REGIONALIZATION OF WINTER LOW-FLOW

CHARACTERISTICS OF TENNESSEE STREAMS

R. H. Bingham__ _______________

US. GEOLOGICAL SURVEY

Water-Resources Investigations Report 86-4007

Prepared in cooperation with the

TENNESSEE DEPARTMENT OF HEALTH AND ENVIRONMENT, OFFICE OF WATER MANAGEMENT

Nashville, Tennessee

1986

UNITED STATES DEPARTMENT OF THE INTERIOR

DONALD PAUL MODEL, Secretary

GEOLOGICAL SURVEY

Dallas L. Peck, Director

For additional information write to:

District Chief U.S. Geological Survey A-413 Federal Building U.S. Courthouse Nashville, Tennessee 37203

Copies of this report can be purchased from:

Open-File Services Section Western Distribution Branch U.S. Geological Survey Box 25425, Federal Center Lakewood, Colorado 80225

CONTENTS

Abstract 1Summary 1Introduction 3Limitations and accuracy of equations 4Estimates of winter low-flow characteristics at ungaged sites 5Verification of regression equations at partial-record sites 6Procedures for regionalizing winter low-flow characteristics 31

Ground water-surface water relations 31Streamflow recession 35Multiple aquifer contributions to streamflow 38

Graphical computation method 38 Weighted-average method 41

Mapping streamflow-recession indexes 41Regression analyses 44

Conclusions 50 References cited 51

Supplement AExamples of estimating winter low flow for ungaged streams 53

Supplement BComparison of winter low-flow estimates for low-flow

partial-record stations in West Tennessee 57

Supplement CComparison of winter low-flow estimates for low-flow partial-record stations in Middle and East Tennessee 59

Supplement DWinter low-flow values estimated from observed streamflow records and regression equations, and data used to derive the equations for Tennessee streams 65

PLATES (in pocket)

Plate I. Map showing streamflow-recession index areas and boundaries, and locations of stations used in the regression analyses, Tennessee

2. Map showing location of low-flow partial-recordstations used to test the regression equations, Tennessee

111

ILLUSTRATIONS Figures 1-12. Graphical solutions for West Tennessee of winter:

1. 1-day 2-year low-flow equation 72. 1-day 10-year low-flow equation 83. 1-day 20-year low-flow equation 94. 3-day 2-year low-flow equation 105. 3-day 10-year low-flow equation 116. 3-day 20-year low-flow equation 127. 7-day 2-year low-flow equation 138. 7-day 10-year low-flow equation 149. 7-day 20-year low-flow equation 15

10. 30-day 2-year low-flow equation 1611. 30-day 10-year low-flow equation 1712. 30-day 20-year low-flow equation 18

13-24. Graphical solutions for Middle and East Tennessee of winter:13. 1-day 2-year low-flow equation 1914. 1-day 10-year low-flow equation 2015. 1-day 20-year low-flow equation 2116. 3-day 2-year low-flow equation 2217. 3-day 10-year low-flow equation 2318. 3-day 20-year low-flow equation 2419. 7-day 2-year low-flow equation 2520. 7-day 10-year low-flow equation 2621. 7-day 20-year low-flow equation 2722. 30-day 2-year low-flow equation 2823. 30-day 10-year low-flow equation 2924. 30-day 20-year low-flow equation 30

25. Plots showing comparison of winter 3-day 20-year low flow from correlation methods with winter 3-day 20-year low flow from regression equation for partial-record stations in West Tennessee 32

26. Plots showing comparison of winter 3-day 20-year low flow from correlation methods with winter 3-day 20-year low flow from regression equation for partial-record stations in Middle and East Tennessee 33

27. Generalized cross section of a streambasin showing ground-water movement 34

28-30. Graphs showing:28. Base-flow recessions for South Fork

Forked Deer River which drains mostly sand 3729. Base-flow recessions for Sewee Creek

which drains mostly limestone and dolomite 3930. Three rates of base-flow recessions for Sequatchie

River which drains mostly limestone and dolomite 4031. Generalized sketch of Sequatchie

River basin and aquifer boundaries 4232. Plots showing comparison of winter 3-day

20-year low flow from measured streamflowwith winter 3-day 20-year low flow fromregression equation for gaging stations in West Tennessee 47

33. Plots showing comparison of winter 3-day 20-year low flow from measured streamflow with winter 3-day 20-year low flow from regression equation for gaging stations in Middle and East Tennessee 48

CONVERSION FACTORS

Analyses and compilations used in this report are in inch-pound units of measurements. Factors for converting inch-pound units to metric (SI) units are listed below.

Multiply

mile (mi)

square mile (mi?)

cubic foot per second (ft3/s)

By To obtain

1.609 kilometer (km)

2.59 square kilometer (km?)

0.0283 cubic meter per second (m3/s)

REGIONALIZATION OF WINTER LOW-FLOW

CHARACTERISTICS OF TENNESSEE STREAMS

R. H. Qngham

ABSTRACT

Procedures for estimating winter (December-April) low flows at ungaged stream sites in Tennessee are based on surface geology and drainage area size. One set of equations applies to West Tennessee streams, and another set applies to Middle and East Tennessee streams. The equations do not apply to streams where flow is significantly altered by activities of man. Stan­ dard errors of estimate of equations for West Tennessee are 22 to 35 percent and for Middle and East Tennessee 31 to 36 percent. Statistical analyses indicate that summer low-flow characteristics are the same as annual low-flow characteristics, and that winter low flows are larger than annual low flows.

Streamflow-recession indexes, in days per log cycle of decrease in dis­ charge, are used to account for effects of geology on low flow of streams. The indexes in Tennessee range from 32 days per log cycle for clay and shale to 350 days per log cycle for gravel and sand, indicating different aquifer characteristics of the geologic units that contribute to streamflows during periods of no surface runoff. Streamflow-recession rate depends primarily on transmissivity and storage characteristics of the aquifers, and the aver­ age distance from stream channels to basin divides. Geology and drainage basin size are the most significant variables affecting low flow in Tennessee streams according to regression analyses.

SUMMARY

Methods for estimating winter (December-April) low-flow characteristics in Tennessee consist of two sets of regression equations that use an index of streamflow recession and size of the drainage basin. One set of equations can be used to estimate winter low flow of streams in West Tennessee which have drainage areas between 25 and 1,940 square miles (mi?). The other set of equations can be used to estimate winter low flow of streams in Middle and East Tennessee which have drainage areas between 2.68 and 2,557 mi 2 . Areas where the separate sets of equations apply are shown on plate 1 (in pocket).

The following equations can be used for estimating winter low-flow char­ acteristics in ungaged streams in West Tennessee.

Standard errorof estimate,in percent

1Q2 = 7.34 x TO'3 Al-01 (G-30)0.75 341Q 10 = 5.10 x TO'4 Al-02 (6-30)1-18 271Q20 = 3.07 x TO'4 Al-02 (6-30)1-26 23

3Q2 = 8.88 x 10'3 Al-01 (6-30)0.72 353Qi 0 = 5.82 x TO'4 Al-02 (6-30)1-16 273Q2() = 2.72 x 10'4 Al-02 (6-30)1-29 25

7Q2 = 1.31 x ID"2 Al-00 (6-30)0-67 357Q10 = 9.20 x TO'4 Al-01 (6-30)1-09 257Q2Q = 4.76 x 10'4 Al-02 (6-30)1-19 22

30Q2 = 0.112 Al-02 (6-30)0.32 3330Q10= 5.04 x 10~3 Al-00 (6-30)0-82 3130Q2o= 2.23 x 10'3 Al-00 (6-30)0-95 3!

The following equations can be used for estimating winter low-flow char­ acteristics in ungaged streams in Middle and East Tennessee.

Standard errorof estimate,in percent

1Q2 = 4.37 x lO'3 Al-03 eO-97 35IQlO = 1.41 x lO'4 Al-01 61-58 351Q20 = 3 -80 x 10~5 Al-00 5!-83 35

3Q2 = 5.77 x 10~3 Al-02 eO.93 343Q] 0 = 1.96 x lO'4 Al-01 61-52 353Q2Q = 5.21 x ID'5 Al-01 61-77 33

7Q2 = 9.78 x lO'3 Al-03 eO-84 347Qi 0 = 4.07 x ID'4 Al-00 Q!.39 357Q2Q = 1-34 x ID'4 A0.99 el-60 34

30Q2 = 0.209 Al- 02 GO.31 313OQio= 4.64 x 10~3 Al-03 eO.93 3630Q2o= 1.33 x 10~3 Al-02 G 1.15 35

Definitions of the above variables are:

XQy = estimated winter low-flow characteristic for the indicated number of consecutive days (X) at the indicated recurrence interval (y);

A = contributing drainage area, in square miles; and 6 = streamflow-recession index, in days per log cycle of decrease

in discharge, determined from plate 1.

INTRODUCTION

Information on low flow characteristics in streams is essential to surface- water quality and water-supply management. The amount of available water in a stream for assimilation and transport of waste is the critical factor in deter­ mining the load capacity of the stream and withdrawal rates for water supply. With the current emphasis on reducing the cost of municipal waste-water treat­ ment plants, the need for winter low-flow information is important to regulatory agencies concerned with this disposal into streams. The anticipated needs for low-flow estimates will increase throughout the State due to U.S. Environmental Protection Agency requirements for review of municipal effluent limits. Imme­ diate applications of the results of this project are to: (1) update the low- flow characteristics of gaged streams, and (2) derive new methods with improved reliability for estimating low-flow characteristics at ungaged stream sites.

In response to the expected increase for low-flow information, the U.S. Geological Survey, in cooperation with the Tennessee Department of Health and Environment, began a study in 1981 to estimate low flow of streams in Tennessee. The study was divided into two phases. During the first phase, statistical analyses of daily streamflow data for continuous-record gaging stations were performed to calculate low flow for selected recurrence intervals and duration of streamflow (Bingham, 1985).

During the second phase of the study, equations were derived by multiple regression techniques to estimate annual low-flow characteristics of ungaged streams in Tennessee. Results of the second phase of the study are in a report by Bingham (1986).

In 1984, the study was extended to derive methods for estimating seasonal low-flow characteristics of ungaged streams, which this report describes. Sea­ sonal low-flow characteristics for continuous-record gages are the discharges taken from a frequency curve of the seasonal values of the lowest mean discharge for a given number of consecutive days. The seasons for these analyses are win­ ter (December 1 through April 30), and summer (May 1 through November 30). Statistical analyses indicate that summer low-flow characteristics are the same as annual low-flow characteristics, and that winter low flows are larger than annual low flows. Thus, for additional analyses in this study only winter low flows are considered. The winter low-flow frequency data for each gage were derived by an adaptation of the log-Pearson Type III flood-frequency program described in U.S. Water Resources Council Bulletin 17B (1981). Curves from the analyses were adjusted to the observed data for stations where significant dif­ ferences in the plotting positions of observed and predicted values occurred (Riggs, 1972). Winter low-flow characteristics for partial-record stations were estimated by correlating measurements at the partial-record stations with con­ current discharges at continuous-record stations.

The purpose of this report is to describe procedures for estimating winter low-flow characteristics in ungaged streams in Tennessee and to summarize methods of analyses. This report is based on low-flow data collected as part of other programs with the Tennessee Department of Health and Environment and with other state and federal agencies.

LIMITATIONS AND ACCURACY OF EQUATIONS

Accuracy of the regression equations is expressed as standard error of estimate in percent. Standard error is computed from the difference between estimates of winter low flow from station data and estimates of winter low flow from the regression equations. Standard error of estimate is the range of error to be expected about two-thirds of the time. The standard error of estimate listed with each of the preceding equations is based on regression analyses using a streamflow-recession index determined from mapped values on plate 1.

The regression equations in this report are limited to estimating the indicated winter low-flow characteristics in natural flow streams in Tennes­ see. The equations are based on drainage areas ranging from 25 to 1,940 mi? for West Tennessee streams, and streamflow-recession indexes ranging from 32 to 350. The following table gives the range in winter low flows corresponding to each low-flow characteristic for stations used in the regressions for West Tennessee.

