Prepared in cooperation with the

Maryland Department of the Environment

Estimation of Selected Streamflow Statistics for a 

Network of Low-Flow Partial-Record Stations in 

Areas Affected by Base Realignment and Closure 

(BRAC) in Maryland 

Scientific Investigations Report 2010–5170

U.S. Department of the Interior

U.S. Geological Survey
Cover.  Map showing locations of areas to be affected by Base Realignment and Closure (BRAC) activities in Maryland, including

Aberdeen Proving Ground and Fort Meade.
Estimation of Selected Streamflow 

Statistics for a Network of Low-Flow 

Partial-Record Stations in Areas Affected 

by Base Realignment and Closure (BRAC) 

in Maryland

By Kernell G. Ries III and Ken Eng

Prepared in cooperation with the 

Maryland Department of the Environment 

Scientific Investigations Report 2010–5170

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Suggested citation:

Ries, K.G., III, and Eng, K., 2010, Estimation of selected streamflow statistics for a network of low-flow partial-record 

stations in areas affected by Base Realignment and Closure (BRAC) in Maryland: U.S. Geological Survey Scientific 

Investigations Report 2010–5170, 40 p.

ISBN 978-1-4113-2971-3
iii

Contents

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

Introduction.....................................................................................................................................................2

Purpose and Scope .............................................................................................................................3

Description of Study Area ..................................................................................................................4

Low-Flow Partial-Record Station Network Design and Operation .......................................................4

Selection of Index Streamgages and Computation of Streamflow Statistics 

at the Streamgages..........................................................................................................................7

Methods for Estimating the Selected Streamflow Statistics at the Low-Flow 

Partial-Record Stations...................................................................................................................7

Maintenance-of-Variance Extension (MOVE1) Method...............................................................15

Moments Method................................................................................................................................15

Q-Ratio Method...................................................................................................................................16

Index-Streamgage Selection............................................................................................................16

Weighting of Independent Estimates ..............................................................................................19

Estimates of the Selected Streamflow Statistics and Comparison of Estimates 

from Different Methods.................................................................................................................20

Summary and Conclusions.........................................................................................................................38

Acknowledgments.......................................................................................................................................39

References Cited..........................................................................................................................................39

Figures

1-2. Maps showing—

1. Location of areas to be affected by Base Realignment and Closure 

(BRAC) activities in Maryland, including Aberdeen Proving Ground 

and Fort Meade....................................................................................................................3

2. Locations of low-flow partial-record stations and index streamgages .....................6

3-4. Graphs showing—

3. MOVE1 relation between low-flow partial-record station 01583200, 

Blackrock Run at Coopersville, MD, and index streamgage 01583500, 

Western Run at Western Run, MD..................................................................................15

4. Relations between log-base 10 residuals from the moments, MOVE1, 

and Q-ratio methods for estimating 7-day, 10-year flows for index 

streamgages in the study area........................................................................................20
iv

Tables

1. Descriptive information for low-flow partial-record stations.........................................................5

2. Historical streamflow measurements and streamflow measurements made 

for this study at the low-flow partial-record stations.............................................................8

3. Descriptive information for index streamgages used to estimate streamflow 

statistics at the low-flow partial-record stations..................................................................12

4. Flow-duration and base-flow statistics for index streamgages used to estimate 

streamflow statistics at the low-flow partial-record stations.............................................13

5. Estimated 7-day, 10-year low-flow statistics and parameters of the log-Pearson 

Type III distribution for index streamgages used to estimate streamflow 

statistics at the low-flow partial-record stations..................................................................14

6. Regression constants and basin-characteristic exponents for equations for 

estimating monthly 85-percent duration flows, 10-year recurrence interval 

minimum base flows, and 7-day, 10-year low flows, with indicators of the 

accuracy of the equations ........................................................................................................18

7. Estimates of the selected streamflow statistics for the low-flow partial-record 

stations determined from index streamgage selection based on physical 

proximity, basin characteristics and τ ....................................................................................23

8. Estimates of the selected streamflow statistics for the low-flow partial-record 

stations determined from index-streamgage selection based on correlation 

coefficient and weighted estimates ........................................................................................33

Conversion Factors and Datum

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 2.590 square kilometer (km2)

Volume

cubic foot (ft3

) 28.32 cubic decimeter (dm3)

cubic foot (ft3

) 0.02832 cubic meter (m3)

Flow rate

cubic foot per second (ft3

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

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

7Q10 7-day, 10-year low flow

ADAPS Automated Data Processing System

APG Aberdeen Proving Ground

ASEE average standard error of estimate

ASEP average standard error of prediction

BRAC Base Realignment and Closure

DoD U.S. Department of Defense

HUC 8-digit hydrologic accounting units

LFPR low-flow partial-record

MDE Maryland Department of the Environment

MOVE1 Maintenance-of-Variance Extension type 1 record extension method

MOMENTS Stedinger and Thomas (1985) record extension method

MSE mean squared error

NSA U.S. National Security Agency

R2 coefficient of determination

R2

adj coefficient of determination adjusted for the number of stations and the 

 number of explanatory variables used to develop the equation

USGS U.S. Geological Survey

WMA Maryland Department of the Environment Water Management Administration

Abbreviations and Acronyms

Estimation of Selected Streamflow Statistics for a 

Network of Low-Flow Partial-Record Stations in 

Areas Affected by Base Realignment and Closure 

(BRAC) in Maryland

By Kernell G. Ries III and Ken Eng

Abstract

The U.S. Geological Survey, in cooperation with the 

Maryland Department of the Environment, operated a network 

of 20 low-flow partial-record stations during 2008 in a region 

that extends from southwest of Baltimore to the northeastern 

corner of Maryland to obtain estimates of selected streamflow 

statistics at the station locations. The study area is expected 

to face a substantial influx of new residents and businesses as 

a result of military and civilian personnel transfers associated 

with the Federal Base Realignment and Closure Act of 2005. 

The estimated streamflow statistics, which include monthly 

85-percent duration flows, the 10-year recurrence-interval 

minimum base flow, and the 7-day, 10-year low flow, are 

needed to provide a better understanding of the availability of 

water resources in the area to be affected by base-realignment 

activities.

Streamflow measurements collected for this study at the 

low-flow partial-record stations and measurements collected 

previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the 

streamflow statistics. Three methods were used to estimate the 

streamflow statistics and two methods were used to select the 

index streamgages. Of the three methods used to estimate the 

streamflow statistics, two of them—the Moments and MOVE1 

methods—rely on correlating the streamflow measurements at 

the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to 

determine the estimates. These methods, recommended for 

use by the U.S. Geological Survey, generally require about 

10 streamflow measurements at the low-flow partial-record 

station. The third method transfers the streamflow statistics 

from the index streamgage to the partial-record station based 

on the average of the ratios of the measured streamflows at 

the partial-record station to the concurrent streamflows at the 

index streamgage. This method can be used with as few as one 

pair of streamflow measurements made on a single streamflow recession at the low-flow partial-record station, although 

additional pairs of measurements will increase the accuracy 

of the estimates. Errors associated with the two correlation 

methods generally were lower than the errors associated with 

the flow-ratio method, but the advantages of the flow-ratio 

method are that it can produce reasonably accurate estimates 

from streamflow measurements much faster and at lower cost 

than estimates obtained using the correlation methods.

The two index-streamgage selection methods were (1) 

selection based on the highest correlation coefficient between 

the low-flow partial-record station and the index streamgages, 

and (2) selection based on Euclidean distance, where the 

Euclidean distance was computed as a function of geographic 

proximity and the basin characteristics: drainage area, percentage of forested area, percentage of impervious area, and 

the base-flow recession time constant, τ. Method 1 generally 

selected index streamgages that were significantly closer to 

the low-flow partial-record stations than method 2. The errors 

associated with the estimated streamflow statistics generally 

were lower for method 1 than for method 2, but the differences 

were not statistically significant.

The flow-ratio method for estimating streamflow statistics 

at low-flow partial-record stations was shown to be independent from the two correlation-based estimation methods. As 

a result, final estimates were determined for eight low-flow 

partial-record stations by weighting estimates from the flowratio method with estimates from one of the two correlation 

methods according to the respective variances of the estimates. 

Average standard errors of estimate for the final estimates 

ranged from 90.0 to 7.0 percent, with an average value of 26.5 

percent. Average standard errors of estimate for the weighted 

estimates were, on average, 4.3 percent less than the best average standard errors of estimate from the separate estimation 

methods.
2 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Introduction

On May 13, 2005, the U.S. Department of Defense 

(DoD) issued a list of suggested military base realignments 

and closures planned to aid in military transformation and 

reduce costs. Subsequently, the U.S Congress appointed 

a Base Realignment and Closure (BRAC) Commission to 

provide an independent, non-partisan review of the DoD’s 

recommendations and to ensure the integrity of the BRAC 

process. The goals of the BRAC recommendations were to 

support force transformation, address new threats and strategies, consolidate business functions, and provide significant 

cost savings. The Commission released its final report to the 

President of the United States on September 8, 2005. The 

President approved the recommendations on September 15, 

2005, and forwarded them to Congress. The recommendations 

became law on November 9, 2005. The military realignments 

as a result of the BRAC process are expected to have a substantial impact on the State of Maryland, where the Aberdeen 

Proving Ground (APG) in Harford County, and Fort George 

G. Meade (Fort Meade) in Anne Arundel County are expected 

to grow larger in order to accommodate transferred Army 

personnel and consolidated operations. 

The Maryland Department of Planning (2006) estimated 

that approximately 25,000 new households will be established 

in Maryland as a result of the BRAC. Of these, approximately 

56 percent of them will be established due to new jobs at APG 

in Harford County, and approximately 42 percent of them will 

be established due to new jobs at Fort Meade in Anne Arundel 

County. The remaining 2 percent of new households will be 

established as a result of new jobs at Joint Base Andrews 

Naval Air Facility, Washington, (formerly Andrews Air Force 

Base) in Prince George’s County. This influx of new residents 

will lead to greater demands for housing, schools, and infrastructure for water, wastewater, power, telecommunications, 

and transportation, particularly in Harford and Cecil Counties.

The increased demand for water and wastewater capacity 

resulting from the influx of new residents and businesses to 

BRAC-affected areas will likely necessitate new applications 

for water-withdrawal and wastewater-discharge permits. The 

Water Management Administration (WMA) of the Maryland 

Department of the Environment (MDE) is responsible for 

evaluating permit applications and issuing these permits 

(Maryland Department of the Environment, 2009). Making 

good permitting decisions will require the WMA to understand 

the natural availability of the affected water resources in relation to current and requested water withdrawals and return 

flows. 

The U.S. Geological Survey (USGS) received funding 

through the MDE in January 2008 to begin a study of the 

potential water-resource impacts that could result from the 

BRAC process on areas in and around APG and Fort Meade. 

The study was funded through June 2009, and consisted of 

four coordinated investigations: (1) water-use activities, (2) 

groundwater simulation modeling, (3) estimation of low-flow 

statistics for streams that could be affected by new water 

withdrawals or pollutant discharges, and (4) hydrologic 

monitoring.

Areas in Maryland that will be affected by the BRAC are 

in the Coastal Plain and Piedmont Physiographic Provinces, 

which are separated by the Fall Line (fig. 1). The Coastal 

Plain, southeast of the Fall Line, is an area of low relief 

adjacent to the Chesapeake Bay. Streams in the Coastal Plain 

have relatively flat gradients, and often are affected by tides 

for substantial distances above their mouths. The Piedmont, 

northwest of the Fall Line, has a gently rolling landscape and 

streams with relatively high gradients, which drain to the 

Chesapeake Bay (Carpenter and Hayes, 1996). The Fall Line 

extends north and south along much of the eastern United 

States, and is named as such because numerous waterfalls 

occur along the line, where rivers transition from the higher 

Piedmont onto the lower Coastal Plain.

The investigation of BRAC water-resource needs was 

divided geographically into a Coastal Plain section that 

focused on Fort Meade, and a Piedmont section that focused 

on APG. Fort Meade is located in the upper part of the Coastal 

Plain near the Fall Line. Most of the anticipated waterresource impacts from this facility are expected to occur 

within the recharge areas of several important Coastal Plain 

aquifers, although some impacts also are likely to occur in 

Piedmont areas adjacent to the base. APG is located primarily 

within the Coastal Plain, but most of the increased water use 

from BRAC-related development is expected to occur in the 

surrounding counties, which are situated largely within the 

Piedmont.

The part of the overall BRAC investigation to estimate 

low-flow statistics for streams that could be affected by new 

water withdrawals or pollutant discharges was further separated into two major tasks. One task was to modify an existing 

Web-based decision-support system named StreamStats (Ries 

and others, 2008) to aid the WMA in evaluating permit applications for new water withdrawals and pollutant discharges 

in the BRAC area. The existing system, which previously 

was available for only part of the BRAC area, allows users to 

select ungaged sites anywhere within the BRAC area, determine drainage boundaries and other basin characteristics, 

and insert the basin characteristics as explanatory variables 

into regression equations to provide estimates of selected 

streamflow statistics for the ungaged sites. For the BRAC 

study, StreamStats was modified to allow its use for the entire 

BRAC area and to provide summaries of water withdrawals 

and return flows upstream from user-selected sites. A separate 

report has been prepared to describe this effort (Ries and others, 2010). The other task, which is addressed in this report, 

was to identify specific sites on streams that may be affected 

by development associated with BRAC and obtain streamflow 

measurements at selected sites that could be used to obtain 

estimates of streamflow statistics with greater accuracy than 

estimates that could be obtained for the sites from available 

regression equations.
Introduction 3

Proving Ground and Fort Meade.

Figure 1. Location of areas to be affected by Base Realignment and Closure (BRAC) activities in Maryland, including Aberdeen 

Purpose and Scope 

The primary purpose of this report is to present streamflow statistics for a network of 20 low-flow partial-record 

(LFPR) stations that was established and operated during 

the summer and fall of 2008 in areas of Maryland that will 

be affected by an influx of new residents and businesses as a 

result of the BRAC process. The estimated streamflow statistics include monthly 85-percent duration flows, the 10-year 

recurrence interval minimum base flow (10-year base flow), 

and the 7-day, 10-year low flow (7Q10). These statistics were 

estimated because they are used by the MDE for making 

permitting decisions. The secondary purpose of this report is 

to present the results of an assessment done to determine the 

adequacy for potential future applications of a new method for 

collecting and analyzing data to obtain estimates of streamflow 

statistics at LFPR stations. The assessment was done by 

comparing the accuracy of estimates obtained by use of established methods for collecting and analyzing data to estimates 

obtained by use of the new method. 

