Prepared in cooperation with The Nature Conservancy and the New York State

Energy Research and Development Authority

Estimation of Unaltered Daily Mean Streamflow at

Ungaged Streams of New York, Excluding Long Island,

Water Years 1961–2010

Scientific Investigations Report 2014–5220

U.S. Department of the Interior

U.S. Geological Survey
1

2

4

3

5

Cover. 1. Photograph looking upstream from the left bank at station 01349541 – Sugarloaf Brook 

south of Tannersville, N.Y.; photograph by Tim Hoffman, U.S. Geological Survey. 

2. Photograph looking from the right bank at station 01421000 – East Branch Delaware River 

at Fishs Eddy, N.Y. 

3. Photograph looking downstream from the New York State Route 8 bridge, downstream 

from station 01425000 – West Branch Delaware River at Stilesville, N.Y. 

4. Photograph looking downstream from station 01427510 – Delaware River at Callicoon, N.Y. 

5. Photograph looking downstream from station 01426000 – Oquaga Creek at Deposit, N.Y. 

The blue line represents the flow-duration curve of the U.S. Geological Survey New York 

Streamflow Estimation Tool.
Estimation of Unaltered Daily Mean 

Streamflow at Ungaged Streams of New 

York, Excluding Long Island, Water Years 

1961–2010

By Christopher L. Gazoorian

Prepared in cooperation with The Nature Conservancy and the New York State 

Energy Research and Development Authority

Scientific Investigations Report 2014–5220

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Gazoorian, C.L., 2015, Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961–2010: U.S. Geological Survey Scientific Investigations Report 2014–5220, 29 p., 

http://dx.doi.org/10.3133/sir20145220.

ISSN 2328-0328 (online) 
iii

Acknowledgements

The author thanks Stacey Archfield of the U.S. Geological Survey for providing technical 

expertise and support on the use of the QPPQ and map correlation method and her technical 

review of the report. The author also thanks Marla Stuckey, Gary Firda, John Williams, and 

Ken Pearsall of the U.S. Geological Survey for their technical review of the report and the New 

York Streamflow Estimation Tool and Martyn Smith, Doug Freehafer, Elizabeth Nystrom, James 

Ulrich, and Jeremy Newson for their data analysis and geographic information system and 

programming support for the New York Streamflow Estimation Tool.

v

Contents

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

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

Background and Problem....................................................................................................................2

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

Previous Studies ...................................................................................................................................2

Purpose and Scope ..............................................................................................................................2

Estimation of Unaltered Daily Mean Streamflow .....................................................................................4

Reference Streamgages in New York and Surrounding States....................................................5

Selection Criteria .........................................................................................................................5

Record Extension Techniques ...................................................................................................5

Regression Analysis.............................................................................................................................8

Flow-Duration Curve Statistics..................................................................................................9

Basin Characteristics..................................................................................................................9

Regression Against Basin Characteristics..............................................................................9

Estimation of Streamflow Time Series from a Reference Streamgage .....................................15

Map Correlation ..................................................................................................................................15

Using the New York Streamflow Estimation Tool for Estimating Unaltered Daily Mean

Streamflow for Ungaged Locations ............................................................................................15

Accuracy and Limitations of Estimated Unaltered Streamflows.........................................................17

Summary........................................................................................................................................................25

References Cited..........................................................................................................................................26

Appendix 1. Flow-Duration Exceedance Probabilities, Observed and Computed From

Streamflow Data, and Regression Equations for Streamgages Used in Regression

Analysis ........................................................................................................................................29

Appendix 2. Description of Reference Streamgages Used in the Development of the New

York Streamflow Estimation Tool With Period of Record and Use of Data .......................29

Appendix 3. Reference Streamgages With Index Streamgage Used for MOVE.3 Record

Extension......................................................................................................................................29

Appendix 4. Basin Characteristics Used in the Development of Flow-Duration Regression

Equations......................................................................................................................................29

Appendix 5. User’s Guide for the New York Streamflow Estimation Tool (NYSET) .......................29

Figures

1. Map showing physiographic provinces of New York.............................................................3

2. Graphs showing the QPPQ method (Fennessey, 1994) used in the New York

Streamflow Estimation Tool (NYSET) showing A, observed daily mean streamflow

at a reference streamgage, B, flow-duration curve at the reference streamgage, C,

constructed flow-duration curve at the ungaged location, and D, estimated daily

mean streamflow at the ungaged location; modified from Stuckey and others (2012).....4

3. Map showing location of U.S. Geological Survey reference streamgages in and

near New York...............................................................................................................................6

4. Map showing location of U.S. Geological Survey reference streamgages and

National Weather Service climate divisions............................................................................7
vi

5. Example correlation map for U.S. Geological Survey streamgage 01312000, Hudson

River near Newcomb, N.Y. ........................................................................................................16

6. Screen capture of summary report generated by the New York Streamflow

Estimation Tool showing flow-duration curves and a hydrograph.....................................18

7. Graphs showing comparison of observed and New York Streamflow Estimation

Tool estimated daily mean streamflows for U.S. Geological Survey streamgages

A, 01414500 Mill Brook near Dunraven, N.Y. and B, 04213500 Cattaraugus Creek at

Gowanda, N.Y..............................................................................................................................21

8. Boxplots showing distribution of, A, Nash-Sutcliffe efficiency values and B,

root-mean-square error by major river basin obtained from comparison between

observed and estimated daily mean streamflows ................................................................23

9. Graphs showing flow-duration curves and hydrographs showing estimated and

observed daily mean flows for U.S. Geological Survey streamgages, A, 04221500,

Genesee River at Scio, N.Y. and, B, 04232100, Sterling Creek at Sterling, N.Y. %,

percent .........................................................................................................................................24

Tables

1. Period and duration of drought when the lowest Palmer drought severity index

occurred during the 1960s drought in streams of New York, excluding Long Island........8

2. Basin characteristics used in the development of regression equations for

flow-duration exceedance probabilities for New York streams.........................................10

2. Basin characteristics used in the development of regression equations for

flow-duration exceedance probabilities for New York streams.........................................11

2. Basin characteristics used in the development of regression equations for

flow-duration exceedance probabilities for New York streams.........................................12

3. Regression coefficients for use with flow-duration exceedance probability

regression equations for New York streams, excluding Long Island ................................14

4. Comparison of low-flow statistics calculated by empirical ranking method and

log-Pearson type III curve fitting at reference stations with observed flows for the

period April 1, 1961, to March 31, 2010....................................................................................19

5. Nash-Sutcliffe efficiencies from comparison of the New York Streamflow

Estimation Tool estimated daily-mean values to observed values at reference gages .22

6. Normalized root-mean-square errors as percentage from comparison of the New

York Streamflow Estimation Tool estimated daily-mean values to observed values

at reference gages .....................................................................................................................22

7. Basin characteristics used in development of regression equations to estimate

flow-duration exceedance probabilities with the New York Streamflow Estimation

Tool for basins in New York.......................................................................................................25
vii

Conversion Factors

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2) 

Flow rate

cubic foot per second (ft3

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

cubic foot per second per square 0.01093 cubic meter per second per 

mile [(ft3

/s)/mi2] square kilometer [(m3/s)/km2]

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

°C = (°F – 32) / 1.8.

Datum

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).

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

Abbreviations

BaSE Baseline Streamflow Estimator

CY climate year

FDC flow-duration curve

GIS geographic information system

GNWISQ get NWIS Web streamflow data files

LOC line of organic correlation

LP3 log-Pearson type III

MA SYE Massachusetts Sustainable-Yield Estimator

MOVE maintenance of variance

NLCD National Land Cover Database 2006

NS Nash-Sutcliffe efficiency

NWIS National Water Information System

OLS ordinary least squares

Pn nth percentile from flow-duration curve
viii

PRISM Parameter-elevation Regressions on Independent Slopes Model

QPPQ Methodology that equates streamflow as a percentile from a flow-duration curve for 

a particular day at a hydrologically similar reference streamgage with streamflow as 

a percentile from the flow-duration curve for the same day at an ungaged location

RMSE root-mean-square error

SREF Streamflow Record Extension Facilitator

WY water year
Estimation of Unaltered Daily Mean Streamflow at 

Ungaged Streams of New York, Excluding Long Island, 

Water Years 1961–2010

By Christopher L. Gazoorian

Abstract

The lakes, rivers, and streams of New York State provide 

an essential water resource for the State. The information 

provided by time series hydrologic data is essential to 

understanding ways to promote healthy instream ecology and 

to strengthen the scientific basis for sound water management 

decision making in New York. The U.S. Geological Survey, 

in cooperation with The Nature Conservancy and the New 

York State Energy Research and Development Authority, 

has developed the New York Streamflow Estimation Tool to 

estimate a daily mean hydrograph for the period from October 

1, 1960, to September 30, 2010, at ungaged locations across 

the State. The New York Streamflow Estimation Tool produces 

a complete estimated daily mean time series from which daily 

flow statistics can be estimated. In addition, the New York 

Streamflow Estimation Tool provides a means for quantitative 

flow assessments at ungaged locations that can be used to 

address the objectives of the Clean Water Act—to restore and 

maintain the chemical, physical, and biological integrity of the 

Nation’s waters.

The New York Streamflow Estimation Tool uses data 

from the U.S. Geological Survey streamflow network for 

selected streamgages in New York (excluding Long Island) 

and surrounding States with shared hydrologic boundaries, 

and physical and climate basin characteristics to estimate the 

natural unaltered streamflow at ungaged stream locations. 

The unaltered streamflow is representative of flows that are 

minimally altered by regulation, diversion, or mining, and 

other anthropogenic activities. With the streamflow network 

data, flow-duration exceedance probability equations were 

developed to estimate unaltered streamflow exceedance 

probabilities at an ungaged location using a methodology 

that equates streamflow as a percentile from a flow-duration 

curve for a particular day at a hydrologically similar reference 

streamgage with streamflow as a percentile from the flowduration curve for the same day at an ungaged location. 

The reference streamgage is selected using map correlation, 

a geostatistical method in which variogram models are 

developed that correlate streamflow at one streamgage with 

streamflows at all other locations in the study area. Regression 

equations used to predict 17 flow-duration exceedance 

probabilities were developed to estimate the flow-duration 

curves at ungaged locations for New York using geographic 

information system-derived basin characteristics.

A graphical user interface, with an integrated spreadsheet 

summary report, has been developed to estimate and display 

the daily mean streamflows and statistics and to evaluate 

different water management or water withdrawal scenarios 

with the estimated monthly data. This package of regression 

equations, U.S. Geological Survey streamgage data, and 

spreadsheet application produces an interactive tool to 

estimate an unaltered daily streamflow hydrograph and 

streamflow statistics at ungaged sites in New York. Among 

other uses, the New York Streamflow Estimation Tool can 

assist water managers with permitting water withdrawals, 

implementing habitat protection, estimating contaminant 

loads, or determining the potential affect from chemical spills.

Introduction

The lakes, rivers, and streams of New York provide an 

essential water resource for the State. The U.S. Geological 

Survey (USGS) operates more than 240 streamgages in New 

York, but these streamgages only monitor a fraction of the 

thousands of rivers and streams that carry water throughout 

the State. This information quantifies the daily mean flows, 

allows for estimating streamflow statistics such as flowduration exceedances, and helps water managers to understand 

the natural flow regime of a stream, which is critical to the 

sustainability and health of aquatic freshwater ecosystems 

(Vogel and others, 2007; Poff and Zimmerman, 2010). Water 

management agencies require an understanding of natural and 

low streamflow characteristics for planning and management 

of waste-loads to streams, permitting streamflow alterations, 

water-quality evaluations, water-supply design, groundwater 

management, and aquatic-habitat protection.