Low-flow Range in winter low flow, characteristic in cubic feet per second

From To

1Q2iQio1Q20

3Q23Qio3Q20

7Q27Q107Q20

30Q230Qio30Q20

1.1.4.4

1.1.4.3

1.4.5.4

5.0.9.6

829466406

849474412

936502431

1540686551

Drainage areas ranged from 2.68 to 2,557 mi 2 for Middle and East Tennessee streams, and streamflow-recession indexes ranged from 32 to 175. The follow­ ing table gives the range in winter low flows corresponding to each low-flow characteristic for stations used in the regressions for Middle and East Tennessee.

Low-flowRange in winter low flow, characteristic in cubic feet per second

From To~~

1Q2iQio1Q20

3Q23Q103Q20

7Q27QlO7Q20

30Q230Q1030Q2Q

0.9.3.2

1.0.3.2

1.1.4.3

1.8.6.3

1340749628

1425818689

1604941794

215011951005

Use of the equations should be limited to the range in winter low flow, drain­ age area, and streamflow-recession indexes used to derive the equations.

The regression equations should not be used on streams where the low flow is significantly affected by regulation or other activities of man. Caution should be used when applying the equations to streams where a significant amount of the low flow is contributed by springs. Definition of the contri­ buting drainage area, in such cases, is uncertain; some of the spring flow might be from adjacent basins. Caution also should be used in applying the equations to streams where most of the formation at or near land surface is limestone. Solution cavities in the limestone may alter the rate of flow con­ siderably within short reaches of the stream channel. For example, a stream channel in limestone can have winter low flow of several cubic feet per second at one site and have zero flow at another site downstream. This commonly occurs in Overton, Putnam, White, Warren, Rutherford, and Williamson Counties of Middle Tennessee, and may occur locally in other counties.

Standard error of estimate listed for each regression equation applies only to the stations used in deriving the regression equation. The average errors associated with use of the equations to estimate winter low flows in ungaged streams are unknown, but are probably slightly larger than the stan­ dard errors of the equations.

ESTIMATES OF WINTER LOW-FLOW CHARACTERISTICS AT UNGAGED SITES

The following procedures can be used to estimate winter low flows for ungaged sites on streams with natural flow in Tennessee. From topographic maps, determine the size of drainage area upstream from the site. From plate 1, determine the streamflow-recession index for the stream basin. Winter low

flows for the site can be estimated by substituting the values of drainage area size and streamflow-recession index into the appropriate regression equations and performing the indicated mathematical operations or by graphical determina­ tion using figures 1 through 24. Examples using the regression equations and graphs to estimate winter low flow in ungaged streams are given in Supplement A of this report.

The estimating methods are modified for a stream basin draining two or more areas of different streamflow-recession indexes. Drainage area is deter­ mined as described in the preceding paragraph. However, discharge from each of two or more streamflow-recession index areas must be computed separately using the equations, and the results weighted based on an estimate of the percentage of the basin draining each streamflow-recession index area.

VERIFICATION OF REGRESSION EQUATIONS AT PARTIAL-RECORD SITES

The regression equations were used to estimate winter 3Q2Q for 238 low- flow partial-record stations within the State (plate 2) and the results were compared with low-flow estimates obtained from correlation methods. The 238 stations exclude those used in the regression analyses. Estimated winter low flows, drainage area, mapped streamflow-recession index (plate 1), and identi­ fication number for the stations are given in Supplement B for West Tennessee and in Supplement C for Middle and East Tennessee. The stations are the same as those used in previous low-flow regionalization work by Bingham (1986). Stations listed in Supplements B and C are assumed to represent flow unaffected by man's activity, and have drainage areas and low-flow values within the limi­ tations of data used to derive the equations for winter 3Q2Q-

The regression equations were used to estimate winter 3Q2Q low flow for partial-record stations and the results were compared withestimates obtained from correlation methods. The standard error of estimate was approximated by assuming the correlation values of winter 3Q2Q low flow to be accurate. Residuals, in log units, were determined as the difference in logarithms of winter low flows from regression equations and from correlation methods. The error was computed by the root-mean-square procedure using the equation:

RMS = x2 + $2,

where RMS = root mean square, in log units,x = mean of the residuals, in log units, and S = standard deviation of the residuals, in log units.

Computed RMS values, in log units, were converted to 36 percent for 33 partial- record stations in West Tennessee and to 44 percent for 205 partial-record sta­ tions in Middle and East Tennessee. A two-sided student's t test indicated insignificant bias in winter low flows determined by the regression equations.

Other comparisons of the winter low-flow estimates were made with graph­ ical plots. The winter 3Q20 low flows from correlation methods for the

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partial-record stations were plotted against winter 3Q20 low flows estimated with the regression equations. Plots of the winter low-flow data for the 33 stations in West Tennessee are illustrated in figure 25. Plots for the 205 stations in Middle and East Tennessee are illustrated in figure 26. According to visual inspection, the plots indicate no bias, however, the largest errors appear to be associated with the smallest low-flow values used for the com­ parison. Although these comparisons between winter low-flow estimates from regression equations and from correlation are not completely independent, they do support confidence in the equations.

PROCEDURES FOR REGIONALIZING WINTER LOW-FLOW CHARACTERISTICS

Basin and climatic characteristics that influence the rate of low flow were analyzed to regionalize methods of estimating winter low flow in ungaged streams statewide. The most significant result of these analyses was to relate the effects of geology to the rate of winter low flow. Streamflow-recession indexes are strongly influenced by aquifers within the geologic framework underlying the stream basin. Thus, the streamflow-recess ion indexes used in these analyses were related to various rock types and combinations of rock types. Similar recession-index areas were then delineated based on geologic maps.

Ground kater-Surface Water Relations

Low flow in a stream is usually ground water discharged from the aquifer system to the stream. During the wet period in the winter and spring, most aquifers underlying the stream basin are recharged by precipitation in excess of the amount of water that can move through aquifers. During and after the wet season, water in the aquifers drains slowly into the adjacent stream and provides base flow during the year. A generalized cross section of a stream basin illustrating the movement of ground water from the aquifer system to the stream is shown in figure 27.

The interactions between the aquifer or groups of aquifers and the streams are extremely complex. The rate of ground-water discharge to a stream is a function of the capacity of the aquifer to store and transmit water, aquifer thickness and areal extent, slope of the ground-water table, amount of preci­ pitation recharging the aquifer, size of the stream basin, and time. Most streams used in these analyses receive water from two or more rock types or geologic units each having different effects on low flow of the streams. For example, sand yields more water to a stream than does clay, and sandstone yields more water to a stream than does shale. Areal and vertical differences in the water yielding characteristics of an aquifer can also occur within a given rock type.

Rorabaugh and others (1966) investigated methods of relating ground water to surface water in the Columbia River basin. In their work, ground-water dis­ charge to selected streams was related to the physical characteristics of the aquifer system as evidenced by the recession pattern of the water level in the

31

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Figure 25.-Comparison of winter 3-day 20-year low flow from correlation methods with winter 3-day 20-year low flow from regression equation for partial-record stations in West Tennessee.

32

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34

aquifer system during a period of no recharge. Rorabaugh also indicates that the streamflow recession for continuous-record gaging stations on unregulated streams can be used to estimate streamflow characteristics.

Trainer and Watkins (1975) used streamflow-recession indexes to estimate average values of aquifer transmissivity and storage in the upper Potomac River basin. Their work shows a direct relation between streamflow recession and the transmissivity of the aquifers. For example, stream basins underlain by aqui­ fers with large transmissivity values had higher indexes of streamflow reces­ sion than basins underlain by aquifers with small transmissivity values. By applying that relation, Bingham (1982) used streamflow-recession indexes and surface geology to regionalize low-flow characteristics of unregulated streams in Alabama. For Tennessee, the same type of relation was used to regionalize low-flow characteristics statewide (Bingham, 1986).

Streamflow recession

The rate of streamflow recession during base flow is controlled by the hydraulic characteristics of the aquifers. The streamflow-recession index (t) can be estimated by the equation (Rorabaugh and others 1966):

t = a*__S, T

Where t = time in days per log cycle;a = distance from the stream to the hydrologic divide, in feet;S = storage coefficient of the aquifer or aquifers; andT = transmissivity of the aquifer or aquifers.

For this report, these characteristics are not necessary because streamflow data were used to estimate the streamflow-recession indexes graphically. How­ ever, according to Trainer and Watkins, (1975, p. 31-32) three factors which affect the streamflow-recession index complicate its definition and interpre­ tation from a graph. Those factors are: (1) the brevity of most recession episodes in a humid region makes the recession curve difficult to establish precisely, (2) losses from ground water and from streamflow through evapo- transpiration distort the ideal recession curve during much of the year, and (3) many recession curves are complex because of nonhomogeneity of the aquifers or the presence of multiple aquifers.

Records from approximately 150 continuous-record gaging stations were examined in an attempt to define the streamflow-recession index areas across Tennessee. Streamflow-recession indexes were defined for 109 of those sites. Streamflow at the remaining stations was significantly affected by activities of man, or the record was too short to define the streamflow-recession indexes. Approximately 6 to 10 recessions were plotted for each of the stations to assure consistency in the recession index definition. For some stations, how­ ever, only two to three recessions could be used for various reasons to esti­ mate the index. The streamflow recessions, for each station, were plotted on semi log graph paper, daily streamflow on the log scale, and time, in days, on the arithmetic scale. The index of streamflow recession for each station was defined in days per log cycle, that is, the number of days required for the flow to decrease one complete log cycle. The base flow recession of a stream should approximate a straight line on a semilog plot.

35

Stream-flow records for periods during November through March were gener­ ally used for defining the streamflow-recession indexes. During that time, interferences from evaporation and transpiration are minimal, and the reces­ sion probably reflects the geohydrologic control on base flow and low flow of streams. However, the recession slope is difficult to determine from stream- flow in the winter because of interruptions from precipitation. Many of the interruptions are brief, and the recession slope may become nearly straight a few days after the streamflow peak.

The peak discharge during a period of rainfall is used as the first plotting point for the streamflow-recession curve. The plotting of stream discharge for each successive day is continued until the streamflow-recession curve approximates a straight line. The number of days required for the straight-line condition to occur after the peak discharge is a function of the basin geometry and the properties of the basin material (Rorabaugh and others, 1966) and is defined as the critical-time factor. The critical-time factor (tc) is expressed by the equation:

tc = 0.2a2S T

The variables a, S, and T are defined previously in this report. The straight-line part of the recession curve is used to define the index of streamflow recession. The streamflow recession for South Fork Forked Deer River at Jackson, Tennessee (station 209, pi. l)»is illustrated in figure 28. The straight-line part of the curve for South Fork Forked Deer River indi­ cates a recession index of about 235 days per log cycle, which defines a critical-time factor of about 47 days.

Definition of the streamflow-recession index, for numerous stations, can be aided or verified by the critical-time factor. After the days per log cycle have been estimated from the recession plot, multiply the number of days by 0.2 to determine the number of days for the recession curve to become an apparent straight line following the peak. The critical-time procedure works fairly well when peak discharge represents medium to high flow. For low to medium discharge, the curves represent increments or additions to the composite of all past events, and, in many cases, the critical-time factor may be as low as 0.1 t and may not be conclusive (Daniel, 1976). In many Tennessee stream basins, the geometry and aquifer characteristics are such that the critical-time factor may represent weeks or months.

Great care is required in estimating the streamflow-recession index from hydrographs because of frequent precipitation during the winter, which inter­ rupts the streamflow recession. Recession curves that become straight-line segments on semilog plots within 6 to 10 days after flood peaks can be deter­ mined readily through inspection of several years of hydrographs for each stream. By contrast, the recession curve that becomes linear after 50 days or more of uninterrupted recession can be determined only approximately be­ cause of frequent precipitation.

36

Multiple Aquifer Contributions To Streamflow

On a statewide basis, the variations of aquifer hydraulic character­ istics and interaction of the aquifers and streamflow are extremely complex. Trainer and Watkins (1975, p. 34) indicate that both areal and vertical differences in hydraulic characteristics of aquifers probably contribute to the complexity of streamflow-recession curves. In many Tennessee streams the base flow represents the effects of several aquifers, each having different hydraulic characteristics.

For the purposes of developing the regression equations, no simple method exists for assigning fractions of low flows to parts of a basin drain­ ing two or more unlike aquifers. In the case of naturally integrated (com­ bined) recessions, assigning fractions of low flows might not be possible while at the same time preserving the statistical validity of the data. Two methods were used, however, to determine a streamflow-recession index of each aquifer in basins where multiple aquifers contribute water to streamflow.