This report describes station selection and operation of 

the network, and methods used to estimate the streamflow 

statistics. Location information, streamflow measurements 

(including historical measurements), basin characteristics, 

and estimated streamflow statistics are provided in this report 

for each of the LFPR stations. Location information, periods 

of record, basin characteristics, and computed streamflow 

statistics also are presented for index streamgages used for 

estimating the streamflow statistics for the LFPR stations. A 

description of the study area also is provided. 
4 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Description of Study Area 

The study area ranges from northeast to southwest of 

Baltimore, Maryland (fig. 1). The counties in Maryland that 

will be most affected by the BRAC are, from northeast to 

southwest, Cecil, Harford, Baltimore, Howard, Anne Arundel, 

Montgomery, and Prince George’s. The City of Baltimore is 

located approximately centrally within the study area, and 

also is expected to be affected by BRAC. These areas are in 

the Piedmont and the Atlantic Coastal Plain Physiographic 

Provinces (Fenneman, 1938). The Fall Line, which roughly 

parallels U.S. Interstate 95 in the study area, separates the 

two physiographic provinces. The Piedmont, northwest of 

the Fall Line, has a gently rolling landscape and streams with 

relatively high gradients, which drain to the Chesapeake Bay 

(Carpenter and Hayes, 1996). The Coastal Plain, southeast 

of the Fall Line, is an area of low relief adjacent to the 

Chesapeake Bay. Streams in the Coastal Plain have relatively 

flat gradients, and often are affected by tides for substantial 

distances above their mouths. The Fall Line extends north and 

south along much of the eastern United States, and is named as 

such because numerous waterfalls occur along the line, where 

rivers transition from the higher Piedmont onto the lower 

Coastal Plain.

APG has been the U.S. Army’s primary chemical warfare 

research and development center since World War I (Spencer 

and others, 2001). It is located in Harford County, primarily on 

land along the northwestern shore of Chesapeake Bay. BRACrelated development in Harford County is expected to occur 

primarily in an inverted “T” shape, running northeast to southwest along the U.S. Interstate 95 corridor, with a perpendicular 

axis to the northwest along Maryland Route 24 into Bel Air, 

although some development also is expected in more sparsely 

developed areas in Harford and Cecil Counties (Michelle 

Dobson, Harford County, oral commun., July 2008). From a 

water-supply perspective, the County is concerned that thousands of additional people could be tapping into the fracturedrock aquifers of the Piedmont in areas west and north of Bel 

Air. Production from the fractured rocks already is marginal 

in some locations (Bolton and others, 2009), and the impact of 

many additional wells could cause significant declines in areas 

where municipal water supplies are not yet available.

Fort Meade is a U.S. Army installation located in Anne 

Arundel County that primarily supports intelligence, knowledge capital, information management organizations, and 

installation operations for facilities and infrastructure in 

support of DoD activities (Anne Arundel County, 2008). The 

National Security Agency (NSA) is located near the western 

boundary of Fort Meade. The BRAC is anticipated to result 

in the addition of 5,695 direct new jobs at Fort Meade and 

NSA (Anne Arundel County, 2008). Development around 

the installation is expected to expand radially along major 

access roads and highways (Anne Arundel County, 2008). 

Substantial amounts of development also are anticipated to 

take place on the grounds of Fort Meade. Numerous row 

houses already have been constructed on the site of the former 

base golf course, and more are planned. From a water-resource 

perspective, Maryland State agencies are concerned that 

the Fort Meade water-supply system, which relies primarily 

on groundwater withdrawn from the Patuxent and Lower 

Patapsco aquifers, could further stress these aquifers. The 

Patuxent aquifer is used for municipal supply in nearby areas 

to the north and east of Fort Meade. At the start of BRAC in 

2005, the potentiometric surface of the aquifer already had a 

drawdown equivalent to more than 40 ft (feet) in areas north 

of Fort Meade (Soeder and others, 2007). Withdrawals of 

groundwater from the Lower Patapsco aquifer, overlying the 

Patuxent, also are a concern. Fort Meade is within the recharge 

area of the Lower Patapsco, and pumpage, if excessive, could 

interfere with aquifer recharge.

Low-Flow Partial-Record Station 

Network Design and Operation

At least 10 years of record usually are required to estimate low-flow frequency statistics, such as the 7Q10, from 

continuous daily streamflow records at streamgages (Riggs, 

1972). At current (2009) prices, the cost for the USGS to 

collect and analyze the 10 years of continuous data needed 

to estimate the 7Q10 at a streamgage in Maryland exceeds 

$140,000. This cost prohibits operating a streamgage everywhere this information is needed. In addition, regulators and 

planners often cannot wait for 10 years for the estimates.

LFPR stations often are established where information on 

low-streamflow conditions is needed, but (1) it is not physically or economically feasible to continuously monitor streamflows at the location, (2) the amount or accuracy of the needed 

streamflow information does not require continuous monitoring at the location, or (3) the information is needed sooner 

than the time that would be required to operate a streamgage 

at the location long enough to accurately compute the statistics 

from the continuous data that would be collected there. At 

LFPR stations, a series of streamflow measurements are made 

during low-flow periods when streamflow is primarily from 

groundwater discharge. These measurements are then related 

to daily mean streamflows on the same days at selected nearby 

streamgages, which are referred to as index streamgages. 

Streamflow statistics for the LFPR stations are then estimated 

from these relations. 

Networks of LFPR stations have been operated intermittently by the USGS in Maryland since at least the mid1950s. These networks have been operated following guidelines described by Riggs (1972) and provided in Technical 

Memorandums issued by the USGS Office of Surface Water, 

which can be found on the Web at http://water.usgs.gov/

osw/pubs/memo.summaries.html#LOW%20FLOW. These 

guidelines suggest that streamflow measurements should be 

obtained several days after the most recent rainfall to assure 

that all streamflow is from groundwater discharge. Each measurement should be obtained on a separate recession to assure 
Low-Flow Partial-Record Station Network Design and Operation 5

that the measured streamflows are independent. As a result, 

LFPR networks usually are operated with a goal of obtaining 

about 10 streamflow measurements at the sites over 3 years of 

operation.

Eng and Milly (2007) developed a new method for 

obtaining streamflow data and estimating streamflow statistics 

at LFPR stations. For this new method of data collection, pairs 

of streamflow measurements are obtained on the same recession. A single pair of measurements can be used to compute 

estimates of the base-flow recession time constant, τ, and 

streamflow statistics but multiple pairs of measurements can 

improve the accuracy of the estimates. As a result, reasonable estimates of streamflow statistics can be obtained after 

collecting data for only a single low-flow season, or less, thus 

decreasing the time and cost needed to obtain the estimates. 

This new method is further described below.

Twenty LFPR stations were operated in the BRAC study 

area during the summer and fall of 2008 (table 1, fig. 2). 

Streamflow measurements obtained for these stations were 

collected in the manner suggested by Eng and Milly (2007). 

LFPR stations were selected for inclusion in the network by 

the USGS in consultation with the MDE. In selecting the 

stations, priority was given to locations on streams that were 

(1) not already gaged, (2) most likely to be affected by the 

BRAC process, (3) minimally affected by water withdrawals 

and return flows, and (4) included in a previous LFPR network, and thus had previous streamflow measurements made 

at the locations. Inclusion of some stations with previous 

streamflow measurements allowed estimating and comparing 

streamflow statistics using traditional estimating techniques 

as well as using the new technique suggested by Eng, Milly, 

Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. 

Geological Survey, U.S. Geological Survey (retired), and 

Cornell University, respectively, written commun., 2008). 

All selected LFPR stations were located within the Piedmont 

areas of Cecil, Harford, Baltimore, Howard, and Montgomery 

Counties. Drainage areas for the LFPR stations ranged from 

2.14 to 30.8 mi2 (square miles). Forested land areas for the 

LFPR stations ranged from 21.3 to 48.1 percent, and impervious surfaces ranged from 0.42 to 28.5 percent. These basin 

characteristics were determined by use of the StreamStats Web 

application for Maryland, which is available on line at http://

streamstats.usgs.gov.

Table 1. Descriptive information for low-flow partial-record stations.

[Latitudes and longitudes are in decimal degrees; drainage areas are in square miles; forest and impervious areas are in percent, determined from the National 

Land Cover Database 2001 (U.S. Geological Survey, 2008a)]

Station 

number

Station name Latitude Longitude Drainage 

area

Forest 

area

Impervious 

area

01494995 Gramies Run near Elk Mills, MD 39.669722 75.830833 30.8 34.8 1.48

01495980 Northeast Creek near Calvert, MD 39.688889 76.008056 13.4 22.5 1.89

01496020 Little Northeast Creek near Pleasant Hill, MD 39.680278 75.929167 5.40 21.3 1.30

01496060 Stony Run near North East, MD 39.606667 75.959167 8.28 48.1 2.67

01496250 Mill Creek at Jackson, MD 39.574722 76.056111 3.55 47.4 3.87

01578150 Deep Creek at Susquehanna Hall Road near Flintville, MD 39.698889 76.263333 6.55 39.8 0.59

01578480 Stone Run at Rising Sun, MD 39.705833 76.077778 6.74 27.2 3.58

01579925 Little Deer Creek near Federal Hill, MD 39.661667 76.448611 13.9 33.6 0.60

01580170 Stout Bottle Branch near Ady, MD 39.620556 76.333611 7.33 23.7 1.81

01580510 Mill Brook near Noble Mill, MD 39.604722 76.240556 4.40 30.4 1.30

01580550 Rock Run at Quaker Bottom Road at Susquehanna State Park, MD 39.601667 76.150556 2.73 35.8 0.98

01581675 West Branch Winters Run near Pleasantville, MD 39.551389 76.446944 8.93 27.1 1.04

01581680 East Branch Winters Run near High Point, MD 39.563333 76.442778 9.57 37.8 1.50

01581985 Second Mine Branch at White Hall, MD 39.623056 76.630000 5.77 37.5 0.51

01583200 Blackrock Run at Coopersville, MD 39.543333 76.733333 9.78 40.8 0.53

01589015 Sucker Branch near Ellicott City, MD 39.278611 76.795000 2.46 25.3 18.00

01590996 Haights Branch near Unity, MD 39.249167 77.065833 2.78 29.5 0.42

01591690 Reddy Branch near Brookeville, MD 39.181944 77.066389 2.14 33.0 2.41

01593650 Middle Patuxent River tributary near Dayton, MD 39.236667 76.940833 4.23 23.0 1.99

01594400 Dorsey Run near Jessup, MD 39.120278 76.782222 11.9 34.0 28.50
6 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Figure 2. Locations of low-flow partial-record stations and index streamgages.

The LFPR network was designed for this study with the 

intention of obtaining two pairs of streamflow measurements 

at each station during the summer of 2008. A total of at least 

5 days of dry weather after a rainfall event were needed to 

obtain a pair of measurements. The fist measurement was 

obtained at a minimum of 3 days after a rainfall event, and at 

least 2 days of dry weather were needed between measurements. Operation of this type of low-flow network was more 

difficult than for a traditional low-flow network because of the 

need to make pairs of measurements within a few days of each 

other and the need to rely on weather forecasts for at least 3 

days in the future when deciding on any given day whether to 

make the first of a pair of measurements. These requirements 

became problematic because unusually frequent rains during 

2008 presented very few opportunities for the collection of 

paired measurements until late summer. As a result, it was necessary to extend data collection into the fall. Also, most summertime rainfall events in Maryland are from thunderstorms of 

limited areal extent and duration, making it difficult to reliably 

determine if a rainfall event had occurred in a particular area.
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 7

In nine cases, initial streamflow measurements were 

made but it rained before the second measurement could be 

made. In five cases, second measurements were made during 

what was thought to be a continuous recession only to find 

after completing the measurements that the streamflow for 

the second measurement was greater than that for the first 

measurement, indicating that the local area had likely experienced an isolated rainfall event between measurements. Two 

usable pairs of measurements were obtained for only 4 of the 

20 LFPR stations. The remaining 16 stations all had one pair 

of useable measurements except for one station, 01589015 

(Sucker Branch near Ellicott City, MD), where no useable 

pairs were obtained. Historical measurements and measurements made during 2008 for the LFPR stations are listed in 

table 2. The number of measurements available at the LFPR 

stations ranged from 2 (stations 01580510, 01581675, and 

01581680) to 20 (station 01593650), with an average of 7.1 

available measurements per station.

Selection of Index Streamgages and 

Computation of Streamflow Statistics 

at the Streamgages

All active streamgages with predominantly natural-flow 

conditions and at least 10 years of streamflow record that were 

located within the five 8-digit hydrologic unit codes (HUCs) in 

the BRAC study area were used as index streamgages for this 

study. These included 23 streamgages in the Chester-Sassafras 

(02060002), the Lower Susquehanna (02050306), the 

Gunpowder-Patapsco (02060003), the Severn (02060004), and 

the Patuxent (02060006) HUCs (Seaber and others, 1987). The 

8-digit HUCs are referred to as accounting units. Additional 

information about HUCs is available online at http://water.

usgs.gov/GIS/huc.html. Station numbers, names, latitudes, 

longitudes, periods of record, and basin characteristics for the 

index streamgages are presented in table 3.

For each index streamgage, monthly 85-percent duration 

flows, the 10-year base flow, and the 7Q10 were computed. 

The monthly 85-percent duration flows are the streamflows 

that were exceeded 85 percent of the time for the given 

month during the period of record. The duration flows were 

computed by use of daily streamflow data from all complete 

water years, which begin on October 1 of the preceding year 

and end on September 30 of the stated year, using the daily 

streamflow values monthly and annual statistics routine of the 

USGS internal Automated Data Processing System (ADAPS) 

computer software (U.S. Geological Survey, 2003). This program computes the flow-duration statistics following methods 

described by Searcy (1959). 

