in operation (Water Resources Council, Hydrology Committee, 1981). This situ-ation affected a small number of stations used in the analysis and typically added few years to the period of record. Because of the inherent uncertainty associated with historical peaks, not all historical peaks were included in the analysis. Typi-cally, historical peaks were included in the analysis if the peak was not the maximum peak of record for the station or if the peak was recorded less than 5 years outside the period during which the station operated. Other factors such as knowledge about a particular event or previous USGS publications were considered as part of the decision to include a historical peak. For example, station 01539000, Fishing Creek near Blooms-
Development of Regression Equations 3
Figu
re 1
. St
ream
flow
-gag
ing
stat
ions
use
d in
dev
elop
men
t of f
lood
-flow
regr
essi
on e
quat
ions
for P
enns
ylva
nia
stre
ams.
PEN
NSY
LVA
NIA
NE
W Y
OR
K
OH
IO
MA
RY
LA
ND
WE
ST V
IRG
INIA
NE
W J
ER
SEY
DE
LA
WA
RE
VIR
GIN
IAV
IRG
INIA
Base
from
U.S
. Geo
logi
cal S
urve
y 1:
2,00
0,00
0 an
d 1:
100,
000
Digi
tal D
ata
Stat
e bo
unda
ry fr
om U
.S. G
eolo
gica
l Sur
vey,
200
5Ri
vers
from
U.S
. Geo
logi
cal S
urve
y, 2
006
Albe
rs E
qual
-Are
a Co
nic
proj
ectio
n: S
tand
ard
Para
llels
29°
30’N
and
45°
30’N
.Ce
ntra
l Mer
idia
n 77
°45’
W, L
atitu
de o
f Orig
in 2
3°00
’N
010
2030
4050
MIL
ES
010
2030
4050
KILO
MET
ERS
75°
76°
77°
78°
79°
80°
81°
42°
41°
40°
STAT
E BO
UNDA
RYCO
UNTY
BOU
NDA
RYRI
VER
CON
TIN
UOUS
-REC
ORD
STRE
AMFL
OW-G
AGIN
G ST
ATIO
NCR
EST-
STAG
E PA
RTIA
L-RE
CORD
STR
EAM
FLOW
-GAG
ING
STAT
ION
EXPL
ANAT
ION
LA
KE
ER
IE
Nor
th B
ranch Su
sque
ha
nna River
Nor
th B
ranch Su
sque
ha
nna River
4 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
burg, Pa., began continuous operation in 1939, but a historical peak was recorded in 1936. Subsequently, the period of record used in the analysis included the period between 1936 and 1939, when the station was not in operation.
Basin Characteristics
A set of 24 climatologic, geologic, hydrologic, and physiographic basin characteristics with possible effects on peak flow was compiled from various geographic information system (GIS) sources. The use of GIS-derived basin charac-teristics in the development of regression equations improved consistency, reproducibility, and ease of use. The basin char-acteristics evaluated in the exploratory regression analysis are presented in table 1.
Regression Analysis
The observed flood-flow frequency statistics were computed for the 306 Pennsylvania stations and were related to the basin characteristics using exploratory Ordinary Least Squares (OLS) and Weighted Least Squares (WLS) regression techniques. The flood flows calculated for each streamflow-gaging station for specified recurrence intervals were weighted for comparison purposes to OLS on the basis of the period of record, [(number of years of record at station * number of sta-tions)/sum of years of record of all stations], and incorporated into the WLS analysis (Helsel and Hirsch, 1992). Regression iterations were performed using a statistical software pack-age, S-PLUS (MathSoft, Inc., 1997), to reduce the number of explanatory variables to those significant at the 95-percent confidence level. Flood-flow and basin-characteristic data for the 16 out-of-state stations were obtained from previously published USGS reports (Dillow, 1996; Lumia and others, 2006; Koltun, 2003; Wiley and others, 2000). Because limited data were available for these sites, they were excluded from the exploratory regression-analysis techniques. Each set of regression equations was constrained to contain the same explanatory variables in an attempt to maintain a monotonic relation between frequency and magnitude for all possible sites, whether the same explanatory variables were significant at all recurrence intervals. Diagnostics used to further evalu-ate the adequacy of the regression models included graphical relations, multicollinearity, standard error, and coefficient of determination (R2) (Helsel and Hirsch, 1992).
The observed flood flows computed according to the guidelines in Bulletin 17B (Water Resources Council, Hydrology Committee, 1981) and the significant explanatory variables found using OLS and WLS were then related using a Generalized Least Squares (GLS) regression analysis to obtain the final regression equation. GLS is considered to be a more accurate regression technique for hydrologic regressions, particularly when using differing record lengths (Tasker and Stedinger, 1989). In addition to differing record lengths, the technique also takes into account variance of flows and cross-
correlation among the stations used in the analysis (Tasker and Stedinger, 1989). This regression technique was incorporated into a USGS software package, GLSNET (Tasker and Sted-inger, 1989), and was used in this analysis.
Flood-Flow Regression EquationsData from 322 stations within Pennsylvania and from sur-
rounding states were used to develop the Q2, Q5, Q10, Q50, Q100, and Q500 flood-flow regression equations. Exploratory regression analysis using OLS and WLS indicated the need for the state to be regionalized. A comparative analysis was done between the updated statewide regression residual values, standard errors, and R2 and those published by Stuckey and Reed (2000) for the previously developed flood-flow regions. Exploratory regressions using these previously defined flood-flow regions in association with the updated peak-flow data did not produce diagnostic statistics indicative of a significant improvement over those resulting from the statewide regres-sion developed using OLS and WLS for the updated Q100 flood flow. Therefore, statewide regression residuals and basin flood-flow yields at the 100-year recurrence interval were used to create four flood-flow regions for the state (fig. 2). The basin flood-flow yields were computed for each station, in cubic feet per second per square mile, by dividing the Q100 flood flow by the respective drainage area. The regionalization process consisted of generating plots of the Q100 regression residual values and basin flood-flow yields for each of the 322 stations included in the study area. These plots were evaluated and regionalized on the basis of similar values. Physiographic provinces and precipitation maps were also used in the delin-eation of the four flood-flow regions. Hydrologic unit code (HUC8) boundaries were followed wherever possible while delineating the flood-flow regions to avoid dividing water-sheds into multiple regions. The Schuylkill River Basin (HUC 02040203) was divided on the basis of differing basin and geologic characteristics.
The North Branch Susquehanna River Basin, parts of the West Branch Susquehanna River Basin, and most of the northern Delaware River Basin are within flood-flow region 1 (fig. 3). The southern part of the Delaware River Basin, including Philadelphia and surrounding areas, and the lower part of the Susquehanna River Basin are within flood-flow region 2 (fig. 4). The Schuylkill River Basin, within the Delaware River Basin, was split between regions 1 and 2; the upper part of the basin is in region 1 and the lower part, down to the mouth, is in region 2. This split was based on statewide regression diagnostics and differing hydrologic characteris-tics between the two parts of the basin. Flood-flow region 3 extends from south-central Pennsylvania northwest to the state borders of New York, Ohio, and West Virginia, encompass-ing parts of the Susquehanna, Ohio, and St. Lawrence River Basins (fig. 5). The Potomac and parts of the Ohio River Basin in the southwestern part of Pennsylvania are within flood-flow
Flood-Flow Regression Equations 5
Table 1. Basin characteristics selected for use in the development of regression equations for flood-flow estimates.—Continued
Basin characteristic Source Reference
Dependent Variables
Estimates of flood flows for the 2-, 5-, 10-, 50-, 100-, and 500-year recurrence inter-vals (expressed in cubic feet per second)
Derived by application of PeakFQ computer program that performs statistical flood-frequency analyses of peak flows recorded at U.S. Geological Survey streamflow-gaging stations following procedures recommended in Water Resources Council Bulletin 17B
streamflow data: U.S. Geological Survey (http://waterdata.usgs.gov/pa/nwis/)
PeakFQ computer program: Flynn and others (2006)
Independent Variables
Basin slope (degrees) Digital Elevation Model (DEM) U.S. Geological Survey (2000a)Mean basin elevation (feet) Digital Elevation Model (DEM) U.S. Geological Survey (2000a)
Forested (percent of basin area) National Land Cover Dataset (NLCD); and enhanced ver-sion (NLCDe)
Homer and others (2004); Price and others (2003)
Glaciated (percent of basin area) From modified geology maps
Pennsylvania Dept. of Con-servation and Natural Re-sources (1997); Environmental Resources Research Institute (1996)
Lakes and open water (percent of basin area)
National Land Cover Dataset (NLCD); and enhanced ver-sion (NLCDe); digitized from USGS quadrangle maps 1:24000 scale
Homer and others (2004); Price and others (2003)
Longest drainage path (mile) National Hydrography Dataset (NHD), 1:24000 scale U.S. Geological Survey (2000b)Stream density (length, in miles, per basin
area, in square miles) National Hydrography Dataset (NHD), 1:24000 scale U.S. Geological Survey (2000b)
Channel slope (feet per mile) Digital Elevation Model (DEM) U.S. Geological Survey (2000a)Soil infiltration index (unitless, 1=well to
4=poor) State Soil Geographic (STATSGO) database U.S. Department of Agriculture (1994)
Mean annual precipitation, 1971-2000 (inches)
Parameter-elevation Regressions on Independent Slopes Model (PRISM) Daly (1996)
Drainage area (square miles) Digital Elevation Model (DEM) U.S. Geological Survey (2000a)
Soil thickness, depth to bedrock (feet) State Soil Geographic (STATSGO) database U.S. Department of Agriculture (1994)
Drainage run-off curve (unitless, 1=well to 7=poor) State Soil Geographic (STATSGO) database U.S. Department of Agriculture
(1994)
Soil available water content (percent) State Soil Geographic (STATSGO) database U.S. Department of Agriculture (1994)
Soil permeability (inches per hour) State Soil Geographic (STATSGO) database U.S. Department of Agriculture (1994)
Urbanized area (percent of basin area) National Land Cover Dataset (NLCD); and enhanced ver-sion (NLCDe)
Homer and others (2004); Price and others (2003)
Residential area (percent of basin area) National Land Cover Dataset enhanced version (NLCDe) Price and others (2003)Mined area (percent of basin area) National Land Cover Dataset enhanced version (NLCDe) Price and others (2003)Commercial, industrial & transportation
area (percent of basin area) National Land Cover Dataset enhanced version (NLCDe) Price and others (2003)
Wetlands (percent of basin area) National Land Cover Dataset (NLCD); and enhanced ver-sion (NLCDe)
Homer and others (2004); Price and others (2003)
Ground-water head, defined as mean basin elevation minus minimum elevation (feet)
Digital Elevation Model (DEM) U.S. Geological Survey (2000a)
6 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
Table 1. Basin characteristics selected for use in the development of regression equations for flood-flow estimates.—Continued
Basin characteristic Source Reference
Shape factor (unitless) is a measure of the shape of a basin computed as the ratio of length of the basin to its computed area
Digital Elevation Model (DEM) U.S. Geological Survey (2000a)
Carbonate bedrock (percent of basin area) From modified geology maps
Pennsylvania Dept. of Con-servation and Natural Re-sources (1997); Environmental Resources Research Institute (1996)
Impervious surface area (percent of basin area) National Land Cover Dataset (NLCD) Homer and others (2004)
Flood-Flow Regression Equations 7
Figu
re 2
. Fl
ood-
flow
regi
ons
and
hydr
olog
ic u
nit c
ode
boun
darie
s in
Pen
nsyl
vani
a.