Graphical Computation Method

The streamflow-recession indexes, as determined graphically, for most of the streams in these analyses represent combined effects of the different aquifers within the basin. For example, flow of Sewee Creek near Decatur, in Meigs County (Station 115, pi. 1), represents the combined effects of two aquifers. One aquifer has a streamflow-recession index of 65 days per log cycle and the other aquifer has a streamflow-recession index of 120 days per log cycle (pi. 1). However, the combined effects of both aquifers define a streamflow-recession index of about 85 days per log cycle from the observed streamflow hydrograph (fig-29).

Significantly different streamflow recessions were estimated for the same stream by separate straight-line segments for different periods of the recession curve. Riggs (1964, p. 353-354) describes how baseflow from two very unlike aquifers in the same drainage basin might produce two very dif­ ferent sloping straight-line segments in the streamflow-recession curve. When different streamflow-recession indexes are observed in a single basin, the resulting streamflow is the sum of the contributions from each part of the drainage area and the separate effects are relatively easily distin­ guished. The streamflow recessions for Sequatchie River near Whitwell, in Marion County (station 137, plate 1), illustrate two indexes representing two unlike aquifers (fig. 30). The recessions also indicate that the com­ bined effects of the two unlike aquifers (32 and 100 days per log cycle) result in a streamflow-recession index of about 85 days per log cycle. How­ ever, for some streams where two or more only slightly different indexes might be expected on the basis of geologic formations, a single observed index can be a combined effect, and the separate effects from each part of the drainage area may be indistinguishable.

38

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40

Weighted-Average Method

The weighted-average streamflow-recession index procedure was applied in mapping the index areas as shown on plate 1; thus the values shown may differ slightly from values obtained by the graphical computation method for the same stations. For the purposes of applying the regressions, however, the effect of contributions from different parts of a basin can be accounted for by the procedure described in Supplement A of this report.

The weighted-average procedure was based on an estimate of the percent­ age of a stream basin draining each of two or more different aquifers. Sequatchie River at station 137 on plate 1 provides an example of the aver­ aging procedure. A generalized sketch of Sequatchie River basin is shown in figure 31. Approximately 75 percent of the basin drains a limestone and dolomite aquifer which has a streamflow-recession index of 100 days per log cycle (fig. 30). Twenty-five percent of the basin drains the overlying shale and sandstone aquifer which has a streamflow-recession index of 32 days per log cycle. The weighted-average streamflow-recession index is computed by summing 75 percent of 100 days per log cycle and 25 percent of 32 days per log cycle. Thus, the weighted-average streamflow-recession index of the two aquifers is 83 days per log cycle for Sequatchie River at station 137 (pi. 1) near Whitwell. This is in close agreement with the 85 days per log cycle estimated with the recession curves in figure 30. The weighted-average streamflow-recession index is considered the best estimate of the combined effects of the two aquifers on low flow of Sequatchie River at station 137.

Mapping Streamflow-Recession Indexes

Streamflow-recession index areas (plate 1) were delineated based on recession indexes derived from streamflow hydrographs, contacts between geo­ logic formations, and the types of geologic formations at land surface in the basin. The types of formations include gravel, sand, clay, and silt in West Tennessee and limestone, chert, shale, sandstone, dolomite, and conglomerate in Middle and East Tennessee. In the mountainous areas of extreme East Ten­ nessee, the surface formations also include siltstone, quartzite, and slate. Streamflow data have not been obtained for all the formations contributing water to streamflow within the State. However, the entire State was mapped based on the assumption that similar types of formations contribute similar amounts of water to streamflow and that ground-water divides of the shallow aquifers correspond to topographic divides.

Boundaries delineating areas of streamflow-recession indexes on plate 1 follow the same general pattern as contacts between formations or groups of formations with major differences in rock type and water-bearing properties. However, the quantitative significance of the several geologic factors that influence low flow in streams cannot be determined precisely.

The streamflow-recession indexes defined for each of the 109 continuous gaging stations were used to represent the relative effects of surface forma­ tions on low flow. These effects were evaluated by plotting gaging station locations and listing their respective streamflow-recession indexes on a map

41

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Limestone and dolomite aquifer, 100 days per log cycle

Basin boundary

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03571000 Sequatchie River near Whitwell

Figure 31 .--Generalized sketch of Sequatchie River basin and aquifer boundaries (station 137 on plate 1).

42

of the State (pi. 1). The data on plate 1 were compared with that on a geo­ logic map of Tennessee (Hardeman and others, 1966) to delineate areas where formation effects on low flow are similar.

Adequate descriptions of the surface formations are essential in deter­ mining the position of streamflow-recession index boundaries. In many areas, several formations with similar rock types and water-bearing properties were grouped together in a single streamflow-recession area. For example, in the Sequatchie River Valley near Chattanooga, several dolomite and limestone for­ mations are at the surface along the floor and walls of the valley. Those formations have similar rock types and were assumed to have similar water­ bearing properties within the Sequatchie Valley, consequently, they were mapped together as a single streamflow-recession index area for the entire length of the valley. Similarly, sand formations in West Tennessee which have essentially the same descriptions were assumed to have the same water­ bearing properties and were mapped together as a single streamflow-recession index area.

Formations with contrasting rock types and water-bearing properties were separated on plate 1 by streamflow-recession index boundaries. For example, formations consisting primarily of clay were separated from formations con­ sisting primarily of sand, and formations consisting primarily of shale were separated from formations consisting primarily of sandstone. The streamflow- recession index areas on plate 1 represent the relative capacity of the for­ mations to release water to streams during low flow. A large number of days per log cycle (sustained base flow) represent slower depletion of water from the formations and a capacity of the formations to release large amounts of water, whereas, a small number of days per log cycle represent faster deple­ tion of water from the formations and a capacity to release only small amounts of water.

The State geologic map (Hardeman and others, 1966) was inadequate in many areas to delineate streamflow-recession index boundaries. In those areas, 7h- minute geologic map quadrangles were used as an aid in delineating the bound­ aries. For example, the boundaries for Crooked Creek basin and for Beaver Creek basin (station number 200, pi. 1) near Huntingdon, in Carrol! County, were based on a geologic map of the Huntingdon quadrangle (Ferguson, 1970) and the Palmer Shelter quadrangle (Parks, 1974). The maps were used to define areas of fluvial deposits in the Crooked Creek and Beaver Creek basins. Be­ cause of higher yielding fluvial deposits, the streamflow-recession index area of 350 days per log cycle was extended to include those stream basins. The fluvial deposits are not apparent on the state geologic map.

For three areas in West Tennessee, a mineral resources map of the Tennes­ see Valley Region (Tennessee Valley Authority, 1970) was used to delineate streamflow-recession index boundaries for local clay deposits near Lexington, Henderson, and Bolivar. Because the capacity of the clay to release water to streams is much smaller than the surrounding sand formation, the index values for the clay areas are significantly smaller than index values for the sand areas. Perhaps the effects of other clay deposits on low flow of West Tennes­ see streams should be accounted for, but streamflow records are not available to determine such effects.

43

The boundary between streamflow-recession index areas of 100 days and 175 days per log cycle in Polk, Monroe, Blount, and Sevier Counties in East Tennessee was delineated based on hydrological and geological information in reports by McMaster and Hubbard (1970) and King (1964).

Although descriptions of formations are some of the criteria used in delineating streamflow-recession index areas on plate 1, local variations in rock type may result in indexes considerably different than the areas indi­ cate. The areas on plate 1 represent approximately average streamflow- recession indexes; the index may vary slightly from stream to stream within each area. The map is limited to 10 categories of index areas for practical application in estimating low flows. Approximately 15 to 20 categories could be delineated, but the map would be too cumbersome and difficult to use. The procedures used to delineate streamflow-recession index areas on plate 1 are highly subjective to interpretation of formation descriptions and to a lack of adequate information for precise positioning of the index boundaries.

Regression Analyses

Winter low flows at gaging stations were related to various basin and climatic characteristics by using regression techniques. Winter low-flow data used in the final regression analyses are tabulated in Supplement D. Charac­ teristics tested were streamflow-recession index, drainage area, mean annual precipitation, and a sum of monthly normal precipitation for December through April. Streamflow-recession index and drainage area were the only character­ istics significant at the 5 percent level of significance.

These regression analyses are similar to those used by Bingham (1986) to regionalize annual low-flow characteristics of streams in Tennessee. In those analyses, characteristics tested were streamflow-recession index, drain­ age area, main channel slope, length of main channel, mean elevation of the basin, percent forest cover within the basin, and mean annual precipitation. Streamflow-recession index and drainage area were also the only character­ istics significant at the 5 percent level of significance in those analyses.

In Tennessee the most widely used low-flow data are the 3Q2Q. Thus, for this study the first regression analyses were performed for the winter 3Q2Q low flow. Analyses for other winter low-flow characteristics were per­ formed after completion of the analyses for the winter 3Q2Q. Low-flow values for other selected frequencies were substituted into the analyses. Estimating equations derived from the regression analyses are of the same general form for all the selected frequencies (see Summary).

To regionalize winter low flows for this study, it was assumed that separation of the State into two parts was necessary; attempts were not made to derive one set of equations to apply statewide. In the previous work by Bingham (1986) attempts were made to derive one set of equations to apply statewide. However, because of significant differences between hydraulic characteristics of aquifers in West Tennessee and hydraulic characteristics of aquifers in the rest of the State, the standard error of estimate of the regression was about 73 percent for the annual 3Q20 low flow. The equation

44

over estimated the annual 3Q2Q for all continuous-record stations in West Tennessee. For subsequent regressions the State was separated into (1) West Tennessee and (2) Middle and East Tennessee which reduced the standard error of estimate to 32 and 33 percent, respectively.

For the regression analyses of winter low flow for West Tennessee streams, 22 continuous-record stations were used to derive an equation to estimate win­ ter 3Q2Q low flow. Variables used in the equation were drainage area and streamflow-recession indexes determined from plate 1. Standard error of esti­ mate for the regression was about 17 percent. In the final regression analyses to derive an equation to estimate winter 3Q2Q low flow for West Tennessee streams, information for 15 low-flow partial-record stations was added to the data set. The partial-record stations were selected randomly for geographic and geologic distribution. The final regression analysis using 22 continuous- record stations and 15 partial-record stations has a standard error of estimate of about 25 percent.

Additional regression analyses were performed for West Tennessee streams to derive equations to estimate winter low-flow characteristics for 1, 3, 7, and 30 consecutive days for recurrence intervals of 2, 10, and 20 years. The standard error of estimates for those equations ranges from 22 to 35 percent. All the equations for West Tennessee streams have the same two independent variables (drainage area, A, and streamflow-recession index, G); the regression constant and variable exponents are different.

In regression analyses for Middle and East Tennessee streams, 82 contin­ uous-record stations were used to derive an equation to estimate winter 3Q2Q low flow. Variables used in the equation were drainage area and streamflow- recession indexes determined from plate 1. Standard error of estimate for the regression was about 30 percent. In the final regression analyses for Middle and East Tennessee streams, information for 109 low-flow partial-record sta­ tions was added to the data set and the regression rerun. The partial-record stations were selected randomly for geographic and geologic distribution. The final regression using 82 continuous-record stations and 109 partial-record stations has a standard error of estimate of about 33 percent.

Additional regression analyses were performed for streams in Middle and East Tennessee to derive equations to estimate winter low-flow characteristics for 1, 3, 7, and 30 consecutive days for recurrence intervals of 2, 10, and 20 years. Standard error of estimates for those equations range from 31 to 36 percent. All the equations for Middle and East Tennessee streams have the same two independent variables (A and G); the regression constant and variable expo­ nents are different.

Equations were also derived to estimate low flows based on drainage area size as the only independent variable. Those equations are unacceptable because the standard errors of estimate associated with the equations are too large. For West Tennessee streams, the errors range from 100 percent for win­ ter 3Q2 to 88 percent for winter 3Q20» For Middle and East Tennessee streams, the errors range from 51 percent for winter 3Q2 to 85 percent for winter 3Q2Q. These large errors indicate the importance of geologic effects

45

on low flow, which are accounted for, to some extent, by the mapped streamflow- recession indexes. After adding the streamflow-recession index variable to the equation for estimating winter 3Q2Q in West Tennessee streams, the standard error of estimate was decreased from 88 to 25 percent. For Middle and East Tennessee streams, the standard error of estimate was decreased from 85 to 33 percent.