The U.S. Geological Survey cooperated in a study with 

The Nature Conservancy and the New York State Energy 

Research and Development Authority to develop a tool for 

estimating continuous daily mean streamflow and streamflow 
2 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

statistics at ungaged locations for the period from October 

1, 1960, to September 30, 2010. The New York Streamflow 

Estimation Tool (NYSET) estimates daily streamflow 

hydrographs using data from existing USGS streamgages 

coupled with explanatory basin characteristics. A graphical 

user interface, with an integrated spreadsheet summary report, 

has been developed to display the estimated daily streamflow 

statistics and evaluate different water management or water 

withdrawal scenarios with the estimated monthly data. 

Among other uses, the NYSET can assist water managers 

with permitting water withdrawals, implementing habitat 

protection, estimating contaminant loads, or determining the 

potential affect from chemical spills.

Background and Problem

The seasonal variability of streamflows in New York 

makes it more challenging for water managers to protect 

the natural ecosystem during months with lower flows. 

Streamflow in many streams in New York are primarily 

sustained by the base flows from adjacent aquifers and 

meltwater runoff from upland parts of the basin. Typically, 

the period from about late June through early October 

(corresponding to the growing season) is when streamflows 

are reduced to their lowest levels of the year and recharge to 

aquifers is reduced. Similarly, the annual minimum streamflow 

at many USGS streamgages in New York is often observed 

during late summer and early fall (U.S. Geological Survey, 

2012). This naturally occurring low flow period, combined 

with permitted water withdrawals, effluent discharges and 

increased demand for water can create a shortage of available 

water and damage to the natural ecosystem. Additionally, 

changes in climate patterns, such as droughts or floods, and 

changes in land use, such as increased industrial and suburban 

growth, may increase alteration to streamflows and aquatic 

biota natural to the lakes and streams of New York.

Physical Setting

The State of New York occupies all or part of eight 

physiographic provinces that differ widely, from the highrelief areas of the Adirondack and Catskill Mountains to the 

low-relief areas along the Great Lakes and in the valleys of 

the Hudson, Mohawk, and St. Lawrence Rivers (fig. 1). Long 

Island, which is excluded from the study area of this report, 

is located in the Coastal Plain province (Fenneman, 1938; 

Lumia and others, 2006). The provinces included in this study 

represent basins with diverse physical characteristics found 

throughout the State.

The St. Lawrence Valley province lies at the extreme 

northern border of New York and is primarily smooth glacial 

plain. The Adirondack province lies in the northern part of 

New York and covers an area of about 10,000 square miles 

(mi2). The western half of the province is a plateau and has 

an abundance of lakes and ponds, whereas the eastern half is 

mostly mountainous. The northern part of western New York 

lies in the Central Lowlands, whereas most of the central and 

southern areas of western New York are in the Appalachian 

Plateau province. The Appalachian Plateau province is mostly 

hilly terrain, with the highest elevations being in the Allegheny 

and Catskill Mountains. Southeastern New York lies in the 

Valley and Ridge, New England, and Piedmont provinces 

(Fenneman, 1938; Lumia and others, 2006).

Previous Studies

Before this study, regression equations to estimate flowduration exceedance probabilities for ungaged streams in 

all of New York had not been developed nor were there any 

statewide tools available for estimating low- and natural-flow 

characteristics for ungaged streams in New York. Lowflow statistics were presented by Eissler (1979) at gaged 

sites across New York State for the minimum 7-day, 2-year 

discharge (7Q2) and the minimum 7-day, 10-year discharge 

(7Q10) which are the annual lowest mean discharges for 

7 consecutive days with a 2-year and 10-year recurrence 

interval, respectively. Previous regression studies include 

regression equations to estimate 7Q10 and 7Q2 low flow 

values for ungaged drainages in the lower Hudson River Basin 

(Barnes, 1986), and another, more recent study focused on low 

flow statistics in the Susquehanna River Basin (not shown; 

Randall, 2010).

Similar tools for estimating daily streamflow and 

assessing water availability were developed by the USGS in 

Massachusetts (Massachusetts Sustainable Yield Estimator 

[MA SYE]) and Pennsylvania (Baseline Streamflow Estimator 

[BaSE]; Archfield and others, 2010; Stuckey and others, 

2012). The MA SYE, BaSE, and NYSET tools all apply the 

QPPQ method introduced by Fennessey (1994) and used by 

Hughes and Smakhtin (1996), Smakhtin (1999), Smakhtin and 

Masse (2000), Mohamoud (2008) , Shu and Ourda (2012), 

and Linhart and others (2013). The MA SYE and BaSE tools 

have been effective at estimating the natural unaltered daily 

streamflow hydrograph at ungaged locations in their respective 

study areas and provide user-friendly ways of computing 

streamflow statistics commonly used for water resource 

management and habitat protection.

Purpose and Scope

This report describes the New York Streamflow 

Estimation Tool (NYSET, version 1.0) to estimate streamflow 

at ungaged sites in New York for water years1 (WYs) 1961 

to 2010 and documents the methods used to develop the 

tool. Parameter-based regression equations used to predict 

17 exceedance probabilities from the flow-duration curve 

(FDC) for ungaged streams in New York and flow-duration 

1

A water year runs from October 1 through September 30 and is designated 

by the year in which it ends.
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-74° -76° -78° -80°

45°44°43°42°41°

95

Base from U.S. Geological Survey 1:2,000,000 and 1:100,000 digital dataUniversal Transverse Mercator Projection, Zone 18N, North American Datum 1983

NEW YORK

VERMONT

MASSACHUSETTS

CONNECTICUT

NEW

JERSEY

PENNSYLVANIA

CANADA

Lake Ontario

Lake Erie

EXPLANATION

Physiographic province

Adirondack MountainsAppalachian PlateauCentral LowlandsLong IslandNew England

Piedmont ProvinceSt. Lawrence ValleyValley and Ridge Province

# U.S. Geological Survey streamgage

0 100 MILES 25 50 75

25 100 KILOMETERS 0 50 75

Figure 1. Physiographic provinces of New York; modified from Lumia and others (2006).
4 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

exceedance probabilities for 90 streamgages are presented 

(appendix 1). Streamflow data from continuous-record 

streamgages were used to develop correlation maps of the 

estimated correlation of streamflow between a reference 

streamgage and an ungaged location. Documentation on 

the proper use, functionality, and limitations of the tool also 

are presented in this report. A user’s manual for NYSET is 

included (appendix 5).

Estimation of Unaltered Daily 

Mean Streamflow

Daily mean streamflow for unaltered ungaged locations 

on streams in New York is estimated for WYs 1961 to 

2010). The QPPQ method is used to estimate unaltered daily 

mean streamflow (fig. 2), which assumes equivalence of 

streamflow, as a percentile from the FDC for a particular day 

at a reference streamgage, where streamflow is measured, 

to the streamflow as a percentile from the FDC for the same 

day at an ungaged location (Fennessey, 1994; Hughes and 

Smakhtin, 1996; Smakhtin, 1999; Smakhtin and Masse, 2000; 

Mohamoud, 2008; Archfield and others, 2010; Shu and Ourda, 

2012; Stuckey and others, 2012; Linhart and others, 2013). 

The reference streamgage must be unaltered by regulation. 

Stuckey and others (2012) define a reference streamgage as a 

composite of the upstream land cover, geology, and hydrologic 

characteristics that can be used to represent ungaged basins 

with similar characteristics. A set of reference streamgages 

from the streamgage network in New York and surrounding 

States was identified to estimate correlations with ungaged 

locations. Where necessary, each reference streamgage record 

was extended by streamflow record extension methods to 

establish a common period of streamflow record. For this 

study the period from WYs 1961 to 2010 is used.

The FDC, a cumulative frequency curve that shows the 

percentage of time that specified streamflows are equaled 

or exceeded (Searcy, 1959), was constructed using the 

complete records for each of the reference streamgages. An 

FDC is built by sorting streamflows observed during a given 

Reference streamgage streamflow

Date

Ungaged streamflow

Date

Exceedance probability

Reference streamgage streamflow

Exceedance probability

Ungaged streamflow

A

D C

B

Figure 2. The QPPQ method (Fennessey, 1994) used in the New York Streamflow Estimation Tool (NYSET) showing A, observed daily 

mean streamflow at a reference streamgage, B, flow-duration curve at the reference streamgage, C, constructed flow-duration curve at 

the ungaged location, and D, estimated daily mean streamflow at the ungaged location; modified from Stuckey and others (2012).
Estimation of Unaltered Daily Mean Streamflow 5

period of time by magnitude and calculating the probability 

a specified streamflow value will be equaled or exceeded. 

For this report, the percentage of time that the streamflow is 

equaled or exceeded is termed exceedance probability, and 

an individual exceedance probability is termed percentile. 

Exceedance probability is used for discussing statistics and 

percentile is used for discussing methodology associated with 

a generic FDC.

At an ungaged location, the FDC is constructed from 

point estimates of streamflow for 17 exceedance probabilities. 

Regression equations, developed using physical and climatic 

basin characteristics and streamflow data from a subset of 

reference streamgages, are applied to estimate each of the 

17 exceedance probabilities. To construct a continuous daily 

FDC, streamflow at all other exceedance probabilities was 

determined by log-log interpolation, completing the FDC 

between the 17 exceedances. Thus, a FDC consisting of 

18,262 streamflow exceedances (one value for each day in 

WYs 1961–2010) is produced to represent the complete range 

of calculable percentile flows at the ungaged location.

When estimating unaltered daily mean streamflow, the 

selection of the reference streamgage is very important in 

attaining the best estimate of daily streamflow at the ungaged 

location. A methodology developed by Archfield and Vogel 

(2010), spatial map correlation, is used to select a reference 

streamgage. Spatial map correlation is a geostatistical 

procedure whereby a reference streamgage is selected whose 

streamflow demonstrates the strongest estimated correlation 

with an ungaged location. Though a nearby streamgage 

commonly exhibits strong estimated correlations, this method 

is unlike the frequently used method of selecting only from 

nearby sites, which assumes the nearest streamgages are 

the best correlated to the ungaged location (Archfield and 

Vogel, 2010).

Reference Streamgages in New York and 

Surrounding States

A total of 121 reference streamgages were selected for 

this study (fig. 3); 115 in New York, 3 in Massachusetts, 2 

in Vermont, and 1 in Pennsylvania (site identifier 76 near 

Waverly, N.Y.). The streamgages used in the study have 

a contributing drainage area that lies in all or parts of all 

physiographic regions that occur in New York, excluding the 

Coastal Plain of Long Island.

Selection Criteria

The criteria for selecting appropriate streamgages include 

streamflow minimally altered by regulation, diversion, or 

mining, and other anthropogenic activities, no days with zero 

flow, and at least 20 years of continuous record; however, 

two streamgages with fewer than 20 years of record were 

included to increase spatial coverage and basin characteristic 

diversity. The average number of years of record is 49.8 years. 

Minimally regulated streamgages for this analysis are those 

with upstream reservoir impoundments that control less than 

15 percent of the contributing drainage area at the streamgage 

and alter less than half the exceedance flows along the FDC. 

For streamgages with at least 20 years of unregulated flow 

data recorded before the impoundment was constructed; 

only the period before the start of regulation was used in the 

analysis. Information on diversions was obtained from USGS 

annual water data reports (data for 2006 and later only, http://

wdr.water.usgs.gov/; data before 2006, in paper format on file 

at the USGS New York Water Science Center).

To avoid using reference streamgage basins with 

potential anthropogenic effects on streamflow, the percentage 

of impervious area within a reference streamgage basin was 

limited to less than 10 percent. The average percentage of 

area classified as impervious from the National Land Cover 

Database (NLCD) 2006 (Fry and others, 2011) for the 

streamgages selected for regression analysis is 0.8 percent; 

with a maximum of 6.7 percent. Additionally, the average 

percent of area classified as urban from NLCD 2006 for the 

streamgages selected for the analysis is 5.4; with the two 

basins with the greatest percent area classified as urban are 

29.5 and 29.1 percent urban.