PEN
NSY
LVA
NIA
NEW
YO
RK
OH
IO
MA
RYLA
ND
WES
T V
IRG
INIA
NEW
JER
SEY
DEL
AWA
RE
VIR
GIN
IAV
IRG
INIA
LAK
E E
RIE
31
42
Base
from
U.S
. Geo
logi
cal S
urve
y 1:
2,00
0,00
0 an
d 1:
100,
000
Digi
tal D
ata
Stat
e bo
unda
ry fr
om U
.S. G
eolo
gica
l Sur
vey,
200
5Ri
vers
from
U.S
. Geo
logi
cal S
urve
y, 2
006
Albe
rs E
qual
-Are
a Co
nic
proj
ectio
n: S
tand
ard
Para
llels
29°
30’N
and
45°
30’N
.Ce
ntra
l Mer
idia
n 77
°45’
W, L
atitu
de o
f Orig
in 2
3°00
’N
010
2030
4050
MIL
ES
010
2030
4050
KILO
MET
ERS
75°
76°
77°
78°
79°
80°
81°
42°
41°
40°
FLOO
D-FL
OW R
EGIO
N B
OUN
DARY
HYDR
OLOG
IC U
NIT
COD
E (H
UC8)
BOU
NDA
RY
EXPL
ANAT
ION
STAT
E BO
UNDA
RYRI
VER
Susq
uehann
a
River
Susq
uehann
a
River
Delaware Ri
ver
Allegheny Rive
r
Allegheny Rive
rWes
t Bra
nc
h Sus
queh
anna
Rive
r
West B
ranc
h Sus
queh
anna
Rive
r
Ohio R
iver
Ohio R
iver
M
onongahela
River
North
Branch Su
sque
ha
nna River
North
Branch Su
sque
ha
nna River
8 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
Figu
re 3
. Fl
ood-
flow
regi
on 1
in P
enns
ylva
nia.
1514
000
1424
500
1526
000
1426
000
1520
000
1519
200
1518
862
1518
000
1532
850
1518
420
1517
000
1533
800
1516
350
1516
500
1533
250
1532
000
1428
750
1429
300
1429
500
1532
200
1429
000
1533
950
1430
000
1534
000
1548
500
1534
500
1430
500
1431
500
1549
500
1550
000
1549
780
1431
680
1536
000
1552
500
1552
100
1438
300
1552
000
1549
000
1538
800
1549
700
1550
500
1553
005
1440
300
1447
500
1553
050
1439
500
1440
400
1447
720
1553
600
1539
500
1447
680
1553
700
1538
000
1553
130
1448
000
1540
000
1442
500
1441
000
1449
500
1446
600
1449
360
1540
200
1450
000
1449
000
1469
500
1451
000
1452
300
1451
800
1452
500
1468
500
1452
000
1451
650
1470
720
1454
600
1470
500
1470
756
1459
500
1470
779
1470
960
1471
000
1470
853
1471
510
1518
500
1516
800
1431
000
1551
000
1539
000
1448
500
1450
500
1453
000
1451
500
1514
000
1424
500
1526
000
1426
000
1520
000
1519
200
1518
862
1518
000
1532
850
1518
420
1517
000
1533
800
1516
350
1516
500
1533
250
1532
000
1428
750
1429
300
1429
500
1532
200
1429
000
1533
950
1430
000
1534
000
1548
500
1534
500
1430
500
1431
500
1549
500
1550
000
1549
780
1431
680
1536
000
1552
500
1552
100
1438
300
1552
000
1549
000
1538
800
1549
700
1550
500
1553
005
1440
300
1447
500
1553
050
1439
500
1440
400
1447
720
1553
600
1539
500
1447
680
1553
700
1538
000
1553
130
1448
000
1540
000
1442
500
1441
000
1449
500
1446
600
1449
360
1540
200
1450
000
1449
000
1469
500
1451
000
1452
300
1451
800
1452
500
1468
500
1452
000
1451
650
1470
720
1454
600
1470
500
1470
756
1459
500
1470
779
1470
960
1471
000
1470
853
1471
510
1518
500
1516
800
1431
000
1551
000
1539
000
1448
500
1450
500
1453
000
1451
500
NEW
YO
RK
PEN
NSY
LVA
NIA
NEW
JER
SEY
CO
NN
ECTI
CU
T
ATLANTIC OCEAN
PEN
NSY
LVA
NIA
PEN
NSY
LVA
NIA
Delawa
re
River
North
Branch Sus
queh
anna River
North
Branch Sus
queh
anna River
Schu
ylkil
l River
Schu
ylkil
l River
Base
from
U.S
. Geo
logi
cal S
urve
y 1:
2,00
0,00
0 an
d 1:
100,
000
Digi
tal D
ata
Stat
e bo
unda
ry fr
om U
.S. G
eolo
gica
l Sur
vey,
200
5Ri
vers
from
U.S
. Geo
logi
cal S
urve
y, 2
006
Albe
rs E
qual
-Are
a Co
nic
proj
ectio
n: S
tand
ard
Para
llels
29°
30’N
and
45°
30’N
.Ce
ntra
l Mer
idia
n 77
°45’
W, L
atitu
de o
f Orig
in 2
3°00
’N
010
2030
4050
MIL
ES
010
2030
4050
KILO
MET
ERS
73°
74°
75°
76°
77°
78°
42°
41°
40°
FLOO
D-FL
OW R
EGIO
N 1
STAT
E BO
UNDA
RY
RIVE
RCo
ntin
uous
-rec
ord
stre
amflo
w-g
agin
g st
atio
nCr
est-s
tage
par
tial-r
ecor
d st
ream
flow
-gag
ing
stat
ion
EXPL
ANAT
ION
STRE
AMFL
OW-G
AGIN
G ST
ATIO
N W
ITH
ABBR
EVIA
TED
STAT
ION
NUM
BER
(FIR
ST N
UMBE
R W
AS R
EMOV
ED)
1449
360
1519
200
Flood-Flow Regression Equations 9
Figu
re 4
. Fl
ood-
flow
regi
on 2
in P
enns
ylva
nia.
Susq
ueha
nna R
iver
Susq
ueha
nna R
iver
Delaw
are Rive
r
1472
620
1472
198
1472
199
1471
980
1472
000
1473
000
1576
320
1473
100
1471
875
1473
120
1472
157
1576
085
1472
174
1574
000
1473
169
1480
300
1576
500
1475
300
1480
800
1480
500
1475
850
1480
610 14
8061
715
7675
415
7500
014
7648
0
1476
500
1578
400
1574
500
1481
000
1477
000
1578
200
1479
820
1574
800
1478
200
1577
500
1472
620
1472
198
1472
199
1471
980
1472
000
1473
000
1576
320
1473
100
1471
875
1473
120
1472
157
1576
085
1472
174
1574
000
1473
169
1480
300
1576
500
1475
300
1480
800
1480
500
1475
850
1480
610 14
8061
715
7675
415
7500
014
7648
0
1476
500
1578
400
1574
500
1481
000
1477
000
1578
200
1479
820
1574
800
1478
200
1577
500
Schuylkil
l R
iver
Schuylkil
l R
iver
PEN
NSY
LVA
NIA
NEW
JER
SEY
MA
RYLA
ND
DEL
AWA
RE
VIR
GIN
IA
PEN
NSY
LVA
NIA
PEN
NSY
LVA
NIA
Base
from
U.S
. Geo
logi
cal S
urve
y 1:
2,00
0,00
0 an
d 1:
100,
000
Digi
tal D
ata
Stat
e bo
unda
ry fr
om U
.S. G
eolo
gica
l Sur
vey,
200
5Ri
vers
from
U.S
. Geo
logi
cal S
urve
y, 2
006
Albe
rs E
qual
-Are
a Co
nic
proj
ectio
n: S
tand
ard
Para
llels
29°
30’N
and
45°
30’N
.Ce
ntra
l Mer
idia
n 77
°45’
W, L
atitu
de o
f Orig
in 2
3°00
’N
05
1015
2025
MIL
ES
05
1015
2025
KILO
MET
ERS
75°
76°
77°
40°
39°
1465
500
1473
880
1465
770
1473
900
1467
043
1465
790
1465
798
1467
050
1465
785
1467
048
1465
500
1473
880
1465
770
1473
900
1467
043
1465
790
1465
798
1467
050
1465
785
1467
048
05
MIL
ES
05
KILO
MET
ERS
Dela
ware
River
FLOO
D-FL
OW R
EGIO
N 2
STAT
E BO
UNDA
RY
RIVE
RCo
ntin
uous
-rec
ord
stre
amflo
w-g
agin
g st
atio
nCr
est-s
tage
par
tial-r
ecor
d st
ream
flow
-gag
ing
stat
ion
EXPL
ANAT
ION
STRE
AMFL
OW-G
AGIN
G ST
ATIO
N W
ITH
ABBR
EVIA
TED
STAT
ION
NUM
BER
(FIR
ST N
UMBE
R W
AS R
EMOV
ED)
1577
500
1473
100
1467
042
1473
950
1474
000
1467
086
1467
087
1467
089
1475
530
1475
510
1475
550
1467
042
1473
950
1474
000
1467
086
1467
087
1467
089
1475
530
1475
510
1475
550
Phila
delp
hia
Cou
nty
10 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
region 4 (fig. 6). The number of streamflow-gaging stations used to develop each flood-flow region and the area of each region are listed in table 2. The largest region is region 3, accounting for almost half the area in the state.
The following basin characteristics were statistically sig-nificant for one or more regression equations: drainage area, mean elevation, and the percentages of carbonate bedrock, urban area, and storage within the basin. A list of the basin characteristics for the stations used in the analysis is provided in appendix 1. When applying the regression equations to estimate flood magnitudes and frequency, it is important to maintain the same source of basin-characteristic data that were used in the development of the equations. Otherwise, the flood flows predicted by the regression equations may not be valid. To form a near-linear relation between the flood flows and basin characteristics, all independent and dependent variables were log-transformed prior to regression analysis. Because percentages can have a value of zero, 1.0 was added to the decimal form of the percentages of carbonate bedrock, urban area, and storage before the log transformation. Percentage of storage was derived from the percentage of lakes, ponds, and wetlands basin characteristics. To increase the variability of the basin characteristic storage area, a multiplication factor of 10 was applied to the decimal form of the basin characteris-tic, in effect resulting in storage area being multiplied by 0.1 rather than 0.01 prior to log transformation, as the other basin characteristics are.
The regression model took the following form in log units:
A = the intercept (estimated by GLS); DA = drainage area, in square miles; El = mean elevation, in feet; C = basin underlain by carbonate bedrock, in
percent; U = urban area in the basin, in percent; Sto = storage in the basin, in percent; and b, c, d, e, and f =basincharacteristiccoefficientsof
regression estimated by GLS.
Regression equations predicting flood magnitudes for the 2-, 5-, 10-, 50-, 100-, and 500-year recurrence intervals were developed for each flood-flow region. The resultant basin-characteristic coefficients along with the standard errors of prediction for the regional flood-flow regression equations are shown in table 3. The standard errors of prediction provide an estimate of reliability of the predicted flood flows (Helsel and Hirsch, 1992). The standard errors of prediction for the flood-flow regression equations ranged from 26 percent for the Q5 in Region 4 to 49 percent for the Q500, also in Region 4. The standard errors of prediction for the Q100 ranged from 36 to 38 percent.
Example using a flood-flow regression equation.Example 1. Calculate the Q100 flood flow for a site near
the confluence of Shohola Creek with the Delaware River in Pike County in the northeastern part of Pennsylvania at latitude 41°25’30” and longitude 74°57’20”. The drainage area
Table 2. Number of streamflow-gaging stations and area in flood-flow regions in Pennsylvania and surrounding states.
1 Drainage area, in square miles, determined from 30-meter digital elevation model (DEM).2 Mean elevation, in feet, is the average elevation in the basin, determined from 30-meter DEM.3 Percent carbonate bedrock is the percent of basin underlain by carbonate bedrock, determined by modified geology maps.4 Percent urban area is the percent of urban area, as defined by low-intensity residential, high-intensity residential, commercial/industrial/transpor-
tation, residential with trees, and residential without trees in the basin, determined by National Land Cover Dataset enhanced (NLCDe).5 Percent storage is the percent of lakes, ponds, and wetlands, determined from U.S. Geological Survey 1:24,000 quadrangles and NLCDe.
14 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
is 77.0 mi2, and the percent storage is 10.2. The basin is unaf-fected by substantial regulation, diversion, or mining.
From figure 2 and the latitude and longitude, the 1. site is in flood-flow region 1.