In the regression analyses, values of 0, 10, 20, and 30 were subtracted from the streamflow-recession index to increase the equation constant and to reduce exponents of the variables. A value of 30 is the feasible maximum value that can be subtracted from the index because of logarithmic transformations used in the regression analyses. However, subtracting values from one of the variables in regression equations can increase the error of estimate and intro­ duce unnecessary bias in results of using those equations.

Bias of the winter low-flow equations in this report was checked with graphical plots. The graphs include plots of regression residuals versus log of the streamflow-recession index, and residuals versus log of drainage area. According to visual inspection, the group of plotting points on each graph for the West Tennessee equations forms a straight line and are assumed to be unbiased. However, the groups of plotting points on the graph of streamflow- recession indexes and regression residuals do not form a straight line for the Middle and East Tennessee equation to estimate winter 3Q2Q low flow. Sub­ tracting values from the streamflow-recession index apparently caused results of the equation to be biased. Regression analyses indicated that the standard error and bias of the winter 3Q2Q equation increased as the value subtracted became larger. Consequently, regression equations for estimating winter low flow in Middle and East Tennessee were derived without subtracting a value from the streamflow-recession index.

The winter 3Q2Q low flows from observed streamflow data for gaging sta­ tions were plotted against predicted winter 3Q2Q low flows estimated with the regression equations. Plots for stations used to derive the winter 3Q20 low- flow equation for West Tennessee streams are illustrated in figure 32. Plots for stations used to derive the winter 3Q2Q low flow-equation for Middle and East Tennessee streams are illustrated in figure 33. Both illustrations indi­ cate that the equations overestimate winter low-flow values of less than about 1 ft3/s at nearly all sites.

Drainage areas for gaging stations used in the regression analyses for West Tennessee streams ranged from 25.0 to 1,940 mi?. However, the distri­ bution of drainage areas vary considerably within that range. For example, only four stations have a drainage area larger than 1,000 mi?, and only two stations have a drainage area larger than 1,500 mi?. The following table summarizes the distribution of drainage areas used in the regression analyses for West Tennessee streams.

46

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3Q 20 =5.21 x 10~5 A 1 -01 G 1 '77

2 points

I___I III I I I I I I I I I I I I1 10 100

WINTER LOW FLOW FROM MEASURED STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 33. Comparison of winter 3-day 20-year low flow from measured streamflow with winter 3-day 20-year low flow from regression equation for gaging stations in Middle and East Tennessee.

1000

48

Range in drainage Number of stationsarea (mi 2 ) in analyses

25-50 950.1-100 9101-250 5251-500 5501-1000 51001-1500 21501-1940 _2

Total stations 37

The streamflow-recession indexes used in the regression analyses for West Tennessee streams ranged from 55 to 350 days per log cycle. The follow­ ing table summarizes distribution of indexes for gaging stations used in the regression analyses.

Range in streamflow- Number of stationsrecession indexes in analyses

60-100 5101-150 6151-200 11201-250 12251-300 2301-350 J_

Total stations 37

Drainage areas for gaging stations used in the regression analyses for Middle and East Tennessee streams ranged from 2.68 to 2,557 mi?. The following table summarizes the distribution of drainage areas used in the regression analyses.

Range in drainage Number of stations area (mi 2 ) in analyses

2.68-10 910.1-25 5025.1-50 3350.1-100 35101-250 31251-500 11501-1000 171001-2000 42001-2557 _]_

Total stations 191

Streamflow-recession indexes used in the regression analyses for Middle and East Tennessee streams ranged from 32 to 175 days per log cycle. The following table summarizes distribution of indexes for gaging stations used in the regression analyses.

Range in streamflow- recess ion indexes

Number of stations in analyses

32-4041-5051-6566-8081-100101-120121-140141-175

Total stations

11233031382928

_]_191

A partial analysis of the sensitivity of the winter 3Q2Q regression equations to the streamf low-recess ion index G was performed for one set of conditions for the variable G. Results of sensitivity of the winter 3Q2Q equation for West Tennessee streams for G equal to 50, 100, and 200 are as follows:

For G=50, a +10 percent error in G results in -29 to +36 percent differ­ ence in winter 3Q2o;

for G=100, a +_10 percent error in G results in -18 to +18 percent differ­ ence in winter 3Q2o; and

for G=200, a jHO percent error in G results in -15 to +16 percent differ­ ence in winter 3Q2Q.

Results for sensitivity of the equations for Middle and East Tennessee indicate that a ±10 percent error in G results in -17.0 to +18.4 percent dif­ ference in winter 3Q2Q.

The sensitivity analyses indicate that the sensitivity of the variable G in the equation decreases for West Tennessee as G increases, and remains about the same for Middle and East Tennessee regardless of the value of G.

CONCLUSIONS

Regression equations derived from observed streamflow data at 228 gaging stations can be used with streamf low-recess ion index and drainage area to estimate winter (December through April) low flow for 1, 3, 7, and 30 consec­ utive days for 2-, 10-, and 20-year recurrence intervals in ungaged streams in Tennessee. One set of equations applies to streams in West Tennessee, and one set applies to streams in Middle and East Tennessee. Standard errors of the regression estimates ranged from 22 to 35 percent for West Tennessee, and from 31 to 36 percent for Middle and East Tennessee. The standard errors apply only to the 228 stations used in the regression analyses. Statistical analyses indicate that summer low-flow characteristics are the same as annual low-flow characteristics, and that winter low flows are larger than annual low flows.

The relative effects of different rock types and geologic units on low flow were accounted for by a streamflow-recession index expressed in days per

50

log cycle. Streamflow recession is controlled by the hydraulic character­ istics of aquifers within the stream basin. The streamflow-recession index is defined as the number of days required for base flow of the stream to recede one complete log cycle. These indexes for gaging stations are related to the geology of the State. Areal distributions of the indexes are shown on plate 1.

REFERENCES CITED

Bingham, R. H., 1982, Low-flow characteristics of Alabama streams: U.S. Geo­ logical Survey Water-Supply Paper 2083, 27 p.

____ 1985, Low flows and flow duration of Tennessee streams through 1981: U.S. Geological Survey Water-Resources Investigations Report 84-4347, 325 p.

____ 1986, Regionalization of low-flow characteristics of Tennesseestreams: U.S. Geological Survey Water-Resources Investigations Report85-4191, 63 p.

Daniel, J. F., 1976, Estimating ground-water evapotranspiration from stream- flow records: Water Resources Research, v. 12, no. 3, p. 360-364.

Ferguson, C. C., 1970, Geologic map of the Huntingdon quadrangle, Tennessee: Tennessee Department of Conservation, Division of Geology, Map GM 9-SW, scale 1:24,000.

Hardeman, W. D., Miller, R. A., and Swingle G. D., compilers, 1966, Geologic map of Tennessee: Tennessee Department of Conservation, Division of Geology, 4 sheets, scale 1:250,000.

King, P. B., 1964, Geology of the Central Great Smoky Mountains Tennessee: U.S. Geological Survey Professional Paper 349-C, 148 p., 13 Plates.

McMaster, W. M., and Hubbard, E.F., 1970, Water resources of the Great Smoky Mountains National Park, Tennessee and North Carolina: U.S. Geological Survey Hydrologic Investigations Atlas, HA-420, 2 sheets, Scale 1:125,000.

Parks, W. S., 1974, Geologic map of the Palmer Shelter quadrangle, Tennessee: Tennessee Department of Conservation, Division of Geology, Map GM 10-NW, scale 1:24,000.

Riggs, H. C., 1964, The base-flow recession curve as an indicator of ground water: International Association of Scientific Hydrology Publication 63, p. 352-363.

_______ 1972, Low-flow investigations: U.S. Geological Survey Techniques ofWater-Resources Investigations, Book 4, Chapter Bl, 18 p.

51

Rorabaugh, M. I., Simons, W. D., Garrett, A. A., and McMurtrey, R. G., 1966, Exploration of methods of relating ground water to surface water Columbia River basin first phase, with a section on Direct computation of ground-water outflow by electric analog by B. H. Bermes: U.S. Geo­ logical Survey Open-File Report, 124 p.

Tennessee Valley Authority, 1970, Mineral resources of the Tennessee Valley Region: Tennessee Valley Authority, Division of Water Control Planning, Geologic Branch, map report.

Trainer, F. W., and Watkins, F. A., Jr., 1975, Geohydrologic reconnaissance of the upper Potomac River basin: U.S. Geological Survey Water-Supply Paper 2035, 68 p.

U.S. Water Resources Council, 1981, Guidelines for determining flood flow frequency: Washington, D. C., U.S. Water Resources Council Bulletin 17B, 183 p.

52

SUPPLEMENT A

Examples of Estimating Winter Low Flow for Ungaged Streams

The following computations demonstrate the application of regression equations for estimating winter low flow in ungaged streams in Tennessee. For the first example, assume a stream site is in West Tennessee and that the entire basin has a single streamflow-recession index. Assume a 30 mi 2 basin lying within a region having a streamflow-recession index (plate 1) of 140. Estimates of winter low flows for the site are computed in the following manner.

1Q2 = 7.34 x 10-3 Al-01 (6-30)0.751Q2 = .00734 (30)1-01 (140-30)0.751Q2 = .00734 (31.04) (33.97)1Q2 = 7.7 ft3 /s

1Q 10 = 5.10 x 10-4 Al-02 (6-30)1-18 IQlO = .000510 (30)1-0 2 (140-30)1-18 IQlO = .000510 (32.11) (256.4) IQlO = 4.2 ft3 /s

1Q2Q = 3.07 x 10-4 Al-02 (6-30)1- 2 6 1Q2Q = .000307 (30)1-02 (140-30)l- 2 6 1Q2Q = .000307 (32.11) (373.4) 1Q2Q = 3.7 ft3 /s

3Q 2 = 8.90 x 10-3 Al-01 (6-30)0.72 3Q2 = .00890 (30)1-01 (140-30)0.72 3Q2 = .00890 (31.04) (29.50) 3Q 2 = 8.1 ft3 /s

3Qi 0 = 5.81 x 10-4 Al-02 (6-30)1-16 3Qi 0 = .000581 (30)I- 02 (140-30)1-16 3Qi 0 = .000581 (32.11) (233.4) 3Qi 0 = 4.4 ft3 /s

3Q20 = 2.72 x 10"4 A!-02 (6-30)1-29 3Q2Q = .000272 (30)I- 02 (140-30)1-29 3Q2Q = .000272 (32.11) (429.9) 3Q 2o =3.8 ft3 /s

7Q2 = 1.31 x 10- 2 Al-00 (6-30)0.677Q2 = .0131 (30)1-00 (140-30)0.67

7Q2 = .0131 (30) (23.32)7Q 2 = 9.2 ftVs

70in = 9 20 x 10"4 Al-01 (G-30) 1 - 09 7g]§ = .0009200 (30)1-01 (140-30)1-097Q 10 = .0009200 (31.04) (167.93) 7Q 10 = 4.8 ft3 /s

53

7Q 2n = 4.76 x 10-4 Al-02 (6-30)1-19 7Q 2 Q = .000476 (30)1-02 (140-30)1-19 7Q2 Q s .000476 (32.11) (268.69) 7Q20 = 4.1 ft3/s

30Q2 =0.112 Al-02 (6-30)0.32 30Q2 = .112 (30)1-02 (140-30)0.32 30Q2 = .112 (32.11) (4.5) 30Q2 = 16.2 ft3/s

30Q10= 5.04 x TO'3 Al -00 (6-30)0.82 30Qio= .00504 (30)1-0° (140-30)0.82 30Q10= .00504 (30) (47.2) 30Q10= 7.1 ft3/s

30Q 2o= 2.23 x TO'3 A! -00 (6-30)0.95 30Q 2 0= .00223 (30)1-00 (140-30)0.95 30Q2Q= .00223 (30) (86.96)

5.8 ft3/s

For the second example, assume a stream site in Middle Tennessee is drain­ ing a basin having two streamf low-recess ion index areas. Seventy percent of the basin is in an area with an index of 50, and 30 percent of the basin has an index of 140. The entire basin has a drainage area of 80 mi2. The estimat­ ing equations are used for the entire basin using each of the two streamflow- recession indexes, then a weighted-average winter low flow is computed based on the percentage of the basin draining each streamf low-recession index area on plate 1. Estimates of winter low flows are computed with the regression equa­ tions in the following manner. First, assume the entire basin is draining an area having a streamf low-recess ion index of 50.