An additional criterion for reference streamgages to 

also be included in the regression analysis for estimating 

flow-duration exceedance probabilities is that the observed 

period of record must include the drought of record for the 

National Weather Service climate division in which the basin 

is located (fig. 4, table 1). This was determined based on the 

monthly Palmer drought severity index (PDSI) as computed 

by the National Climatic Data Center for the period of record, 

January 1895 through April 2013 (Northeast Regional Climate 

Center, 2011). All reference streamgages where the period 

of greatest PDSI did not occur within the observed period of 

daily record were excluded from the regression analysis. This 

ensures that the observed FDCs for all streamgages include 

the same period of extreme drought that occurred in the 1960s 

defining the low-flow part of the flow-duration curve. Of the 

121 reference streamgages, 90 met this additional criterion. 

A complete listing of streamgages used in the analysis and if 

they were used in regression analysis and (or) a time-series 

reference streamgage, is presented in appendix 2.

Record Extension Techniques

A complete daily streamflow record at the reference 

streamgage for the period of interest (WYs 1961 to 2010) 

is required to estimate daily mean streamflow using the 

QPPQ method for any ungaged stream location. Of the 121 

selected reference streamgages, 26 had a complete record 

with unregulated flow for the entire period of interest. The 

remaining streamgages had record lengths of 9 to 88 years 

that included none or part of the period of interest. Streamflow 

records that did not include the complete period of interest 

were extended to complete the WY 1961 to 2010 period using 

the Streamflow Record Extension Facilitator (SREF; Granato, 
6 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010 EXPLANATION

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Base from U.S. Geological Survey 1:2,000,000 and 1:100,000 digital dataUniversal Transverse Mercator Projection, Zone 18N, North American Datum 1983

NEW YORK

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CONNECTICUT

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JERSEY

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Lake Ontario

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Figure 3. Location of U.S. Geological Survey reference streamgages in and near New York.
Estimation of Unaltered Daily Mean Streamflow 7

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Lake Ontario

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EXPLANATION

Climate divisions

Central Lakes, NYChamplain Valley, NYEastern Plateau, NYGreat Lakes, NYHudson Valley, NYMohawk Valley, NYNorthern Plateau, NYNorthern, NJ

Northwest Plateau, PANorthwest, CTPocono Mountains, PASoutheastern, VTSt. Lawrence Valley, NYUpper Susquehanna, PAWestern Plateau, NYWestern, MAWestern, VT

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NEW YORK

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JERSEY

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45°44°43°42°41°

0 100 MILES 25 50 75

25 100 KILOMETERS 0 50 75

; from Northeast Regional eather Service climate divisions Location of U.S. Geological Survey reference streamgages and National W Figure 4.

Climate Center (2011).
8 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

Table 1. Period and duration of drought when the lowest Palmer drought severity index occurred during the 

1960s drought in streams of New York, excluding Long Island.

[Data are from Northeast Regional Climate Center (2011). PDSI, Palmer drought severity index]

Climate division Drought period Duration Lowest PDSI 

Central Lakes, N.Y. 12/1960–1/1961 2 months -4.18 in 1/1961

Champlain Valley, N.Y. 11/1964–7/1965 9 months -4.61 in 7/1965

Eastern Plateau, N.Y. 8/1964–2/1966 19 months -5.99 in 11/1964

Great Lakes, N.Y. 11/1960–1/1961 3 months -5.09 in 1/1961

Hudson Valley, N.Y. 5/1964–9/1966 29 months -6.66 in 11/1964

Mohawk Valley, N.Y. 9/1964–1/1965 5 months -4.62 in 11/1964

Northern Plateau, N.Y. 10/1964–7/1965 10 months -4.18 in 7/1965

St. Lawrence Valley, N.Y. 11/1960–1/1961 3 months -3.89 in 1/1961

Upper Susquehanna, Pa. 8/1964–1/1966 18 months -5.87 in 12/1964

Western, Mass. 6/1964–9/1966 28 months -5.48 in 11/1964

Western, Vt. 9/1964–9/1965 13 months -5.22 in 7/1965

Western Plateau, N.Y. 11/1960–1/1961 3 months -4.64 in 1/1961

2009). The number of incomplete years of record during WYs 

1961 to 2010 that required years of record extension range 

from 1 to 50 years with an average of 21 years. Streamflow 

data estimated by the years of record extension analysis 

were not used in the development of regression equations or 

correlation maps.

The SREF methodology relies on the assumption that 

long-term (greater than 10 years) streamflow records from 

hydrologically similar streamgages can be used to estimate 

missing records at a streamgage of interest (Granato, 2009). 

The SREF program produces estimated daily mean streamflow 

at streamgages with limited data for extending or augmenting 

the streamflow record (Granato, 2009). The line of organic 

correlation (LOC) regression as part of a maintenance of 

variance (MOVE) method is applied for record extension in 

SREF. The LOC for streamflow record extension can predict 

flows with variance and probability distribution that closely 

estimate those of the observed record (Helsel and Hirsch, 

1992). The MOVE.3 method (Vogel and Stedinger, 1985) was 

used for this analysis.

For this study, streamgages used to extend the record of a 

streamgage with an incomplete period of record during WYs 

1961 to 2010 are referred to as “index streamgages.” To ensure 

a reasonable application of MOVE.3, an index streamgage 

was considered only if there is at least 10 years of concurrent 

record with the incomplete streamgage record. The 10 years 

of concurrent record do not need to occur within the historical 

period of interest (WYs 1961–2010). The period-of-record at 

the index streamgages was analyzed for correlation and record 

extension procedures. The records outside of WYs 1961 to 

2010 were removed after the streamflow record extensions 

were completed. A maximum of two streamgages was used 

for record extension (appendix 3). The period of available 

concurrent record, strength of correlation, and distribution 

of LOC residuals were all considered during selection of the 

index streamgages. To ensure a good fit (similar hydrologic 

conditions) between the index streamgage and a streamgage 

with an incomplete period of record, the concurrent records 

were evaluated graphically and statistically using correlation 

and the coefficient of determination (R2

) statistic. Record 

extension correlations ranged from 0.83 to 0.99, with a mean 

of 0.94. Streamflows were log transformed before LOC 

regression. A listing of streamgages that required record 

extension techniques and the index streamgages used to extend 

the records is provided in appendix 3.

Regression Analysis

To estimate points along a FDC at ungaged locations, 

observed streamflow data through WY 2010 from 90 of the 

121 reference streamgages in New York and surrounding 

States were used to develop regression equations for 

17 percentiles along the FDC (appendix 1). Physical and 

climate basin characteristics known to potentially affect 

a range of streamflow, such as basin slope, soil properties 

and precipitation were computed for the basins draining 

to the streamgage locations and flow-duration exceedance 

probabilities were computed for the streamgages using the 

entire period of observed unregulated flow. The flow-duration 

exceedance probabilities (dependent variable) were related 

to the basin characteristics (independent or explanatory 

variables) using regression analysis for all 17 exceedance 

probabilities. To complete the FDC the remaining streamflow 

exceedance probabilities are determined by log-log 

interpolation, building a continuous daily FDC.
Estimation of Unaltered Daily Mean Streamflow 9

Flow-Duration Curve Statistics

Using the program Get NWIS WEB Streamflow Files 

(GNWISQ; Granato, 2009), daily streamflow values for 

the selected streamgages were compiled from the National 

Water Information System (NWIS) Web application (http://

waterdata.usgs.gov/nwis). GNWISQ provides an easy-to-use 

interface for batch downloads from NWIS and formats the 

retrieved files for further analysis. The downloaded observed 

daily streamflows were reviewed for completeness and 

accuracy then ranked, using the Weibull plotting position, to 

compute an exceedance probability for each corresponding 

ranked streamflow (Stedinger and others, 1993). The observed 

period of record for unregulated flow at a streamgage was used 

for computing the flow-duration exceedance probabilities used 

in the regression analysis. No estimated data from the record 

extension analysis were used to develop regression equations.

Basin Characteristics

A total list of 85 climate and physical basin 

characteristics, which potentially may affect a range of 

streamflow exceedances, was compiled from various GIS 

sources (table 2). Basin characteristics derived with Arc Hydro 

for Esri ArcGIS 10.0 were used exclusively to improve the 

consistency, reproducibility, and ease-of-use of the resulting 

regression equations. Some basin characteristics evaluated 

were used in previous regression analysis in New York (Lumia 

and others, 2006).

Many of the physical basin characteristics including 

drainage area, slope and geographic locations of basin 

centroids and outlets were derived using digital elevation 

maps (DEM; U.S. Geological Survey, 2000). Most climate 

basin characteristics were raster-based datasets retrieved from 

the PRISM in 800-meter resolution for the normal (30-year) 

period from 1971 to 2000 (Daly, 1996). The two climate 

variable exceptions were mean annual runoff based on gridded 

contour maps produced by the USGS (Randall, 1996) and 

the median seasonal maximum snow depth (Cember and 

Wilks, 1993). Randall (1996) produced mean annual runoff 

maps incorporating 1951 to 1980 climate normal, streamflow 

and local surficial geology data. A similar analysis of mean 

annual runoff for New York has not been completed using 

more recent data; therefore, the data from Randall (1996) were 

considered the most reliable for this study.

The SSURGO (U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011) provided nearly 

complete raster coverages of soil properties for New York 

State. However, there were gaps in the data, primarily in 

the Adirondack region. To fill in these gaps and extend the 

area of soils coverage statewide, the Digital General Soil 

Map of the United States (STATSGO2) dataset was used in 

areas of incomplete coverage by SSURGO. The STATSGO2 

dataset has the same data structure as SSURGO, but with 

a 1:250,000 resolution compared with SSURGO with a 

1:24,000 resolution (U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2013). No STATSGO2 data 

were used in regression equation development, but are needed 

to apply the regression equations to ungaged stream locations 

whose basins lie in part, or completely, within areas where 

SSURGO data are unavailable.

Regression Against Basin Characteristics

To relate basin characteristics to the observed flowduration exceedance probabilities, exploratory ordinary least 

squares (OLS) and weighted least squares (WLS) regression 

techniques were applied (Tasker, 1980; Helsel and Hirsch, 

1992). Flow-duration exceedance probabilities were weighted 

for the WLS regression technique using (number of days of 

record at streamgage divided by sum of days of record of all 

streamgages) to apply weights accounting for differing periods 

of record (Stuckey and others, 2012). This method results in 

longer periods of record being assigned greater weight in the 

regression with the assumption that the daily flow statistics, 

particularly variance, are better defined with a longer record. 

Regression iterations were completed using the statistical 

software package R (R Core Team, 2013) with additional 

functionality from R packages MASS (Venables and Ripley, 

2002), leaps (Lumley, 2009), and MPV (Braun, 2013). The 

regression diagnostics used to assess the resulting regressions 

include graphical relations, multicollinearity, prediction 

error sum of squares (PRESS) statistics, variance inflation 

factor (VIF) statistics, standard errors, and coefficients of 

determination (R2

; Helsel and Hirsch, 1992).