Using coefficients from table 3, the Q100 2. regional regression equation is: logQ^ 100 = 2.56172 + 0.81626 log(DA) – 0.41724 log(1 + (0.1 × Sto))
Substituting the basin characteristics for the site 3. into the equation produces: logQ^ 100 = 2.56172 + 0.81626 log(77.0) - 0.41724 log(1 + (0.1 × 10.2)) logQ^ 100 = 2.56172 + (1.53987) - (0.12740) logQ^ 100 = 3.97419 Q^100 = 9,420 ft3/s
Just as a station has a period of record that should be taken into consideration when computing flood frequencies from gaging-station peak-flow data, regression equations have an equivalent period of record that should be taken into con-sideration when using the equations to compute flood frequen-cies. The equivalent years of record provide indicators of the accuracy of the regression equations. The equivalent years of record are computed from a factor that is based on the skew coefficient of the population of annual peaks, the standard deviation of the logarithms of the annual peaks at individual stations used in the development of the regression equations, and the standard error of prediction of the regression equa-tions. This methodology is presented by Hardison (1971). The equivalent years of record for each of the regression equations are shown in table 4. For the Q100, the equivalent period
of record ranges from 11 years for Region 3 to 15 years for Region 2. To summarize, the Q100 calculated from the equa-tion developed for Region 3 is comparable to the Q100 deter-mined from a record from a station that has been in operation for 11 years.
A weighted method to minimize the temporal bias associated with stations has been suggested by Flippo (1977), Stuckey and Reed (2000), Water Resources Council, Hydrol-ogy Committee (1981), and others to compute flood-flow statistics for a streamflow-gaging station. Observed flood frequency-magnitude estimates may contain time-sampling variability because of the specific time span associated with the period of record for a station. The period of record for a station may or may not include years when large floods occurred. Inclusion of several large floods, or lack of any large floods, can change flood frequency-magnitude estimates for stations, especially those with short periods of record. To minimize this bias, a method has been developed that incor-porates the observed, as well as the predicted, flood flows into a weighted average flood-frequency discharge estimate using the period of record of the station and the equivalent period of record for the regression equation.
The weighted average discharge estimates are computed from the equation:
QQ N Q NE
N NET W
T G T R
( )
( ) ( )
( )=
( )+ ( )
+
^
where QT(W) =theweightedflooddischargefortheT-year
recurrence interval, in cubic feet per second;
QT(G) =theobservedflooddischargecomputedfromstreamflow-gaging-stationdataforthe T-year recurrence interval, in cubic feet
Table 4. Equivalent period of record for regression equations developed for estimating flood magnitudes for selected recurrence intervals in Pennsylvania.
[Methodology used described by Hardison (1971); flood-flow regions are shown in figure 2]
Flood-recurrence interval
Equivalent period of record (years)
Flood-flow region 1 Flood-flow region 2 Flood-flow region 3 Flood-flow region 4
per second; N = the number of years of record at the
streamflow-gaging station used to calculate QT(G);
QT R^( ) = the predicted flood discharge computed
from regression equations for the T-year recurrence interval, in cubic feet per second; and
NE = average equivalent years of record associated with the regression equation in table 4.
Example showing the calculation of weighted flood flows.Example 2. Calculate the weighted flood-frequency
discharge estimate for streamflow-gaging station 01546400, Spring Creek at Houserville, Pa., at latitude 40°50’01” and longitude 77°49’40”. The drainage area is 58.5 mi2, mean ele-vation is 1,340 ft, percentage of carbonate bedrock is 75.1, and the basin contains 0.13 percent storage. The station operated from 1985 to 2005 as a continuous-record station, for a total of 21 years. The basin is unaffected by regulation, diversion, or mining. The reported Q100 determined from streamflow data is 2,840 ft3/s.
The Q100 computed from the regional regression 1. equation is 3,500 ft3/s (see Example 1 for meth-odology), and from table 4, the equivalent years of record for the regression equation is 11 years.
Substituting the discharges and number of years 2. into equation 2 produces: Q100(W) = [(2,840 × 21) + (3,500 × 11)] / (21 + 11)Q100(W) = 3,070 ft3/s
The observed, predicted, and weighted flood flows for the stations used in the analysis are shown in appendix 2. Additional techniques for estimating magnitude of flood flows at selected recurrence intervals in Pennsylvania under other situations have been identified by Stuckey and Reed (2000).
Limitations of Regression EquationsCertain conditions can limit the application of the regres-
sion equations presented in this report. The equations should not be used if the drainage area is less than 1.0 mi2 or greater than 2,000 mi2. Regions 1, 3, and 4 do not include a vari-able for percentage of urban development in the regression equations, and as a result, effects from urbanization may not be captured in regression-equation results for these regions. A summary of the range of all the variables used to develop the regression equations is presented in table 5. Predicted streamflow characteristics for basins with basin characteristics outside these ranges may not be valid. Particularly, regres-sion equations developed for regions 1 and 3 are sensitive to percent storage, and results from these regression equations should be reviewed carefully to determine accuracy for basins with percent storage outside the range listed in table 5. When applying the regression equations to estimate flood mag-nitudes and frequency, it is important to maintain the same source of basin-characteristic data that were used in the devel-opment of the equations. Otherwise, the flood flows predicted by the regression equations may not be valid.
The regression equations should not be used to predict flood flows if streamflow at the site of interest is substantially affected by an upstream flood-control reservoir. The stream-flow-gaging stations that were excluded from the regression analysis because of substantial upstream regulation are listed in appendix 3 with observed flood flows for specified recur-rence intervals. The 500-year recurrence flow is not listed in the appendix because the storage capacity for some flood-control reservoirs may not be sufficient to store all the runoff associated with the 500-year flood event.
SummaryFlood-flow statistics provide the foundation for Flood
Insurance Studies (FIS), flood-plain management, and the design of bridges and flood-control structures. Accessible
Table 5. Summary of the variables used to develop the flood-flow regression equations for Pennsylvania.
16 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
methods that produce estimates of the frequency and magni-tude of floods are important to engineers and planners working on such projects. The USGS, in cooperation with the Federal Emergency Management Agency (FEMA), the Pennsylvania State Association of Township Supervisors (PSATS), and the Susquehanna River Basin Commission (SRBC), developed flood-flow regression equations to estimate flood flows for ungaged streams in Pennsylvania using data from 322 contin-uous-record and crest-stage partial-record streamflow-gaging stations with 10 or more years of record in Pennsylvania and surrounding states.
Regression equations were developed to estimate the Q2, Q5, Q10, Q50, Q100, and Q500 flood discharges for four flood-flow regions in Pennsylvania. The following basin char-acteristics were significant at the 95-percent confidence level for one or more regression equations: drainage area, mean elevation, and the percentages of carbonate bedrock, urban area, and storage within the basin. Standard errors of predic-tion ranged from 26 percent for the Q5 in Region 4 to 49 per-cent for the Q500, also in Region 4. The equivalent periods of record for the Q100 regression equations ranged from 11 years for Region 3 to 15 years for Region 2. To minimize temporal bias that may be associated with a station, a weighting method is presented that incorporates the observed, as well as the pre-dicted, flood flows into a weighted-average flood-frequency discharge estimate.
Certain conditions can limit the application of the regres-sion equations presented in this report. The equations should not be used if the contributing drainage area is less than 1.0 mi2 or greater than 2,000 mi2. The regression equations should not be used to predict flood-flow frequency statistics if streamflow at the site of interest is substantially affected by an upstream flood-control reservoir. Estimates of flood-flow magnitude for streamflow-gaging stations substantially affected by upstream regulation are presented. Predicted streamflow characteristics for basins with basin characteristics outside the ranges used to develop the regression equations may not be valid.
AcknowledgmentsSpecial thanks are extended to the USGS Pennsylvania
Water Science Center (and Maryland, New York, Ohio, West Virginia) Hydrologic Surveillance Program staffs for their compilation and meticulous review of station data that were used to determine the observed flood frequencies. David Holtschlag (USGS Michigan Water Science Center) and Kara Watson (USGS New Jersey Water Science Center) provided critical colleague reviews.
References Cited
Daly, Christopher, 1996, Overview of the PRISM Model [online]: accessed June 24, 2008, at http://www.prism.oregonstate.edu/docs/tech_desc.html
Dillow, J.J.A., 1996, Technique for estimating magnitude and frequency of peak flows in Maryland: U.S. Geological Sur-vey Water-Resources Investigations Report 95-4154, 55 p.
Dinicola, Karen, 1996, The “100-Year Flood”: U.S. Geologi-cal Survey Fact Sheet 229-96, 2 p.
Ehlke, M.H., and Reed, L.A., 1999, Comparison of meth-ods for computing streamflow statistics for Pennsylvania streams: U.S. Geological Survey Water-Resources Investi-gations Report 99-4068, 80 p.
Environmental Resources Research Institute, 1996, Areas of carbonate lithology (limeston.zip): Pennsylvania Depart-ment of Environmental Protection, accessed June 24, 2008, at ftp://www.pasda.psu.edu/pub/pasda/compendium/.
Flippo, H.N., Jr., 1977, Floods in Pennsylvania: Harrisburg, Pa., Pennsylvania Department of Environmental Resources, Water Resources Bulletin No. 13, 59 p.
Flippo, H.N., Jr., 1982, Evaluation of the streamflow data program in Pennsylvania: U.S. Geological Survey Water-Resources Investigations 82-21, 56 p.
Flynn, K.M., Kirby, W.H., and Hummel, P.R., 2006, Users manual for PeakFQ, annual flood frequency analysis using Bulletin 17B Guidelines: U.S. Geological Survey Tech-niques and Methods Report, book 4, chap. B4, 42 p.
Hardison, C.H., 1971, Prediction error of regression estimates of streamflow characteristics at ungaged sites, in Geological Survey Research 1971: U.S. Geological Survey Profes-sional Paper 750-C, p. C228-C236.
Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in water resources: Amsterdam, The Netherlands, Elsevier, Sarah Burgerhartstraat 25, 1000 AE Studies in Environmen-tal Science 49, 529 p.
Homer, C., Huang, C., Yang, L., Wylie, B., and Coan, M., 2004, Development of a 2001 National Landcover Data-base for the United States: Photogrammetric Engineering and Remote Sensing, v. 70, no. 7, July 2004, p. 829-840, accessed October 24, 2007, at http://www.mrlc.gov/ mrlc2k_publications.asp
Koltun, G.F., 2003, Techniques for estimating flood-peak dis-charges of rural, unregulated streams in Ohio (2d ed.): U.S. Geological Survey Water-Resources Investigations Report 03-4164, 75 p.
References Cited 17
Lumia, Richard, Freehafer, D.A., and Smith, M.J., 2006, Magnitude and frequency of floods in New York: U.S. Geological Survey Scientific Investigations Report 2006-5112, 152 p.
MathSoft, Inc., 1997, S-PLUS user’s guide: Seattle, Wash., Data Analysis Products Division, MathSoft, 620 p.
Pennsylvania Department of Conservation and Natu-ral Resources, 1997, Glacial deposits of Penn-sylvania: Bureau of Topographic and Geo-logic Survey, accessed February 28, 2008, at http://www.dcnr.state.pa.us/topogeo/field/glacial.aspx
Price, C., Nakagaki, N., Hitt, K., and Clawges, R., 2003, Min-ing GIRAS—Improving on a national treasure of land use data: ESRI International User Conference 2003 Proceed-ings, accessed October 3, 2005, at http://gis.esri.com/library/userconf/proc03/p0904.pdf
Roland, M.A., and Stuckey, M.H., 2007, Analysis of flood-magnitude and flood-frequency data for streamflow-gaging stations in the Delaware and North Branch Susquehanna River Basins in Pennsylvania: U.S. Geological Survey Open-File Report 2007-1235, 22 p.
Stuckey, M.H., and Reed, L.A., 2000, Techniques for estimat-ing magnitude and frequency of peak flows for Pennsyl-vania streams: U.S. Geological Survey Water-Resources Investigations Report 00-4189, 43 p.
Tasker, G.D., and Stedinger, J.R., 1989, An operational GLS model for hydrologic regression: Journal of Hydrology, v. 3, p. 361-375.
U.S. Department of Agriculture, 1994, State Soil Geographic (STATSGO) data base for Pennsylvania [online]: accessed January 17, 2006, at http://www.ncgc.nrcs.usda.gov/ products/datasets/statsgo
U.S. Geological Survey, 2000a, US GeoData Digital Elevation Models: U.S. Geological Survey Fact Sheet 040-00, 3 p., accessed January 30, 2006, at http://erg.usgs.gov/isb/pubs/factsheets/fs04000.html
U.S. Geological Survey, 2000b, The National Hydrog-raphy Dataset [online]: accessed January 3, 2006, at http://nhd.usgs.gov/chapter1/index.html
Water Resources Council, Hydrology Committee, 1981, Guidelines for determining flood flow frequencies: Wash-ington, D.C., Bulletin 17B, variously paged.