3Q 2 = 5.77 x TO'3 Al-02 60.93 3Q2 = .00577 (80)1-02 (50)0.93 3Q 2 = .00577 (87.33) (38.02) 3Q2 = 19.2 fWs

Then assume the entire basin is draining an area having a streamf low-recession index of 140.

3Q2 = 5.77 x TO'3 Al-02 60.933Q2 = .00577 (80)1-02 (140)0.933Q 2 = .00577 (87.33) (99.06)3Q 2 = 50 f t3/s

The estimated low flows of 19.2 ft3/s and 50 ft3/s for 3Q2 are weighted based on the 70 and 30 percent of the basin draining areas of each streamflow- recession index.

19.2 ft3/s (0.7) = 13.4 ft3/ s50 ft3/s (0.3) = 15.0 ft3/s

Weighted-average 3Q2 low flow = 28.4 ft3/s

The 28.4 ft3/s is rounded to the nearest whole number, thus, 28 ft3/s is the estimated 3Q2 for the stream site in the second example.

54

The same procedure applies for estimating winter low flows using equations for the selected recurrence intervals for the stream site in the second exam­ ple. The appropriate equation for estimating winter low flows for each recur­ rence interval is used for each index area and a weighted-average low flow is computed based on the percent of the basin draining each index area.

For the third example, assume a stream site in East Tennessee is draining a basin having three streamflow-recession index areas and 50 percent of the basin has an index of 65, 30 percent has an index of 100, and 20 percent has an index of 50. Drainage area of the basin is 125 mi?. The estimating equa­ tions are used by applying each of the three streamflow-recession indexes to the entire basin, then a weighted-average winter low flow is computed based on the percent of the basin in each index area. Estimates of winter low flows for this example are computed in the following manner. First, assume the entire basin has a streamflow-recession index of 65.

3Q2 = 5.77 x 10-3 Al-02 00.93 3Q2 = .00577 (125) 1 - 02 (65)0.93 3Q2 = .00577 (137.7) (48.5) 3Q2 = 38.5 fWs

Next, assume the entire basin has a streamflow-recession index of 100.

3Q2 = 5.77 x 10-3 A!-02 G 0.93 3Q2 = .00577 (125) 1 - 02 (100)0.93 3Q2 = .00577 (137.7) (72.4) 3Q2 = 57.5 ftVs

Finally, assume the entire basin has a streamflow-recession index of 50.

3Q2 = 5.77 x 10-3 Al-02 00.933Q2 = .00577 (IZS) 1 ^2 (50)0.933Q2 = .00577 (137.7) (38.0)3Q2 = 30.2 fWs

The estimated low flows of 38.5 ft3/s , 57.5 ft3/s , and 30.2 ft3/s are weighted based on 50, 30, and 20 percent of the basin draining areas of each streamflow-recession index.

38.5 ft3/s (0.5) = 19.2 ft3/s57.5 ft3/s (0.3) = 17.2 ft3/s30.2 ft3/s (0.2) = 6.0 ft3/s

weighted-average low flow = 42.4 ft3/s

The 42.4 ft3/s is rounded to the nearest whole number, thus, 42 ft3/s is the estimated 3Q2 for the stream site in the third example.

The weighted-average low flow procedure should be used for all ungaged stream sites within the State where the basin is draining more than one stream- flow-recession index area.

55

Graphical solutions for the equations for estimating winter low flows in Tennessee streams are presented in figures 1 through 24. The dashed line and arrows on figure 1 indicate the procedure to follow for the following example.

A = 100 mi2G = 80, determined from plate 1

Enter the figure with drainage area (100 mi^) along the vertical scale. Move horizontally to the line for a streamflow-recession index of 80, then move down to the discharge scale. An estimate of about 14 ft3/s for winter 1Q2 was obtained from figure 1. The same procedure applies to figures 2 through 12 for winter low-flow estimates for West Tennessee streams. The following result for a stream in Middle or East Tennessee is obtained using the same method as described above except figure 13 is used for the following example:

A = 100 mi2 G = 40

from figure 13, 1Q£ = 18 ft3 /s.

56

SUPPLEMENT B

Comparison of Winter Low-flow Estimates for Low-flow Partial-Record Stations in West Tennessee

[OBS = map index numbers which correspond to those on plate 2; STAN = down­ stream order station number; DA = drainage area, in square miles; INDEX = mapped (plate 1) streamf low-recess ion index number, in days per log cycle (index value is a weighted average for basin where the basin lies in multiple streamflow-recession index areas); COR3Q20 = estimated 3-day 20-year winter low flow, in cubic feet per second, from correlation method; and COM3Q20 = estimated 3-day 20-year winter low flow, in cubic feet per second, from regression equation]

57

SUPPLEMENT B Continued

OBS

153207208209210211212213214215

216217218219220221222223224225

226227228229230231232233234235

236237238

STAN

03594422036063000702420007024350070244000702470007024730070247500702476007024770

07024800070249000702505007025100070259000702729007027680070282000702892007029275

07029350070293700702937307029374070294800702949007029675070300500703021007030212

070303570703060007031650

DA

49.588.226.520455.767.6

15634.293.4286

752110238268

173639.9

6871048173310

32944.155.956.0

12112251.4

230878.780.6

726597699

INDEX

250230350315245320245300190210

17521514513518070

220175210175

90240200200350350155170165165

140225215

COR3Q20

16.027.09.574.07.6

33.057.012.015.094.0

20020.020.020.0

3401.1

17519050.064.0

23.017.020.020.054.054.09.2

48030.030.0

90.0230240

COM3Q20

15.324.413.190.616.830.047.913.719.470.7

14327.632.933.0

3521.4

18520142.358.1

19.812.812.412.461.862.37.7

43013.113.4

96.9166182

58

SUPPLEMENT C

Comparison of Winter Low-Flow Estimates for Low-Flow Partial-Record Stations in Middle and East Tennessee

[OBS = map index numbers which correspond to those on plate 2; STAN = down­ stream order station number; DA = drainage area, in square miles; INDEX = mapped (plate 1) streamflow-recession index number, in days per log cycle (index value is a weighted average for basin where the basin lies in multiple streamflow-recession index areas); COR3Q20 = estimated 3-day 20-year winter low flow, in cubic feet per second, from correlation method; and COM3Q20 = estimated 3-day 20-year winter low flow, in cubic feet per second, from regression equation]

59

SUPPLEMENT C Continued

OBS

123456789

10

11121314151617181920

21222324252627282930

31323334353637383940

STAN

03403750034100500341468003417695034178500341803003419270034208800342120003422620

03422950034245200342475003424900034267000342690003433720034338100343391003434580

03434585034346400343470003435044034351100343512003435300034361300343630003436460

03436490034366550343693003454790034612600346522003465610034656310346623403467895

DA

24071270.815.340.313.837.7

29731.13.01

6.3629.8

22726.97.03

12580.227.266.2727

5.0510784378.419.769.2

54720.569.3179

45552.255.732.65.22

57.323.14.2115.59.30

INDEX

32355065656560140120120

806043355551908010055

80906052505370808080

7712012010010010012012012082

COR3Q20

0.718.02.42.56.62.37.0

88.010.01.2

1.03.59.4.4.9

9.56.85.5

14.064.0

.812.091.05.41.24.1

35.01.67.214.0

11013.06.65.8.6

8.26.51.53.31.2

COM3Q20

6.121.43.91.33.51.22.9

1038.0.7

.82.39.7.8.4

7.212.63.412.548.7

.616.866.04.61.14.2

56.02.68.822.9

55.013.514.56.11.010.85.91.14.01.2

60

SUPPLEMENT a Continued

OBS

41424344454647484950

51525354555657585960

61626364656667686970

71727374757677787980

STAN

03468050034681960346910003469105034691190346913003469230034692530346928203469400

03470330034785500347859003481700034818000348181503484200034847970348623003486488

03486860034871000348754803487562034918000349200503492995034948000349495503497113

03497200034987150349900003499053034990550349906203499110034992900349941203518130

DA

30.83.48

46.13.74

18.011020.031.87.23

59.9

28.348.08.326.77

24.470.057.832.639.06.78

9.0620.336.343.232.33.13

30.658.83.626.36

60.117.913.511.830.632.0

3525.00

10.560.3

INDEX

70120140100100105135125130125

80120115757575

10510010070

1201201101005010080508080

16512012012012012010512092115

COR3Q20

3.01.0

16.01.53.8

26.07.47.02.6

17.0

3.915.02.6.9

3.18.99.610.05.6.8

1.94.85.06.02.0.5

5.72.7.8

1.4

25.04.53.03.9

10.08.4

92.02.51.7

15.0

COM3Q20

3.1.9

15.7.7

3.322.76.38.82.1

16.7

3.612.42.0.7

2.77.9

11.96.17.3.7

2.35.28.08.11.8.6

3.93.2.4.8

27.44.63.53.07.98.3

73.51.31.7

14.5

61

SUPPLEMENT C-Continued

OBS

81828384858687888990

919293949596979899100

101102103104105106107108109110

111112113114115116117118119120

STAN

03518456035184700351875003519000035196000351966003519700035277000352820003531700

03531800035342000353450003535055035351830353518703535195035352000353540003538215

03538244035419950354200003543300035442200355670003557200035573000356492003565087

03565410035654370356544403565730035660500356610203566117035661230356612803566137

DA

59.921.725.2

27111.243.430.74.83

21.723.9

4.6539.39.45

1037.12

36.452.556.186.818.4

12.411.8

10832.36.483.829.90

1017.40

33.5

24.322.126.869.315.621.22.872.81

42.111.6

INDEX

105175571051201201105050105

65656787827076798235

70623510565577690no120

140140140140100100120120120120

COR3Q20

11.011.02.5

68.01.5

13.05.8.2.6

4.5

.54.4.4

14.01.84.56.56.07.6.35

1.31.83.56.8.3.2.6

21.01.66.6

4.16.88.0

23.02.12.9.2.6

10.02.5

COM3Q20

12.310.91.7

56.42.9

11.26.8.3

1.24.9

.43.4.9

15.2.9

3.66.17.0

11.5.5

1.2.9

3.26.6.6.3

1.115.91.68.7

8.27.59.1

23.72.93.9.7.7

10.93.0

62

SUPPLEMENT C Continued

OBS

121122123124125126127128129130

131132133134135136137138139140

141142143144145146147148149150

151152154155156157158159160161

STAN

03566235035664300356655003566625035674000356749403567496035675900356863003568670

03570560035706020357084003571825035720900357803003578500035785040357970003580500

03580700035833300358340003583480035840500358820003588260035883400358851503588600

03593585035941400359448403595100035955000359613003596700035972000359722003597787

DA

65.910.86.68

10815314.219.312.163.970.7

12.11065.50

11778.221.641.350.541.277.1

24.628.986.622.98.1018.653.631.58.58

46.6

21.784.4

25113.040.430.616.880.185.517.2

INDEX

120656558

120120120806565

1009366525048809214060

95105705050140140140140140

13095

15014012014050515052

COR3Q20

7.5.4.4

9.436.03.24.41.04.65.9

2.17.7.4

7.83.2.7

5.66.815.07.8

7.47.4

16.01.6.3

7.414.012.51.718.0

9.612.090.02.56.715.0

.74.34.61.8

COM3Q20

17.1.9.6

7.840.13.65.01.55.66.2

2.217.6

.57.04.31.15.28.214.05.9

4.25.98.71.3.4

6.318.310.72.9

15.9

6.414.698.24.4

10.510.4

.94.64.71.0

63

SUPPLEMENT C--Continued

OBS

162163164165166167168169170171

172173174175176177178179180181

182183184185186187188189190191

192193194195196197198199200201

202203204205206

STAN

03597900035992500359941803599450036002560360108003601100036015000360155003601700

03601900036019800360211003602192036022000360222903602232036022450360259003602630

03602660036027000360347903603500036035400360356003603580036035860360359003603600

03603690036037100360371603603730036037700360385003603860036039000360405003604150

0360420003604240036046200360595303605968

DA

49.69161028

74.032.814.848.311245.299.8

1545.699.0021.26.216.31

13.719.822.97.64

30.851.226.975.121.412.1

10110.115.3

126

19.36.57

20.124.656.622.812.356.4

51615.2

45.183.631.324.854.5

INDEX

346260353895745472

115

130959514080110120140140140

140140125130140140140140140140

14013013513595140140115120105

11596

140120120

COR3Q20

1.077.070.02.61.22.34.57.05.6

28.0

52.0.7

1.66.0.8.7

1.46.8

11.03.4

5.510.05.9

23.010.05.7

34.02.64.5

44.0

8.73.57.07.22.04.33.314.0

1804.0

14.024.08.63.07.6

COM3Q20

1.476.080.62.21.12.55.37.14.7

24.2

46.51.01.57.2.8

1.43.56.77.72.6

10.417.57.5

22.57.24.1

34.73.45.2

43.3

6.51.96.47.89.77.74.113.6

1373.1

10.814.710.66.4

14.1

64

SUPPLEMENT D

Winter Low-Flow Values Estimated from Observed Streamflow Records and Regression Equations, and Data Used to Derive the Equations for Tennessee Streams

Map index numbers correspond to station identification numbers on plate 1; streamflow-recession index number from plate 1; *sites used to derive low-flow equations for streams in West Tennessee; mi? = square miles; ft3/s = cubic feet per second]

Map index No.