The 10-year base-flow values, defined as the minimum 

annual base flow that can be expected to occur, on average, 

once in 10 years, were computed for the index streamgages 

used in this study by the MDE. Base flow is the component of 

the total streamflow that is derived from groundwater discharge. The MDE determined annual base-flow time series 

using a computer program by Rutledge (1998) that separates 

out the groundwater component from the total streamflow for 

each day in the period of record and then sums the daily baseflow values to determine the total base flow for each year. The 

10-year base-flow values were then computed from the annual 

base-flow time series. The 10-year base-flow values were 

computed by the MDE in units of inches per year to provide a 

direct comparison to annual rainfall. The values were converted to units of cubic feet per second (ft3

/s) for consistency 

with the units of the other streamflow statistics that were 

estimated for this study. The monthly 85-percent duration 

flows and the 10-year base flows for the index streamgages 

are provided in table 4. The 10-year base flows are provided in 

units of inches per year as well as in cubic feet per second.

The 7Q10 is the lowest 7-day mean streamflow that is 

expected to occur, on average, once in 10 years. The 7Q10 

values for the index streamgages were determined by fitting 

a log-Pearson Type III distribution to annual series of minimum 7-day mean flows following methods described by 

Riggs (1972). The 7Q10 values were computed from all 

complete climatic years, which begin on April 1 of the stated 

year and end on March 31 of the following year. Climatic 

years normally are used instead of water years to compute 

7Q10 because late March and early April are normally times 

of relatively high streamflow in most of North America, and 

thus it is unlikely that an annual minimum 7-day mean flow 

would occur at a time that spans two climatic years. The 

SWSTAT program (U.S. Geological Survey, 2008b) is available for computing these statistics. The 7Q10 flows for the 

index streamgages are provided in table 5, along with means, 

standard deviations, and skews of the logarithms of the annual 

7-day low flows, the frequency factors, K, and the years of 

record that were used to compute the 7Q10 values from the 

log-Pearson Type III distribution.

Methods for Estimating the Selected 

Streamflow Statistics at the Low-Flow 

Partial-Record Stations

Three methods were used to estimate the streamflow 

statistics for the LFPR stations by relating measured streamflows at the LFPR stations to concurrent daily streamflows at 

index streamgages. These methods include the Maintenanceof-Variance Extension type 1 (MOVE1) method proposed by 

Hirsch (1982), a Moments approach (Moments) described 

by Stedinger and Thomas (1985), and a flow-ratio approach 

(Q-ratio) first proposed by Potter (2001) and modified by 

Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological 

Survey, U.S. Geological Survey, U.S. Geological Survey 

(retired), and Cornell University, respectively, written commun., 2008). Both the MOVE1 and Moments methods were 
8 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

recommended for use by the USGS Office of Surface Water 

in Technical Memorandum No. 86.02, Low- Flow Frequency 

Estimation at Partial-Record Sites, issued December 16, 

1985 (available online at http://water.usgs.gov/admin/memo/

SW/sw86.02.html.) Both methods assume a linear relation 

between the streamflows at the LFPR station and the index 

streamgage that remains constant with time, thus the relation 

between the same-day streamflows can be used to estimate 

streamflow statistics that represent long-term conditions. Both 

the MOVE1 and Moments methods are suggested for use 

with 10 or more measurements at the LFPR station, whereas 

the Q-ratio method can produce estimates from a single pair 

of measurements made on the same recession. Eng, Milly, 

Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. 

Geological Survey, U.S. Geological Survey (retired), and 

Cornell University, respectively, written commun., 2008) indicated that two pairs of measurements produce optimal Q-ratio 

estimates, and additional pairs of measurements will reduce 

errors with diminishing returns. All three methods are further 

described in the following sections.

Table 2. Historical streamflow measurements and streamflow measurements made for this study at the low-flow partial-record 

stations.

[Streamflows are in cubic feet per second. Shaded streamflows were intended to be paired but second measured streamflow was higher than first streamflow.]

Station number Year Month Day Streamflow Paired

01494995 1981 11 5 1.62 No

1982 11 3 1.02 No

1983 4 21 5.94 No

1983 6 14 3.05 No

1983 8 26 0.649 No

2008 8 11 0.86 Yes

2008 8 14 0.654 Yes

2008 10 22 0.511 No

2008 10 24 0.514 No

01495980 2008 8 11 4.19 No

2008 9 3 2.09 Yes

2008 9 5 1.28 Yes

01496020 2008 8 11 2.15 Yes

2008 8 14 1.28 Yes

2008 10 22 1.39 Yes

2008 10 24 1.37 Yes

01496060 1981 11 14 2.17 No

1982 8 18 1.58 No

1983 4 21 17.8 No

1983 5 13 6.67 No

1983 6 13 4.98 No

1983 8 17 1.27 No

2008 8 11 1.12 Yes

2008 8 14 0.848 Yes

2008 10 22 0.741 No

2008 10 24 0.79 No
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 9

Table 2. Historical streamflow measurements and streamflow measurements made for this study at the low-flow partial-record 

stations.

[Streamflows are in cubic feet per second. Shaded streamflows were intended to be paired but second measured streamflow was higher than first streamflow.]

Station number Year Month Day Streamflow Paired

01496250 1981 11 4 1.61 No

1982 4 13 3.78 No

1982 8 16 1.86 No

1983 4 21 8.68 No

1983 5 13 5.36 No

1983 6 15 4.43 No

2008 8 14 1.22 Yes

2008 8 18 0.815 Yes

2008 10 22 1.19 Yes

2008 10 24 0.786 Yes

01578150 2008 8 11 3.14 No

2008 9 3 2.4 Yes

2008 9 5 2.16 Yes

01578480 1981 11 3 2.35 No

1982 3 30 2.75 No

1982 8 17 1.7 No

1983 4 21 10.7 No

1983 6 16 4.39 No

2008 8 11 2.04 No

2008 9 3 0.817 Yes

2008 9 5 0.614 Yes

01579925 1974 10 24 7.45 No

1975 11 17 20.9 No

1975 11 17 20.9 No

1976 3 8 16.7 No

1976 6 8 13.6 No

1976 7 27 8.28 No

1976 8 25 6.89 No

1977 8 4 6.43 No

1977 9 21 5.34 No

1978 9 12 8.81 No

1978 11 3 6.79 No

1979 5 2 18.9 No

2002 9 19 1.39 No

2008 8 12 4.06 No

2008 9 3 3.95 Yes

2008 9 5 3.46 Yes
10 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Table 2. Historical streamflow measurements and streamflow measurements made for this study at the low-flow partial-record 

stations.

[Streamflows are in cubic feet per second. Shaded streamflows were intended to be paired but second measured streamflow was higher than first streamflow.]

Station number Year Month Day Streamflow Paired

01580170 1980 5 15 11.3 No

1980 6 23 8.76 No

1980 7 17 5.99 No

1980 9 4 3.94 No

1981 3 27 4.46 No

1981 8 28 2.3 No

1982 5 18 4.79 No

1982 9 15 2.72 No

2002 9 19 1.04 No

2008 8 11 3.77 Yes

2008 8 13 3.16 Yes

01580510 2008 8 11 1.16 Yes

2008 8 13 1.06 Yes

01580550 2008 8 11 0.75 No

2008 9 3 0.419 Yes

2008 9 5 0.373 Yes

01581675 2008 8 11 3.49 Yes

2008 8 13 3.1 Yes

01581680 2008 8 11 3.5 Yes

2008 8 13 3.24 Yes

01581985 2008 8 14 2.85 No

2008 9 3 2.45 No

2008 9 16 2.63 Yes

2008 9 19 2.54 Yes

01583200 1956 05 26 10.4 No

1957 05 07 10.6 No

1957 08 22 2.68 No

1958 06 06 13.8 No

1958 09 09 4.96 No

1959 05 12 5.33 No

1959 09 28 1.5 No

1962 07 30 4.59 No

1962 08 30 2.9 No

1963 07 30 3.44 No

1963 09 26 2.1 No

1966 07 21 1.26 No

2002 09 19 0.95 No

2008 09 03 3.09 No

2008 09 16 3.83 Yes

2008 09 19 3.63 Yes
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 11

Table 2. Historical streamflow measurements and streamflow measurements made for this study at the low-flow partial-record 

stations.

[Streamflows are in cubic feet per second. Shaded streamflows were intended to be paired but second measured streamflow was higher than first streamflow.]

Station number Year Month Day Streamflow Paired

01589015 2008 9 3 0.131 No

2008 9 17 0.285 No

2008 9 19 0.46 No

2008 10 20 0.282 No

2008 10 24 0.293 No

01590996 2008 8 7 0.562 Yes

2008 8 14 0.43 Yes

2008 10 20 0.592 Yes

2008 10 24 0.568 Yes

01591690 2008 8 12 0.175 No

2008 9 16 0.321 Yes

2008 9 23 0.249 Yes

2008 10 20 0.324 Yes

2008 10 24 0.317 Yes

01593650 1977 5 31 2.18 No

1977 8 4 1.15 No

1977 9 15 0.692 No

1978 9 21 1.72 No

1978 11 6 1.72 No

1979 5 3 3.86 No

1980 5 15 4.6 No

1980 6 24 3.41 No

1980 9 2 1.22 No

1981 3 27 2.39 No

1981 8 27 0.84 No

1982 5 17 2.08 No

1982 9 14 0.342 No

1990 4 27 4.12 No

1990 9 10 2.07 No

2002 9 20 0.108 No

2008 8 7 0.84 Yes

2008 8 14 0.653 Yes

2008 10 20 0.967 No

2008 10 24 1.08 No

01594400 2008 9 17 2.77 No

2008 9 23 3.3 No

2008 10 20 2.96 Yes

2008 10 24 2.56 Yes
12 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Table 3. Descriptive information for index streamgages used to estimate streamflow statistics at the low-flow partial-record stations.

[Latitudes and longitudes are in decimal degrees; drainage areas are in square miles; forest and impervious areas are in percent, determined from the National 

Land Cover Database 2001 (U.S. Geological Survey, 2008a); τ (base-flow recession constant) is in days; --, not available]

Streamgage 

number Streamgage name Latitude Longitude Period of record

Drainage 

area

Forest 

area

Impervious 

area τ

01493000 Unicorn Branch near Millington, 

MD

39.24969 75.86131 1948–2004, 

2007

19.7 -- 1.01 33.4

01493500 Morgan Creek near Kennedyville, 

MD

39.28003 76.01456 1952–2007 12.5 -- 1.39 46.2

01495000 Big Elk Creek at Elk Mills, MD 39.65706 75.82236 1932–2006 53.3 27.7 1.58 47.2

01580000 Deer Creek at Rocks, MD 39.62997 76.40331 1927–2007 94.3 35.8 1.36 51.4

01581500 Bynum Run at Bel Air, MD 39.54147 76.33011 1945–1969, 

2000–2007

8.38 -- 13.8 32.0

01581700 Winters Run near Benson, MD 39.51994 76.37297 1968–2007 34.6 -- 2.28 50.9

01582000 Little Falls at Blue Mount, MD 39.60408 76.62047 1945–2007 53.8 42.1 0.89 46.6

01583100 Piney Run at Dover, MD 39.52061 76.76689 1983–1987, 

1997–2008

12.5 33.5 1.71 50.1

01583500 Western Run at Western Run, MD 39.51078 76.67650 1945–2007 60.3 36.3 0.86 49.9

01583570 Pond Branch at Oregon Ridge, MD 39.48031 76.68750 1983–1985, 

1999–2007

0.13 100 0.00 43.5

01583580 Baisman Run at Broadmoor, MD 39.47947 76.67803 1965–1968, 

2000–2008

1.49 71.8 0.41 45.6

01584050 Long Green Creek at Glen Arm, 

MD

39.45469 76.47889 1976–2007 9.3 22.9 1.53 55.1

01584500 Little Gunpowder Falls at Laurel 

Brook, MD

39.50536 76.43178 1927–1969, 

1999–2008

36.1 34.6 0.83 58.6

01585100 Whitemarsh Run at White Marsh, 

MD

39.37053 76.44592 195–1988, 

1992–2007

7.56 -- 30.9 25.1

01585200 West Branch Herring Run at 

Idlewylde, MD

39.37364 76.58433 1958–1986, 

1997–2007

2.18 1.53 28.5 32.9

01586210 Beaver Run near Finksburg, MD. 39.48944 76.90294 1983–2007 14.1 23.1 4.10 39.7

01586610 Morgan Run near Louisville, MD 39.45189 76.95531 1983-2008 28.1 35.0 1.56 36.9

01589100 East Branch Herbert Run at 

Arbutus, MD

39.24000 76.69219 1958–1988, 

1999–2007

2.43 6.08 45.7 36.2

01589300 Gwynns Falls at Villa Nova, MD 39.34589 76.73319 1957–1987, 

1997–2007

32.6 18.9 21.1 39.0

01589330 Dead Run at Franklintown, MD 39.31122 76.71664 1960–1986, 

1999–2007

5.47 4.05 45.3 28.7

01591000 Patuxent River near Unity, MD 39.23825 77.05572 1945–2008 35.0 42.6 0.93 32.1

01591400 Cattail Creek near Glenwood, MD 39.25597 77.05106 1979–2008 22.8 24.5 1.88 41.2

01591700 Hawlings River near Sandy Spring, 

MD

39.17467 77.02158 1979–2007 27.2 32.3 3.86 35.9
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 13

Table 4. Flow-duration and base-flow statistics for index streamgages used to estimate streamflow statistics at the low-flow partial-record stations.[All streamflow statistics are in units of cubic feet per second except for 10-year base flows, which also are provided in units of inches; --, not available]

Streamgage 

Number

October 

85-

percent 

flow

November 

85-

percent 

flow

December 

85-

percent 

flow

January 

85-

percent 

flow

February 

85-

percent 

flow

March 

85-

percent 

flow

April 

85-

percent 

flow

May 

85-

percent 

flow

June 

85-

percent 

flow

July 

85-

percent 

flow

August 

85-

percent 

flow

September 

85-

percent 

flow

10-year 

base flow

10-year 

base flow 

(inches)