Wiley, J.B., Atkins, J.T., Jr., and Tasker, G.D., 2000, Estimat-ing magnitude and frequency of peak discharges for rural, unregulated streams in West Virginia: U.S. Geological Sur-vey Water-Resources Investigations Report 00-4080, 70 p.
18 Regression Equations for Estimating Flood Flows for Ungaged Streams in Pennsylvania
References Cited 19
Appendixes
Appendix 1. Streamflow-gaging stations and basin characteristics used in development of flood-flow regression equations for Pennsylvania streams.
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.
Appendix 3. Flood-flow magnitudes for selected recurrence intervals for streamflow-gaging stations in Pennsylvania with drainage areas less than 2,000 square miles and streamflow substantially affected by upstream regulation.
20 Regression Equations for Estimating Flood Flows at Selected Recurrence IntervalsA
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0142
4500
C42
0545
7519
25Tr
out C
reek
at C
anno
nsvi
lle, N
.Y.
1941
-196
323
49.5
----
3.04
001
4260
00C
4203
3175
2542
Oqu
aga
Cre
ek a
t Dep
osit,
N.Y
.19
41-2
005
3567
.6--
--.5
60
0142
8750
C41
4028
7522
35W
est B
ranc
h La
ckaw
axen
Riv
er n
ear A
lden
ville
, Pa.
1975
-200
632
40.6
1,75
00
1.95
.28
0142
9000
C41
3514
7519
38W
est B
ranc
h La
ckaw
axen
Riv
er a
t Pro
mpt
on, P
a.19
42-2
005
1659
.71,
650
05.
43.3
701
4293
00P
4139
2675
1712
Dyb
erry
Cre
ek a
bove
Res
ervo
ir ne
ar H
ones
dale
, Pa.
1975
-200
428
46.1
1,50
00
2.27
.21
0142
9500
C41
3626
7516
03D
yber
ry C
reek
nea
r Hon
esda
le, P
a.19
42-2
005
1664
.61,
470
03.
57.2
101
4300
00C
4133
4375
1454
Lack
awax
en R
iver
nea
r Hon
esda
le, P
a.19
42-2
005
1116
41,
510
04.
881.
4301
4305
00C
4129
1075
1115
Lack
awax
en R
iver
at W
est H
awle
y, P
a.19
22-1
942
1719
81,
470
04.
531.
6601
4310
00C
4129
0575
1320
Mid
dle
Cre
ek n
ear H
awle
y, P
a.19
45-1
986
4178
.41,
400
06.
95.6
701
4315
00C
4128
3475
1021
Lack
awax
en R
iver
at H
awle
y, P
a.19
09-1
959
5129
01,
440
05.
171.
5301
4316
80P
4123
1575
1420
Mill
Bro
ok n
ear P
aupa
ck, P
a.19
60-1
980
204.
841,
540
03.
572.
0501
4383
00P
4119
3574
4750
Vand
erm
ark
Cre
ek a
t Milf
ord,
Pa.
1962
-200
645
5.09
1,06
00
.75
5.31
0143
9500
C41
0515
7502
20B
ush
Kill
at S
hoem
aker
s, Pa
.19
09-2
006
9811
71,
270
011
.25
3.65
0144
0300
P41
0950
7516
00M
ill C
reek
at M
ount
ainh
ome,
Pa.
1961
-200
646
5.9
1,62
00
1.29
12.8
0144
0400
C41
0505
7512
54B
rodh
ead
Cre
ek n
ear A
nalo
min
k, P
a.19
58-2
006
4965
.91,
380
05.
123.
701
4410
00C
4058
4575
1205
McM
icha
el C
reek
nea
r Stro
udsb
urg,
Pa.
1911
-195
528
65.3
952
.23
3.34
3.17
0144
2500
C40
5955
7508
35B
rodh
ead
Cre
ek a
t Min
isin
k H
ills,
Pa.
1951
-200
656
259
1,13
0.0
63.
978.
2901
4466
00C
4054
0075
1208
Mar
tins C
reek
nea
r Eas
t Ban
gor,
Pa.
1961
-198
626
10.4
947
07.
34.0
601
4475
00C
4107
4975
3733
Lehi
gh R
iver
at S
todd
arts
ville
, Pa.
1942
-200
665
91.7
1,83
00
14.0
47.
4701
4476
80C
4103
5575
3114
Tunk
hann
ock
Cre
ek n
ear L
ong
Pond
, Pa.
1966
-200
640
201,
880
021
.24
.74
0144
7720
C41
0505
7536
21To
byha
nna
Cre
ek n
ear B
lake
slee
, Pa.
1955
-200
645
118
1,85
00
18.3
29.
901
4480
00C
4102
2575
4542
Lehi
gh R
iver
at T
anne
ry, P
a.19
15-1
959
4532
01,
790
013
.28
6.76
0144
8500
C41
0208
7532
37D
illdo
wn
Cre
ek n
ear L
ong
Pond
, Pa.
1949
-200
658
2.39
1,89
00
5.08
.42
0144
9000
C40
4945
7542
20Le
high
Riv
er a
t Leh
ight
on, P
a.19
82-2
006
2558
91,
640
08.
686.
2301
4493
60C
4053
5175
3010
Poho
poco
Cre
ek a
t Kre
sgev
ille,
Pa.
1967
-200
640
49.9
1,06
00
1.93
7.3
0144
9500
C40
5522
7533
32W
ild C
reek
at H
atch
ery,
Pa.
1941
-197
818
16.8
1,39
00
5.66
.55
0145
0000
C40
4954
7540
53Po
hopo
co C
reek
nea
r Par
ryvi
lle, P
a.19
41-1
970
2910
91,
070
04.
034.
1101
4505
00C
4048
2275
3554
Aqu
ashi
cola
Cre
ek a
t Pal
mer
ton,
Pa.
1940
-200
667
76.7
867
4.91
1.32
2.03
0145
1000
C40
4525
7536
12Le
high
Riv
er a
t Wal
nutp
ort,
Pa.
1942
-200
514
889
1,40
0.7
46.
515.
5401
4515
00C
4034
5675
2860
Littl
e Le
high
Cre
ek n
ear A
llent
own,
Pa.
1935
-200
661
80.8
532
63.7
.73
1301
4516
50C
4035
4775
2828
Littl
e Le
high
Cre
ek a
t Ten
th S
t. B
r. at
Alle
ntow
n, P
a.19
87-2
006
2098
509
69.4
.76
19.8
0145
1800
C40
3942
7537
38Jo
rdan
Cre
ek n
ear S
chne
cksv
ille,
Pa.
1967
-200
640
5367
50
.35
1.79
0145
2000
C40
3723
7528
58Jo
rdan
Cre
ek a
t Alle
ntow
n, P
a.19
45-2
006
6275
.862
011
.3.4
24.
9601
4523
00C
4043
1075
2210
East
Bra
nch
Mon
ocac
y C
reek
nea
r Bat
h, P
a.19
63-1
981
195.
5362
319
.51.
067.
3601
4525
00C
4038
2875
2247
Mon
ocac
y C
reek
at B
ethl
ehem
, Pa.
1945
-200
662
44.5
494
62.8
.94
12.8
Appendix 1 21A
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0145
3000
C40
3655
7522
45Le
high
Riv
er a
t Bet
hleh
em, P
a.19
06-2
005
511,
280
1,17
011
4.92
8.4
0145
4600
C40
3405
7519
45Po
lk V
alle
y R
un a
t Hel
lerto
wn,
Pa.
1963
-198
018
1.72
649
23.2
1.09
.02
0145
9500
C40
2601
7507
01To
hick
on C
reek
nea
r Pip
ersv
ille,
Pa.
1936
-200
538
97.4
509
05.
034.
8601
4655
00C
4010
2674
5726
Nes
ham
iny
Cre
ek n
ear L
angh
orne
, Pa.
1933
-200
674
210
305
1.83
1.00
26.8
0146
5770
C40
0755
7459
40Po
ques
sing
Cre
ek a
t Tre
vose
Roa
d, P
hila
., Pa
.19
65-1
981
175.
0921
54.
31.5
590
0146
5785
C40
0522
7459
37W
alto
n R
un a
t Phi
lade
lphi
a, P
a.19
65-1
978
142.
1714
20
.79
67.1
0146
5790
C40
0454
7458
57B
yber
ry C
reek
at C
halfo
nt R
oad,
Phi
la.,
Pa.
1966
-197
813
5.34
133
01.
9768
0146
5798
C40
0325
7459
08Po
ques
sing
Cre
ek a
t Gra
nt A
ve. a
t Phi
lade
lphi
a, P
a.19
66-2
006
4121
.413
31.
032.
5776
.301
4670
42C
4005
2375
0410
Penn
yPac
k C
reek
at P
ine
Roa
d, a
t Phi
lade
lphi
a, P
a.19
65-1
981
1737
.926
01.
88.8
172
.401
4670
43C
4005
2775
0315
Stre
am ‘A
’ at P
hila
delp
hia,
Pa.
1965
-198
016
2.7
175
0.6
094
.401
4670
48C
4003
0075
0159
Penn
yPac
k C
r at L
ower
Rha
wn
St B
dg, P
hila
., Pa
.19
66-2
006
4149
.823
31.
43.8
874
.401
4670
50C
4003
1975
0122
Woo
den
Brid
ge R
un a
t Phi
lade
lphi
a, P
a.19
65-1
981
173.
3611
30
.66
6701
4670
86C
4002
4775
0640
Taco
ny C
reek
at C
ount
y Li
ne, P
hila
delp
hia,
Pa.
1966
-198
621
16.6
254
0.5
486
.701
4670
87C
4000
5775
0550
Fran
kfor
d C
reek
at C
asto
r Ave
, Phi
lade
lphi
a, P
a.19
82-2
005
2430
.422
00
.34
88.8
0146
7089
C40
0025
7505
33Fr
ankf
ord
Cre
ek a
t Tor
resd
ale A
ve.,
Phila
., Pa
.19
66-1
981
1633
.820
60
.36
89.6
0146
8500
C40
3745
7607
30Sc
huyl
kill
Riv
er a
t Lan
ding
ville
, Pa.
1942
-200
642
133
1,11
00
1.56
8.61
0146
9500
C40
4825
7558
20Li
ttle
Schu
ylki
ll R
iver
at T
amaq
ua, P
a.19
20-2
006
8742
.91,
380
02.
643.
9601
4705
00C
4031
2175
5955
Schu
ylki
ll R
iver
at B
erne
, Pa.
1942
-200
665
355
1,02
0.1
21.
745.
7401
4707
20C
4034
2375
5234
Mai
den
Cre
ek T
ribut
ary
at L
enha
rtsvi
lle, P
a.19
62-1
980
187.
4664
20
.21
.87
0147
0756
C40
3051
7552
60M
aide
n C
reek
at V
irgin
ville
, Pa.
1973
-199
523
159
665
10.8
.80
1.34
0147
0779
C40
2448
7610
19Tu
lpeh
ocke
n C
reek
nea
r Ber
nvill
e, P
a.19
72-2
006
3366
.552
383
.2.6
84.
5101
4708
53C
4020
2476
0837
Furn
ace
Cre
ek a
t Rob
eson
ia, P
a.19
83-2
005
235.
797
80
.40
.03
0147
0960
C40
2214
7601
32Tu
lpeh
ocke
n C
r at B
lue
Mar
sh D
amsi
te n
ear R
eadi
ng, P
a..
1965
-200
514
175
544
42.1
1.94
3.08
0147
1000
C40
2208
7558
46Tu
lpeh
ocke
n C
reek
nea
r Rea
ding
, Pa.
1951
-200
528
211
529
41.3
1.70
3.94
0147
1510
C40
2005
7556
12Sc
huyl
kill
Riv
er a
t Rea
ding
, Pa.
1757
-193
029
880
740
191.
545.
5601
4718
75C
4020
2275
4433
Man
ataw
ny C
reek
nea
r Spa
ngsv
ille,
Pa.
1994
-200
613
56.9
670
28.5
1.40
1.55
0147
1980
C40
1622
7540
49M
anat
awny
Cre
ek n
ear P
otts
tow
n, P
a.19
72-2
006
3285
.558
826
.11.
042.