Data from the 90 streamgages were used to develop 

regression equations to estimate the 1-, 5-, 10-, 15-, 20-, 

25-, 35-, 50-, 65-, 75-, 80-, 85-, 90-, 95-, and 99-percent 

flow-duration exceedance probabilities (P1, P5, P10, P15, 

P20, P25, P35, P50, P65, P75, P80, P85, P90, P95, and P99, 

respectively). To represent the extreme ends of the FDC 

from WYs 1961 to 2010, two additional regression equations 

were developed for the 0.0055- and 99.9945-percent flowduration exceedance probabilities (P0.0055 and P99.9945, 

respectively). The P00.0055 and P99.9945-percent exceedance 

probabilities are the largest and smallest possible daily 

streamflow quantiles calculated using the Weibull plotting 

position for a record containing 18,262 daily streamflow 

values. Limited to observed data for the regression analysis, 

the number of streamgages used to develop the regression 

equations for the lower and upper ends of the FDC was 

restricted to those streamgages with a period of record 

including at least 18,262 daily streamflow values. Regression 

equations to estimate the P0.0055 and P99.9945 were 

developed using data from 46 streamgages (appendix 1) in and 

near New York. Additional streamgages, originally considered 

for inclusion in the regression analysis were removed from 

the analysis before the final equations were developed. 

Outliers and streamgages with high leverage or influence 

were only removed from regression analysis if sufficient 

data or information were found to support the removal of 

the streamgages, such as questionable levels of regulation 
10 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

Table 2. Basin characteristics used in the development of regression equations for flow-duration exceedance probabilities for New 

York streams.

[ft, feet; NLCD, National Land Cover Database; DEM, digital elevation model; mi2, square miles; mi, miles; PRISM, Parameter-Elevation Regressions on Independent Slopes Model ; in., inches; °F, degrees Fahrenheit; ft/mi, feet per mile; m, meters; SSURGO, Soil Survey Geographic database; 

UTM, Universal Transverse Mercator]

Basin characteristic Source Reference

Agricultural, in percent of basin area NLCD 2006 Fry and others (2011)

Basin at elevation greater than 1,000 ft, in percent of basin area DEM U.S. Geological Survey (2000)

Basin at elevation greater than 1,200 ft, in percent of basin area DEM U.S. Geological Survey (2000)

Basin at elevation greater than 2,000 ft, in percent of basin area DEM U.S. Geological Survey (2000)

Basin at elevation greater than 500 ft, in percent of basin area DEM U.S. Geological Survey (2000)

Drainage area, in mi2 DEM U.S. Geological Survey (2000)

Elevation of basin centroid, in ft DEM U.S. Geological Survey (2000)

Elevation of basin outlet, in ft DEM U.S. Geological Survey (2000)

Forested, in percent of basin area NLCD 2006 Fry and others (2011)

Impervious surface, in percent of basin area NLCD 2006 Fry and others (2011)

Lag factor DEM U.S. Geological Survey (2000)

Main channel length, in mi DEM U.S. Geological Survey (2000)

Maximum basin elevation, in ft DEM U.S. Geological Survey (2000)

Mean annual maximum temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean annual minimum temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean annual precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean annual runoff, 1951–1980, in in. Gridded 

contour map

Randall (1996)

Mean April precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean August precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean autumn, in September through November precipitation, 1971–2000, 

800-m normals, in in.

PRISM Daly (1996)

Mean basin elevation, in ft DEM U.S. Geological Survey (2000)

Mean basin slope, in degrees DEM U.S. Geological Survey (2000)

Mean December precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean February precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean January precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean July precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean June precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean March precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean maximum April temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum August temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum December temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)
Estimation of Unaltered Daily Mean Streamflow 11

Table 2. Basin characteristics used in the development of regression equations for flow-duration exceedance probabilities for New 

York streams.

[ft, feet; NLCD, National Land Cover Database; DEM, digital elevation model; mi2, square miles; mi, miles; PRISM, Parameter-Elevation Regressions on 

Independent Slopes Model ; in., inches; °F, degrees Fahrenheit; ft/mi, feet per mile; m, meters; SSURGO, Soil Survey Geographic database; UTM, Universal 

Transverse Mercator]

Basin characteristic Source Reference

Mean maximum February temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum January temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum July temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum June temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum March temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum May temperature , 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum November temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum October temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean maximum September temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean May precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean minimum April temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum August temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum December temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum February temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum January temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum July temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum June temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum March temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum May temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum November temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum October temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean minimum September temperature, 1971–2000, 800-m normals, in °F PRISM Daly (1996)

Mean November precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean October precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean September precipitation, 1971–2000, 800-m normals, in in. PRISM Daly (1996)

Mean spring, in March through May precipitation, 1971–2000, 800-m 

normals, in in.

PRISM Daly (1996)

Mean summer, in June through August precipitation, 1971–2000, 800-m 

normals, in in.

PRISM Daly (1996)

Mean winter, in December through February precipitation, 1971–2000, 

800-m normals, in in.

PRISM Daly (1996)

Minimum basin elevation, in ft DEM U.S. Geological Survey (2000)

Overland flow distance, in m DEM U.S. Geological Survey (2000)

Riparian zone, in mi2 DEM U.S. Geological Survey (2000)
12 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

Table 2. Basin characteristics used in the development of regression equations for flow-duration exceedance probabilities for New 

York streams.

[ft, feet; NLCD, National Land Cover Database; DEM, digital elevation model; mi2, square miles; mi, miles; PRISM, Parameter-Elevation Regressions on 

Independent Slopes Model ; in., inches; °F, degrees Fahrenheit; ft/mi, feet per mile; m, meters; SSURGO, Soil Survey Geographic database; UTM, Universal 

Transverse Mercator]

Basin characteristic Source Reference

Seasonal maximum snow depth, 50th percentile Gridded 

contour map

Cember and Wilks (1993)

Slope 10-85 of channel, in ft/mi DEM U.S. Geological Survey (2000)

Slope ratio, unitless DEM U.S. Geological Survey (2000)

Slope, lower half of channel, in ft/mi DEM U.S. Geological Survey (2000)

Slope, upper half of channel, in ft/mi DEM U.S. Geological Survey (2000)

Underlain by clay, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group A, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group AD, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group B, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group BD, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group C, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group CD, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by hydrologic soils group D, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by sand, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Underlain by silt, in percent of basin area SSURGO U.S. Department of Agriculture, Natural 

Resources Conservation Service, 2011

Urban, in percent of basin area NLCD 2006 Fry and others (2011)

Water, in percent of basin area NLCD 2006 Fry and others (2011)

Wetland, in percent of basin area NLCD 2006 Fry and others (2011)

Wetness Index, in unitless DEM U.S. Geological Survey (2000)

X location of basin centroid, in UTM zone 18N m DEM U.S. Geological Survey (2000)

X location of basin outlet, in UTM zone 18N m DEM U.S. Geological Survey (2000)

Y location of basin centroid, in UTM zone 18N m DEM U.S. Geological Survey (2000)

Y location of basin outlet, in UTM zone 18N m DEM U.S. Geological Survey (2000)
Estimation of Unaltered Daily Mean Streamflow 13

or unusual basin characteristics or streamflow. All outliers 

or streamgages with high leverage that were identified and 

determined to influence the regression analyses for several 

flow-duration exceedance probabilities were removed from 

all 17 regression analyses to maintain consistency. Initially, 

statewide regression equations were developed and residual 

standard errors were mapped to determine if regionalization 

was appropriate. To improve the regression equations, the 

possibility of regionalizing the State was evaluated during 

exploratory regression analysis using OLS and WLS. The 

creation of regions based on the statewide residuals, 8-digit 

hydrologic unit code boundaries, physiographic provinces, and 

(or) major basins was explored, but no overall improvement 

was noted. The final regression equations for the 17 flowduration exceedance probabilities were developed using WLS 

on a statewide scale. An additional equation was developed as 

an alternate for predicting the P99.9945-percent exceedance 

probability in instances where the primary equation results 

in a higher flow estimate for the P99.9945 flow than the P99 

flow, which is a physical impossibility. The alternate equation 

uses only the P99 flow as a predictor, forcing the P99.9945 

flow to be less than the P99. Of the 46 streamgages used 

to develop the primary regression equation to estimate the 

P99.9945-percent exceedance probability flow, only 1 required 

the implementation of the alternate equation (appendix 1). 

The alternate equation only affects the flow estimates between 

the P99 and P99.9945-percent exceedance probability flows 

(the lowest 0.0055-percent of flows) for the 50-year estimated 

time series hydrograph. A summary of the regression equation 

coefficients is available in table 3.

The basin characteristics determined to be significant at 

the 95-percent confidence level for one or more regression 

equations are drainage area; mean annual runoff; percent 

hydrologic soils group A; percent hydrologic soils group B; 

mean monthly precipitation for the months of May, June and 

July; mean summer precipitation; maximum June temperature; 

X location of the basin centroid; Y location of the basin 

centroid; slope of the lower half of the main channel; and 

the percentage of basin above 1,200-foot (ft) elevation above 

North American Vertical Datum of 1988 (NAVD 88; table 2). 

Basin characteristics of the streamgage basins used in the 

analysis are listed in appendix 4. To form a near-linear relation 

between the flow-duration exceedance probabilities and basin 

characteristics, all independent and dependent variables were 

log-transformed (base 10) before regression analysis. For 

the basin characteristics measured as a percent, a constant of 

0.0004 was added to the decimal form of the percentage for all 

zero values. The regression model took the following form in 

log units:

logQpˆ = A+ + blog Da c log Mar + d log HA+ e log HB

f log P5 + g log P6 + h log P7 + + i log PS j logT6 , (1)

 k logYcent + l log Xcent + + mlog Sl nlog E12

or in arithmetic space:

Qpˆ = 10A b (Da ) (Mar c

) (HAd) ( HBe) (P5f) (P6g) , (2)

(P7h) (PSi) (T6 j) (Ycent k) ( Xcentl m ) (Sl ) (E12n)

where

 log = log to base 10;

Qpˆ = flow-duration exceedance probability, in 

cubic feet per second;

 A = the intercept;

 Da = drainage area, in square miles;

 Mar = mean annual runoff, in inches per square 

mile;

 HA = basin underlain by hydrologic soils group 

A, in percent;

 HB = basin underlain by hydrologic soils group 

B, in percent;

 P5 = mean precipitation for the month of May, in 

inches;

 P6 = mean precipitation for the month of June, in 

inches;

 P7 = mean precipitation for the month of July, in 

inches;

 PS = mean precipitation during summer (June, 

July, and August), in inches;

 T6 = maximum temperature in June temperature, 

in degrees Fahrenheit;

 Ycent = Y location of the basin centroid, in 

Universal Transverse Mercator meters;

 Xcent = X location of the basin centroid, in 

Universal Transverse Mercator meters;

 Sl = slope of the lower half of the main channel, 

in feet per mile;

 E12 = basin above 1,200 ft elevation above NAVD 

88, in percent; and

 b-n = coefficients of regression estimated by 

WLS.