123456789

10

11121314151617181920

21222324252627282930

31323334353637383940

StationNo.

03408500034095000341450003415000034155000341600003416100034178000341800003418020

03418050034193000341950003420000034201200342020003420500034208000342090003421000

03422800034246700342660003426800034268500342688003427500034279000342900003430100

03431600034317000343180003433500034337000343400003434500034346000343500703435400

Drainage area (mi 2)

38227220211444510613815.178.722.5

50.316.7

15717578.8

174126132303642

15.813725.539.124.524.0

26265.1571892

51.624.397.2

40859.6

11568156.211.298.0

Streamflow 1Q2 recession

index

32374748536062656565

6575757667371406011085

603590

104506046344545

373510032130100569057

100

Observed (ft 3 /s)

10466.272.617.3

10434.037.02.4

17.35.4

17.05.4

66.063.530.029.060.340.0155248

_ _--10.015.14.59.0

45.69.60

91.2122

11.04.8

32.368.418.042.016014.03.0

32.0

Regression (ftVs)

56.245.642.424.010727.737.44.0

22.06.1

13.95.1

51.458.222.728.874.934.6146247

__--9.516.95.16.0

54.29.7

118187

8.33.6

41.560.232.349.317521.32.6

41.8

1Q10

Observed (ftVs)

20.015.017.24.6

31.010.014.01.06.22.0

6.01.9

25.020.46.75.0

40.411.077.098.8

__--4.66.51.43.8

12.72.40

23.933.8

5.02.0

17.717.912.027.069.98.01.0

12.0

Regression (ftVs)

13.612.113.17.6

35.110.113.91.68.52.4

5.42.2

21.324.38.97.7

45.912.675.9

107

_ _--4.68.81.72.7

16.52.5

34.954.6

2.31.0

20.814.519.224.658.810.11.0

20.9

1Q20

Observed (ftVs)

9.09.0

10.54.2

25.07.6

12.0.8

4.71.5

4.51.4

21.014.63.23.5

36.77.2

61.074.8

_ _

4.13.65.0.9

2.98.41.6

15.222.3

2.9.9

14.910.011.024.056.17.1.7

9.0

Regression (ftVs)

8.47.89.05.2

24.77.3

10.21.26.31.8

4.01.7

16.418.76.75.0

41.19.1

63.884.6

__3.53.77.41.21.711.21.6

2J.536.8

1.5.6

17.19.016.920.3.41.88.1.7

17.3

65

SUPPLEMENT D Continued

Map index No.

41424344454647484950

51525354555657585960

61626364656667686970

71727374757677787980

Station No.

03435500034357900343590003436000034361000343620003436430034367000343690003436970

03455000034612000346130003464815034650000346550003466200034663700346670003466840

03466885034670000346749003468250034691120346916003469238034695000347000003476980

03478602034816250348200003484420034849110348550003486500035875200348755003491000

Streamflow 10.2 Drainage recession

area index (mi 2 )

70675.132.0

18693518813012434.511.9

185810.255.381.015.9

80578.114.940.478.0

7.9922041.210.411.264.124.076.2

35318.4

12.912.6

10213.825.5

13710.344.536.347.3

75508055758080120120120

14010094

1001001001201205098

5068655010072

111958050

968876

10070no506510070

Observed (ftVs)

1268.66.2

36.527440.031.046.515.04.9

13409.8

26.031.08.0

56726.06.64.421.0

.630.05.41.46.818.014.048.0150

1.9

4.53.9

34.06.08.3

86.24.7

--12.012.5

Regression (ftVs)

24116.310.745.332265.845.063.517.15.7

11904.1

21.934.46.5

136039.57.28.6

32.4

1.666.111.32.14.519.710.930.7126

3.8

5.04.5

33.45.67.4

64.72.1

--15.114.0

1Q10

Observed (ftVs)

50.33.43.214.297.518.011.023.58.22.4

7494.314.014.03.1

28817.03.71.5

14.0

.317.03.0.5

3.68.88.0

24.077.4

.6

2.41.916.02.62.6

46.01.3

--5.54.6

Regression (ftVs)

96.95.34.815.5

12928.319.535.49.83.4

6902.210.717.33.4

17422.24.22.9

16.1

.625.74.4.7

2.48.16.015.053.41.3

2.52.2

14.12.93.1

34.1.7

--7.75.7

1Q20

Observed (ftVs)

43.02.62.710.972.016.09.0

23.08.01.8

6283.0

12.010.02.0

23016.03.61.3

13.5

.216.02.7.35

3.07.06.719.063.0

.4

2.01.5

12.02.01.8

38.1.7

1.74.63.8

Regression (ftVs)

74.03.73.7n.o98.222.115.230.58.52.9

6131.88.714.32.8

14319.23.62.013.2

.419.23.3.5

2.06.25.1

12.241.6

.9

2.11.710.910.92.3

28.8.5

3.66.44.3

66

SUPPLEMENT D Continued

Map index No.

81828384858687888990

919293949596979899

100

101102103104105106107108109no111112113114115116117118119120

. - "

StationNo.

_

03491300034945280349474003495000034973000349800003498500034992000349930003499620

03518410035185000351880003519640035197320352004303527600035280000352830003528400

03531815035319000353200003532100035322000353400003534980035350000353505003538180

03538225035396000353980003543200035435000354423503557148035615000356504003565080

Drainage area (mi 2 )

47.018.26.68

61.410619226913.211.29.62

67.111827.916.047.223.385.8

147419.02.68

19.962.5

68531.224.024.57.82

68.593.310.2

82.5139518.026.411722.279.4

44714.88.54

______ Streamflow 1Q2 rpression

index1 -~

65120506514590100135120120

87112100120140120606590120

1157510090425382807570

6532325384701151401?0120

Observed (ftVs)

9.210.0

.912.0

1151171789.87.55.0

33.510211.012.337.013.023.0

5543.4.96

9.722.026812.03.28.41.8

20.532.04.8

34.945.0207

3.338.54.436.0

5355.54.0

Regression (ftVs)' ' '

13.08.81.4

17.064.975.4118

7.15.44.6

24.856.511.57.7

27.327.322.3

4477.01.2

9.319.9

30811.64.35.42.6

23.330.12.9

23.119.976.95.9

42.46.4

38.5275

7.14.1

~~ W\Q

Observed (ftVs)

3.65.8.3

4.75956.086.06.63.22.8

14.053.45.86.418.06.68.3

2202.0.58

5.39.6

no5.0.7

2.2.8

8.116.01.7

11.57.5

43.0.8

18.51.719.0

1902.92.5

Regression (ftVs)

5.15.1.5

6.640.834.957.94.53.22.7

11.830.25.94.5

17.16.68.2

1623.4.7

5.38.4

1485.61.31.91.2

10.312.61.2

8.94.918.42.1

19.02.7

21.1164

4.22.4

1Q20

Observed (ftVs)

2.54.8.2

4.139.039.069.05.92.52.3

9.039.04.94.815.05.47.0

1751.7.50

4.58.0

90.04.2.5

1.2.7

6.613.01.3

8.02.8

17.0.6

15.01.317.0

1052.52.2

Regression (ftVs)

3.84.4.3

4.936.928.047.64.02.72.3

9.225.64.93.9

15.35.75.9

1192.7.7

4.56.5

1224.5.9

1.3.9

8.09.7.9

6.63.0

1 1.41.4

15.02.018.1

1473.62.1

67

SUPPLEMENT D Continued

Map index No.

121122123124125126127128129130

131132133134135136137138139140

141142143144145146147148149150

151152153154155156 *157158159160

StationNo.

03565120035651600356525003565300035655000356612603566250035662600356632003566420

03566450035665430356750003570580035706000357083503571000035715000357183503578000

03579100035803000358120003582000035833000358336003583500035840000358450003585250

03585260035879000358840003588500035909000359330003593580035936000359370003593800

Drainage area (mi 2 )

37.832.711431.857.029.388.744.522.718.8

28.313.2

42823.786.2

27440211628.265.6

27555.949.4

82747.520.224.4

366178436.6

17.415.443.0

34842.549.426.966.714.9

104

Streamflow 1Q2 recession

index

1201201206514013095904880

676012072808085656550

905050no37501006075

140

1401401401386865130130130125

Observed («Vs)

16.015.652.29.6

35.020.032.013.010.07.5

4.04.7

1758.629.010214241.08.2

21.7

88.69.511.0

3234.75.89.1

99.061823.0

8.312.027.2

18115.07.56

16.040.08.4

56.6

Regression (ftVs)

18.716.158.28.7

33.215.635.916.84.66.2

7.93.3

2277.1

29.596.915232.87.714.2

10912.010.6

4117.64.210.098.862521.0

9.88.6

24.821012.25.4

14.336.37.8

55.1

1Q10

Observed (ft'/s)

8.48.7

27.74.8

19.711.017.06.62.14.3

1.61.7

1043.19.8

28.051.513.02.53.0

36.84.74.7

1682.52.85.5

47.528718.0

5.58.415.3

1146.63.1611.027.05.6

35.4

Regression (ftVs)

10.79.3

32.53.4

20.79.4

17.58.01.52.8

3.21.2

1233.012.941.467.012.53.04.7

50.14.03.5

2082.11.45.2

35.124613.2

6.35.515.6

1254.91.88.6

21.54.8

31.7

1Q20

Observed (ftVs)

7.37.6

23.74.0

16.79.815.05.41.23.6

1.31.4

90.32.57.8

21.042.012.02.01.8

28.93.93.7

1442.12.24.9

39.023117.0

4.97.4

13.0103

5.22.569.2

23.05.0

30.8

Regression (ftVs)

9.38.0

28.12.518.58.314.26.41.02.2

2.4.9

1062.310.132.252.99.32.23.2

40.12.82.4

1751.41.04.3

25.518811.9

5.65.0

14.0111

3.71.57.6

19.04.2

27.6

68

SUPPLEMENT D Continued

Map index No.

161162 *163164165166167168 *169170

171172173174175176177178179180

181182183184185186187188189190

191192193194195 *196 *197 *198 *199 *200 *

Station No.