2201
4720
00C
4014
3075
3907
Schu
ylki
ll R
iver
at P
otts
tow
n, P
a.19
02-2
005
511,
150
684
18.7
1.42
6.55
0147
2157
C40
0905
7536
06Fr
ench
Cre
ek n
ear P
hoen
ixvi
lle, P
a.19
69-2
006
3859
.153
0.6
21.
321.
7601
4721
74C
4005
2275
3750
Pick
erin
g C
reek
nea
r Che
ster
Spr
ings
, Pa.
1967
-198
317
5.98
439
0.2
87.
2801
4721
98C
4023
3875
3057
Perk
iom
en C
reek
at E
ast G
reen
ville
, Pa.
1982
-200
524
3862
33.
351.
422.
9801
4721
99C
4022
2675
3122
Wes
t Bra
nch
Perk
iom
en C
reek
at H
illeg
ass,
Pa.
1982
-200
524
2368
54.
761.
202.
4601
4726
20C
4024
1475
1405
East
Bra
nch
Perk
iom
en C
reek
nea
r Dub
lin, P
a.19
84-2
005
224.
0742
00
1.64
.36
0147
3000
C40
1346
7527
07Pe
rkio
men
Cre
ek a
t Gra
terf
ord,
Pa.
1915
-200
591
279
468
1.27
1.46
6.67
0147
3100
P40
1226
7521
57Za
char
ias C
reek
nea
r Ski
ppac
k, P
a.19
60-1
980
217.
2932
20
.06
9.65
22 Regression Equations for Estimating Flood Flows at Selected Recurrence IntervalsA
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0147
3120
C40
0952
7526
01Sk
ippa
ck C
reek
nea
r Col
lege
ville
, Pa.
1966
-199
429
53.7
289
00.
1624
.701
4731
69C
4004
4575
2740
Valle
y C
reek
at P
a. T
urnp
ike
Br n
ear V
alle
y Fo
rge,
Pa.
1983
-200
523
20.8
356
66.9
.54
42.9
0147
3880
P40
0813
7511
21Pi
ne R
un T
ribut
ary
at F
ort W
ashi
ngto
n, P
a.19
62-1
979
182.
0228
70
.19
62.9
0147
3900
C40
0726
7513
13W
issa
hick
on C
reek
at F
ort W
ashi
ngto
n, P
a.19
62-2
006
2540
.530
27.
66.4
053
.601
4739
50C
4004
5075
1335
Wis
sahi
ckon
Cr a
t Bel
ls M
ill R
d, P
hila
., Pa
.19
66-1
981
1653
.628
519
.1.5
055
.201
4740
00C
4004
4575
1343
Wis
sahi
ckon
Cre
ek a
t Mou
th, P
hila
delp
hia,
Pa.
1966
-200
540
6428
416
.53
57.4
0147
5300
C40
0121
7525
20D
arby
Cre
ek a
t Wat
erlo
o M
ills n
ear D
evon
, Pa.
1972
-199
926
5.1
435
0.2
567
.201
4755
10C
3955
4475
1622
Dar
by C
reek
nea
r Dar
by, P
a.19
64-1
990
2737
.432
50
.33
75.1
0147
5530
C39
5829
7516
49C
obbs
Cr a
t U.S
. Hgh
wy
No.
1 a
t Phi
lade
lphi
a, P
a.19
65-2
005
184.
7831
90
.42
87.7
0147
5550
C39
5502
7514
52C
obbs
Cre
ek a
t Dar
by, P
a.19
64-1
990
2722
208
0.3
087
.401
4758
50C
3958
3575
2613
Cru
m C
reek
nea
r New
tow
n Sq
uare
, Pa.
1977
-200
529
15.8
420
0.3
430
.701
4764
80C
3954
5875
2413
Rid
ley
Cre
ek a
t Med
ia, P
a.19
87-2
005
1830
.237
40
.36
23.4
0147
6500
C39
5410
7523
35R
idle
y C
reek
at M
oyla
n, P
a.19
32-1
955
2431
.936
80
.37
26.6
0147
7000
C39
5208
7524
31C
hest
er C
reek
nea
r Che
ster
, Pa.
1932
-200
675
61.1
339
0.5
638
.101
4782
00C
3946
5475
4803
Mid
dle
Bra
nch
Whi
te C
lay
Cre
ek n
ear L
ande
nber
g, P
a.19
60-1
995
3212
.745
24.
89.8
66.
9101
4798
20C
3949
0075
4131
Red
Cla
y C
reek
nea
r Ken
nett
Squa
re, P
a.19
88-2
005
1828
.337
111
.11.
2417
.601
4803
00C
4004
2275
5140
Wes
t Bra
nch
Bra
ndyw
ine
Cre
ek n
ear H
oney
Bro
ok, P
a.19
60-2
006
4718
.772
63.
362.
262.
6101
4805
00C
3959
0875
4940
Wes
t Bra
nch
Bra
ndyw
ine
Cre
ek a
t Coa
tesv
ille,
Pa.
1942
-200
645
46.1
663
1.35
1.50
4.33
0148
0610
P39
5820
7551
06Su
cker
Run
nea
r Coa
tesv
ille,
Pa.
1964
-200
539
2.62
544
25.0
821
.401
4806
17C
3957
4275
4806
Wes
t Bra
nch
Bra
ndyw
ine
Cre
ek a
t Mod
ena,
Pa.
1970
-200
637
55.3
633
5.34
1.27
10.5
0148
0800
C40
0020
7542
20Ea
st B
ranc
h B
rand
ywin
e C
reek
at D
owni
ngto
wn,
Pa.
1942
-196
811
81.6
531
6.72
2.03
9.03
0148
1000
C39
5211
7535
37B
rand
ywin
e C
reek
at C
hadd
s For
d, P
a.19
12-2
006
8728
749
07.
631.
0611
.701
5140
00C
4207
4576
1615
Ow
ego
Cre
ek n
ear O
weg
o, N
.Y.
1930
-199
970
185
----
.28
--01
5163
50C
4147
3977
0450
Tiog
a R
iver
nea
r Man
sfie
ld, P
a.19
72-2
005
3415
31,
870
0.2
41.
4501
5165
00C
4147
2777
0054
Cor
ey C
reek
nea
r Mai
nesb
urg,
Pa.
1955
-200
652
12.2
1,77
00
.32
.06
0151
6800
P41
4919
7705
50M
anns
Cre
ek n
ear M
ansf
ield
, Pa.
1960
-197
717
3.04
1,52
00
.01
001
5170
00C
4148
5476
5755
Elk
Run
nea
r Mai
nesb
urg,
Pa.
1955
-197
824
10.2
1,81
00
.03
.02
0151
8000
C41
5430
7707
47Ti
oga
Riv
er a
t Tio
ga, P
a.18
89-2
005
3928
21,
770
0.2
51.
2601
5184
20P
4150
3377
1625
Cro
oked
Cr b
l Cat
lin H
ollo
w a
t Mid
dleb
ury
Cen
ter,
Pa.
1985
-200
520
74.4
1,71
00
.24
.35
0151
8500
C41
5408
7708
55C
rook
ed C
reek
at T
ioga
, Pa.
1954
-197
421
122
1,67
00
.39
.45
0151
8862
C41
5523
7731
56C
owan
esqu
e R
iver
at W
estfi
eld,
Pa.
1984
-200
521
90.6
1,96
00
.26
.78
0151
9200
P41
5915
7718
09C
owan
esqu
e R
iver
at E
lkla
nd, P
a.19
80-2
005
2623
41,
850
0.1
3.5
101
5200
00C
4159
4877
0825
Cow
anes
que
Riv
er n
ear L
awre
ncev
ille,
Pa.
1952
-200
527
298
1,78
00
.15
.53
0152
6000
C42
0400
7717
02Tu
scar
ora
Cre
ek n
ear S
outh
Add
ison
, N.Y
.19
37-1
972
4611
4--
0.2
10
0153
2000
C41
4225
7629
06To
wan
da C
reek
nea
r Mon
roet
on, P
a.19
14-2
006
9321
51,
600
0.4
9.5
7
Appendix 1 23A
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0153
2200
P41
3525
7625
60So
uth
Bra
nch
Tow
anda
Cre
ek a
t New
Alb
any,
Pa.
1963
-199
530
13.4
1,56
00
0.25
0.06
0153
2850
C41
5145
7600
26M
B W
yalu
sing
Cre
ek n
ear B
ircha
rdvi
lle, P
a.19
60-1
979
205.
671,
480
0.2
4.0
601
5332
50P
4142
2576
0710
Tusc
aror
a C
reek
nea
r Silv
ara,
Pa.
1963
-199
533
11.8
1,25
00
1.81
.16
0153
3800
C41
4810
7538
40B
utle
r Cre
ek a
t Gib
son,
Pa.
1963
-197
915
7.51
1,60
00
2.40
.43
0153
3950
C41
3429
7538
32SB
Tun
khan
nock
Cre
ek n
ear M
ontd
ale,
Pa.
1961
-197
818
12.6
1,51
00
3.65
2.1
0153
4000
C41
3330
7553
42Tu
nkha
nnoc
k C
reek
nea
r Tun
khan
nock
, Pa.
1914
-200
693
383
1,33
00
2.87
3.06
0153
4500
C41
3016
7532
33La
ckaw
anna
Riv
er a
t Arc
hbal
d, P
a.19
40-2
005
2010
81,
730
02.
827.
0301
5360
00C
4121
3375
4441
Lack
awan
na R
iver
at O
ld F
orge
, Pa.
1939
-200
521
335
1,54
00
3.04
17.5
0153
8000
C41
0333
7605
38W
apw
allo
pen
Cre
ek n
ear W
apw
allo
pen,
Pa.
1920
-200
687
43.8
1,38
00
4.33
11.1
0153
8800
P41
1840
7608
50H
untin
gton
Cre
ek n
ear P
ikes
Cre
ek, P
a.19
60-1
980
214.
971,
580
0.1
1.0
601
5390
00C
4104
4176
2553
Fish
ing
Cre
ek n
ear B
loom
sbur
g, P
a.19
36-2
006
7127
41,
320
0.6
7.3
0153
9500
C41
0450
7630
40Li
ttle
Fish
ing
Cre
ek a
t Eye
rs G
rove
, Pa.
1941
-195
818
56.5
1,08
00
.13
.65
0154
0000
C41
0010
7627
50Fi
shin
g C
reek
at B
loom
sbur
g, P
a.19
14-1
931
1835
51,
230
.14
.56
.66
0154
0200
C40
5110
7616
48Tr
exle
r Run
nea
r Rin
gtow
n, P
a.19
59-1
979
211.
771,
440
0.3
00
0154
1000
C40
5349
7840
38W
est B
ranc
h Su
sque
hann
a R
iver
at B
ower
, Pa.
1889
-200
592
315
1,72
00
.10
1.83
0154
1200
C40
5741
7831
10W
B S
usqu
ehan
na R
iver
nea
r Cur
wen
svill
e, P
a.19
56-1
965
1036
71,
700
0.4
21.
6301
5415
00C
4058
1878
2422
Cle
arfie
ld C
reek
at D
imel
ing,
Pa.
1914
-200
547
371
1,71
00
.87
1.44
0154
2000
C40
5058
7816
05M
osha
nnon
Cre
ek a
t Osc
eola
Mill
s, Pa
.19
36-1
993
5268
.71,
820
0.0
72.
5101
5425
00C
4107
0378
0633
WB
Sus
queh
anna
Riv
er a
t Kar
thau
s, Pa
.19
36-2
005
211,
460
1,71
00
.51
1.93
0154
2720
P41
1258
7834
60W
ilson
Run
at P
enfie
ld, P
a.19
62-1
995
338.
41,
770
00
.08
0154
2810
C41
3444
7817
34W
aldy
Run
nea
r Em
poriu
m, P
a.19
64-2
005
425.
241,
850
00
001
5430
00C
4124
4878
1150
Drif
twoo
d B
r Sin
nem
ahon
ing
Cr a
t Ste
rling
Run
, Pa.
1914
-200
592
272
1,74
00
.12
.62
0154
3500
C41
1902
7806
12Si
nnem
ahon
ing
Cre
ek a
t Sin
nem
ahon
ing,
Pa.
1936
-200
570
685
1,72
00
.14
.42
0154
3700
P41
3108
7801
40Fi
rst F
ork
Sinn
emah
onin
g C
reek
at W
harto
n, P
a.19
84-2
005
2218
21,
900
0.2
2.2
701
5444
50P
4138
4977
3922
Ger
man
ia B
ranc
h at
Ger
man
ia, P
a.19
64-1
979
112.