Standard errors of prediction provide an estimate 

of reliability of the predicted flow-duration exceedance 

probabilities and are shown for the developed regression 

equations in table 3 (Stuckey and others, 2012). The range of 

standard error of prediction for the flow-duration exceedance 

probability regression equations is from 0.03 to 0.27 in 

log units (6.6 to 93 percent), with the average standard 

error of all 17 flow-duration equations equal to 27 percent 

(table 3). The highest errors occur in the regression equations 

estimating the low-flow portions of the FDC; the extreme 

low-flow exceedance probability of P99.9945 has an error of 

93 percent and P99 and P95 have errors of 92 and 49 percent, 

respectively. The uncertainty associated with the regression 

equations is estimated by the R2

. In comparing the R2 for P65 

(0.990) and P99.9945 (0.853), the higher R2 value indicates 

that 99.0 percent of the P65 value is explained by the effect 

of basin characteristics selected for use in the P65 regression 

+

+
14 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010 ork streams, excluding Long Island. Regression coefficients for use with flow-duration exceedance probability regression equations for New Y Table 3. , square miles; °F, degrees Fahrenheit; m, meters; ft/mi, feet per mile; P[n], [n] probability exceedance; --, basin characteristic not significant] [mi2Flow duration exceed- ance Intercept Basin characteristics coefficients Ob- served flow statistic coeffi- cient, P99 Coef- ficient of determi- nation (R2) adjusted for the number of predictor variables Standard error of model Drain- age area, in mi2 Mean annual runoff, in inches 1951– 1980 Percentage of hydrologic soils Mean precipitation, in inches, 1971–2000 Maximum tempera- ture in June, in °F 1971–2000 Location of basin centroid, in m Slope, lower half of main chan- nel, in ft/mi Percentage of basin above 1,200 feet elevation Group 

A

Group 

B May June July Sum- mer

X

Y in Log units in percent

P0.0055 65.2397 0.9866 -- -- -- -- 1.8825 -- -- -- 0.2133 -9.8940 0.1172 -- 0.951 0.094 23

P1 0.3206 0.9604 1.1831 -- -0.0604 -- -- -1.1457 -- -- -- -- -- -- 0.993 0.052 14

P5 -0.3018 1.0031 1.0315 -- -0.0273 -- -- -0.5273 -- -- -- -- -- -- 0.997 0.036 8.8

P10 -0.6798 1.0118 0.9187 -- -0.0148 -- -- -- -- -- -- -- -- -- 0.997 0.030 7.3

P15 -0.6530 1.0156 0.9594 -- -- 0.2581 -- -- -0.3477 -- -- -- -- -- 0.998 0.028 6.6

P20 -0.7731 1.0181 0.9581 -- -- 0.3841 -- -- -0.3976 -- -- -- -- -- 0.997 0.029 7.0

P25 -0.8510 1.0163 0.9921 -- 0.0210 0.5214 -- -- -0.5355 -- -- -- -- -- 0.997 0.031 7.2

P35 -1.1180 1.0165 1.0417 -- 0.0385 0.6195 -- -- -0.5551 -- -- -- -- -- 0.996 0.036 8.7

P50 -2.0038 1.0166 1.0929 -- 0.0533 -- -- 0.6097 -- -- -- -- -- -- 0.993 0.045 11

P65 3.8155 1.0310 0.7557 -- 0.1123 -- -- 1.4385 -- -3.3025 -- -- -- -- 0.990 0.061 14

P75 13.1196 1.0396 -- 0.0570 0.1781 -- -- 2.8016 -- -8.3346 -- -- -- -- 0.979 0.087 22P80 14.9630 1.0481 -- 0.0779 0.2081 -- -- 2.8620 -- -9.4231 -- -- -- -- 0.973 0.102 26

P85 16.7651 1.0554 -- 0.1047 0.2402 -- -- 2.8999 -- -10.4886 -- -- -- -- 0.964 0.122 31P90 18.0498 1.0562 -- 0.1342 0.2740 -- -- 2.8915 -- -11.2622 -- -- -- -- 0.952 0.143 38P95 20.5953 1.0654 -- 0.1695 0.3218 -- -- 2.8778 -- -12.7425 -- -- -- -- 0.937 0.170 49P99 25.9723 1.0728 -- 0.2362 0.4022 -- -- 2.9287 -- -15.8240 -- -- -- -- 0.908 0.229 92

P99.9945 -7.7526 1.4689 -- - 0.5999 -- -- 5.4351 -- -- -- 0.5897 0.3840 0.853 0.266 93

Alternate equation for 0.999945 flow duration exceedance probabilityP99.9945 -0.545800 -- -- -- -- -- -- -- -- -- -- -- -- -- 1.160400 0.931 0.329 167.9
Using the New York Streamflow Estimation Tool for Estimating Unaltered Daily Mean Streamflow for Ungaged Locations 15

equation. Whereas only 85.3 percent of the P99.9945 value is 

described by its regression equation, indicating that additional 

variables may be affecting this extreme low-flow (table 3). 

The flow-duration exceedance probabilities computed from 

observed streamflow data and regression equations for 

streamgages used in the regression analysis are displayed in 

appendix 1.

It is important to use the same data source as was used to 

develop the regression equations for determination of the basin 

characteristics to maintain consistency in the accuracy of the 

regression estimates. This is not possible for some areas where 

SSURGO data were unavailable; STATSGO2 data have been 

included in StreamStats to complete areas where SSURGO 

data are missing. Accuracy may still differ from what was 

found in the regression analysis.

Estimation of Streamflow Time Series from a 

Reference Streamgage

Selection of an appropriate reference streamgage 

is crucial to achieving the most accurate estimates when 

applying the QPPQ method. Selecting the closest reference 

streamgage to the ungaged location as the best reference 

streamgage is intuitive, assuming the closer the ungaged 

location is to a reference streamgage, and the more 

hydrologically similar they are (Stuckey and others, 2012). 

However, the closest streamgage may not have the most 

physically or hydrologically similar basin to those at the 

ungaged location. The spatial map correlation method 

described by Archfield and Vogel (2010) determined that the 

closest reference streamgage is not always the best choice.

Map Correlation

Map correlation is a geostatistical approach used to select 

a reference streamgage with the highest correlated streamflow 

with an ungaged location. When applying the map correlation 

method, a variogram model for each reference streamgage 

is developed describing a map of continuous streamflow 

correlation estimates between it and all other available 

reference streamgages in New York and surrounding States 

(fig. 5; Archfield and Vogel, 2010). The expected correlation 

at the ungaged location is estimated by applying ordinary 

kriging (Isaaks and Srivastava, 1989). The streamgage 

whose map has the highest estimated correlation coefficient 

at the ungaged location is selected as the most appropriate 

reference streamgage.

Stuckey and others (2012) determined that using the 

Spearman’s rho correlation coefficient, a nonparametric 

measure of correlation, was preferable to alternate correlation 

metrics. Stuckey and others (2012) evaluated measures of 

distance and determined that using distance between basin 

centroids may be more appropriate than distances between 

basin outlets. For this study, Spearman’s rho correlation 

centroid distances were used to apply the map correlation 

method. The spherical variogram model is a broadly applied 

variogram function and was selected to describe the spatial 

structure within the correlation of daily streamflow between 

the reference streamgages.

Variogram models were developed for 117 reference 

streamgages in and near New York with minimally altered 

streamflow and at least 20 years of continuous record during 

WYs 1961 to 2010 using the Geostatistical Analyst extension 

of Esri ArcMAP 10.0. Variogram models for four reference 

streamgages with 9 to 18 years of record also were included to 

improve spatial coverage. The reference streamgages listed in 

appendix 2 were used to apply the map correlation method.

It is ideal for the common period of streamflow record 

between reference streamgages to represent a broad range 

of streamflow values. One potential source of error from 

insufficient common periods of record is poor selection of 

a reference streamgage based on misleading correlation 

coefficients. Streamflow records of shorter duration often 

exhibit a more limited range of streamflows than those 

of longer duration, which may indicate they should be 

removed from the dataset due to not adequately estimating a 

representative historical hydrograph. No streamgage records 

with short common periods of record were removed in this 

study. A potential benefit may be gained from retaining short 

period of record correlation pairs because the performance 

of map correlation (kriging) is contingent on data density 

(Skoien and Blöschl, 2007; Archfield and Vogel, 2010), and 

data obtained from short common periods of record have value 

for defining the spatial-correlation structure (Stuckey and 

others, 2012).

Using the New York Streamflow 

Estimation Tool for Estimating 

Unaltered Daily Mean Streamflow for 

Ungaged Locations

The NYSET is used to estimate daily streamflow 

hydrographs for WYs 1961 to 2010 at rural ungaged sites 

in New York using data from existing USGS streamgages 

coupled with explanatory basin characteristics. A graphical 

user interface, with an integrated spreadsheet summary 

report, displays the estimated daily streamflow statistics and 

allows water management to evaluate different scenarios or 

water withdrawal scenarios with estimated monthly data. 

This package of regression equations, USGS streamgage 

data, and spreadsheet application produce an interactive tool 

to estimate an unaltered daily streamflow hydrograph and 

streamflow statistics at ungaged sites in New York. The New 

York Streamflow Estimation Tool uses a similar model as 

the Massachusetts Sustainable-Yield Estimator (MA SYE; 

Archfield and others, 2010) and BaSE (Stuckey, 2012) tools; 

however, parts of both models and the original programming 

for BaSE have been modified for use in this application 
16 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

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Base from U.S. Geological Survey 1:2,000,000 and 1:100,000 digital dataUniversal Transverse Mercator Projection, Zone 18N, North American Datum 1983

NEW YORK

VT

MA

CT

NJ

PENNSYLVANIA

CANADA

EXPLANATION

Spearman's rho

0.379−0.476>0.476−0.533>0.533−0.566>0.566−0.586>0.586−0.597>0.597−0.616>0.616−0.649>0.649−0.706>0.706−0.804>0.804−0.971

# U.S. Geological Survey streamgage

Lake Ontario

0 40 80 KILOMETERS

0 40 80 MILES

Figure 5. Example correlation map for U.S. Geological Survey streamgage 01312000, Hudson River near Newcomb, N.Y. (fig. 1, streamgage 2)
Accuracy and Limitations of Estimated Unaltered Streamflows 17

and written as a standalone application on a Visual Basic 

.NET (VB.NET) platform with Microsoft Excel output. The 

NYSET output files include reference streamgage information, 

unaltered daily mean streamflow, daily and monthly flow 

statistics, FDCs, and hydrographs.

Basin characteristic information for the ungaged 

location may be calculated using USGS StreamStats for New 

York on the opening page of NYSET. The calculated basin 

characteristics may then be entered in the NYSET Basin 

Characteristics tab manually or imported from an ArcGIS 

10.1 geodatabase file downloaded from StreamStats (U.S. 

Geological Survey, 2014). NYSET can import the geodatabase 

file downloaded from StreamStats and complete the basin 

characteristics screen form with the required information. By 

default, NYSET selects an appropriate reference streamgage 

for a user-entered ungaged location by maximizing the 

estimated streamflow correlation. A user-specified option of 

manually selecting a different reference streamgage is also 

available. With complete information for the ungaged location 

of interest entered into NYSET, the Compute Unaltered 

Streamflows function computes the unaltered daily mean 

streamflows and associated streamflow statistics for the 

ungaged location for WYs 1961 to 2010.

A report output file in the form of a Microsoft Excel 

spreadsheet is generated summarizing the reference 

streamgage and ungaged location information. This summary 

includes basin characteristic information for the ungaged 

location and reference streamgages, percent difference in basin 

characteristics between the two locations, and any warnings 

associated with the basin characteristics (fig. 6). FDCs and 

hydrographs are presented for the ungaged location in cubic 

feet per second and cubic feet per second per square mile. 

The estimated daily flows for the ungaged location can be 

easily exported to a text file, which can be used in statistical 

software packages to determine additional daily streamflow 

statistics. An additional spreadsheet displaying select monthly 

exceedance probability flows also is created.

The user also can manipulate additional monthly 

withdrawals and discharges, designate monthly instream-flow 

targets and determine the remaining instream-flow after the 

user defined alterations. The Unaltered streamflow column 

is automatically filled in with the mean monthly flows for 

each month and can be edited by the user. The instream-flow 

target represents the user-defined minimum acceptable flows. 

The “Difference from target” column represents the surplus 

or deficit from the instream-flow target designated by the 

user for the exceedance or mean flows used in the “Unaltered 

streamflow” column. For example, if the Q50 (50-percent 

exceedance flow) flow in January is 100 ft3/s (unaltered 

streamflow) and the instream-flow target was 80 ft3/s, then 

there would be a surplus (difference from target) of 20 ft3/s, 

50 percent of the time. If additional withdrawals were 

specified, the difference from target value would be reduced 

by those withdrawals. More detailed information, instructions 

for use, and all related links to files for the NYSET tool are in 

appendix 5.