01493000 6.77 8.16 10.2 12.7 16.1 19.3 18.0 12.5 8.74 6.88 6.46 6.35 10.2 7.001493500 3.24 4.29 4.81 4.79 5.51 5.88 5.35 4.32 3.56 2.85 2.67 2.71 4.42 4.801495000 18.4 24.2 28.2 33.4 39.7 47.9 44.7 36.2 27.1 19.4 16.8 15.9 29.4 7.501580000 38.1 46.6 53.3 62.8 72.1 90.2 89 78.4 62.7 47.8 39.3 35 56.9 8.201581500 1.51 2.33 2.95 4.23 4.94 6.06 5.09 3.62 2.35 1.27 0.92 0.83 3.08 5.001581700 14.3 18.4 22.6 24.9 30.1 33.5 34.4 28.5 21.8 15.4 12.5 11.5 21.4 8.401582000 22.6 27.9 31.1 34.4 42.1 50.4 49 42.5 34.2 25.9 21.3 19.3 30.9 7.801583100 5.00 6.60 7.10 7.12 9.70 11.0 11.0 8.82 6.37 4.74 4.80 4.40 -- --01583500 21.1 26.2 30.8 35.3 43.5 52.8 48.7 41.4 31.9 22.8 18.9 17.3 31.5 7.101583570 0.050 0.060 0.070 0.070 0.080 0.090 0.090 0.070 0.050 0.030 0.020 0.030 0.053 5.501583580 0.38 0.45 0.56 0.63 0.78 0.99 1.00 0.90 0.56 0.29 0.21 0.22 0.483 4.401584050 2.89 3.76 4.47 5.26 6.80 7.75 7.59 6.06 4.80 3.48 2.76 2.51 4.86 7.101584500 13.5 17.2 20.5 23.4 26.6 32.6 30.5 26.1 19.2 14.4 13.1 11.4 18.1 6.801585100 1.38 2.08 2.59 2.64 3.46 3.68 3.52 2.63 1.68 1.19 0.93 0.95 2.56 4.601585200 0.31 0.43 0.60 0.65 0.91 0.93 0.93 0.76 0.6 0.37 0.28 0.26 0.642 4.001586210 4.38 5.79 7.06 8.2 10.9 13.4 13.0 9.69 6.65 4.59 3.67 3.22 8.51 8.201586610 7.94 10.9 13.6 15.8 21.2 25.9 26.1 20.1 14.4 9.26 6.95 5.91 16.1 7.801589100 0.56 0.67 0.79 0.89 1.22 1.29 1.22 0.91 0.78 0.65 0.53 0.52 0.877 4.901589300 9.06 12.6 15.0 16.7 19.4 22.0 22.2 17.3 12.7 9.07 7.63 6.54 13.9 5.801589330 0.55 0.80 1.12 1.31 1.54 1.92 1.72 1.29 0.93 0.68 0.51 0.51 1.25 3.101591000 7.42 10.9 14.8 17.8 22.3 29.1 27.1 20.7 13.2 7.9 6.04 5.47 15.7 6.101591400 5.50 8.06 11.0 12.1 16.6 17.4 16.5 13.0 9.14 6.08 4.27 3.92 10.7 6.401591700 4.41 7.83 11.8 13.6 17.4 20.7 19.5 15.0 8.72 5.15 3.21 3.16 11.6 5.8
14 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Table 5. Estimated 7-day, 10-year low-flow statistics and parameters of the log-Pearson Type III distribution for index streamgages 

used to estimate streamflow statistics at the low-flow partial-record stations.

[7-day, 10-year low flows are in units of cubic feet per second; means, standard deviations, skews, and K factors are in log-base 10 units]

Station number 7-day, 10-year 

low flow Mean Standard deviation Skew K factor Years of record

01493000 3.22 0.816 0.288 -3.469 -1.071 58

01493500 1.71 0.508 0.206 -0.665 -1.329 54

01495000 8.73 1.252 0.233 -1.019 -1.335 75

01580000 22.9 1.634 0.208 -1.453 -1.324 81

01581500 0.258 -0.018 0.430 -1.386 -1.327 28

01581700 5.59 1.139 0.312 -2.239 -1.256 40

01582000 12.5 1.375 0.209 -0.666 -1.329 63

01583100 2.51 0.707 0.231 -1.229 -1.332 17

01583500 10.7 1.348 0.238 -0.851 -1.334 63

01583570 0.016 -1.354 0.325 -0.437 -1.318 12

01583580 0.168 -0.392 0.289 -0.542 -1.324 13

01584050 1.59 0.508 0.237 -0.164 -1.298 32

01584500 6.59 1.139 0.246 -1.797 -1.301 53

01585100 0.452 -0.022 0.247 -0.265 -1.306 45

01585200 0.092 -0.564 0.468 -3.846 -1.012 39

01586210 1.54 0.584 0.298 -1.396 -1.326 25

01586610 2.98 0.869 0.297 -0.823 -1.333 26

01589100 0.346 -0.222 0.186 -0.037 -1.285 40

01589300 3.75 0.890 0.239 -0.498 -1.322 42

01589330 0.276 -0.261 0.231 -0.100 -1.292 36

01591000 1.85 0.811 0.413 -1.594 -1.316 64

01591400 1.24 0.666 0.432 -1.392 -1.326 30

01591700 0.972 0.574 0.440 -1.210 -1.332 29
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 15

Maintenance-of-Variance Extension (MOVE1) 

Method

Before the MOVE1 method is applied, a graph of the 

logarithms-base 10 of the streamflow measurements for the 

LFPR station (Yi

) and the logarithms-base 10 of the same-day 

mean streamflows for the index streamgage (Xi

) is constructed 

to ascertain the linearity of the relation. The correlation coefficient, r, also is computed as an indicator of linearity using:

r

X X Y Y

n s s X Y

i i

x y

i i = − −

−

∑( )( )

( )1

(1)

where X and Y are the means, sx and sy are the standard deviations of Xi

 and Yi , and n is the number of concurrent streamflows (Iman and Conover, 1983). If the relation appears linear, 

then estimates of the logarithms-base 10 of the streamflow 

statistics (Yj

) for the LFPR station are obtained by use of the 

MOVE1 equation:

ˆ ( ) y

j j x

s

Y Y X X

s

= + − (2)

where Xj are the logarithms-base 10 of the streamflow statistics 

computed from available data at the index streamgage, and all 

other variables are as previously defined (Hirsch, 1982). The 

estimates are then retransformed by exponentiation (10Ŷj

) to 

convert the estimates into their original units of measurement, 

cubic feet per second. 

The MOVE1 relation between LFPR station 01583200, 

Blackrock Run at Coopersville, and index streamgage 

01583500, Western Run at Western Run, MD, is shown in 

figure 3. The line through the data points was determined by 

inserting the same-day streamflows for the index streamgage 

(Xi

) into the MOVE1 equation in place of the streamflow 

statistics for the index streamgage (Xj

) shown in equation 2 to 

obtain estimated same-day streamflows for the LFPR station 

(Ŷl), and then connecting the points to illustrate how the 

MOVE1 estimates fit the original data.

An indicator of the errors associated with the MOVE1 

estimates can be obtained by computing the mean-squared 

error (MSE) of the estimates of instantaneous streamflow (Ŷl) 

at the LFPR determined from the MOVE1 relation. The MSE 

is computed as:

2

1

ˆ ( ) / ( 2) n

M l i i MSE Y Y n = = − − ∑ (3)

The MSEM is a sample estimate of the model variance of 

the MOVE1 relation. Estimates of streamflow statistics 

determined from the MOVE1 relations will have somewhat 

greater errors than the indicated MSE values because the 

values do not account for sampling errors associated with the 

limited data available to establish the relation and to compute 

the streamflow statistics for the index streamgages. The MSE 

also does not account for errors associated with obtaining the 

streamflow measurements at the LFPR stations.

Moments Method

The Moments method developed by Stedinger and 

Thomas (1985) is applicable only for estimating low-flowfrequency statistics. As a result, it was useful only to estimate 

7-day, 10-year low-flow frequency statistics for this study. 

In this method, ordinary-least-squares regression analysis is 

used to fit a line of relation between the base-10 logarithms 

of the streamflow measurements at a LFPR station and the 

base-10 logarithms of the same-day streamflows at an index 

streamgage. This linear relation is then used to obtain sample 

estimates of base-10 logarithms of the mean (μ) and standard 

deviation (σ) of the annual minimum N-day low flows at the 

LFPR station. Stedinger and Thomas (1985) provided equations that can be used to adjust the sample estimates to obtain 

unbiased estimates of the parameters. Estimates of base-10 

logarithms of the low-flow-frequency statistics can be computed by inserting the unbiased parameter estimates into the 

equation:

YT = μ + KT σ (4)

where YT

 is the base-10 logarithm of the annual minimum 

N-day mean flow that is exceeded, on average, once in T

years, and KT

 is a frequency factor for the log-Pearson Type III 

distribution that depends on the skew of the annual minimum 

N-day low flows and the recurrence interval to be estimated. 

Stedinger and Thomas (1985) showed that it is reasonable to 

assume that the KT

 for the LFPR station is the same as the KT

for the index streamgage, and they provide an equation for 

Figure 3. MOVE1 relation between low-flow partial-record 

station 01583200, Blackrock Run at Coopersville, MD, and index 

streamgage 01583500, Western Run at Western Run, MD.
16 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

computing the variance of the YT estimate. Estimates from 

equation 4 can be retransformed by exponentiation (10YT ) to 

obtain estimates in units of cubic feet per second.

Q-Ratio Method

Potter (2001) developed a method by which a base-flow 

statistic is estimated as the product of the base-10 logarithm 

of the computed statistic at the index streamgage and the 

geometric mean of the base-10 logarithms of the ratios of the 

measured base-flow discharges and the concurrent discharges 

at the index streamgage. Potter (2001) assumed a bivariate 

normal distribution for the flows at the assumed LFPR station 

and the index streamgage. The method was used to estimate 

the median daily discharge, the 0.90 quantile of daily streamflow, and the mean base flow for two watershed pairs in 

Wisconsin. Potter (2001) obtained estimates with low standard 

error and low bias when the log-transformed streamflows for 

the stations were highly correlated and had nearly equal variances, but results were not as good when these conditions did 

not exist.

The modified Q-ratio approach by Eng, Milly, Tasker, 

and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological 

Survey, U.S. Geological Survey (retired), and Cornell 

University, respectively, written commun., 2008) was applied 

in this study. This method does not assume a bivariate normal 

distribution. As a result, logarithmic transformations are 

not done on the computed streamflow statistic at the index 

streamgage or on the ratios of the concurrent streamflows, thus 

allowing application of the method at locations with zero-flow 

values. Estimates obtained by use of the Q-ratio approach are 

determined by

Ŷj = WXj (5)

where W is calculated as

W

n

Y

X

i

i i

n

= =

∑

1

1

(6)

and n is the total number of concurrent measurements between 

the LFPR and index streamgage. The MSE was calculated by

2

1

ˆ ( ) / ( 2) n

Q l i i MSE Y Y n = = − − ∑ (7)

where MSEQ is a sample estimate of the model variance of the 

Q-ratio method estimates. 

Index-Streamgage Selection

The USGS provides no official guidance on selecting 

index streamgages to estimate low-flow statistics for LFPR 

stations, and various researchers have used different selection 

methods. For example, Stedinger and Thomas (1985) based 

selection on similar drainage areas and base-flow recession 

characteristics. Riggs (1972) suggested selecting an index 

streamgage with concurrent streamflows that are directly proportional to those at the LFPR station. Potter (2001) suggested 

that selection of an index streamgage should be based on the 

similarity of the variances determined from the logarithms of 

the continuous base-flow records at the index streamgage and 

LFPR station, but this guidance is useful only if some continuous streamflow record is available for the LFPR station. Reilly 

and Kroll (2003) estimated 7Q10s and the associated variances 

for LFPR stations using multiple index streamgages that were 

selected on the basis of geographic proximity and similarity 

of basin characteristics. The estimates for the LFPR stations 

with the lowest variances were then used as the final estimates 

for the LFPR stations. Ries and Friesz (2000) also estimated 

7Q10s, as well as other low-flow statistics, and their associated variances for multiple index streamgages selected on the 

basis of having correlation coefficients of at least 0.80, and 

obtained final estimates by weighting the estimates obtained 

from the relations with each index streamgage according to 

the variances of the estimates. Eng and Milly (2007) suggested 

that, as an alternative to either matching or minimizing statistical properties, a better method for selecting a single index 

streamgage would be based on variables derived from baseflow analysis, such as the base-flow-recession time constant, τ, 

that can be calculated at LFPR stations.

Eng and Milly (2007) defined τ as the long-term recession 

rate of streamflow from groundwater discharge. Streamflows 

during base-flow periods will decline more slowly in streams 

with large τ values compared to streams with small τ values. 

Streams with similar τ values can be expected to decline at 

similar rates. Eng and Milly (2007) explain in detail the physical basis for τ and provide the following equation for computing τ, in units of days:

ln ln j j J

J t

Q Q

τ

+

∆ = − (8)

where Qj is the daily streamflow on day j, Qj+J is the streamflow on day j + J, J is the number of days between two 

streamflow measurements made on a single recession, and Δt

is the length of 1 day. This equation is used to compute τ from 

each pair of measurements made on the same recession at the 

LFPR stations, and the values from the individual recessions 

are averaged to obtain the final τ values for the LFPR stations.

A computer program developed by Ken Eng (U.S. 

Geological Survey, written commun., 2009) was used in this 

study to select index streamgages by either maximizing the 

correlation coefficient or minimizing the Euclidean distance 

metric, Ri , from the LFPR station to index streamgage i, where 

Ri

 is a function of geographic proximity, τ, and other basin 

characteristics (Eng, Milly, Tasker, and Gruber-Veilleux, U.S. 

Geological Survey, U.S. Geological Survey, U.S. Geological 

Survey (retired), and Cornell University, respectively, written 

commun., 2008). Ri

 is computed by
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 17

2 1/2

1 log

log log [ ( ) ] p

k ki

i

k k

R ω

ω ω

σ =

− = ∑ (9)

where k is a basin characteristic from 1 to p, p is the total 

number of basin characteristics, ω is a selected basin characteristic, and log k

σ ω is the regional standard deviation of the kth

basin characteristic. The geographic proximity is included as 

a basin characteristic in equation 9. The selection process first 

established a subset of all available index streamgages whose 

geographic proximity was within the specified limit of 140 

km (kilometers). From this subset, Ri

 values were calculated 

between the LFPR site and each candidate index site, and the 

candidate index site associated with the lowest Ri

 value was 

selected.

The program allows specification of a maximum geographic proximity, and whether or not to include any of up to 

four basin characteristics in the selection process. A maximum 

physiographic proximity of 140 km was used for this study 

to avoid spurious index-station selections. The basin characteristics used for this study were drainage area, percentage of 

forested area, percentage of impervious surfaces, and τ.