03594040035941200359415003594160035941800359426003594400035944450359530003596000

03596500035970000359770003598000035995000360038003600500036016950360186003601950

03602235036025000360260003603000036035500360366003603720036037500360400003604060

03604180036045000360460003605555036062800360650003607000036072000702425007024300

Streamflow 1Q2 Drainage recession

area index (mi 2 )

53.745.525.8

20150.724.716.8

115.035.3107

20866.3130481120837.517.58.4315.35.56

22.720274.7

255760.237.713.419.1

4477.34

15.270724.831.941.4

20537947.943.555.5

66757766649560

20560100

105454490504510013013075

1201351359014014014014012095

140125135110230240200240200350

Observed (ftVs)

23.613.910.082.012.06.93.8

67.09.2

38.0

no12.222.0

15623910.06.56.014.02.4

6.491.054.0

88727.033.05.6

11.0251

2.3

9.841015.016.217.093.410627.518.035.7

Regression (ftVs)

15.16.08.258.513.49.74.2

42.48.9

45.8

95.012.925.3194283

7.27.14.38.01.7

11.111842.3

108035.121.77.510.8

2372.8

8.539513.614.516.787.313920.115.531.9

1Q10

Observed (ftVs)

12.34.04.8

46.66.64.31.9

38.04.9

20.4

62.05.36.8

85.773.55.13.93.89.8.9

3.658.835.0

49318.022.03.87.2

1671.5

6.1270

9.610.611.062.886.020.010.026.9

Regression (ftVs)

5.92.33.6

22.45.34.81.6

29.13.3

24.9

48.34.07.6

87.987.62.33.72.74.9.7

6.469.825.6

47221.813.64.86.9

1291.4

5.7218

8.47.912.065.395.514.710.428.1

1Q20

Observed (ftVs)

8.82.43.8

40.85.83.81.6

32.04.2

17.1

504.45.0

74.450.04.13.53.59.0.8

3.153.632.0

42716.020.03.36.5

1501.3

5.4245

8.69.49.8

56.780.017.59.30

24.8

Regression (ftVs)

4.41.82.8

16.63.93.91.2

26.12.4

18.9

40.22.75.1

70.360.51.53.12.44.3.6

5.661.822.8

37619.612.24.36.2

1111.2

4.9189

7.56.710.959.385.213.49.3

26.5

69

SUPPLEMENT D Continued

Map Index No.

201 *202 *203 *204 *205 *206 *207 *208 *209 *210 *

211 *212 *213 *214 *215 *216 *217 *218 *219 *220 *

221 *222 *223 *224 *225 *226 *227 *228 *

Station No.

07024500070247200702500007025300070253500702550007026000070273000702750007027700

07028000070285000702890007029000070291000702938007029400070294100702944007029500

0702970007030000070300200703020907030280070304000703050007031700

Drainage area (nii 2 )

38313720383.736.7

480185216049525.0

100373.488.2

36986794.883747.640.4

1480

84.31940

92.076.9

50571.9

503770

Streamf lov recession

index

23530015030065

20517523023060

19514012019516014013025060

160

210175170165150170230210

v 1Q 2

Observed (ft'/s)

15185.033.435.03.2

140--65.0188

1.1

28615.017.0

12626844.227823.05.0

637

29.082920.518.093.918.0

229295

Regression (ft'/s)

16170.156.942.64.0

180--65.5205

2.4

36319.019.7

13226224.7

20820.63.9

450

31.764228.723.314322.3

209297

1Q10

Observed (ft'/s)

10667.022.629.0

.7113 48.0134

.42

19712.99.4

10115116.5

14718.01.6

329

19.046615.014.069.014.0

179218

Regression (ftVs)

12058.133.435.11.4

126__47.8152

.8

25010.610.189.716213.8

11515.41.2

281

21.942217.814.284.913.8

155211

1Q20

Observed (ftVs)

96.962.020.828.0

.6108_.35.0124

.38

17812.58.0

96.213012.5

12217.01.2

273

16.540614.013.061.913.0

168192

Regression (ftVs)

10953.929.032.51.1

113_.43.3137

.6

2229.28.6

79.814211.998.314.11.0

245

19.737115.712.573.712.2

140189

70

SUPPLEMENT D--Continued

Map index No.

123456789

10

11121314151617181920

21222324252627282930

31323334353637383940

Station No.

03408500034095000341450003415000034155000341600003416100034178000341800003418020

03418050034193000341950003420000034201200342020003420500034208000342090003421000

03422800034246700342660003426800034268500342688003427500034279000342900003430100

03431600034317000343180003433500034337000343400003434500034346000343500703435400

Drainage area (mi 2 )

38227220211444510613815.178.722.5

50.316.7

15717578.8

174126132303642

16.813725.539.124.524.026265.1

57189?

51.624.397.2

40859.6

11568158.211.298.0

Streamflo* recession

index

32374748536062656565

6575757667371406011085

603590

104506046344545

373510032130100569057

100

* 3Q2

Observed (ftVs)

11371.177.018.2

12236.842.02.5

18.25.3

17.05.7

76.066.116.031.062.136.0162262

10.016.34.79.2

48.39.0

97.3129

13.05.4

35.777.921.043.017114.03.4

34.0

Regression (ftVs)

61.950.146.326.411630.140.64.4

23.96.7

15.25.6

55.262.524.631.878.937.6154261

10.318.15.76.6

59.110.8

128202

9.24.1

44.366.234.352.518823.02.9

44.7

3Q10

Observed (ftVs)

21.016.017.74.8

39.511.617.01.16.62.1

6.42.0

30.021.46.46.0

41.213.080.0105

.9

5.07.01.64.2

14.72.7

28.335.7

5.42.3

18.219.89.5

28.072.48.01.1

15.0

Regression (ftVs)

15.513.714.68.4

38.911.015.11.79.22.6

5.82.4

23.026.29.68.7

47.513.780.0

116

1.7

4.89.31.92.4

18.42.8

39.061.3

2.51.1

21.916.619.926.065.110.71.0

22.1

3Q20

Observed (ftVs)

10.010.010.74.5

27.110.013.0

.95.51.8

5.41.7

22.017.04.92.5

37.48.5

65.080.2

.84.74.05.341.13.3

10.11.9

19.023.7

3.01.0

14.910.19.0

24.057.67.1.7

13.0

Regression (ftVs)

9.68.89.95.8

27.28.111.11.36.82.0

4.41.9

17.720.27.25.6

42.810.067.590.9

1.34.03.97.81.31.8

12.41.8

26.241.0

1.6.7

18.210.217.721.54o.O8.7.8

18.3

71

SUPPLEMENT D Continued

Map index No.

41424344454647484950

51525354555657585960

61626364656667686970

71727374757677787980

Station No.

03435500034357900343590003436000034361000343620003436430034367000343690003436970

03455000034612000346130003464815034650000346550003466200034663700346670003466840

03466885034670000346749003468250034691120346916003469238034695000347000003476980

03478602034816250348200003484420034849110348550003486500034875200348755003491000

Streamflow 30.2 Drainage recession

area index (mi 2 )

70675.132.0

18693518813012434.511.9

185810.255.381.015.9

80578.114.940.478.0

7.9922041.210.411.264.124.076.2

35318.4

12.912.6

10213.825.5

13710.344.536.347.3

75508055758080120120120

140100941001001001201205098

5068655010072

111958050

968876

10070

110506510070

Observed (ftVs)

13216.07.0

39.029341.032.049.316.08.0

142510.029.036.08.4

61628.07.05.5

22.0

1.231.76.51.67.4

20.015.054.0164

2.4

5.24.537.07.0

10.097.05.0

--12.213.2

Regression (ftVs)

25617.911.649.234070.548.467.218.26.2

12204.5

23.536.87.0

38242.07.89.5

34.7

1.871.112.42.44.921.311.732.91344.3

5.44.9

36.06.18.1

68.62.4

--16.215.3

3Q10

Observed (ftVs)

52.16.03.214.599.419.011.024.48.52.4

8184.516.018.03.8

33718.04.01.7

15.0

.3518.03.2.6

4.010.08.8

27.086.3

.8

2.52.0

17.03.23.5

54.01.3

--5.64.7

Regression (ftVs)

1055.95.1

17.014030.420.937.010.13.5

7222.2

11.318.23.5

18623.24.33.117.0

.627.94.8.8

2.58.76.215.857.51.4

2.72.3

15.23.03.3

35.8.8

--8.16.1

3Q20

Observed (ftVs)

48.05.33.013.072.117.010.324.08.21.9

6893.012.011.02.9

24017.03.71.4

14.0

.217.03.0.4

3.27.47.0

20.066.0

.5

2.21.813.02.42.4

44.0.7

1.85.04.1

Regression (ftVs)

80.14.14.012.0

10623.816.432.18.93.0

6411.99.2

15.12.9

13420.13.82.2

14.1

.420.93.6.6

2.16.75.413.044.71.0

2.21.9

11.72.62.5

30.41.83.96.84.7

72

SUPPLEMENT D Continued

Map index No.

81828384858687888990

919293949596979899

100

101102103104105106107108109no111112113114115116117118119120

Station No.

03491300034945280349474003495000034973000349800003498500034992000349930003499620

03518410035185000351880003519640035197320352004303527600035280000352830003528400

03531815035319000353200003532100035322000353400003534980035350000353505003538180

03538225035396000353980003543200035435000354423503557148035615000356504003565080

Streamflow 3Q2 Drainage recession

area index (mi 2 )

47.018.26.68

61.410619226913.211.29.62

67.111827.916.047.223.385.8

147419.02.68

19.962.5

68531.224.024.57.82

68.593.310.2

82.513951826.411722.279.4

44714.88.54

65120506514590100135120120

87112100120140120606590120

1157510090425382807570

653232538470115140120120

Observed (ftVs)

10.111.01.0

13.012312419012.08.05.4

37.010911.013.040.014.024.0

5803.51.0

10.024.0

28713.03.68.71.9

22.735.05.4

38.548.0

2213.8

41.34.838.0

6095.74.7

Regression (ftVs)

14.19.51.5

18.668.380.3125

7.65.85.0

26.66012.48.3

29.012.224.0

4747.61.3

10.021.6

32412.64.86.02.8

25.232.53.9

25.122.184.56.5

45.57.1

41.0287

7.74.4

3Q10

Observed (ftVs)

3.96.0.3

4.960.060.087.07.23.32.9

15.057.06.06.518.06.78.4

2252.2.6

5.811.0

1125.0.8

2.3.8

9.619.01.8

12.08.0

46.01.0

19.01.8

20.0210

3.02.7

Regression (ftVs)

5.55.3.5

7.242.137.261.34.63.22.8

12.231.76.24.717.66.88.9

1783.6.8

5.49.1

1585.91.42.11.3

11.013.61.3

9.65.6

21.12.2

20.32.9

22.11714.32.5

3Q20

Observed (ftVs)

2.95.0.2

4.340.040.070.06.42.62.5

9.440.05.15.0

15.35.57.4

1802.0.52

4.88.5

97.44.5.6

1.2.7

7.414.01.3

8.23.017.0

.815.31.4

17.0no

2.52.2

Regression (ftVs)

4.14.7.4

5.338.329.950.64.22.92.5

9.827.05.24.115.66.06.5

1302.9.7

4.77.0

1294.81.01.51.08.610.51.0

7.23.513.01.6

16.12.219.0

1533.82.2

73

SUPPLEMENT D«Cont1nued

Map index No.

121122123124125126127128129130

131132133134135136137138139140

141142143144145146147148149150

151152153154155156 *157158159160

Station No.

03565120035651600356525003565300035655000356612603566250035662600356632003566420

03566450035665430356750003570580035706000357083503571000035715000357183503578000

03579100035803000358120003582000035833000358336003583500035840000358450003585250

03585260035879000358840003588500035909000359330003593580035936000359370003593800

Drainage area (mi 2 )

37.832.711431.857.029.388.744.522.718.8

28.313.2

42823.786.2

27440211628.265.6

27555.949.4

82747.520.224.4

366178436.6

17.415.443.0

34842.549.426.966.714.9

104

Streamflow 3Q2 recession

index

1201201206514013095904880

676012072808085656550

905050no37501006075

140

1401401401386865130130130125

Observed (ftVs)

16.716.054.010.836.921.036.014.010.08.1

4.45.5

1859.8

34.0no16447.09.8

23.9

11310.012.0

3445.26.29.4

10568824.0

8.615.028.8

19017.08.416.041.08.8

57.6

Regression (ftVs)

20.017.361.79.5

35.116.638.518.15.16.7

8.73.6

2387.8

31.810416235.58.415.6

11613.211.7

4298.54.710.8

10665822.4

10.59.3

26.421913.35.815.338.58.4

58.4

3Q10

Observed (ftVs)

8.78.8

28.05.2

20.212.018.07.02.24.6

1.81.7

1083.1

10.028.052.013.02.54.9

44.84.85.0

1732.82.85.7

50.031418.0

5.68.615.8

1217.23.411.027.05.8

36.0

Regression (ft'/s)

11.19.6

34.03.7

21.39.718.58.51.63.0

3.41.3

1303.2

13.844.572.013.63.35.1

53.54.43.9

2212.31.65.4

38.526913.6

6.45.7

16.0130

5.31.98.9

22.34.9

32.9

3Q20

Observed (ft'/s)

7.57.7

23.94.219.011.015.05.61.33.9

1.41.5

93.32.78.4

24.045.012.02.12.8

34.34.04.1

1462.42.05.2

40.525017.0

5.07.8

13.4109

5.82.719.4

24.05.6

31.4

Regression (ftVs)

9.78.4

29.52.8

19.38.715.16.91.12.4

2.61.0

1112.510.834.756.810.12.43.6

42.93.02.7

1851.51.14.5

27.920312.4

5.95.214.5

1164.01.48.019.84.4

28.9

74

SUPPLEMENT D Continued

Map index No.