In addition to the estimated daily mean streamflow, 

the NYSET computes a suite of daily mean flow statistics. 

The statistics computed are mean, median, 7Q2, 7Q10, and 

monthly probability flows for the 1-, 2-, 5-, 10-, 15-, 20-, 25-, 

30-, 35-, 40-, 45-, 50-, 55-, 60-, 65-, 70-, 75-, 80-, 85, 90-, 95-, 

98- and 99-percent exceedances. These statistics, including the 

7Q2 and 7Q10, are computed by empirically ranking the flows 

using the Weibull plotting position for the period of interest.

The 7-day low-flow statistics are computed in NYSET by 

identifying the lowest mean consecutive 7-day period in each 

climate year2 (CY) in the estimated streamflow dataset. The 

7-day flow values calculated for each CY are then ranked to 

identify the 50- and 90-percent exceedances flow values (7Q2 

and 7Q10, respectively). A log-Pearson type III (LP3) fit to 

the data is not used, though typically the USGS would use an 

LP3 type analysis to estimate 7-day low flow statistics (Riggs, 

1972; Suro and Gazoorian, 2011). The complexity involved 

in fitting LP3 computations to the estimated dataset would 

substantially slow down the processing speed of the NYSET 

and add an additional layer of uncertainty by transfer of 

at-site skew values from a reference streamgage. To improve 

performance and not introduce additional uncertainty, the 

n-day statistics computed by the NYSET are rank-based flow 

estimates. Based on an analysis of all reference streamgages 

with observed periods of record including CYs 1961 to 2009, 

a 49-year daily mean flow record, the empirical ranking 

method produces 7Q2 and 7Q10 estimates similar to those 

from an LP3 curve fitting (table 4). The monthly probability 

flows are computed by extracting each daily mean flow value 

that occurs in the given month for the estimated period and 

ranking them to identify the value of each of the probability 

flows estimated.

Accuracy and Limitations of Estimated 

Unaltered Streamflows

Accuracy of unaltered daily streamflow estimates for 

ungaged locations depends on the uncertainties associated 

with the multiple steps, as defined by Stuckey and others 

(2012). The steps that may each produce individual 

uncertainties include (1) streamflow measurements at 

reference streamgages, (2) streamflow record extensions 

at reference streamgages, (3) selection of a reference 

streamgage using the map correlation method, (4) transfer 

of exceedance probabilities from a reference streamgage 

to the ungaged location, and (5) estimation of the FDC for 

an ungaged location based on regression equations and 

basin characteristics.

Streamflow at each reference streamgage is determined 

daily during the period of record based on a stage-discharge 

relation unique to each individual streamgage, which is 

2

A climate year runs from April 1 through March 31 and is designated by 

the year in which it starts.
18 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

Figure 6. Screen capture of summary report generated by the New York Streamflow Estimation Tool showing flow-duration curves 

and a hydrograph.
Accuracy and Limitations of Estimated Unaltered Streamflows 19

Table 4. Comparison of low-flow statistics calculated by empirical ranking method and log-Pearson type III curve fitting at reference 

stations with observed flows for the period April 1, 1961, to March 31, 2010.

[Data are for climate years 1961 to 2009. ID, Identification number; mi2, square miles; 7Q2, 7-day, 2-year discharge ; ft3/s, cubic feet per second; 

LP3, log-Pearson type III; %, percent; 7Q10, 7-day, 10-year discharge]

U.S. Geological Survey streamgage

Drainage 

area, 

in mi2

7Q2, in ft3/s 7Q10m in ft3/s

ID

Map

number

(fig. 1)

Name LP3 Empirical 

ranking1

Difference, 

in % LP3 Empirical ranking1

Difference, 

in %

01334500 15 Hoosic River near Eagle Bridge, NY 510 151 146 -3.2 94.7 95.3 0.6

01350000 17 Schoharie Creek at Prattsville, NY 237 20.8 19.1 -7.9 8.78 8.14 -7.3

01365000 24 Rondout Creek near Lowes Corners, 

NY

38.3 11.7 11.1 -4.5 6.12 6.29 2.7

01372500 32 Wappinger Creek near Wappingers 

Falls, NY

181 17.7 18.6 4.8 5.80 4.71 -18.7

01413500 37 East Branch Delaware River at 

Margaretville, NY

163 22.2 22.0 -0.9 10.8 10.4 -3.1

01414500 39 Mill Brook at Dunraven, NY 25.2 4.52 4.57 1.2 2.24 2.29 2.1

01420500 45 Beaver Kill at Cooks Falls, NY 241 66.5 65.1 -2.0 37.2 38.7 4.0

01423000 49 West Branch Delaware River at 

Walton, NY

332 43.9 41.3 -5.9 22.1 23.3 5.4

01435000 58 Neversink River near Claryville, NY 66.6 27.1 27.6 1.6 13.8 13.7 -0.7

01503000 66 Susquehanna River at Conklin, NY 2,232 311 289 -7.0 178 187 4.7

01512500 73 Chenango River near Chenango Forks, 

NY

1,483 242 235 -2.8 136 145 6.5

01529500 80 Cohocton River near Campbell, NY 470 46.5 46.7 0.5 26.4 26.7 1.2

03011020 82 Allegheny River at Salamanca, NY 1,608 242 238 -1.6 141 129 -8.3

04214500 85 Buffalo Creek at Gardenville, NY 142 12.8 13.0 1.4 5.93 5.57 -6.0

04215500 87 Cazenovia Creek at Ebenezer, NY 135 13.5 14.1 4.6 7.19 6.57 -8.5

04217000 89 Tonawanda Creek at Batavia, NY 171 12.7 11.7 -7.9 6.60 6.00 -9.1

04230500 98 Oatka Creek at Garbutt, NY 200 33.3 33.0 -1.0 20.4 19.0 -6.8

04231000 99 Black Creek at Churchville, NY 130 5.23 6.29 20.1 1.41 1.00 -29.2

04233000 101 Cayuga Inlet near Ithaca, NY 35.2 4.70 4.57 -2.7 2.83 2.57 -9.2

04234000 102 Fall Creek near Ithaca, NY 126 18.8 19.3 2.4 8.82 9.29 5.3

04243500 104 Oneida Creek at Oneida, NY 113 26.3 25.4 -3.2 17.3 18.3 5.8

04256000 109 Independence River at 

Donnattsburg, NY

88.7 33.0 33.9 2.6 22.7 21.6 -4.8

1

Weibull plotting position.
20 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

constructed from measured discharge and observed stage 

data. The associated accuracy for each reference streamgage 

is documented for each year of record in annual data reports. 

Most published streamflow records for stations in New York 

are rated as good to fair (U.S. Geological Survey, 2011). These 

ratings reflect that 95 percent of the data are within 10 (good) 

to 15 (fair) percent of their true values.

Additional uncertainty to unaltered streamflow estimates 

is introduced by streamflow record extension and is difficult 

to quantify. Because the length of record requiring extension 

at the reference streamgages varied from none to 100 percent 

of the record during the period of interest, the uncertainty 

introduced to the estimated record is inconsistent. A general 

sense of the accuracy of these estimates can be estimated 

by observing the correlation coefficients. For this study, the 

correlation coefficients range from 0.75 to 0.99 (a perfect 

correlation would be equal to 1). Streamgages requiring a 

smaller part of the record be extended generally will have 

less overall uncertainty than those requiring a long part of the 

record be extended, assuming similar quality correlations to 

the index streamgage used for record extension. Correlations, 

and associated uncertainties, are less likely to agree when 

there is a nonlinear relation between the logarithm of 

streamflow at a streamgage requiring record extension and the 

logarithm of streamflow at the index streamgage used to apply 

the extension. Therefore, the overall uncertainty introduced 

by record extension is determined by the length of extension 

period, strength of index streamgage correlation, and quality 

of the relation between daily streamflow and daily exceedance 

probabilities when streamflow is used as a surrogate for 

exceedance probability.

The accuracy with which the best correlated reference 

streamgage is selected by map correlation affects the 

uncertainty in the unaltered streamflow estimates. Uncertainty 

is introduced into the daily exceedance probabilities for the 

ungaged location because even the best correlated reference 

streamgage would not have a perfect correlation. As the 

correlation between an ungaged location and the reference 

streamgage decrease, the uncertainty in unaltered streamflow 

estimates increase. If map correlation does not select the 

best correlated reference streamgage, the uncertainty also 

would increase. The accuracy of map correlation to ungaged 

locations across New York remains unknown, but could be 

assessed by measuring streamflows at ungaged locations, 

computing correlations to reference streamgages and 

comparing them with the estimated correlations from the 

map correlation.

The QPPQ method relies on the assumption that both 

locations have equivalent exceedance probabilities at the same 

time. Although this assumption is more likely to be true for 

locations with similar size drainage and in close proximity to 

the reference streamgage, its validity for ungaged locations 

statewide is unknown.

The FDC constructed for the ungaged locations 

by regression estimates of the 17 specified exceedance 

probabilities includes errors in the regressions and associated 

uncertainties introduced from interpolation of the remaining 

exceedance probabilities occurring between the 17 exceedance 

probabilities on the FDC. Part of the regression errors are 

inherited from uncertainties of individual datasets from 

which basin characteristics are computed. Additionally, the 

dataset from 1951 to 1980 for mean annual runoff could be 

a possible limitation given that it is being applied to estimate 

streamflow during periods beginning 10 years after 1951 and 

ending 30 years after 1980. Standard errors of prediction for 

the 17 regression estimates range from 6.6 to 93 percent, and 

the standard error of prediction for the alternative equation is 

168 percent (table 3). Archfield and others (2010) and Stuckey 

and others (2012) noted “hook” features when plotting 

observed and estimated daily mean streamflows at the extreme 

highest and lowest streamflows. The hook feature also was 

apparent when plotting the data from this study. Stuckey and 

others (2012) determined that a use of log-log interpolation 

smoothed out the hook features in the higher flows; however, 

a minor hook feature remained, affecting the extreme low 

streamflows (below P99) observed for more than the 50-year 

period, typically resulting in under prediction of extreme 

low flows. The NYSET data also indicated that a log-log 

interpolation method produced a straighter fit in the higher 

flow part of the plots, but at low flows the hook persisted. It is 

unclear why the hook remains in the low flow part even when 

using a log-log interpolation method. For development of the 

NYSET, the log-log interpolation method was used.

To evaluate the effectiveness of the overall QPPQ 

method applied within NYSET, a comparison of observed 

and estimated daily mean streamflows was done for each 

of the reference streamgages, except for two that have no 

unaltered flows concurrent with the historical period of interest 

estimated by NYSET. Only observed daily mean streamflows 

for WYs 1961 to 2010 were included for this comparison. 

Estimated streamflows were produced using the NYSET and 

the default option of map correlation for reference streamgage 

selection. The comparison is a reasonable method to show 

how the NYSET can be expected to perform over the range of 

basin characteristics found across the State, though an analysis 

of streamgages not included in the model was not completed. 

Nash-Sutcliffe (NS) efficiency values (Nash and Sutcliffe, 

1970) and normalized root-mean-square error (RMSE), as 

a percent, were computed as a measure of goodness of fit. 