The program first establishes the subset of all available 

index streamgages whose geographic proximity is within 

the specified limit and then calculates the Ri

 values between 

the LFPR station and each candidate index streamgage. The 

candidate index streamgage associated with the lowest Ri

value is then used to estimate the low-flow statistics for the 

LFPR station using all three estimation methods described 

above. The program also computes the estimators of the model 

variances of the estimated low-flow statistics. Program runs 

were made for each LFPR station using both station-selection 

methods and the results were compared to determine the 

best estimates for each LFPR station. The τ values used for 

the index streamgages in equation 9 were the averages of τ

values computed from the daily mean streamflows at the index 

streamgages on the same days that were used to compute the 

average τ values for the LFPR stations. This differs from the 

approach that Eng and Milly (2007) used, which is to use the 

average of τ values calculated from 400 independent recessions made at random from the daily mean streamflows at the 

index streamgage. The average index-streamgage τ values 

computed from the days of concurrent streamflows provides 

a more direct comparison of τ under the conditions when the 

measurements were made than comparing the LFPR station τ

to the average index streamgage τ computed from 400 random 

recessions.

Regression analyses were run to determine whether 

the basin characteristics chosen for use in the index-station 

selection process were actually important in explaining the 

variation in the streamflow statistics of interest for this study. 

Streamflow statistics and the basin characteristics—drainage 

area, percent forested land area, percent impervious surfaces, 

and τ—for each index streamgage were used to develop a 

regression equation for each streamflow statistic. The equations were in the form of:

 Q = aDAb

Fc(I+1)dτ e (10)

where Q is the streamflow statistic, a is the regression constant, DA is the drainage area, in square miles, F is the 

percentage of forested area in the basin, I is the percentage of 

impervious surfaces in the basin, τ is as previously defined, 

and b, c, d, and e are regression coefficients. Results from the 

regression analyses are shown in table 6.

P-values were used to determine if the regression 

constants and exponents in the equations were statistically 

significant. The p-values are shown for each equation in table 

6 on the line below the listing of the equation. The p-values 

indicate the probability that there is no real relation between 

the streamflow statistic and the regression-equation parameter. 

Statistical significance was assumed at a maximum p-value of 

0.05, which indicates a 5-percent probability of erroneously 

accepting the variable as statistically significant. The regression constant and drainage area were statistically significant in 

each of the regression equations. The percentage area of forest 

was statistically significant for the October through January 

85-percent duration flows. The percentage of impervious area 

was statistically significant for the February through May 

85-percent duration flows and the 10-year base flow. τ was 

statistically significant for the October through January and 

May through September 85-percent duration flows, as well as 

for the 7Q10.

The equations in table 6 were developed only as a means 

of determining which variables to include in the index-station 

selection process. As all of the variables were statistically 

significant for at least some of the statistics, all of the variables 

were used as criteria for selecting index streamgages. The 

equations could potentially be used to estimate the streamflow 

statistics for ungaged sites in the study area, except that τ 

cannot be computed for ungaged sites. Only the equations for 

the February through April 85-percent duration flows and the 

10-year base flow do not include the τ variable.

The R2

adj values in table 6 are the adjusted coefficients of 

determination, which state the percentage of the variation in 

the streamflow statistics used as the dependent variables in the 

equations that is explained by the variation in the basin characteristics used as the explanatory variables. The R2

adj values 

are adjusted for the number of streamgages and the number 

of explanatory variables used to develop the equations. These 

values were all were very high, ranging from 95.8 for the 

7Q10 to 99.6 for the January 85-percent duration flow.

In addition to the R2

adj values, other indicators of the 

accuracy of the equations provided in table 6 are the average 

standard errors of estimate (ASEE) and prediction (ASEP), 

both given in percent. The ASEE is an indication of the 

model error, and is determined from the differences between 

the observed values of the streamflow statistics for the 

streamgages and the values estimated from the regression 

equations. Approximately two-thirds of the estimates had 

errors that were within the given average ASEE, which ranged 

from 40.2 percent for the 7Q10 to 11.9 percent for the January 

85-percent duration flow. The ASEP is an indicator of the error 
18 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Table 6. Regression constants and basin-characteristic exponents for equations for estimating monthly 85-percent duration flows, 

10-year recurrence interval minimum base flows, and 7-day, 10-year low flows, with indicators of the accuracy of the equations.

[All streamflow statistics are in units of cubic feet per second; regression constants (a) and exponents (b), (c), (d), and (e) are unitless; red values on second 

lines are p-values associated with the regression coefficients; adjusted R2 is the proportion of the variation in the dependent variable that is explained by the 

explanatory variables, adjusted for the number of stations used in the analysis and the number of explanatory variables; t is the base-flow recession constant; 

ASEE is the average standard error of estimate; ASEP is the average standard error of prediction.]

Statistic (a)

Constant

(b)

Drainage 

area

(square 

miles)

(c)

Forest

Area

(percent)

(d)

Impervious

area

(percent + 1)

(e)

τ

(days)

Adjusted R2

(percent)

ASEE

(percent)

ASEP

(percent)

October 85-percent flow -2.837 1.009 0.131 1.28 98.68 20.9 29.5

0.000 0.000 0.044 0.001

November 85-percent flow -2.182 1.034 0.142 0.93 99.27 17.2 26.1

0.000 0.000 0.012 0.003

December 85-percent flow -1.556 1.039 0.141 0.600 99.53 13.6 22.1

0.000 0.000 0.003 0.011

January 85-percent flow -1.412 1.059 0.139 0.53 99.58 11.9 18.8

0.000 0.000 0.001 0.010

February 85-percent flow -0.179 1.064 -0.145 99.19 16.4 21.8

0.000 0.000 0.000

March 85-percent flow -0.110 1.077 -0.166 99.47 13.6 17.4

0.008 0.000 0.000

April 85-percent flow -0.113 1.07 -0.173 99.37 15.6 19.7

0.011 0.000 0.000

May 85-percent flow -0.986 1.067 -0.149 0.47 99.47 13.5 17.7

0.050 0.000 0.001 0.049

June 85-percent flow -2.396 1.065 1.2 99.08 17.9 23.9

0.000 0.000 0.000

July 85-percent flow -2.788 1.089 1.32 99.07 19.8 24.8

0.000 0.000 0.000

August 85-percent flow -3.299 1.109 1.56 98.46 24.8 28.9

0.000 0.000 0.000

September 85-percent flow -3.380 1.045 1.64 98.38 24.1 30.6

0.000 0.000 0.000

10-year base flow -0.368 1.083 -0.117 99.16 17.5 21.1

0.000 0.000 0.005

7-day, 10-year low flow -4.952 1.007 2.46 95.84 40.2 46.5

0.000 0.000 0.000
Methods for Estimating the Selected Streamflow Statistics at the Low-Flow Partial-Record Stations 19

associated with estimating the streamflow statistics for locations other than the streamgages used to develop the equations, 

including the locations of LFPR stations. Approximately twothirds of the estimates for these ungaged locations will have 

errors that are within the given ASEP, which ranged from 46.5 

percent for the 7Q10 to 17.4 percent for the March 85-percent 

duration flow.

Weighting of Independent Estimates

The Interagency Advisory Committee on Water Data 

(IACWD) (1982) showed that if two independent floodfrequency estimates are available for a streamgage, then an 

improved estimate can be obtained for the streamgage by 

computing the weighted average of the independent estimates 

using the equation:

y x

y x

xV yV z V V+ = + (11)

where z is the logarithm of the weighted flood-frequency 

estimate, x and y are the logarithms of the two independent 

flood-frequency estimates, and Vx and Vy are the variances of 

those estimates, in units of squared logarithms. The variance 

of the resulting improved estimate will be less than the variance for either of the independent estimates, and is computed 

using the equation:

x y

z

x y

V V

V

V V = + (12)

where Vz is the variance of the weighted estimate. The above 

equations are applicable not just to flood-frequency estimates 

for streamgages, but also to independent estimates of any 

streamflow statistic for a LFPR station. 

An analysis was done to investigate the potential independence of the MOVE1, Moments, and Q-ratio methods 

used for estimating streamflow statistics for this study. The 

analysis was done using resampling techniques on the daily 

time series for the 23 index streamgages and treating them as 

LFPR stations. This method was first applied by Eng, Milly, 

Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. 

Geological Survey, U.S. Geological Survey (retired), and 

Cornell University, respectively, written commun., 2008), and 

is summarized here. All independent recessions of at least 8 

days or longer were identified from daily time-series for the 

index streamgages. The first 5 days of each recession were 

truncated and then daily mean streamflows for a pair of days 

were randomly selected as simulated LFPR streamflow measurements. The truncation was done to avoid selection of daily 

mean streamflows that may be affected by channel storage and 

direct runoff contributions. The sensitivity of performance to 

the number of measurements, n, was explored by varying n

across the values 2, 3, 4, 5, 6, 7, 8, 10, 15, and 18, which are 

the values of n at the LFPR stations in this study (see tables 1 

and 2). The sampling of the time series described above was 

repeated 500 times for each value of n to obtain robust error 

statistics. Maximum correlation among concurrent streamflow 

measurements and hybrid space of geographic proximity and 

basin characteristics were used to select index streamgages. 

For each value of n, the Moments method, MOVE1, and the 

Q-ratio methods were applied to calculate estimates of the 

7Q10. This process was repeated using the remaining 499 

datasets. For each LFPR station, 500 residuals were computed 

by subtracting the estimated 7Q10 (log-base 10) from the 

computed 7Q10 (log-base 10) at the station that is treated as a 

LFPR station. 

As an example, the averages of the 500 squared 

errors across the 23 simulated LFPR stations (actual index 

streamgages) using the MOVE1 method ranged from 0.0011 

to 0.22, with an arithmetic regional average of 0.048 for n

equal to 18. This regional average variance reflects the errors 

that can be expected when applying the MOVE1, Moments, 

and (or) Q-ratio methods at a real LFPR station with 18 

streamflow measurements. The simulated LFPR stations with 

large average squared errors relative to the regional average of 

0.048 were stations that did not have index streamgages with 

hydrologically similar basins nearby, as defined by the hybrid 

space or by maximum correlation of concurrent streamflows 

of less than 0.75. In this study, all actual LFPR stations had a 

hydrologically similar basin nearby (average correlation coefficient equal to 0.968). 

Graphs of the relations between the residuals from each 

estimation method, shown in figure 4, were used to evaluate 

independence among them. Regression equations and coefficients of determination (R2

) are included in the graphs in 

figure 4 to explain the relations, where y is the dependent variable shown on the y axis of the graphs and x is the explanatory 

variable shown on the x axis. The R2 values are a measure of 

the proportion of the variation in y that is explained by the 

variation in x. Results showed that the Moments and MOVE 

methods produce highly correlated estimates, indicating that 

the methods are not independent. Estimates from the Q-ratio 

method are independent from both the Moments and MOVE 

methods, however. The correlation between the Moments and 

MOVE methods is not unexpected, as both methods use the 

same streamflow data and a line-fitting technique to determine 

the estimates. The Q-ratio method uses different streamflow 

data and does not rely on a line-fitting technique to determine 

the estimates. As a result, it also is not unexpected that the 

Q-ratio method would give estimates that are independent 

from the Moments and MOVE estimates.

In application of the weighting method, the variances for 

the Q-ratio estimates from index-streamgage selection based 

on geographical proximity and similarity of basin characteristics were compared to the variances for the estimates from 

index-station selection based on correlation coefficients. The 

Q-ratio estimates with the lower variances were used in the 

weighting process along with the MOVE1 or Moments estimates for the LFPR station that had the lowest variance.
20 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Figure 4. Relations between log-base 10 residuals from 

the Moments, MOVE1, and Q-ratio methods for estimating 

7-day, 10-year flows for index streamgages in the study area. 

[Equations relate the dependent variables on the y axis to the 

explanatory variables on the x axis. R2

 is the coefficient of 

determination, a measure of the proportion of the variation in 

the dependent variable that is explained by the explanatory 

variable.]

Estimates of the Selected Streamflow 

Statistics and Comparison of Estimates 

from Different Methods

Estimates of the selected streamflow statistics determined 

from the three different estimation methods and the two different index-streamgage selection methods are provided in tables 

7 and 8. Ideally, tables 7 and 8 would be combined to facilitate 

comparisons of estimates across all methods, but it was not 

possible to fit the combined table on the width of a single 

landscaped page. Estimates for the LFPR stations determined 

based on relations developed with index streamgages that were 

selected on the basis of geographic proximity and similarity 

of basin characteristics are provided in table 7. For each LFPR 

station listed in the table, the following are included: the total 

number of streamflow measurements and the number of pairs 

of measurements that were available for the analyses, the 

average τ value computed from the paired measurements, the 

selected index streamgage, the straight-line distance from the 

LFPR station to the index streamgage, the distance ranking of 

the index streamgage, estimates of the 14 streamflow statistics—monthly 85-percent duration flows, the 10-year base 

flow, and the 7Q10—determined from the three estimation 

methods, and the respective ASEEs. The ASEEs displayed in 

tables 7 and 8, in units of percent, were converted from variances (for the Moments method) and MSEs (for the MOVE1 

method), in units of squared base-10 logarithms, to be more 

easily understood by use of the equation:

ASEE = × 100 exp (5.3018 ) 1 V − (13)

where V is the variance or MSE computed for the estimate 

(Stedinger and Thomas, 1985). All statistics determined from 

each estimation method for an individual station have the 

same ASEE. MOVE1 estimates were provided only when six 

or more measurements were available for computation. The 

Moments method could be used only to obtain estimates of the 

7Q10, and only when eight or more measurements were available for computation.

Estimates of the streamflow statistics for the LFPR 

stations determined from relations developed with index 

streamgages that were selected on the basis of maximum 

correlation coefficient are provided in table 8. For each LFPR 

station listed in the table, the following are included: the 

selected index streamgage, its distance, distance rank, the 

correlation coefficient, the estimated streamflow statistics 

determined from the three estimation methods (where applicable), the weighted estimates, and the respective ASEEs. 

Where available, the weighted estimates are the best estimates 

available for the stations. The weighted estimates of the 

streamflow statistics were determined by combining the best 

Q-ratio estimates from either of the two index-station selection 

approaches with the best estimates from either of the other 

two estimation methods, based on the minimum variance of 
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 21

the estimates. The weighted estimates and their variances 

were computed using equations 11 and 12, and the estimated 

streamflow statistics that are shaded in gray for each LFPR 

station in either table 7 or table 8. The estimates used to determine the final weighted estimates are sometimes listed in different tables. For example, the weighted estimates determined 

for LFPR station 01579925 (Little Deer Creek near Federal 

Hill, MD) were determined by weighting the Q-ratio estimates 

from table 7 with the MOVE1 estimates from table 8, with 

the exception of the weighted estimate for the 7Q10, which 

was determined by weighting the Q-ratio estimate from table 

7 with the Moments estimate from table 8. The variances of 

the weighted estimates that are shown in tables 7 and 8 were 

converted to ASEEs using equation 13. The maximum correlation index-station selection method was used only when at 

least six concurrent streamflows were available from which to 

compute the correlations. As a result, weighted estimates were 

not available for 12 of the 20 LFPR stations.