392,
150
0.0
1.0
601
5445
00C
4128
3377
4934
Ket
tle C
reek
at C
ross
For
k, P
a.19
36-2
005
6513
61,
890
0.3
2.0
501
5456
00C
4123
2277
4128
Youn
g W
oman
s Cre
ek n
ear R
enov
o, P
a.19
65-2
005
4146
.21,
820
0.0
1.1
101
5460
00C
4056
3077
4740
Nor
th B
ald
Eagl
e C
reek
at M
ilesb
urg,
Pa.
1911
-193
418
119
1,40
07.
47.3
2.7
201
5464
00C
4050
0177
4940
Sprin
g C
reek
at H
ouse
rvill
e, P
a.19
85-2
005
2158
.51,
340
75.1
.13
11.1
0154
6500
C40
5323
7747
40Sp
ring
Cre
ek n
ear A
xem
ann,
Pa.
1936
-200
566
87.2
1,28
083
.1.1
111
.501
5471
00C
4055
5477
4713
Sprin
g C
reek
at M
ilesb
urg,
Pa.
1967
-200
539
142
1,26
078
.3.1
59.
201
5472
00C
4056
3577
4712
Bal
d Ea
gle
Cre
ek b
l Spr
ing
Cre
ek a
t Mile
sbur
g, P
a.19
56-2
005
5026
51,
320
46.2
25.
4501
5475
00C
4103
0677
3617
Bal
d Ea
gle
Cre
ek a
t Bla
ncha
rd, P
a.19
55-2
005
1533
91,
250
44.6
1.99
4.89
0154
7700
C41
0334
7736
22M
arsh
Cre
ek a
t Bla
ncha
rd, P
a.19
56-2
005
5044
.11,
300
.35
.05
.53
0154
7800
C41
0126
7754
15So
uth
Fork
Bee
ch C
reek
nea
r Sno
w S
hoe,
Pa.
1959
-198
123
12.2
1,96
00
.01
2.6
24 Regression Equations for Estimating Flood Flows at Selected Recurrence IntervalsA
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0154
7950
C41
0642
7742
09B
eech
Cre
ek a
t Mon
umen
t, Pa
.19
68-2
005
3815
21,
670
00.
080.
7201
5480
05P
4104
5177
3259
Bal
d Ea
gle
Cre
ek n
ear B
eech
Cre
ek S
tatio
n, P
a.19
11-2
005
9456
21,
360
27.4
1.24
3.24
0154
8020
P41
0030
7719
35B
ull R
un n
ear L
ogan
ton,
Pa.
1963
-198
119
1.92
1,81
0.7
30
001
5485
00C
4131
1877
2652
Pine
Cre
ek a
t Ced
ar R
un, P
a.19
19-2
005
8760
41,
880
0.2
1.4
501
5490
00C
4118
4577
2245
Pine
Cre
ek n
ear W
ater
ville
, Pa.
1909
-192
012
750
1,83
00
.22
.38
0154
9500
C41
2825
7713
52B
lock
hous
e C
reek
nea
r Eng
lish
Cen
ter,
Pa.
1936
-200
565
37.7
1,77
00
.15
.81
0154
9700
C41
1625
7719
28Pi
ne C
reek
bl L
Pin
e C
reek
nea
r Wat
ervi
lle, P
a.19
58-2
005
4894
41,
790
0.2
9.3
801
5497
80C
4125
0477
0946
Larr
ys C
reek
at C
ogan
Hou
se, P
a.19
60-1
978
196.
81,
610
0.0
3.2
501
5500
00C
4125
0677
0159
Lyco
min
g C
reek
nea
r Tro
ut R
un, P
a.19
14-2
005
9217
31,
730
0.1
6.2
201
5505
00P
4116
0177
0249
Lyco
min
g C
reek
nea
r Will
iam
spor
t, Pa
.19
88-2
005
1426
41,
570
0.2
0.8
401
5510
00C
4115
1577
0040
Gra
fius R
un a
t Will
iam
spor
t, Pa
.19
40-1
953
143.
0390
80
.16
5.46
0155
2000
C41
1930
7654
46Lo
yals
ock
Cre
ek a
t Loy
also
ckvi
lle, P
a.19
26-2
005
8043
51,
670
0.8
0.3
301
5521
00P
4120
1076
5745
Mill
Cre
ek n
ear W
arre
nsvi
lle, P
a.19
61-1
978
1811
.91,
380
05.
30.2
201
5525
00C
4121
2576
3206
Mun
cy C
reek
nea
r Son
esto
wn,
Pa.
1936
-200
565
23.8
1,85
00
.21
.19
0155
3005
P41
1227
7645
09M
uncy
Cre
ek n
ear M
uncy
, Pa.
1989
-200
517
196
1,24
00
.43
.601
5530
50P
4107
0577
0400
Whi
te D
eer H
ole
Cre
ek n
ear E
limsp
ort,
Pa.
1961
-199
533
19.2
1,53
00
.29
001
5531
30C
4103
3177
0437
Sand
Spr
ing
Run
nea
r Whi
te D
eer,
Pa.
1968
-198
114
4.93
1,60
00
02.
9501
5536
00C
4104
5776
3917
EB C
hilli
squa
que
Cre
ek n
ear W
ashi
ngto
nvill
e, P
a.19
60-1
978
199.
4879
90
.72
.07
0155
3700
C41
0342
7640
50C
hilli
squa
que
Cre
ek a
t Was
hing
tonv
ille,
Pa.
1980
-200
526
51.5
735
6.65
1.14
.23
0155
5000
C40
5200
7702
55Pe
nns C
reek
at P
enns
Cre
ek, P
a.19
30-2
005
7630
11,
390
241.
15.6
0155
5500
C40
3640
7654
44Ea
st M
ahan
tang
o C
reek
nea
r Dal
mat
ia, P
a.19
30-2
005
7616
291
50
.25
1.6
0155
5800
P40
2235
7825
55M
cDon
ald
Run
nea
r Eas
t Fre
edom
, Pa.
1959
-197
819
1.44
1,32
00
01.
6401
5560
00C
4027
4778
1200
Fran
ksto
wn
Br J
unia
ta R
iver
at W
illia
msb
urg,
Pa.
1889
-200
589
291
1,53
021
.31
7.55
0155
6400
P40
3347
7820
35Sa
ndy
Run
nea
r Bel
lwoo
d, P
a.19
62-1
981
205.
931,
610
9.15
019
.201
5565
00C
4037
4078
1738
Littl
e Ju
niat
a R
iver
at T
ipto
n, P
a.19
36-1
981
3693
.71,
730
5.13
.29
9.83
0155
7100
C40
4000
7815
00Sc
hell
Run
at T
yron
e, P
a.19
58-1
981
231.
711,
500
00
4.92
0155
7500
C40
4101
7814
02B
ald
Eagl
e C
reek
at T
yron
e, P
a.19
36-2
005
6644
.11,
630
5.04
.02
1.19
0155
8000
C40
3645
7808
27Li
ttle
Juni
ata
Riv
er a
t Spr
uce
Cre
ek, P
a.19
36-2
005
6722
01,
570
20.5
.18
5.51
0155
9000
C40
2905
7801
09Ju
niat
a R
iver
at H
untin
gdon
, Pa.
1896
-200
510
481
61,
420
32.6
.25
4.43
0155
9500
C40
3125
7758
15St
andi
ng S
tone
Cre
ek n
ear H
untin
gdon
, Pa.
1889
-195
829
128
1,21
05.
11.6
3.0
901
5597
00C
3958
4078
3708
Sulp
hur S
prin
gs C
reek
nea
r Man
ns C
hoic
e, P
a.19
62-1
978
175.
281,
690
1.73
.01
2.12
0155
9790
P40
0245
7831
45R
ayst
own
Bra
nch
Juni
ata
Riv
er a
t Wol
fsbu
rg, P
a.19
89-2
005
1313
11,
680
1.17
.75
1.11
0156
0000
C40
0418
7829
34D
unni
ng C
reek
at B
elde
n, P
a.19
36-2
005
7017
21,
590
4.27
.21
1.23
0156
1000
C39
5720
7815
15B
rush
Cre
ek a
t Gap
svill
e, P
a.19
30-1
958
2936
.51,
570
0.1
41.
1601
5620
00C
4012
5778
1556
Ray
stow
n B
ranc
h Ju
niat
a R
iver
at S
axto
n, P
a.18
89-2
005
9375
61,
500
14.2
.27
1.71
Appendix 1 25A
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0156
2500
C40
2100
7807
50G
reat
Tro
ugh
Cre
ek n
ear M
arkl
esbu
rg, P
a.19
30-1
957
2884
.61,
490
00.
310.
501
5630
00C
4025
3578
0147
Ray
stow
n B
ranc
h Ju
niat
a R
iver
nea
r Hun
tingd
on, P
a.19
36-1
971
2695
61,
470
11.7
1.40
1.51
0156
3800
P40
0520
7802
55El
ders
Bra
nch
near
Hus
tont
own,
Pa.
1960
-197
819
3.44
1,17
00
.07
.04
0156
4500
C40
1245
7755
32A
ughw
ick
Cre
ek n
ear T
hree
Spr
ings
, Pa.
1939
-200
567
205
1,18
04.
46.4
4.8
201
5645
12P
4016
5577
5327
Aug
hwic
k C
reek
nea
r Shi
rleys
burg
, Pa.
1990
-200
516
296
1,17
07.
03.4
7.7
101
5650
00C
4039
1777
3460
Kis
haco
quill
as C
reek
at R
eeds
ville
, Pa.
1936
-200
551
164
1,22
024
.8.1
91.
401
5657
00C
4036
2077
1840
Littl
e Lo
st C
reek
at O
akla
nd M
ills,
Pa.
1960
-198
122
6.52
758
47.8
.50
1.77
0156
5920
P40
2115
7738
55Li
ck R
un n
ear E
ast W
ater
ford
, Pa.
1962
-198
120
8.34
1,02
09.
09.4
1.2
0156
6000
C40
3055
7725
10Tu
scar
ora
Cre
ek n
ear P
ort R
oyal
, Pa.
1889
-200
562
214
1,01
00
1.05
.101
5665
00C
4033
5577
0705
Coc
olam
us C
reek
nea
r Mill
erst
own,
Pa.
1930
-197
229
57.2
813
5.66
.73
.21
0156
7500
C40
2215
7724
09B
ixle
r Run
nea
r Loy
svill
e, P
a.19
54-2
005
5215
907
0.9
1.2
301
5680
00C
4019
2477
1009
Sher
man
Cre
ek a
t She
rman
s Dal
e, P
a.19
27-2
005
7620
71,
010
0.9
8.3
701
5685
00C
4027
3776
4506
Cla
rk C
reek
nea
r Car
sonv
ille,
Pa.
1938
-199
659
221,
050
04.
62.0
501
5693
40P
4007
4077
3250
New
burg
Run
at N
ewbu
rg, P
a.19
64-1
995
325.
4280
40
01.
9501
5698
00C
4014
0577
0823
Leto
rt Sp
ring
Run
nea
r Car
lisle
, Pa.
1976
-200
530
21.6
498
99.5
124
.701
5700
00C
4015
0877
0117
Con
odog
uine
t Cre
ek n
ear H
oges
tow
n, P
a.19
12-2
005
7347
075
438
.1.8
53.
9801
5710
00C
4018
3076
5100
Paxt
on C
reek
nea
r Pen
broo
k, P
a.19
40-1
998
3511
.245
730
.1.0
464
.201
5715
00C
4013
2976
5354
Yello
w B
reec
hes C
reek
nea
r Cam
p H
ill, P
a.19
10-2
005
6221
680
934
.21.
606.
2201
5718
20C
4034
5076
2418
Swat
ara
Cre
ek a
t Rav
ine,
Pa.
1996
-200
610
43.9
1,14
00
.67
3.41
0157
2000
C40
3215
7622
40Lo
wer
Litt
le S
wat
ara
Cre
ek a
t Pin
e G
rove
, Pa.
1920
-198
418
34.3
840
0.3
3.6
701
5720
25C
4031
5776
2409
Swat
ara
Cre
ek n
ear P
ine
Gro
ve, P
a.19
89-2
005
1611
693
80
.59
2.67
0157
2190
C40
2845
7631
52Sw
atar
a C
reek
nea
r Inw
ood,
Pa.