NS efficiency values were evaluated for daily mean flows 

and the log of daily mean flows. Examples of a comparison 

of the observed and estimated streamflows for streamgages 

01414500, Mill Brook near Dunraven, N.Y. and 04213500, 

Cattaraugus Creek at Gowanda, N.Y. are shown in figure 7A

and B, respectively. These streamgages represent the best 

(01414500) and worst (04213500) NS efficiency values of 

the 119 sites evaluated. To estimate how well the model 

performed, the results were evaluated using the complete 

set of streamgages and also by major river basin. Median 

NS efficiencies for daily mean flows and log daily mean 

flows, statewide, were 0.84 to 0.89, respectively, and the 

median normalized RMSE was 2.05. The distribution of NS 
Accuracy and Limitations of Estimated Unaltered Streamflows 21

Estimated daily mean streamflow, in cubic feet per second

Observed daily mean streamflow, in cubic feet per second

0.1

10

100

1,000

10,000

0.1 1 10 100 1,000 10,000

Nash-Sutcliffe efficiency value = 0.99

A

10

100

1,000

10,000

100,000

B

10 100 1,000 10,000 100,000

Estimated daily mean streamflow, in cubic feet per second

Observed daily mean streamflow, in cubic feet per second

Nash-Sutcliffe efficiency value = 0.36

1

Figure 7. Graphs showing comparison of observed and New York Streamflow Estimation Tool 

estimated daily mean streamflows for U.S. Geological Survey streamgages A, 01414500 Mill Brook 

near Dunraven, N.Y. and B, 04213500 Cattaraugus Creek at Gowanda, N.Y.
22 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

efficiencies and normalized RMSE by major river basin is 

in tables 5 and 6 and figure 8. Based on these metrics, the 

NYSET performed best in the Delaware and Susquehanna 

River basins, indicating results in these basins are generally 

the most reliable. Although model performance in other 

areas of New York State was generally good, the diversity of 

basins tested resulted in a large range of NS and normalized 

RMSE values.

Flow-duration curves and hydrographs generated in 

NYSET for streamgages 04221500, Genesee River at Scio, 

N.Y. and 04232100, Sterling Creek at Sterling, N.Y. are shown 

in figure 9A and B, respectively. These streamgages represent 

the best (04221500) and worst (04232100) correlations with 

reference streamgages with observed streamflow for WY 

1961 to 2010. Streamgage 04221500 was associated with 

reference streamgage 04221000 with a correlation of 0.999, 

and streamgage 04232100 was associated with reference 

streamgage 04245000 with a correlation of 0.888 for estimates 

of daily mean flow. The period from 2002 to 2006 is shown in 

the hydrographs in figure 9.

NYSET uses estimates of streamflow derived from 

regression equations, and is not intended to be used for 

streams with basin characteristics outside the range used 

to develop the equations. Streamflow estimates may not be 

valid for streams with basin characteristics outside this range. 

The range of basin characteristics used in the development 

of the regression equations is shown in table 7. Estimated 

streamflows produced by the NYSET do not include 

alterations to streamflow by regulation, mining, or other 

large water uses. Results from the NYSET also may not be 

valid where groundwater and surface-water divides are not 

coincident. This can occur in areas with karst topography or 

mining activity.

Table 5. Nash-Sutcliffe efficiencies from comparison of the New York Streamflow Estimation Tool estimated daily-mean values to 

observed values at reference gages.

[Excludes two reference gages (01421000, 01437000) with no unregulated, observed flows concurrent with the historical period of interest]

Major river basin Number 

of sites

Nash-Sutcliffe efficiency of flow Nash-Sutcliffe efficiency of log flows

Minimum Maximum Mean Median Minimum Maximum Mean Median

All 119 0.36 0.99 0.79 0.84 -6.98 0.99 0.75 0.89

Hudson 33 0.36 0.99 0.78 0.84 -1.98 0.97 0.76 0.89

Delaware 21 0.74 0.99 0.88 0.90 0.49 0.99 0.88 0.90

Susquehanna 22 0.63 0.99 0.89 0.86 0.76 0.99 0.91 0.93

Great Lakes, Lake Champlain, 

St. Lawrence

38 0.36 0.98 0.72 0.78 -6.98 0.98 0.72 0.78

Other 5 0.47 0.91 0.71 0.72 0.76 0.94 0.86 0.88

Table 6. Normalized root-mean-square errors as percentage from comparison of the New York Streamflow Estimation Tool estimated 

daily-mean values to observed values at reference gages.

[Excludes two reference gages (01421000, 01437000) with no unregulated, observed flows concurrent with the historical period of interest]

Major river basin Number of sites Normalized root-mean-square error

Minimum Maximum Mean Median

All 119 0.43 6.34 2.38 2.05

Hudson 33 0.56 6.02 2.64 2.59

Delaware 21 0.43 3.08 0.88 0.90

Susquehanna 22 0.59 4.87 1.84 1.80

Great Lakes, Lake Champlain, 

St. Lawrence

38 0.59 5.95 0.72 0.78

Other 5 1.40 6.34 2.91 2.32
Accuracy and Limitations of Estimated Unaltered Streamflows 23

Nash-Sutcliffe efficiency value 

0.2

0.4

0.6

0.8

1.0

1.2

Hudson River

Delaware River

Susquehanna 

River

Great Lakes/ 

St. Lawrence River

Normalized root-mean-square error in percent

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

A

B

90th percentile

75th percentile

50th percentile (median)

25th percentile

10th percentile

Major river basins

EXPLANATION

Values above the 90th percentile

Values below the 10th percentile

33 21 22 38

33 Number of values

33 21 22 38

Figure 8. Boxplots showing distribution of, A, Nash-Sutcliffe efficiency 

values and B, root-mean-square error by major river basin obtained from 

comparison between observed and estimated daily mean streamflows.
24 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010 10 1.0 100 1,000 10,000 100,000 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Streamflow, in cubic feet per second

A. 04221500 - Flow-duration curve

EXPLANATION

Observed streamflow

Estimated streamflow

100

10

1.0

1,000

10,000

100,000

2002 2003 2004 2005 2006

Streamflow, in cubic feet per second

A. 04221500 - Hydrograph

EXPLANATION

Estimated streamflowObserved Streamflow

Nash-Sutcliffe efficiency value = 0.96Normalized root-mean-square error = 0.59%

10

1.00.1

100

1,000

10,000

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Streamflow, in cubic feet per second

B. 04232100 

EXPLANATION

Observed streamflowEstimated streamflow

100

10

1.00.1

1,000

10,000

2002 2003 2004 2005 2006

Streamflow, in cubic feet per second

B. 04232100

Estimated streamflowObserved streamflow

EXPLANATION

Nash-Sutcliffe efficiency value =0.58 Normalized root-mean-square error = 3.14%

Exceedance probability

Exceedance probability

Year

Year

A, 04221500, Genesee Flow-duration curves and hydrographs showing estimated and observed daily mean flows for U.S. Geological Survey streamgages, 

. %, percent. B, 04232100, Sterling Creek at Sterling, N.Y . and, 

Figure 9.River at Scio, N.Y
Summary 25

Table 7. Basin characteristics used in development of regression equations to estimate flow-duration exceedance probabilities with 

the New York Streamflow Estimation Tool for basins in New York.

Basin characteristic Minimum Maximum Mean

Drainage area, in square miles 3.14 4,780 288

Mean annual runoff, 1951–1980, in inches 11.6 37.4 22.9

Percent hydrologic soils group A 0.62 51.2 6.52

Percent hydrologic soils group B 1.14 65.7 16.8

Mean May precipitation, 1971–2000, in inches 3.15 5.68 4.10

Mean June precipitation, 1971–2000, in inches 3.59 5.33 4.32

Mean July precipitation, 1971–2000, in inches 3.20 5.26 4.12

Mean summer precipitation, 1971–2000, in inches 10.5 15.5 12.5

Maximum June temperature, in degrees Fahrenheit, 

1971–2000

68.8 78.8 74.2

X location of basin centroid, in meters 166,690.76 657,531.03 480,630.94

Y location of basin centroid, in meters 4,557,789.39 4,913,180.43 4,713,574.01

Slope, lower half of main channel, in feet per mile 1.56 152 25.3

Percent of basin above 1,200 feet elevation 0 100 66.6

Summary

The ability to estimate daily mean streamflow for any 

location on a stream in New York can aid in managing the 

water resources of the State. Time series hydrologic data are 

essential to understanding ways to promote healthy instream 

ecology and to strengthen the scientific basis for sound water 

management decision making in New York. Generating 

daily mean flows at ungaged streams, allows for estimating 

streamflow statistics such as flow-duration exceedances, and 

helps water managers to understand the natural flow regime 

of a stream, which is critical to the sustainability and health of 

aquatic freshwater ecosystems.

The U.S. Geological Survey, in cooperation with 

The Nature Conservancy and the New York State Energy 

Research and Development Authority, has developed the New 

York Streamflow Estimation Tool (NYSET) to estimate a 

continuous daily mean streamflow hydrograph for the period 

from October 1, 1960, to September 30, 2010, at ungaged 

locations across New York State. The NYSET equates the 

streamflow as a percentile from the flow-duration curve (FDC) 

for a particular day at an ungaged location with the streamflow 

as a percentile for the same day at a reference streamgage by 

applying a modified QPPQ approach. Estimated streamflow 

correlations at ungaged locations, by map correlation, is used 

to select an appropriate reference streamgage for streamflow 

estimation. Basin characteristics are used to develop 

regression equations to construct a daily FDC for ungaged 

locations. The estimated FDC is used to select streamflow 

percentiles corresponding to those at the reference streamgage.

Regression equations were developed to predict flowduration exceedance probabilities for 17 percentiles along the 

FDC using data from 90 streamgages. The standard errors of 

prediction for the flow-duration regression equations range 

from 6.6 to 93 percent, with the average standard error for the 

suite of equations equal to 27 percent. The map correlation 

method was used for the selection of a reference streamgage 

with minimally altered streamflow in and near New York using 

a spherical variogram model.

The NYSET generates daily mean streamflow estimates 

for an ungaged location by first selecting a reference 

streamgage using the map correlation method as a default. 

An option exists for manual selection by the user. After a 

reference streamgage is identified, the NYSET then equates 

the percentiles at the gaged site with percentiles at the ungaged 

location for each date from October 1, 1960, to September 

30, 2010. Regression equations and interpolation are used 

to convert the percentiles to streamflow at the ungaged 

location. The NYSET outputs a summary report in the form 

of a Microsoft Excel spreadsheet. This summary includes 

basin characteristic information for the ungaged location 

and reference streamgages, percent difference in basin 

characteristics between the two locations, and any warnings 

associated with the basin characteristics. Mean and median 

streamflows, 7Q2, 7Q10, and select monthly flow statistics are 

computed for the ungaged location. FDCs and hydrographs 

are presented for the ungaged location in cubic feet per second 

and cubic feet per second per square mile. The estimated daily 

flows for the ungaged location can be easily exported to a text 

file, which can be used in a statistical software package to 

determine additional daily streamflow statistics.

Accuracy of estimated unaltered daily mean streamflow 

for ungaged locations is affected by the uncertainties 

introduced by the multiple steps involved in the process. 

Uncertainty is introduced during the selection of the reference 

streamgage, estimation of exceedance probabilities for the 
26 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

ungaged location, and the QPPQ process. It is difficult to 

quantify the overall uncertainty associated with the estimated 

daily mean flows at the ungaged location because of the 

number of potential sources. Observed and estimated daily 

mean flows for a subset of reference streamgages were 

examined for accuracy. Nash-Sutcliffe (NS) efficiency values 

were evaluated for daily mean flows and the log of daily mean 

flows. To estimate how well the model performed, the results 

were evaluated using the complete set of streamgages and 

by subsetting them into groups based on which major river 

basin each site is in. Median NS efficiencies for daily mean 

flows and log daily mean flows, statewide, were 0.84 to 0.89, 

respectively, and the median normalized root-mean-square 

error was 2.05.

The New York Streamflow Estimation Tool NYSET 

uses estimates of streamflow derived from regression 

equations, and is not intended to be used for streams with 

basin characteristics outside the range used to develop the 

equations. Streamflow estimates may not be valid for streams 

with basin characteristics outside this range. Estimated 

streamflows produced by the NYSET do not include 

alterations to streamflow by regulation, mining, or other 

large water uses. Results from the NYSET also may not be 

valid where groundwater and surface-water divides are not 

coincident. This can occur in areas with karst topography or 

mining activity.