The number of streamflow measurements used to estimate the streamflow statistics often was less than the total 

number of measurements that were available at the LFPR stations because the index streamgages were not always in operation during times when measurements were made at the LFPR 

stations. In addition, when paired measurements were made, 

only the first of the two measurements was used to estimate 

streamflow statistics with the MOVE1 and Moments methods 

because an assumption for those methods is that the measurements are not correlated. Only estimates from the Q-ratio 

method were available for the new LFPR stations that were 

established for this study, as a maximum of five measurements 

were made at those stations. All concurrent measurements 

were used to compute the Q-ratio estimates, as an assumption 

of independence of the measurements is not required for that 

method. An estimate of the 10-year base flow is not available 

for LFPR station 01581985 (Second Mine Branch at White 

Hall, MD) because this statistic was not computed by MDE 

for the selected index streamgage, station 01583100 (Piney 

Run at Dover, MD).

Estimates were determined using the Q-ratio method for 

all 20 LFPR stations when station selection was based on geographic proximity and similarity of basin characteristics. As 

a minimum of six concurrent streamflow measurements were 

required for index-streamgage selection based on the maximum correlation coefficient, estimates were obtained for only 

eight LFPR stations using that selection method. An average 

of 4.4 measurements was available when selection was based 

on geographic proximity and similarity of basin characteristics, whereas an average of 10.8 measurements was available 

when selection was based on the correlation coefficient.

Moments estimates were available for only two LFPR 

stations and MOVE1 estimates were available for only three 

LFPR stations when selection was based on geographic proximity and similarity of basin characteristics because the number of concurrent streamflow measurements available was less 

than the minimum number required. Averages of the ASEE 

values for all available estimates from this index-streamgage 

selection method were 22.9 percent for the Moments method, 

33.3 percent for the MOVE1 method, and 41.2 percent for 

the Q-ratio method. The average of the ASEE values for the 

Q-ratio method is based on 17 LFPR stations because only two 

measurements were available for 3 of the 20 LFPR stations, 

making computation of the ASEEs for those LFPR stations 

impossible. Estimates were available from all three estimation methods for only two stations when this index-station 

selection method was used. The averages of the ASEE values 

for these two stations were 22.9 percent for the Moments, 

13.0 percent for the MOVE1, and 25.8 percent for the Q-ratio 

methods.

Moments estimates were available for five LFPR stations 

and MOVE1 and Q-ratio estimates were available for eight 

LFPR stations when selection was based on the correlation 

coefficient. Averages of the ASEE values for all available estimates from this index-streamgage selection method, were 14.2 

percent for the Moments, 23.6 percent for the MOVE1, and 

32.1 percent for the Q-ratio methods. Estimates were available 

from all three estimation methods for five stations when this 

index-streamgage selection method was used. The averages of 

the ASEE values for these five stations were 14.2 percent for 

the Moments, 17.4 percent for the MOVE1, and 26.5 percent 

for the Q-ratio methods.

When the estimates from all three estimation methods 

are combined for the two index-station selection methods, a 

total of seven comparisons between the estimation methods 

are available. The averages of the ASEE values for these five 

stations are 16.7 percent for the Moments method, 16.2 percent for the MOVE1 method, and 26.3 percent for the Q-ratio 

method.

Weighted estimates were computed for eight LFPR 

stations in the manner described above. The estimates from 

the Moments, MOVE1, or Q-ratio methods that were used to 

compute the weighted estimates are shaded gray in tables 7 

and 8. The average of the ASEE values for the weighted estimates is 15.5 percent. In comparison, the average of the ASEE 

values for the best individual estimate for these eight LFPR 

stations is 19.8 percent, indicating that ASEEs were reduced 

an average of 4.3 percent as a result of weighting. The average 

of the ASEE values for the best estimates available for all 20 

LFPR stations ranged from 90.0 percent to 7.0 percent, with 

an average ASEE of 26.5 percent. This does not include the 

three LFPR stations for which errors from the Q-ratio method 

could not be computed because too few measurements were 

available.

Direct comparisons were not possible between the errors 

associated with the estimates obtained for the LFPR stations 

for this study and the errors associated with estimates obtained 

from the regression equations published by Carpenter and 

Hayes (1996). It was possible to compute only ASEEs for the 

estimation methods used in this study, whereas Carpenter and 

Hayes (1996) published only ASEPs for their regression equations. Usually, ASEPs are a few percentage points higher than 

ASEEs. The ASEPs that apply to the four hydrologic regions 

(Eastern Piedmont region, subregions A to D) from Carpenter 
22 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

and Hayes (1996) that are within the study area for this study 

range from 20 to 44 percent. 

An examination of differences in the performance of 

the index-streamgage selection methods was made using 

a limited dataset of 20 sets of estimates from selection of 

index streamgages based on geographic proximity and basin 

characteristics and 8 sets of estimates from selection of indexstations based on the correlation coefficient. Average distances 

between the LFPR station and the selected index streamgage 

were 16.1 miles when index-streamgage selection was based 

on the correlation coefficient, and 39.9 miles when indexstreamgage selection was based on geographic proximity 

and similarity of basin characteristics. When the 23 potential 

index streamgages were ranked according to distance from 

the LFPR station, the average distance ranking was 5.0 for 

index streamgages selected based on the correlation coefficient, whereas the average distance ranking was 13.0 for index 

streamgages selected based on geographic proximity and basin 

characteristics. The closest station was never selected when 

selection was based on geographic proximity and similarity of 

basin characteristics, but the closest station was selected four 

of eight times when station selection was based on the correlation coefficient.

When comparisons were made using only the eight 

LFPR stations that had estimates available from both indexstreamgage selection methods, the average distances between 

the LFPR station and the selected index streamgage were 16.1 

miles when station selection was based on the correlation 

coefficient, and 44.6 miles when station selection was based 

on geographic proximity and similarity of basin characteristics. The average distance rankings between the LFPR station 

and the selected index streamgage were 5.0 when station 

selection was based on the correlation coefficient and 14.0 

when station selection was based on geographic proximity 

and similarity of basin characteristics. Paired, one-sided t-tests 

of the direct comparisons of distance and distance rankings 

indicated distances were significantly closer (p = 0.013) and 

distance rankings were significantly higher (p = 0.007) for the 

correlation-coefficient selection method than for the geographic proximity and basin-characteristics selection method. 

Probability plots were used to assure that the assumption of 

normality of the data required for use of the t-tests was valid. 

These results should be qualified by the very small sample size 

of eight observations. It is possible that different results could 

be obtained with more index streamgages for comparison 

or with index streamgages located in areas that are hydrologically different from the study area. Future studies could 

attempt to improve the results by modifying equation 9 to give 

more weight to the geographic proximity or by reducing the 

maximum distance allowed for selection from 87 miles (140 

kilometers) to a smaller value. Currently, all parameters are 

weighted equally in equation 9.

The fact that one index-streamgage selection method 

generally selects index streamgages that are closer to the 

LFPR station than another method does not necessarily 

indicate that the estimates for the method that selects closer 

index streamgages are more accurate than the estimates for the 

other method. For example, an index streamgage on a nearby 

tributary stream with basin characteristics similar to those for 

a LFPR station also on a tributary stream is likely to be a better match for the LFPR station than an index streamgage that 

is geographically closer but on the much larger main stream. 

In Maryland, a nearby index streamgage that is located in the 

Piedmont physiographic region is likely to be a better match 

for a LFPR station that is also in the Piedmont physiographic 

region than a geographically closer index streamgage that is in 

the Coastal Plain physiographic region because the hydrology 

of the two physiographic regions is different. 

A comparison of the errors in the estimates obtained 

from the two index-station selection methods is a better way 

to examine the relative performance of the methods, but 

direct comparisons of the errors could only be made for 7Q10 

estimates obtained from the Q-ratio method. Direct comparisons of the errors could not be made for the other two flowestimation methods because different index streamgages were 

chosen by the two station-selection methods and the numbers 

of streamflow measurements that were available at the different index streamgages were not the same. In the eight direct 

comparisons between Q-ratio estimates obtained from the 

two different station-selection methods, the ASEE was 32.1 

percent for the Q-ratio estimates obtained when index-station 

selection was based on the correlation coefficient, whereas 

the ASEE was 46.6 percent when index-station selection was 

based on geographic proximity and basin characteristics. 

Although this 14.5-percent difference in ASEE between the 

methods is fairly large, a t-test indicated the difference is not 

statistically significant (p = 0.158).
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 23

Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued[τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available]

Partialrecord 

station 

number

Total

measurements Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01494995 9 1 11.0 Oct. 85% 01591700 89.1 22 7 0.663 73.7 0.625 63.7

Nov. 85% 1.13 73.7 1.11 63.7

Dec. 85% 1.65 73.7 1.67 63.7

Jan. 85% 1.88 73.7 1.93 63.7

Feb. 85% 2.36 73.7 2.47 63.7

Mar. 85% 2.77 73.7 2.94 63.7

Apr. 85% 2.62 73.7 2.77 63.7

May 85% 2.05 73.7 2.13 63.7June 85% 1.24 73.7 1.24 63.7

July 85% 0.765 73.7 0.73 63.7

Aug. 85% 0.494 73.7 0.455 63.7

Sept. 85% 0.487 73.7 0.448 63.7

BaseFlow10yr 1.62 73.7 1.65 63.7

7Q10 0.164 73.7 0.138 63.7

01495980 3 1 4.1 Oct. 85% 01583570 49.0 14 3 7.39 51.3

Nov. 85% 8.87 51.3

Dec. 85% 10.3 51.3

Jan. 85% 10.3 51.3

Feb. 85% 11.8 51.3

Mar. 85% 13.3 51.3

Apr. 85% 13.3 51.3

May 85% 10.3 51.3June 85% 7.39 51.3

July 85% 4.44 51.3

Aug. 85% 2.96 51.3

Sept. 85% 4.44 51.3

BaseFlow10yr 7.84 51.3

7Q10 2.37 51.3
24 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued [τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available] Partial- record station number Total measure- ments Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01496020 4 2 5.8 Oct. 85% 01583580 53.5 13 4 1.00 90.0

Nov. 85% 1.19 90.0

Dec. 85% 1.48 90.0

Jan. 85% 1.67 90.0

Feb. 85% 2.06 90.0

Mar. 85% 2.62 90.0

Apr. 85% 2.64 90.0

May 85% 2.38 90.0June 85% 1.48 90.0

July 85% 0.767 90.0

Aug. 85% 0.555 90.0

Sept. 85% 0.582 90.0

BaseFlow10yr 1.28 90.0

7Q10 0.444 90.0

01496060 10 1 10.8 Oct. 85% 01583580 50.4 13 4 0.598 107

Nov. 85% 0.708 107

Dec. 85% 0.881 107

Jan. 85% 0.991 107

Feb. 85% 1.23 107

Mar. 85% 1.56 107

Apr. 85% 1.57 107

May 85% 1.42 107June 85% 0.881 107

July 85% 0.456 107

Aug. 85% 0.330 107

Sept. 85% 0.346 107

BaseFlow10yr 0.760 107

7Q10 0.264 107
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 25

Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued[τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available]

Partialrecord 

station 

number

Total

measurements Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01496250 10 2 9.9 Oct. 85% 01591400 69.5 22 8 1.330 11.6 1.16 15.0

Nov. 85% 1.870 11.6 1.70 15.0

Dec. 85% 2.470 11.6 2.32 15.0

Jan. 85% 2.690 11.6 2.55 15.0

Feb. 85% 3.570 11.6 3.49 15.0

Mar. 85% 3.720 11.6 3.66 15.0

Apr. 85% 3.550 11.6 3.47 15.0

May 85% 2.870 11.6 2.74 15.0June 85% 2.090 11.6 1.92 15.0

July 85% 1.450 11.6 1.28 15.0

Aug. 85% 1.060 11.6 0.899 15.0

Sept. 85% 0.979 11.6 0.825 15.0

BaseFlow10yr 2.410 11.6 2.25 15.0

7Q10 0.352 25.6 0.349 11.6 0.261 15.0

01578150 3 1 19.0 Oct. 85% 01591400 62.4 21 3 3.94 10.6

Nov. 85% 5.77 10.6

Dec. 85% 7.88 10.6

Jan. 85% 8.67 10.6

Feb. 85% 11.9 10.6

Mar. 85% 12.5 10.6

Apr. 85% 11.8 10.6

May 85% 9.31 10.6June 85% 6.55 10.6

July 85% 4.35 10.6

Aug. 85% 3.06 10.6

Sept. 85% 2.81 10.6

BaseFlow10yr 7.66 10.6

7Q10 0.888 10.6
26 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued [τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available] Partial- record station number Total measure- ments Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01578480 8 1 7.0 Oct. 85% 01583570 44.9 14 5 1.44 72.7

Nov. 85% 1.73 72.7

Dec. 85% 2.01 72.7

Jan. 85% 2.01 72.7

Feb. 85% 2.30 72.7

Mar. 85% 2.59 72.7

Apr. 85% 2.59 72.7

May 85% 2.01 72.7June 85% 1.44 72.7

July 85% 0.863 72.7

Aug. 85% 0.575 72.7

Sept. 85% 0.863 72.7

BaseFlow10yr 1.52 72.7

7Q10 0.460 72.7

01579925 16 1 15.1 Oct. 85% 01583580 20.2 9 4 7.52 10.3

Nov. 85% 8.91 10.3

Dec. 85% 11.1 10.3

Jan. 85% 12.5 10.3

Feb. 85% 15.4 10.3

Mar. 85% 19.6 10.3

Apr. 85% 19.8 10.3

May 85% 17.8 10.3June 85% 11.1 10.3

July 85% 5.74 10.3

Aug. 85% 4.16 10.3

Sept. 85% 4.36 10.3

BaseFlow10yr 9.56 10.3

7Q10 3.33 10.3
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 27

Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued[τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available]