1989
-200
517
161
919
0.8
12.
4601
5729
00P
4024
2576
3315
Ree
ds C
reek
nea
r Ono
, Pa.
1962
-198
120
8.69
518
3.64
.29
9.58
0157
3000
C40
2409
7634
39Sw
atar
a C
reek
at H
arpe
r Tav
ern,
Pa.
1889
-200
587
337
754
1.32
1.05
2.92
0157
3160
C40
2034
7633
46Q
uitta
pahi
lla C
reek
nea
r Bel
legr
ove,
Pa.
1975
-199
319
74.2
527
75.6
.41
16.1
0157
3500
C40
2350
7642
35M
anad
a C
r at M
anad
a G
ap, P
a.19
38-1
958
2113
.580
30
.28
.83
0157
3560
C40
1754
7640
05Sw
atar
a C
reek
nea
r Her
shey
, Pa.
1975
-200
531
483
687
12.9
.92
4.99
0157
4000
C40
0456
7643
13W
est C
onew
ago
Cre
ek n
ear M
anch
este
r, Pa
.19
29-2
005
7751
062
56.
171.
453.
2301
5745
00C
3952
4376
5113
Cod
orus
Cre
ek a
t Spr
ing
Gro
ve, P
a.19
30-2
005
3675
.570
316
.83.
623.
7401
5748
00C
3948
5776
3759
EB C
odor
us C
reek
Trib
utar
y ne
ar W
inte
rsto
wn,
Pa.
1960
-197
516
5.23
901
0.3
7.4
701
5750
00C
3955
1476
4457
Sout
h B
ranc
h C
odor
us C
reek
nea
r Yor
k, P
a.19
28-1
995
4311
774
71.
97.9
02.
9101
5760
85C
4008
4175
5920
Littl
e C
ones
toga
Cre
ek n
ear C
hurc
htow
n, P
a.19
82-1
995
145.
8262
551
.01
1.31
0157
6320
P40
1244
7607
30St
ony
Run
at R
eam
stow
n, P
a.19
64-1
995
313.
5652
310
.90
20.4
0157
6500
C40
0300
7616
39C
ones
toga
Riv
er a
t Lan
cast
er, P
a.19
29-2
005
7732
251
844
.31.
038.
0201
5767
54C
3956
4776
2205
Con
esto
ga R
iver
at C
ones
toga
, Pa.
1985
-200
520
470
479
59.7
811
.6
26 Regression Equations for Estimating Flood Flows at Selected Recurrence IntervalsA
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0157
7500
C39
4621
7618
58M
uddy
Cre
ek a
t Cas
tle F
in, P
a.19
29-1
972
1513
365
00.
330.
460.
701
5782
00P
3950
3576
1145
Con
owin
go C
reek
nea
r Buc
k, P
a.19
63-2
005
415.
5365
60
1.28
1.46
0157
8400
C39
5341
7606
50B
ower
y R
un n
ear Q
uarr
yvill
e, P
a.19
63-1
981
195.
9865
525
.4.9
8.0
201
6007
00P
3955
3578
3940
Littl
e W
ills C
reek
at B
ard,
Pa.
1961
-198
121
10.3
1,83
00
.02
.04
0160
1000
C39
4843
7843
00W
ills C
reek
bel
ow H
yndm
an, P
a.19
52-2
005
3814
62,
030
.96
.14
.33
0160
1500
C39
4007
7847
18W
ills C
reek
nea
r Cum
berla
nd, M
d.19
30-1
990
6124
7--
--.0
3--
0160
3500
C39
4723
7838
48Ev
itts C
reek
nea
r Cen
terv
ille,
Pa.
1933
-198
250
30.2
1,62
021
.8.2
2.2
0161
3050
C39
5354
7807
57To
nolo
way
Cre
ek n
ear N
eedm
ore,
Pa.
1963
-200
541
10.7
1,24
00
.14
.91
0161
3500
C39
4323
7803
38Li
ckin
g C
reek
nea
r Syl
van,
Pa.
1931
-194
111
158
1,04
016
.2.7
1.7
201
6140
90C
3955
4877
2623
Con
ococ
heag
ue C
reek
nea
r Fay
ette
ville
, Pa.
1961
-198
121
5.05
1,55
00
.55
001
6145
00C
3942
5777
4928
Con
ococ
heag
ue C
reek
at F
airv
iew,
Md.
1889
-199
064
494
--42
1.35
--01
6389
00P
3947
4577
1150
Whi
te R
un n
ear G
etty
sbur
g, P
a.19
61-1
980
2012
.555
30
2.31
8.64
0300
7800
C41
4907
7817
35A
llegh
eny
Riv
er a
t Por
t Alle
gany
, Pa.
1975
-200
531
248
2,06
00
.09
.94
0300
8000
C41
5340
7820
57N
ewel
l Cre
ek n
ear P
ort A
llega
ny, P
a.19
60-1
978
197.
791,
840
00
.103
0096
80C
4148
3578
2550
Pota
to C
reek
at S
met
hpor
t, Pa
.19
72-1
997
2416
01,
980
0.4
2.8
0301
0500
C41
5748
7823
11A
llegh
eny
Riv
er a
t Eld
red,
Pa.
1916
-200
590
550
1,98
00
1.45
.86
0301
0655
C41
5742
7811
54O
sway
o C
reek
at S
hing
leho
use,
Pa.
1975
-200
531
98.7
2,03
00
.13
.22
0301
1020
C42
0923
7842
56A
llegh
eny
Riv
er a
t Sal
aman
ca, N
.Y.
1904
-199
996
1,61
0--
--1.
040
0301
1800
C41
4559
7843
08K
inzu
a C
reek
nea
r Guf
fey,
Pa.
1966
-200
540
38.8
2,05
00
.64
1.09
0301
3000
C42
1015
7904
10C
onew
ango
Cre
ek a
t Wat
erbo
ro, N
.Y.
1938
-199
456
290
----
4.69
--03
0150
00C
4156
1779
0760
Con
ewan
go C
reek
at R
usse
ll, P
a.19
36-2
005
7081
61,
520
06.
452.
5703
0150
80P
4155
5579
0538
Ack
ley
Run
nea
r Rus
sell,
Pa.
1962
-198
120
9.65
1,90
00
0.1
603
0152
80C
4154
1079
1418
Jack
son
Run
nea
r Nor
th W
arre
n, P
a.19
63-1
979
1712
.81,
650
02.
33.9
0301
5390
P41
5629
7938
41H
are
Cre
ek n
ear C
orry
, Pa.
1964
-198
519
13.6
1,63
00
3.41
.26
0301
5500
C41
5109
7919
03B
roke
nstra
w C
reek
at Y
oung
svill
e, P
a.19
10-2
005
9632
11,
600
02.
961.
0803
0175
00C
4136
0779
0301
Tion
esta
Cre
ek a
t Lyn
ch, P
a.19
38-1
979
4223
31,
760
0.1
11.
2903
0190
00C
4128
2579
2305
Tion
esta
Cre
ek a
t Neb
rask
a, P
a.19
10-1
940
1946
91,
690
0.5
8.8
203
0204
40P
4145
3179
3408
WB
Cal
dwel
l Cre
ek n
ear G
rand
Val
ley,
Pa.
1964
-198
116
4.37
1,68
00
0.0
803
0205
00C
4128
5479
4144
Oil
Cre
ek a
t Rou
sevi
lle, P
a.19
10-2
005
9630
01,
520
01.
321.
1703
0213
50C
4200
5579
4658
Fren
ch C
reek
nea
r Wat
tsbu
rg, P
a.19
75-2
005
3192
1,60
00
2.48
.503
0214
10C
4204
5479
5102
Wes
t Bra
nch
Fren
ch C
reek
nea
r Low
ville
, Pa.
1975
-199
420
52.3
1,47
00
5.25
1.12
0302
1700
C41
5553
8005
02Li
ttle
Con
neau
ttee
Cre
ek n
ear M
cKea
n, P
a.19
61-1
978
183.
61,
440
00
.01
0302
2500
C41
4250
8008
50Fr
ench
Cre
ek a
t Sae
gers
tow
n, P
a.19
13-1
939
1862
91,
420
04.
541.
3903
0225
40C
4141
2680
0254
Woo
dcoc
k C
reek
at B
loom
ing
Valle
y, P
a.19
75-2
005
3131
.11,
450
02.
03.1
803
0230
00C
4140
2080
1255
Cus
sew
ago
Cre
ek n
ear M
eadv
ille,
Pa.
1911
-193
828
90.2
1,25
00
7.31
2.07
Appendix 1 27A
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0302
3500
C41
2815
8001
05Fr
ench
Cre
ek a
t Car
lton,
Pa.
1909
-192
517
998
1,37
00
5.43
2.4
0302
4000
C41
2615
7957
22Fr
ench
Cre
ek a
t Utic
a, P
a.19
13-2
005
381,
030
1,37
00
5.29
2.33
0302
5000
C41
2543
7952
48Su
gar C
reek
at S
ugar
cree
k, P
a.19
33-1
979
4716
61,
440
01.
90.3
103
0252
00C
4125
2079
5059
Patc
hel R
un n
ear F
rank
lin, P
a.19
61-1
978
185.
671,
400
00
.81
0302
6400
P41
1053
7941
25R
iche
y R
un a
t Em
lent
on, P
a.19
63-1
981
195.
691,
390
00
3.18
0302
6500
C41
3752
7834
37Se
venm
ile R
un n
ear R
asse
las,
Pa.
1952
-200
554
7.84
2,07
00
0.1
603
0280
00C
4134
3178
4133
Wes
t Bra
nch
Cla
rion
Riv
er a
t Wilc
ox, P
a.19
55-2
005
5163
1,96
00
.18
1.17
0302
9000
C41
2515
7844
10C
lario
n R
iver
at R
idgw
ay, P
a.19
41-2
004
1230
31,
910
0.9
32.
7103
0292
00P
4119
1779
0439
Cle
ar C
reek
nea
r Sig
el, P
a.19
60-1
981
217.
321,
750
00
.03
0302
9400
C41
2016
7912
50To
ms R
un a
t Coo
ksbu
rg, P
a.19
60-1
978
1912
.61,
570
0.1
71
0302
9500
C41
1950
7912
33C
lario
n R
iver
at C
ooks
burg
, Pa.
1936
-200
567
807
1,78
00
.49
1.38
0303
0500
C41
1133
7926
25C
lario
n R
iver
nea
r Pin
ey, P
a.19
36-2
005
5896
61,
740
0.4
11.
4603
0310
00C
4108
5779
3937
Cla
rion
Riv
er a
t St.
Pete
rsbu
rg, P
a.19
42-1
953
121,
240
1,66
00
.32
1.58
0303
1780
P41
1453
7850
08M
ill C
reek
nea
r Bro
ckw
ay, P
a.19
65-1
981
172.
021,
760
0.1
2.1
203
0319
50C
4059
3079
0526
Big
Run
nr S
pran
kle
Mill
s, Pa
.19
64-1
981
187.
381,
510
00
.503
0325
00C
4059
4079
2340
Red
bank
Cre
ek a
t St.
Cha
rles,
Pa.
1910
-200
596
528
1,56
00
.72
2.79
0303
4000
C40
5621
7900
31M
ahon
ing
Cre
ek a
t Pun
xsut
awne
y, P
a.19
36-2
005
7015
81,
580
0.2
33.
0303
0345
00C
4050
1079
0637
Littl
e M
ahon
ing
Cre
ek a
t McC
orm
ick,
Pa.
1940
-200
566
87.4
1,56
00
0.3
503
0350
00C
4054
0579
1335
Mah
onin
g C
reek
nea
r Day
ton,
Pa.
1917
-194
024
321
1,53
00
1.03
1.79
0303
8000
C40
3917
7920
56C
rook
ed C
reek
at I
daho
, Pa.
1936
-200
570
191
1,27
00
.81
1.21
0303
9000
C40
4313
7930
42C
rook
ed C
reek
at C
rook
ed C
reek
Dam
, Pa.
1910
-199
130
275
1,24
00
1.62
1.09
0303
9200
C40
0249
7849
58C
lear
Run
nea
r Buc
ksto
wn,
Pa.
1961
-197
818
3.68
2,70
00
.25
.36
0304
0000
C40
1708
7855
15St
onyc
reek
Riv
er a
t Fer
ndal
e, P
a.19
14-2
005
9045
22,
160
01.