References Cited

Archfield, S.A., and Vogel, R.M., 2010, Map correlation 

method—Selection of a reference streamgage to estimate 

daily streamflow at ungaged catchments: Water Resources 

Research, v. 46, no. 10, 15 p. [Also available at http://

dx.doi.org/10.1029/2009WR008481.]

Archfield, S.A., Vogel, R.M., Steeves, P.A., Brandt, S.L., 

Weiskel, P.K., and Garabedian, S.P., 2010, The Massachusetts sustainable-yield estimator—A decision-support tool 

to assess water availability at ungaged stream locations in 

Massachusetts: U.S. Geological Survey Scientific Investigations Report 2009–5227, 41 p., plus CD–ROM. [Also available at http://pubs.usgs.gov/sir/2009/5227/.]

Barnes, C.R., 1986, Method for estimating low-flow statistics 

for ungaged streams in the lower Hudson River basin, New 

York: U.S. Geological Survey Water-Resources Investigations Report 85–4070, 22 p. [Also available at http://pubs.

er.usgs.gov/publication/wri854070.]

Braun, W.J., 2013, MPV—Data sets from Montgomery, Peck 

and Vining’s book: The Comprehensive R Archive Network 

Web page, accessed December 5, 2014, at http://cran.rproject.org/web/packages/MPV/index.html.

Cember, R.P., and Wilks, D.S., 1993, Climatological atlas of 

snowfall and snow depth for the northeastern United States 

and southeastern Canada: Ithaca, N.Y., Northeast Regional 

Climate Center Publication RR 93–1, 18 p.

Daly, Christopher, 1996, Overview of the PRISM model: 

PRISM Climate Group Web page, accessed December 7, 

2011, at http://www.ocs.orst.edu/prism/overview.html.

Eissler, B.B., 1979, Low-flow frequency analysis of streams in 

New York: New York State Department of Environmental 

Conservation Bulletin 74, 176 p., 3 pls.

Fenneman, N.M., 1938, Physiography of eastern United 

States: New York, McGraw-Hill, 714 p.

Fennessey, N.M., 1994, A hydro-climatological model of daily 

streamflow for the northeast United States: Medford, Mass., 

Tufts University, Ph.D. dissertation, [variously paged].

Fry, J.A., Xian, George, Jin, Suming, Dewitz, J.A., Homer, 

C.G., Yang, Limin, Barnes, C.A., Herold, N.D., and 

Wickham, J.D., 2011, Completion of the 2006 National 

Land Cover Database for the conterminous United States: 

PE&RS, v. 77, no. 9, p. 858–864.

Granato, G.E., 2009, Computer programs for obtaining and 

analyzing daily mean streamflow data from the U.S. Geological Survey National Water Information System web site: 

U.S. Geological Survey Open-File Report 2008–1362, 123 

p., 5 appendixes, CD–ROM. [Also available at http://pubs.

usgs.gov/of/2008/1362/.]

Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in 

water resources: Amsterdam, Elsevier, Studies in Environmental Science 49, 522 p.

Hughes, D.A., and Smakhtin, V.U., 1996, Daily flow time 

series patching or extension—A spatial interpolation 

approach based on flow-duration curves: Hydrological Sciences Journal, v. 41, no. 6, p. 851–871.

Isaaks, E.H., and Srivastava, R.M., 1989, An Introduction to 

applied geostatistics: New York, Oxford University Press, 

561 p.

Linhart, S.M., Nania, J.F., Christiansen, D.E., Hutchinson, 

K.J., Sanders, C.L., Jr., and Archfield, S.A., 2013, Comparison between two statistically based methods, and two 

physically based models developed to compute daily mean 

streamflow at ungaged locations in the Cedar River basin, 

Iowa: U.S. Geological Survey Scientific Investigations 

Report 2013–5111, 7 p. [Also available at http://pubs.usgs.

gov/sir/2013/5111/.]

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. [Also available at http://pubs.usgs.gov/sir/2006/5112/.]
References Cited 27

Lumley, Thomas, 2009, Leaps—Regression subset selection: The Comprehensive R Archive Network Web page, 

accessed December 5, 2014, at http://cran.r-project.org/web/

packages/leaps/index.html.

Mohamoud, Y.M., 2008, Prediction of daily flow-duration 

curves and streamflow for ungauged catchments using 

regional flow-duration curves: Hydrological Sciences Journal, v. 53, no. 4, p. 706–724.

Nash, J.E., and Sutcliffe, J.V., 1970, River flow forecasting 

through conceptual models; part I—A discussion of principles: Journal of Hydrology, v. 10, no. 3, p. 282–290.

Northeast Regional Climate Center, 2011, U.S. drought monitor—Northeast: Ithaca, N.Y., Northeast Regional Climate 

Center Northeast Drought database, accessed November 4, 

2011, at http://www.nrcc.cornell.edu/page_drought.html.

Poff, N.L., and Zimmerman, J.K.H., 2010, Ecological 

responses to altered flow regimes—A literature review 

to inform the science and management of environmental 

flows: Freshwater Biology, v. 55, no. 1, p. 194–205.

R Core Team, 2013, R—A language and environment for statistical computing: R Foundation for Statistical Computing 

Web page, accessed December 5, 2014, at http://www.Rproject.org/.

Randall, A.D., 1996, Mean annual runoff, precipitation, and 

evapotranspiration in the glaciated northeastern United 

States, 1951–80: U.S. Geological Survey Open-File Report 

96–395, 2 sheets. [Also available at http://ny.water.usgs.

gov/pubs/of/of96395/OF96-395.html.]

Randall, A.D., 2010, Low flow of streams in the Susquehanna 

River basin of New York: U.S. Geological Survey Scientific 

Investigations Report 2010–5063, 57 p., accessed December 

5, 2014, at http://pubs.usgs.gov/sir/2010/5063/.

Riggs, H.C., 1972, Low-flow investigations: U.S. Geological Survey Techniques of Water-Resources Investigations, 

book 4, chap. B1, 18 p. [Also available at http://pubs.usgs.

gov/twri/twri4b1/pdf/twri_4-B1_a.pdf.]

Searcy, J.K., 1959, Flow-duration curves, part 2 of Manual of 

hydrology—Low flow techniques: U.S. Geological Survey 

Water-Supply Paper 1542–A, p. 1–33. [Also available at 

http://pubs.usgs.gov/wsp/1542a/report.pdf.]

Shu, Chang, and Ourda, T.B.M.J., 2012, Improved methods 

for daily streamflow estimates at ungauged sites: Water 

Resources Research, v. 48, no. 2, 15 p. [Also available at 

http://dx.doi.org/10.1029/2011WR011501.]

Skøien, J.O., and Blöschl, Günter, 2007, Spatiotemporal 

topological kriging of runoff time series: Water Resources 

Research, v. 43, no. 9, 21 p. [Also available at http://dx.doi.

org/10.1029/2006WR005760.]

Smakhtin, V.Yu., 1999, Generation of natural daily flow timeseries in regulated rivers using non-linear spatial interpolation technique: Regulated Rivers Research and Management, v. 15, no. 4, p. 311–323.

Smakhtin, V.Yu., and Masse, B., 2000, Continuous daily 

hydrograph simulation using duration curves of a precipitation index: Hydrological Processes, v. 14, no. 6, p. 

1083–1100.

Stedinger, J.R., and Tasker, G.D., 1985, Regional hydrologic 

analysis—1. Ordinary, weighted and generalized least 

squares compared: Water Resources Research. v. 21, no. 9, 

p. 1421–1432.

Stedinger, J.R., Vogel, R.M., and Foufoula-Georgiou, Efi, 

1993, Frequency analysis of extreme events, chap. 18 of

Maidment, D.R., ed., Handbook of hydrology: New York, 

McGraw-Hill, 1,424 p.

Stuckey, M.H., Koerkle, E.H., and Ulrich, J.E., 2012, Estimation of baseline daily mean streamflows for ungaged 

locations on Pennsylvania streams, water years 1960–2008: 

U.S. Geological Survey Scientific Investigations Report 

2012–5142, 61 p. [Also available at http://pubs.usgs.gov/

sir/2012/5142/.]

Suro, T.P., and Gazoorian, C.L., 2011, Changes in low-flow 

frequency from 1976–2006 at selected streamgages in 

New York, excluding Long Island: U.S. Geological Survey 

Scientific Investigations Report 2011–5112, 21 p. [Also 

available at http://pubs.usgs.gov/sir/2011/5112/.]

Tasker, G.D., 1980, Hydrologic regression with weighted 

least squares: Water Resources Research, v. 16, no. 6, p. 

1107–1113.

U.S. Department of Agriculture, Natural Resources Conservation Service, 2011, Web soil survey [database for New 

York]: U.S. Department of Agriculture, Natural Resources 

Conservation Service, accessed August 2011, at http://

websoilsurvey.nrcs.usda.gov/.

U.S. Department of Agriculture, Natural Resources Conservation Service, 2013, Web soil survey [database for New 

York]: U.S. Department of Agriculture, Natural Resources 

Conservation Service, accessed August 2013, at http://

websoilsurvey.nrcs.usda.gov/.

U.S. Geological Survey, 2000, US GeoData digital elevation models: U.S. Geological Survey Fact Sheet 00–040, 

2 p. [Also available at http://pubs.er.usgs.gov/publication/

fs04000.]

U.S. Geological Survey, 2012, Water data for the nation: U.S. 

Geological Survey National Water Information System Web 

page, accessed June 23, 2011, at http://waterdata.usgs.gov/

nwis/.
28 Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams, Excluding Long Island, Water Years 1961–2010

U.S. Geological Survey, 2014, New York: U.S. Geological 

Survey StreamStats Program Web page, accessed December 

5, 2014, at http://water.usgs.gov/osw/streamstats/new_york.

html.

Venables, W.N., and Ripley, B.D., 2002, Modern applied statistics with S (4th ed.): New York, Springer, 495 p.

Vogel, R.M., and Stedinger, J.R., 1985, Minimum variance streamflow record augmentation procedures: Water 

Resources Research, v. 21, no. 5, p. 715–723.

Vogel, R.M., Sieber, Jack, Archfield, S.A., Smith, M.P., Apse, 

C.D., and Huber‐Lee, Annette, 2007, Relations among storage, yield, and instream flow: Water Resources Research, v. 

43, no. 5, paper W05403, 12 p., accessed August 2013, at 

http://dx.doi.org/10.1029/2006WR005226.
Appendix 1–5 29

Appendixes 1–5 

[Available at http://dx.doi.org/10.3133/sir20145220]

Appendix 1. Flow-Duration Exceedance Probabilities, Observed and Computed From Stream

 flow Data, and Regression Equations for Streamgages Used in Regression 

 Analysis.

Appendix 2. Description of Reference Streamgages Used in the Development of the New York 

 Streamflow Estimation Tool With Period of Record and Use of Data.

Appendix 3. Reference Streamgages With Index Streamgage Used for MOVE.3 Record 

 Extension.

Appendix 4. Basin Characteristics Used in the Development of Flow-Duration Regression 

 Equations.

Appendix 5. User’s Guide for the New York Streamflow Estimation Tool (NYSET). 

Prepared by the Pembroke Publishing Service Center.

For more information concerning this report, contact:

Director

New York Water Science Center

U.S. Geological Survey

425 Jordan Road

Troy, NY 12180-8349

dc_ny@usgs.gov

or visit our Web site at:

http://ny.water.usgs.gov
Gazoorian—Estimation of Unaltered Daily Mean Streamflow at Ungaged Streams of New York, Water Years 1961–2010—SIR 2014–5220

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20145220