Partialrecord 

station 

number

Total

measurements Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01580170 11 1 11.3 Oct. 85% 01591400 55.6 21 10 3.26 14.4 2.54 36.6

Nov. 85% 4.27 14.4 3.72 36.6

Dec. 85% 5.31 14.4 5.07 36.6

Jan. 85% 5.68 14.4 5.58 36.6

Feb. 85% 7.10 14.4 7.65 36.6

Mar. 85% 7.34 14.4 8.02 36.6

Apr. 85% 7.07 14.4 7.61 36.6

May 85% 5.98 14.4 5.99 36.6June 85% 4.66 14.4 4.21 36.6

July 85% 3.50 14.4 2.80 36.6

Aug. 85% 2.73 14.4 1.97 36.6

Sept. 85% 2.57 14.4 1.81 36.6

BaseFlow10yr 5.21 14.4 4.93 36.6

7Q10 1.150 20.1 1.14 14.4 0.572 36.6

01580510 2 1 22.2 Oct. 85% 01583580 31.4 12 2 0.069 --

Nov. 85% 0.082 --

Dec. 85% 0.102 --

Jan. 85% 0.115 --

Feb. 85% 0.143 --

Mar. 85% 0.181 --

Apr. 85% 0.183 --

May 85% 0.164 --June 85% 0.102 --

July 85% 0.053 --

Aug. 85% 0.038 --

Sept. 85% 0.040 --

BaseFlow10yr 0.804 --

7Q10 0.031 --
28 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued [τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available] Partial- record station number Total measure- ments Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01580550 3 1 17.2 Oct. 85% 01583580 37.4 13 3 1.02 26.4

Nov. 85% 1.20 26.4

Dec. 85% 1.50 26.4

Jan. 85% 1.68 26.4

Feb. 85% 2.09 26.4

Mar. 85% 2.65 26.4

Apr. 85% 2.67 26.4

May 85% 2.41 26.4June 85% 1.50 26.4

July 85% 0.775 26.4

Aug. 85% 0.562 26.4

Sept. 85% 0.588 26.4

BaseFlow10yr 1.29 26.4

7Q10 0.449 26.4

01581675 2 1 16.9 Oct. 85% 01591400 37.4 13 2 2.94 --

Nov. 85% 4.31 --

Dec. 85% 5.88 --

Jan. 85% 6.47 --

Feb. 85% 8.87 --

Mar. 85% 9.30 --

Apr. 85% 8.82 --

May 85% 6.95 --June 85% 4.89 --

July 85% 3.25 --

Aug. 85% 2.28 --

Sept. 85% 2.10 --

BaseFlow10yr 3.42 --

7Q10 0.663 --
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 29

Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued[τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available]

Partialrecord 

station 

number

Total

measurements Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01581680 2 1 25.9 Oct. 85% 01583580 17.2 10 2 0.212 --

Nov. 85% 0.251 --

Dec. 85% 0.313 --

Jan. 85% 0.352 --

Feb. 85% 0.436 --

Mar. 85% 0.553 --

Apr. 85% 0.559 --

May 85% 0.503 --June 85% 0.313 --

July 85% 0.162 --

Aug. 85% 0.117 --

Sept. 85% 0.123 --

BaseFlow10yr 2.46 --

7Q10 0.094 --

01581985 4 1 86.2 Oct. 85% 01583100 11.8 5 4 2.19 5.4

Nov. 85% 2.89 5.4

Dec. 85% 3.11 5.4

Jan. 85% 3.12 5.4

Feb. 85% 4.25 5.4

Mar. 85% 4.82 5.4

Apr. 85% 4.82 5.4

May 85% 3.86 5.4June 85% 2.79 5.4

July 85% 2.08 5.4

Aug. 85% 2.10 5.4

Sept. 85% 1.93 5.4

BaseFlow10yr NA

7Q10 1.10 5.4
30 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued [τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available] Partial- record station number Total measure- ments Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01583200 16 1 55.9 Oct. 85% 01583100 2.8 1 4 2.76 32.0

Nov. 85% 3.64 32.0

Dec. 85% 3.92 32.0

Jan. 85% 3.93 32.0

Feb. 85% 5.35 32.0

Mar. 85% 6.07 32.0

Apr. 85% 6.07 32.0

May 85% 4.87 32.0June 85% 3.51 32.0

July 85% 2.62 32.0

Aug. 85% 2.65 32.0

Sept. 85% 2.43 32.0

BaseFlow10yr NA

7Q10 1.380 32.0

01589015 5 0 NA Oct. 85% 01585200 16.0 5 5 0.330 49.1

Nov. 85% 0.458 49.1

Dec. 85% 0.639 49.1

Jan. 85% 0.692 49.1

Feb. 85% 0.969 49.1

Mar. 85% 0.990 49.1

Apr. 85% 0.990 49.1

May 85% 0.809 49.1June 85% 0.639 49.1

July 85% 0.394 49.1

Aug. 85% 0.298 49.1

Sept. 85% 0.277 49.1

BaseFlow10yr 0.683 49.1

7Q10 0.149 49.1
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 31

Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued[τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available]

Partialrecord 

station 

number

Total

measurements Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01590996 4 2 26.1 Oct. 85% 01583570 30.6 10 4 0.639 47.2

Nov. 85% 0.766 47.2

Dec. 85% 0.894 47.2

Jan. 85% 0.894 47.2

Feb. 85% 1.02 47.2

Mar. 85% 1.15 47.2

Apr. 85% 1.15 47.2

May 85% 0.894 47.2June 85% 0.639 47.2

July 85% 0.383 47.2

Aug. 85% 0.256 47.2

Sept. 85% 0.383 47.2

BaseFlow10yr 0.677 47.2

7Q10 0.204 47.2

01591690 5 2 27.6 Oct. 85% 01586210 30.6 10 5 0.214 18.3

Nov. 85% 0.283 18.3

Dec. 85% 0.345 18.3

Jan. 85% 0.401 18.3

Feb. 85% 0.533 18.3

Mar. 85% 0.655 18.3

Apr. 85% 0.636 18.3

May 85% 0.474 18.3June 85% 0.325 18.3

July 85% 0.224 18.3

Aug. 85% 0.179 18.3

Sept. 85% 0.157 18.3

BaseFlow10yr 0.416 18.3

7Q10 0.075 18.3
32 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 7. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index streamgage selection based on physical proximity, basin characteristics and τ.—Continued [τ is the base-flow recession constant, in days; all estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates in table 8; --, not available] Partial- record station number Total measure- ments Pairs Average

τ

Statistic

Index-streamgage selection based on physical proximity, basin characteristics, and τ

Index 

streamgage Distance Distance rank Concurrent streamflows Moments estimate Moments ASEE MOVE1 esti- mate MOVE1 ASEE Q-ratio esti- mate Q-ratio ASEE

01593650 20 1 27.8 Oct. 85% 01583570 24.3 10 5 1.00 35.5

Nov. 85% 1.21 35.5

Dec. 85% 1.41 35.5

Jan. 85% 1.41 35.5

Feb. 85% 1.61 35.5

Mar. 85% 1.81 35.5

Apr. 85% 1.81 35.5

May 85% 1.41 35.5June 85% 1.00 35.5

July 85% 0.603 35.5

Aug. 85% 0.402 35.5

Sept. 85% 0.603 35.5

BaseFlow10yr 1.06 35.5

7Q10 0.322 35.5

01594400 4 1 27.6 Oct. 85% 01493000 64.2 22 4 3.28 28.7

Nov. 85% 3.96 28.7

Dec. 85% 4.95 28.7

Jan. 85% 6.16 28.7

Feb. 85% 7.81 28.7

Mar. 85% 9.36 28.7

Apr. 85% 8.73 28.7

May 85% 6.06 28.7June 85% 4.24 28.7

July 85% 3.34 28.7

Aug. 85% 3.13 28.7

Sept. 85% 3.08 28.7

BaseFlow10yr 4.95 28.7

7Q10 1.56 28.7
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 33

Table 8. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index-streamgage selection based on correlation coefficient and weighted estimates.—Continued[All estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates]

Partial-record station 

number

Statistic

Index-streamgage selection based on correlation coefficient Weighted

Index 

streamgage Distance

Distance 

rank

Concurrent 

streamflows

Correlation 

coefficient

Moments 

estimate

Moments

ASEE

MOVE1 

estimate

MOVE1 

ASEE

Q-ratio 

estimate

Q-ratio 

ASEE Estimate ASEE

01494995 Oct. 85% 01591000 1.1 1 7 0.987 0.645 37.0 0.555 36.0 0.599 25.4

Nov. 85% 0.924 37.0 0.815 36.0 0.868 25.4

Dec. 85% 1.23 37.0 1.11 36.0 1.17 25.4

Jan. 85% 1.46 37.0 1.33 36.0 1.39 25.4

Feb. 85% 1.80 37.0 1.67 36.0 1.73 25.4

Mar. 85% 2.31 37.0 2.18 36.0 2.24 25.4

Apr. 85% 2.16 37.0 2.03 36.0 2.09 25.4

May 85% 1.68 37.0 1.55 36.0 1.61 25.4June 85% 1.11 37.0 0.987 36.0 1.04 25.4

July 85% 0.684 37.0 0.591 36.0 0.636 25.4

Aug. 85% 0.532 37.0 0.451 36.0 0.491 25.4

Sept. 85% 0.485 37.0 0.409 36.0 0.446 25.4

BaseFlow10yr 0.537 37.0 1.17 36.0 0.864 25.4

7Q10 0.191 37.0 0.138 36.0 0.164 25.4

 01495980 Insufficient measurements available for use of this index-streamgage selection method 01496020 Insufficient measurements available for use of this index-streamgage selection method

01496060 Oct. 85% 01586210 10.1 1 6 0.987 0.777 23.0 1.64 57.0 0.912 21.1

Nov. 85% 1.18 23.0 2.17 57.0 1.33 21.1

Dec. 85% 1.58 23.0 2.65 57.0 1.75 21.1

Jan. 85% 1.98 23.0 3.08 57.0 2.15 21.1

Feb. 85% 3.02 23.0 4.09 57.0 3.18 21.1

Mar. 85% 4.10 23.0 5.03 57.0 4.25 21.1

Apr. 85% 3.92 23.0 4.88 57.0 4.07 21.1

May 85% 2.53 23.0 3.64 57.0 2.70 21.1June 85% 1.45 23.0 2.50 57.0 1.61 21.1

July 85% 0.833 23.0 1.72 57.0 0.972 21.1

Aug. 85% 0.598 23.0 1.38 57.0 0.719 21.1

Sept. 85% 0.492 23.0 1.21 57.0 0.603 21.1

BaseFlow10yr 2.09 23.0 3.19 57.0 2.26 21.1

7Q10 0.165 23.0 0.579 57.0 0.229 21.1
34 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 8. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index-streamgage selection based on correlation coefficient and weighted estimates.—Continued [All estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates] Partial-re- cord station number Statistic Index-streamgage selection based on correlation coefficient Weighted Index streamgage Distance Dis- tance rank Concurrent streamflows Correlation coefficient Moments estimate Mom- ents ASEE MOVE1 estimate MOVE1 ASEE Q-ratio estimate Q-ratio ASEE Estimate ASEE 01496250 Oct. 85% 01591000 45.4 15 8 0.995 1.30 9.8 0.821 36.7 1.25 8.2 Nov. 85% 1.72 9.8 1.21 36.7 1.71 8.2 Dec. 85% 2.16 9.8 1.64 36.7 2.20 8.2 Jan. 85% 2.47 9.8 1.97 36.7 2.49 8.2 Feb. 85% 2.92 9.8 2.47 36.7 3.09 8.2 Mar. 85% 3.55 9.8 3.22 36.7 3.58 8.2 Apr. 85% 3.37 9.8 3.00 36.7 3.40 8.2 May 85% 2.76 9.8 2.29 36.7 2.75 8.2 June 85% 1.98 9.8 1.46 36.7 1.96 8.2 July 85% 1.36 9.8 0.874 36.7 1.33 8.2 Aug. 85% 1.11 9.8 0.668 36.7 1.05 8.2 Sept. 85% 1.04 9.8 0.605 36.7 0.972 8.2 BaseFlow10yr 2.25 9.8 1.74 36.7 2.25 8.2 7Q10 0.467 14.8 0.466 9.8 0.205 36.7 0.466 8.2 01578150 Insufficient measurements available for use of this index-streamgage selection method 01578480 Oct. 85% 01582000 18.0 1 7 0.990 1.40 41.3 1.57 34.2 1.50 25.9 Nov. 85% 1.78 41.3 1.94 34.2 1.88 25.9 Dec. 85% 2.02 41.3 2.16 34.2 2.10 25.9 Jan. 85% 2.27 41.3 2.39 34.2 2.34 25.9 Feb. 85% 2.86 41.3 2.93 34.2 2.90 25.9 Mar. 85% 3.52 41.3 3.50 34.2 3.51 25.9 Apr. 85% 3.41 41.3 3.41 34.2 3.41 25.9 May 85% 2.90 41.3 2.96 34.2 2.93 25.9 June 85% 2.25 41.3 2.38 34.2 2.33 25.9 July 85% 1.64 41.3 1.80 34.2 1.73 25.9 Aug. 85% 1.31 41.3 1.48 34.2 1.41 25.9 Sept. 85% 1.17 41.3 1.34 34.2 1.27 25.9 BaseFlow10yr 2.01 41.3 2.15 34.2 2.09 25.9 7Q10 0.707 41.3 0.869 34.2 0.802 25.9
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 35

Table 8. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index-streamgage selection based on correlation coefficient and weighted estimates.—Continued[All estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates]