132.
9403
0410
00P
4020
3778
5307
Littl
e C
onem
augh
Riv
er a
t Eas
t Con
emau
gh, P
a.19
36-2
005
7018
62,
070
0.9
25.
2903
0415
00C
4025
0979
0135
Con
emau
gh R
iver
at S
ewar
d, P
a.19
36-2
005
7072
72,
090
0.9
75.
3503
0420
00C
4028
2479
1101
Bla
cklic
k C
reek
at J
osep
hine
, Pa.
1952
-200
554
192
1,81
00
.19
2.02
0304
2170
P40
3631
7909
49St
oney
Run
at I
ndia
na, P
a.19
64-1
977
134.
511,
340
00
67.1
0304
2200
C40
3345
7856
44Li
ttle Y
ello
w C
reek
nea
r Stro
ngst
own,
Pa.
1961
-198
719
7.36
1,84
00
0.1
903
0425
00C
4031
0279
1019
Two
Lick
Cre
ek a
t Gra
ceto
n, P
a.19
52-2
005
1717
11,
530
0.7
05.
2703
0430
00C
4028
2579
1215
Bla
cklic
k C
reek
at B
lack
Lic
k, P
a.19
05-1
951
4739
01,
650
0.5
73.
5403
0450
00C
4017
3379
2027
Loya
lhan
na C
reek
at K
ings
ton,
Pa.
1940
-200
566
172
1,72
00
.25
2.11
0304
5500
C40
2340
7925
55Lo
yalh
anna
Cre
ek a
t New
Ale
xand
ria, P
a.19
11-1
940
1926
51,
550
01.
084.
903
0475
00C
4032
0579
2755
Kis
kim
inet
as R
iver
at A
vonm
ore,
Pa.
1884
-193
748
1,72
01,
750
01.
424.
3303
0490
00C
4042
5779
4159
Buf
falo
Cre
ek n
ear F
reep
ort,
Pa.
1941
-200
564
137
1,25
00
.05
1.73
0304
9800
C40
3113
7956
18Li
ttle
Pine
Cre
ek n
ear E
tna,
Pa.
1963
-200
542
5.78
1,11
00
026
28 Regression Equations for Estimating Flood Flows at Selected Recurrence IntervalsA
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0306
2500
C39
3745
7957
10D
ecke
rs C
reek
at M
orga
ntow
n, W
.V.
1947
-199
751
63.2
1,77
0--
----
0307
0420
C39
4551
7935
14St
ony
Fork
Trib
utar
y ne
ar G
ibbo
n G
lade
, Pa.
1978
-198
912
.92
1,87
00
00.
1903
0705
00C
3937
1879
4218
Big
San
dy C
reek
nea
r Roc
kvill
e, W
.V.
1888
-199
711
020
02,
070
----
--03
0720
00C
3945
3379
5815
Dun
kard
Cre
ek a
t Sha
nnop
in, P
a.19
41-2
005
6522
91,
220
0.1
4.6
603
0725
90C
3947
4479
4747
Geo
rges
Cre
ek a
t Sm
ithfie
ld, P
a.19
64-1
978
1516
.31,
390
0.1
09.
4503
0728
40C
3959
5180
0231
Tenm
ile C
reek
nea
r Cla
rksv
ille,
Pa.
1969
-197
911
133
1,17
00
.06
3.29
0307
2880
P39
5627
8017
21B
row
ns C
reek
nea
r Nin
eveh
, Pa.
1963
-199
533
17.7
1,25
00
.03
.23
0307
3000
C39
5523
8004
22So
uth
Fork
Ten
mile
Cre
ek a
t Jef
fers
on, P
a.19
32-1
995
6418
01,
210
0.0
62.
2603
0743
00C
3952
0479
4140
Lick
Run
at H
opw
ood,
Pa.
1959
-197
820
3.8
1,99
00
0.8
0307
4500
C39
5848
7945
52R
edst
one
Cre
ek a
t Wal
ters
burg
, Pa.
1943
-200
563
73.7
1,28
00
.27
13.6
0307
8000
C39
4208
1908
12C
asse
lman
at G
rant
svill
e, M
d.19
48-1
990
4362
.5--
--2.
39--
0307
8500
C39
4334
7902
55B
ig P
iney
Run
nea
r Sal
isbu
ry, P
a.19
33-1
970
3824
.52,
560
.45
1.12
.78
0307
9000
C39
5135
7913
40C
asse
lman
Riv
er a
t Mar
klet
on, P
a.19
15-2
005
9138
22,
360
.03
.81
2.09
0308
0000
C39
4913
7919
18La
urel
Hill
Cre
ek a
t Urs
ina,
Pa.
1914
-200
592
121
2,21
00
.65
.71
0308
2200
C40
0059
7925
33Po
plar
Run
nea
r Nor
mal
ville
, Pa.
1961
-197
818
9.27
1,94
00
0.2
303
0825
00C
4001
0379
3538
Youg
hiog
heny
Riv
er a
t Con
nells
ville
, Pa.
1860
-194
150
1,33
02,
260
21.
571.
6603
0830
00C
4006
1879
3001
Gre
en L
ick
Run
at G
reen
Lic
k R
eser
voir,
Pa.
1929
-197
951
3.11
1,91
00
0.0
603
0835
00C
4014
2479
4824
Youg
hiog
heny
Riv
er a
t Sut
ersv
ille,
Pa.
1921
-194
121
1,71
02,
020
1.54
1.27
3.56
0308
3600
P40
1359
7949
06G
illes
pie
Run
nea
r Sut
ersv
ille,
Pa.
1959
-198
121
4.05
1,12
00
011
.603
0840
00C
4027
0179
4250
Abe
rs C
reek
nea
r Mur
rysv
ille,
Pa.
1949
-199
345
4.39
1,16
00
.13
45.1
0308
4500
C40
2309
7945
55Tu
rtle
Cre
ek a
t Tra
fford
, Pa.
1917
-195
538
55.9
1,12
00
.01
22.4
0308
5500
C40
2402
8005
48C
harti
ers C
reek
at C
arne
gie,
Pa.
1916
-200
582
257
1,13
00
.52
26.4
0308
6100
C40
3627
8009
49B
ig S
ewic
kley
Cre
ek n
ear A
mbr
idge
, Pa.
1963
-197
816
15.6
1,09
00
013
.803
0987
00C
4107
2080
3808
Cra
b C
reek
at Y
oung
stow
n, O
hio
1959
-198
224
141,
060
--6.
6531
.803
1000
00C
4130
4580
2815
Shen
ango
Riv
er n
ear T
urne
rsvi
lle, P
a.19
12-1
922
1115
21,
090
022
.61
5.56
0310
1000
C41
2950
8027
55Su
gar R
un a
t Pym
atun
ing
Dam
, Pa.
1935
-195
521
8.59
1,12
00
.32
1.55
0310
2500
C41
2519
8022
35Li
ttle
Shen
ango
Riv
er a
t Gre
envi
lle, P
a.19
14-2
005
8910
41,
210
05.
832.
4703
1029
50C
4126
3480
3518
Pym
atun
ing
Cre
ek a
t Kin
sman
, Ohi
o19
66-2
001
3696
.71,
030
--12
.96
.32
0310
3000
C41
1840
8028
40Py
mat
unin
g C
reek
nea
r Ora
ngev
ille,
Pa.
1914
-196
348
169
1,05
00
12.5
3.6
503
1040
00C
4113
5580
3035
Shen
ango
Riv
er a
t Sha
ron,
Pa.
1912
-193
821
608
1,10
00
11.8
64.
603
1045
00C
4100
0080
2105
Shen
ango
Riv
er a
t New
Cas
tle, P
a.19
13-1
933
2079
81,
090
010
.27
7.11
0310
4760
C41
1110
8019
38H
arth
egig
Run
nea
r Gre
enfie
ld, P
a.19
69-1
980
122.
261,
260
04.
122.
0803
1060
00C
4049
0180
1433
Con
noqu
enes
sing
Cre
ek n
ear Z
elie
nopl
e, P
a.19
16-2
005
9035
61,
190
0.3
510
0310
6500
C40
5302
8014
02Sl
ippe
ry R
ock
Cre
ek a
t Wur
tem
burg
, Pa.
1912
-196
856
398
1,31
00
4.02
2.53
0310
8000
C40
3740
8020
16R
acco
on C
reek
at M
offa
tts M
ill, P
a.19
16-2
005
9017
81,
110
0.5
48.
55
Appendix 1 29A
ppen
dix
1.
Stre
amflo
w-g
agin
g st
atio
ns a
nd b
asin
cha
ract
eris
tics
used
in d
evel
opm
ent o
f flo
od-fl
ow re
gres
sion
equ
atio
ns fo
r Pen
nsyl
vani
a st
ream
s.—
Cont
inue
d
[C, c
ontin
uous
-rec
ord
stat
ion;
P, p
artia
l-rec
ord
stat
ion;
ddm
mss
, deg
rees
, min
utes
, sec
onds
; mi²,
squa
re m
iles;
ft, f
eet;
--, n
ot u
sed
in re
gres
sion
ana
lysi
s]
U.S
. Geo
logi
cal
Surv
ey
stre
amflo
w-
gagi
ng s
tatio
n nu
mbe
r
Type
Latit
ude
(ddm
mss
)Lo
ngitu
de
(ddm
mss
)St
atio
n na
me
Peri
od o
f re
cord
1 (w
ater
ye
ar)2
Num
ber o
f ye
ars
used
in
ana
lysi
s3
Bas
in c
hara
cter
istic
s
Dra
inag
e ar
ea
(mi2 )
Mea
n el
evat
ion
(ft)
Perc
ent
carb
on-
ate
bedr
ock
Perc
ent
stor
age
Perc
ent
urba
n ar
ea
0310
9000
C40
4655
8045
33Li
sbon
Cre
ek a
t Lis
bon,
Ohi
o19
47-1
981
356.
191,
180
--0.
401.
8503
1095
00C
4040
3380
3227
Littl
e B
eave
r Cre
ek n
ear E
ast L
iver
pool
, Ohi
o19
16-2
001
8649
61,
140
--.4
23.
6403
1111
50C
4011
5480
2428
Bru
sh R
un n
ear B
uffa
lo, P
a.19
61-1
985
2110
.31,
190
00
1.11
0421
3000
C41
5537
8036
15C
onne
aut C
reek
at C
onne
aut,
Ohi
o19
23-2
001
6617
51,
010
--2.
731.
7604
2130
40C
4156
4280
2651
Rac
coon
Cre
ek n
ear W
est S
prin
gfie
ld, P
a.19
61-1
995
342.
682
10
6.01
3.61
0421
3075
C41
5931
8017
29B
rand
y R
un n
ear G
irard
, Pa.
1987
-200
519
4.45
898
0.2
29.
104
2132
00P
4205
5480
0435
Mill
Cre
ek a
t Erie
, Pa.
1964
-200
542
9.16
1,05
00
035
.21 P
erio
d of
reco
rd m
ay in
clud
e hi
stor
ical
pea
ks, p
erio
ds o
f flo
w re
gula
tion,
and
bre
aks i
n sy
stem
atic
per
iod
of re
cord
. 2 W
ater
yea
r is d
efin
ed a
s a 1
2-m
onth
per
iod
begi
nnin
g O
ctob
er 1
and
end
ing
Sept
embe
r 30.
The
wat
er y
ear i
s des
igna
ted
by th
e ca
lend
ar y
ear i
n w
hich
it e
nds.
3 Num
ber o
f yea
rs u
sed
in a
naly
sis p
rimar
ily c
onsi
sts o
f the
syst
emat
ic p
erio
d of
reco
rd a
nd m
ay in
clud
e hi
stor
ic p
eak
year
. Bre
aks i
n sy
stem
atic
per
iod
of re
cord
and
flow
-reg
ulat
ed y
ears
are
not
incl
uded
.
30 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
32 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
34 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
36 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
38 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
40 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
42 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
44 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
46 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
48 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
50 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
52 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued
54 Regression Equations for Estimating Flood Flows for Selected Recurrence Intervals
Appendix 2. Flood-flow magnitudes for selected recurrence intervals computed from observed streamflow-gaging station data, predicted from regional regression equations, and a weighted average for streamflow-gaging stations used in analysis.—Continued