Partial-record station 

number

Statistic

Index-streamgage selection based on correlation coefficient Weighted

Index 

streamgage Distance

Distance 

rank

Concurrent 

streamflows

Correlation 

coefficient

Moments 

estimate

Moments

ASEE

MOVE1 

estimate

MOVE1 

ASEE

Q-ratio 

estimate

Q-ratio 

ASEE Estimate ASEE

01579925 Oct. 85% 01580000 3.8 1 15 0.986 4.54 15.3 4.90 15.4 6.59 8.5

Nov. 85% 5.67 15.3 5.99 15.4 7.89 8.5

Dec. 85% 6.57 15.3 6.85 15.4 9.67 8.5

Jan. 85% 7.86 15.3 8.07 15.4 11.03 8.5

Feb. 85% 9.15 15.3 9.27 15.4 13.47 8.5

Mar. 85% 11.7 15.3 11.6 15.4 17.13 8.5

Apr. 85% 11.5 15.3 11.4 15.4 17.21 8.5

May 85% 10.0 15.3 10.1 15.4 15.38 8.5June 85% 7.85 15.3 8.06 15.4 10.07 8.5

July 85% 5.83 15.3 6.15 15.4 5.77 8.5

Aug. 85% 4.70 15.3 5.05 15.4 4.33 8.5

Sept. 85% 4.14 15.3 4.50 15.4 4.29 8.5

BaseFlow10yr 7.06 15.3 7.32 15.4 8.78 8.5

7Q10 2.577 10.6 2.59 15.3 2.94 15.4 2.96 7.4

01580170 Oct. 85% 01582000 19.8 7 10 0.998 2.98 10.3 3.05 9.5 3.02 7.0

Nov. 85% 3.72 10.3 3.77 9.5 3.74 7.0

Dec. 85% 4.17 10.3 4.20 9.5 4.18 7.0

Jan. 85% 4.63 10.3 4.64 9.5 4.64 7.0

Feb. 85% 5.73 10.3 5.68 9.5 5.71 7.0

Mar. 85% 6.93 10.3 6.81 9.5 6.86 7.0

Apr. 85% 6.73 10.3 6.62 9.5 6.67 7.0

May 85% 5.79 10.3 5.74 9.5 5.76 7.0June 85% 4.61 10.3 4.62 9.5 4.61 7.0

July 85% 3.44 10.3 3.50 9.5 3.47 7.0

Aug. 85% 2.80 10.3 2.88 9.5 2.84 7.0

Sept. 85% 2.52 10.3 2.61 9.5 2.57 7.0

BaseFlow10yr 4.14 10.3 4.17 9.5 4.16 7.0

7Q10 1.588 10.3 1.59 10.3 1.69 9.5 1.64 7.0
36 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland Table 8. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index-streamgage selection based on correlation coefficient and weighted estimates.—Continued [All estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates] Partial-re- cord station number Statistic Index-streamgage selection based on correlation coefficient Weighted Index streamgage Distance Dis- tance rank Concurrent streamflows Correlation coefficient Moments estimate Mom- ents ASEE MOVE1 estimate MOVE1 ASEE Q-ratio estimate Q-ratio ASEE Estimate ASEE 01580510 Insufficient measurements available for use of this index-streamgage selection method 01580550 Insufficient measurements available for use of this index-streamgage selection method 01581675 Insufficient measurements available for use of this index-streamgage selection method 01581680 Insufficient measurements available for use of this index-streamgage selection method 01581985 Insufficient measurements available for use of this index-streamgage selection method 01583200 Oct. 85% 01583500 4.5 2 15 0.99 3.43 13.1 3.73 18.1 3.54 10.6 Nov. 85% 4.43 13.1 4.64 18.1 4.50 10.6 Dec. 85% 5.37 13.1 5.45 18.1 5.40 10.6 Jan. 85% 6.30 13.1 6.25 18.1 6.28 10.6 Feb. 85% 8.07 13.1 7.70 18.1 7.94 10.6 Mar. 85% 10.1 13.1 9.34 18.1 9.87 10.6 Apr. 85% 9.22 13.1 8.62 18.1 9.01 10.6 May 85% 7.61 13.1 7.33 18.1 7.51 10.6 June 85% 5.59 13.1 5.65 18.1 5.61 10.6 July 85% 3.76 13.1 4.03 18.1 3.86 10.6 Aug. 85% 3.01 13.1 3.34 18.1 3.13 10.6 Sept. 85% 2.71 13.1 3.06 18.1 2.83 10.6 BaseFlow10yr 5.51 13.1 5.57 18.1 5.53 10.6 7Q10 1.533 12.3 1.54 13.1 1.90 18.1 1.65 10.1
Estimates of the Selected Streamflow Statistics and Comparison of Estimates from Different Methods 37

Table 8. Estimates of the selected streamflow statistics for the low-flow partial-record stations determined from index-streamgage selection based on correlation coefficient and weighted estimates.—Continued[All estimated streamflow statistics are in cubic feet per second; distances are in miles; %, percent; Moments is the method developed by Stedinger and Thomas (1985); MOVE1 is the method developed by Hirsch (1982); Q-ratio is the method developed by Potter (2001) and modified by Eng, Milly, Tasker, and Gruber-Veilleux (U.S. Geological Survey, U.S. Geological Survey, U.S. Geological Survey (retired), and Cornell University, respectively, written commun., 2008); ASEE is the average standard error of estimate, in percent; shaded values were used to compute weighted estimates]

Partial-record station 

number

Statistic

Index-streamgage selection based on correlation coefficient Weighted

Index 

streamgage Distance

Distance 

rank

Concurrent 

streamflows

Correlation 

coefficient

Moments 

estimate

Moments

ASEE

MOVE1 

estimate

MOVE1 

ASEE

Q-ratio 

estimate

Q-ratio 

ASEE Estimate ASEE

 01589015 Insufficient measurements available for use of this index-streamgage selection method 01590996 Insufficient measurements available for use of this index-streamgage selection method 01591690 Insufficient measurements available for use of this index-streamgage selection method

01593650 Oct. 85% 01591700 26.3 12 18 0.809 0.712 38.4 1.07 50.1 25.7

Nov. 85% 1.01 38.4 1.33 50.1 25.7

Dec. 85% 1.31 38.4 1.57 50.1 25.7

Jan. 85% 1.63 38.4 1.80 50.1 25.7

Feb. 85% 2.27 38.4 2.21 50.1 25.7

Mar. 85% 3.10 38.4 2.69 50.1 25.7

Apr. 85% 2.72 38.4 2.48 50.1 25.7

May 85% 2.10 38.4 2.11 50.1 25.7June 85% 1.38 38.4 1.62 50.1 25.7

July 85% 0.806 38.4 1.16 50.1 25.7

Aug. 85% 0.597 38.4 0.962 50.1 25.7

Sept. 85% 0.518 38.4 0.881 50.1 25.7

BaseFlow10yr 1.35 38.4 1.60 50.1 25.7

7Q10 0.247 22.9 0.241 38.4 0.547 50.1 19.0

 01594400 Insufficient measurements available for use of this index-streamgage selection method
38 Estimation of Streamflow Statistics for a Network of Low-Flow Partial-Record Stations in Areas Affected by BRAC in Maryland

Summary and Conclusions

The U.S. Geological Survey (USGS), in cooperation with 

the Maryland Department of the Environment (MDE), operated a network of 20 low-flow partial-record (LFPR) stations 

during 2008 in central and northeastern Maryland to obtain 

estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of 

new residents and businesses as a result of military and civilian personnel transfers associated with the Base Realignment 

and Closure Act of 2005 (BRAC). The estimated streamflow 

statistics are needed to provide a better understanding of water 

availability in the BRAC-affected areas in anticipation of 

increased requests to the MDE for new water-withdrawal and 

wastewater-discharge permits. The estimated streamflow statistics include monthly 85-percent duration flows, the 10-year 

base flow, and the 7-day, 10-year low flow.

Three methods were used to estimate the streamflow 

statistics for the LFPR stations by relating the streamflow 

measurements made at the LFPR stations to concurrent 

daily streamflows at nearby, hydrologically similar index 

streamgages, and two methods were used to select the index 

streamgages. The LFPR-station network was designed with 

the intention of obtaining two pairs of streamflow measurements at each LFPR station so that the recently developed 

Q-ratio approach could be used to estimate the streamflow 

statistics. The Q-ratio approach requires as few as one pair 

of measurements made on a single streamflow recession, 

but accuracy of the estimates improves with more pairs of 

measurements. The MOVE1 and Moments methods also were 

used to estimate the streamflow statistics at 8 of the 20 LFPR 

stations by making use of additional measurements made 

previously at those stations. The MOVE1 and the Moments 

approaches normally require the collection of approximately 

10 streamflow measurements at the LFPR stations on independent recessions over a period of about 3 years.

The two methods for selecting the index streamgages 

included (1) maximizing the correlation coefficient, and (2) 

minimizing the Euclidean distance between the LFPR station 

and the candidate index streamgage, where the Euclidean distance was computed as a function of geographic proximity and 

the basin characteristics: drainage area, percentage of forested 

area, percentage of impervious area, and the base-flow recession time constant, τ. The τ values were determined for the 

LFPR stations from the rates of change in flow between the 

pairs of streamflow measurements made on the same recession. Corresponding τ values for the index streamgages were 

computed from the daily streamflows on the same days as 

measurements were made at the LFPR stations.

An analysis of estimated 7-day, 10-year low flows determined by use of the three different flow-estimation methods 

on resampled daily streamflow data for the index streamgages 

indicated that there was no correlation between the estimates 

obtained from the Q-ratio method and the estimates obtained 

from either of the other two methods. As a result, when 

estimates were available from two or more methods for a 

LFPR station, final estimates for the station were determined 

by weighting the Q-ratio estimate with the best estimate from 

the other methods on the basis of the variance of the estimates. 

Average standard errors of estimate (ASEEs) for the final 

estimates for 17 of the 20 LFPR stations ranged from 90.0 

to 7.0 percent, with an average value of ASEE of 26.5 percent. ASEEs for three LFPR stations could not be computed 

because only two measurements were available at the stations.

Sample sizes generally were too small to test for significant differences in the accuracy of the three estimation 

methods. Direct comparisons between all three methods were 

available only for seven LFPR stations. From these comparisons, the average values of the ASEEs for the MOVE1 and 

Moments methods were comparable, at 16.7 and 16.2 percent, 

respectively. The average value of the ASEE for the Q-ratio 

method was 26.3 percent. Although the ASEEs for the Q-ratio 

method generally were higher than the ASEEs for the other 

two estimation methods, the ASEEs for the Q-ratio method 

still are reasonable given the reduced time and cost needed to 

obtain the estimates. The value of weighting independent estimates was illustrated by the fact that the weighted estimates 

had ASEEs that were, on average, 4.3 percent lower than the 

best ASEE from the separate estimation methods.

Index streamgages that were selected based on the correlation coefficient were, on average, significantly closer in distance to the LFPR station and had significantly higher distance 

rankings than index streamgages selected based on geographic 

proximity and similarity of basin characteristics. Closer 

proximities between the LFPR stations and the selected index 

streamgages for the correlation-coefficient station-selection 

method do not necessarily indicate that errors associated with 

estimates of streamflow statistics from that station-selection 

method are less than the errors associated with the estimates 

from the geographic-proximity and basin-characteristics 

station-selection method, however. Direct comparisons of the 

ASEEs obtained for estimates of the 7-day, 10-year low flow 

from the Q-ratio method for eight LFPR stations indicated that 

the average value of the ASEE when index-streamgage selection was based on the correlation coefficient was 14.5 percent 

lower than when index-streamgage selection was based on 

geographic proximity and basin characteristics, but this difference was not statistically significant. As a result, it cannot 

be concluded that one index-streamgage selection method is 

superior to the other.

Future studies could attempt to improve the results for 

the geographic proximity and basin characteristics indexstreamgage selection method by giving more weight to the 

geographic proximity or by reducing the maximum distance 

allowed for selection from 87 miles (140 kilometers) to a 

smaller value. Possible improvements also could be made by 

use of different basin characteristics in the selection process 

that better describe the variation in streamflow statistics. The 

basin characteristics used in this analysis were limited to 

those that could be computed at the time by the StreamStats 
References Cited 39

Web application. Also, more paired streamflow measurements 

available at the LFPR stations could lead to better estimates of 

average τ at the stations.

Operation of the low-flow network in the manner 

required for use of the Q-ratio approach was more difficult 

than for a traditional low-flow network because of the need to 

make pairs of measurements within a few days of each other 

and the need to rely on weather forecasts for at least 3 days in 

the future when deciding on any given day whether to make 

the first of a pair of measurements. This manner of operation 

was especially difficult during a summer of above-average 

precipitation. Two useable pairs of streamflow measurements 

were obtained at only four of the LFPR stations. Frequent 

summer thunderstorms gave few opportunities of at least 

5 days of dry weather needed to obtain a pair of measurements on the same recession. In addition, the often localized 

extent of the thunderstorms made it difficult to determine with 

confidence when the drainage basins for the LFPR stations 

had received rain. Second measurements were obtained nine 

times when available weather information indicated dry conditions had prevailed since the previous measurement, but the 

computed streamflow was higher for the second measurement 

than for the first measurement. It is likely that ASEEs for the 

estimated streamflow statistics at the LFPR stations where 

only one pair of measurements was obtained would have been 

lower if a second pair of measurements had been made.

Acknowledgments

The authors would like to thank MDE for its support of 

this work. In particular, John Grace and Patrick Hammond 

provided perspective on the needs of MDE for streamflow 

statistics and how MDE uses that information, and they 

provided guidance throughout the project. Patrick Hammond 

also provided streamflow statistics that he computed for many 

streamgages in Maryland. The authors also would like to 

thank the several hydrologic technicians from the MarylandDelaware-District of Columbia Water Science Center who 

made streamflow measurements for this project. In particular, 

James Dine helped to select candidate stations, made initial 

inspections of them to determine adequacy for use in the 

network, developed station descriptions, coordinated the datacollection and database-management efforts, and assisted with 

computing streamflow statistics for the streamgages used as 

index streamgages. James Dine’s help was invaluable to the 

successful completion of this study. In addition, the authors 

acknowledge USGS hydrologist Michael Koterba for helping 

to provide some of the information used to describe the study 

area in this report. Finally, the authors appreciate the help of 

USGS employees Jean Wilson, Valerie Gaine, Betzaida Reyes, 

and Timothy Auer, for providing editing, illustrations preparation, and final layout of this report.

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Prepared by USGS West Trenton Publishing Service Center.

Edited by Valerie M. Gaine.

Graphics and layout by Timothy W. Auer.

For additional information, contact:

Kernell G. Ries III, Office of Surface Water

443-498-5617

or Director, MD-DE-DC Water Science Center

U.S. Geological Survey

5522 Research Park Drive

Baltimore, MD 21228

443-498-5500

or visit the MD-DE-DC Water Science Center Web site at:

http://md.water.usgs.gov 

or the StreamStats homepage at:

http://streamstats.usgs.gov
Ries, K.G., III, and Eng, K.—Estimation of Streamflow Statistics for Low-Flow Partial-Record Stations in Areas Affected by BRAC in MD—Scientific Investigations Report 2010–5170

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