161162 *163164165166167168 *169170

171172173174175176177178179180181

182183184185186187188189190191

192193194195 *196 *197 *198 *199 *200 *

Station No.

03594040035941200359415003594160035941800359426003594400035944450359530003596000

0359650003597000035977000359800003599500036003800360050003601695036018600360195003602235

03602500036026000360300003603550036036600360372003603750036040000360406003604180

036045000360460003605555036062800360650003607000036072000702425007024300

Drainage area (mi 2 )

53.745.525.8

20150.724.716.8

11535.3

107

20866.3130481120837.517.58.4315.35.56

22.7

20274.7

255760.237.713.419.1

4477.3415.2

70724.831.941.4

20537947.943.555.5

Streamflow 30.2 recession

i ndex

66757766649560

20560

100

105454490504510013013075120

1351359014014014014012095140

125135no230240200240200350

Observed (ftVs)

24.514.811.085.012.07.24.1

70.59.6

39.6

13013.022.0

16528211.07.06.2

14.02.76.8

94.856.0

91428.034.06.011.0

2612.510.0

42212.017.018.098.011028.019.036.9

Regression (ftVs)

16.46.49.0

63.115.110.44.6

43.69.8

48.8

10114.327.8

205303

8.07.74.78.61.8

12.0

12344.7

112037.123.18.011.5

2483.09.1

41214.516.417.189.014220.516.032.2

3Q10

Observed (ftVs)

12.64.25.1

47.07.04.52.0

39.65.2

21.2

64.05.67.2

90.1108

5.24.13.89.8.9

3.6

59.535.0

50518.523.04.07.4

1741.76.4

2727.4

11.010.065.091.021.011.027.5

Regression (ftVs)

6.42.43.8

24.35.85.11.7

29.93.6

24.1

51.04.48.4

94.997.82.53.92.85.0.8

6.6

72.426.5

51022.514.04.97.0

1351.55.6

229

8.212.366.897.715.210.728.7

30.20

Observed (ftVs)

8.82.524.2

41.06.04.01.7

33.04.617.8

50.04.65.0

77.880.54.33.63.56.4.8

3.2

53.832.0

43616.520.03.86.8

1571.55.7

2458.710.010.058.186.019.09.5

25.5

Regression (ftVs)

4.81.83.0

18.14.34.21.3

27.12.7

20.0

42.63.05.7

75.267.01.73.22.54.5.6

5.8

64.523.7

40420.412.74.56.4

1161.25.1

1987.87.0

1 1.361.888.214.09.6

28.0

75

SUPPLEMENT D Continued

Map index No.

202 *203 *204 *205 *206 *207 *208 *209 *210 *211 *

212 *213 *214 *215 *216 *217 *218 *219 *220 *221 *

222 *223 *224 *225 *226 *227 *228 *

Station No.

07024720070250000702530007025350070255000702600007027300070275000702770007028000

07028500070289000702900007029100070293800702940007029410070294400702950007029700

07030000070300200703020907030280070304000703050007031700

Drainage area (mi 2 )

13720383.736.7

480185216049525.0

1003

73.488.236986794.8

83747.640.4

148084.3

194092.076.9

50571.9

503770

Streamflow 30.2 recession

index

30015030065

20517523023060

195

14012019516014013025060160210

175170165150170230210

Observed (ftVs)

88.035.234.03.7

14359568.0

1971.1

292

15.317.0

12928345.7

30624.05.6

66826.5

84921.018.294.618.5

233295

Regression (ftVs)

71.059.043.24.3

18763067.0

2102.6

372

19.820.713627025.7

21721.14.3

46532.5

66129.624.114823.1

213304

3Q10

Observed (ft'/s)

68.023.131.0

.711539350.0138

.45200

13.19.6

10215617.2

15819.01.8

34120.0

47416.014.069.414.0

181218

Regression (ftVs)

59.334.535.91.4

12941049.0155

.8255

11.010.591.8

16614.3

11815.91.3

28722.5

43018.414.787.514.3

158215

3Q20

Observed (ftVs)

65.021.030.0

.6no35245.0127

.3182

12.78.3

96.913313.0

13017.51.3

28217.0

41214.013.063.613.0

170192

Regression (ftVs)

56.629.734.21.1

11636445.0143

.6229

9.48.8

82.914512.2

10014.71.0

25120.4

38116.212.875.512.6

145196

76

SUPPLEMENT D Continued

Map index No.

123456789

10

11121314151617181920

21222324252627282930

31323334353637383940

Station No.

03408500034095000341450003415000034155000341600003416100034178000341800003418020

03418050034193000341950003420000034201200342020003420500034208000342090003421000

03422800034246700342660003426800034268500342688003427500034279000342900003430100

03431600034317000343180003433500034337000343400003434500034346000343500703435400

Drainage area (mi 2 )

38227220211444510613815.178.722.5

50.316.7

15717578.8

174126132303642

16.813725.539.124.524.0

26265.1

571892

51.624.397.2

40859.6

11568156.211.298.0

Streamflow 7Q£ recession

index

32374748536062656565

65757576673714060no85

603590

104506046344545

373510032130100569057100

Observed (ftVs)

14592.793.622.917943.056.03.0

22.97.1

22.06.6

10278.019.036.068.858.0190325

--12.018.96.2

11.065.912.0

119155

16.06.9

40.498.121.047.020115.04.3

40.0

Regression (ftVs)

79.863.657.332.414336.248.85.2

28.57.9

18.06.6

65.473.929.340.288.045.4177308

_ _--11.820.66.97.9

73.413.7

161254

11.55.1

50.885.438.360.4

23126.53.5

51.3

7Q10

Observed (ftVs)

31.019.020.55.2

50.013.021.01.28.22.6

8.02.1

47.022.07.6

11.044.715.092.0126

_ _-_5.38.01.74.416.03.0

31.037.0

6.22.7

19.824.513.030.083.88.51.2

16.0

Regression (ftVs)

19.717.217.810.346.413.117.92.110.93.1

6.92.8

26.530.111.411.050.716.387.4130

_ _-_5.510.42.33.0

22.43.6

47.574.2

3.21.4

24.521.121.629.076.812.21.3

24.7

7Q20

Observed (ftVs)

17.011.012.15.0

35.010.016.01.06.11.9

6.01.7

26.017.65.64.0

40.49.8

73.093.5

_ _

-_

4.26.01.23.511.02.0

21.028.0

3.21.3

16.015.612.026.065.77.4.8

13.3

Regression (ftVs)

12.711.412.57.3

33.19.713.31.68.22.4

5.32.2

20.523.48.77.3

44.912.172.9

102

_ ___4.58.71.72.215.62.4

32.650.7

2.21.0

20.313.519.023.955.19.91.0

20.4

77

SUPPLEMENT D Continued

Map index No.

41424344454647484950

51525354555657585960

61626364656667686970

71727374757677787980

Station No.

03435500034357900343590003436000034361000343620003436430034367000343690003436970

03455000034612000346130003464815034650000346550003466200034663700346670003466840

03466885034670000346749003468250034691120345916003469238034695000347000093476980

03478602034816250348200003484420034849110348550003486500034875200348755003491000

Streamflow 7Q2 Drainage recession

area index (mi 2 )

70675.132.0

18693518813012434.511.9

185810.255.381.015.9

80578.114.940.478.0

7.9922041.210.411.264.124.076.2

35318.4

12.912.610213.825.5

13710.344.536.347.3

75508055758080120120120

140100941001001001201205098

5068655010072

111958050

968876

10070

110506510070

Observed (ftVs)

16618.07.2

44.433552.042.054.917.08.8

160411.533.039.09.2

68930.07.65.8

23.0

1.235.06.62.08.4

24.017.062.0189

2.9

5.65.1

41.98.212.0

1095.5

--15.115.0

Regression (ftVs)

30621.813.560.040883.056.976.120.56.9

13905.0

27.142.27.9

44647.38.611.639.9

2.285.114.72.95.5

25.213.237.91595.2

6.25.6

42.56.99.5

78.32.8

--18.518.0

7Q10

Observed (ftVs)

59.66.53.415.9

10221.013.025.99.52.7

9415.1

18.020.04.0

38818.04.21.8

16.0

.719.03.4.7

4.611.010.031.099.41.1

3.22.8

22.24.04.8

65.42.3

--6.05.0

Regression (ftVs)

1207.25.9

20.415934.724.040.311.23.8

7532.6

12.820.44.0

20425.34.83.9

19.1

.832.45.71.02.810.27.017.965.31.8

3.12.6

17.53.53.9

39.41.0 9.17.2

7U20

Observed (ftVs)

49.06.23.312.072.118.010.526.09.02.2

7944.315.016.03.0

32217.54.01.6

15.0

.618.03.2.6

3.99.48.4

25.081.7

.9

3.02.3

18.43.43.7

56.41.5

--5.44.25

Regression (ftVs)

91.25.24.714.8

12127.218.934.59.73.4

6482.2

10.516.93.4

16521.84.22.8

15.8

.624.54.3.7

2.47.96.014.750.91.3

2.62.213.72.93.0

33.2.7

--7.65.6

78

SUPPLEMENT D--Continued

Map index No.

81828384858687888990

919293949596979899

TOO

101102103104105106107108109110

111112113114115116117118119120

StationNo.

03491300034945280349474003495000034973000349800003498500034992000349930003499620

03518410035185000351880003519640035197320352004303527600035280000352830003528400

03531815035319000353200003532100035322000353400003534980035350000353505003538180

03538225035396000353980003543200035435000354423503557148035615000356504003565080

Drainage area (mi 2 )

47.018.26.68

61.410619226913.211.29.62

67.111827.916.047.223.385.8

147419.02.68

19.962.568531.224.024.57.82

68.593.310.2

82.513951826.411722.279.4

44714.88.54

Streamflow 70.2 recession

index

65120506514590100135120120

87112100120140120606590120

1157510090425382807570

653232538470

115140120120

Observed (ftVs)

11.813.01.3

20.013614021211.09.06.4

48.012513.015.037.016.027.0

6674.01.1

11.027.033715.04.811.02.2

26.340.06.2

45.454.0

2525.3

50.06.2

43.0708

7.05.4

Regression (ftVs)

16.810.61.8

22.175.993.61458.46.45.5

30.968.214.19.3

32.113.729.2

5788.71.5

11.225.4

37814.55.87.33.2

29.438.33.7

30.028.3109

7.853.28.3

46.4323

8.64.9

7Q10

Observed (ftVs)

4.06.4.4

6.570.065.9100

7.33.93.1

19.067.56.57.3

20.07.49.0

2502.2.62

6.212.0

1255.7.85

3.1.9

10.421.02.1

13.510.049.01.1

21.22.1

21.0255

3.32.8

Regression (ftVs)

6.55.9.6

8.544.841.867.95.03.63.1

13.934.87.05.2

19.07.510.6

2054.1.9

6.110.5

1736.81.82.51.5

12.615.71.6

11.47.2

26.82.7

23.13.4

24.31814.82.8

7Q20

Observed (ftVs)

3.05.2.3

5.548.052.388.06.53.32.6

15.056.15.26.016.05.87.6

2002.0.55

5.09.3

1074.8.65

1.9.8

7.917.01.5

9.64.830.0

.816.31.5

17.01252.72.3

Regression (ftVs)

4.95.2.5

6.440.033.655.64.53.22.7

11.229.45.94.517.06.67.9

1513.4.8

5.38.2

1405.51.31.91.2

10.012.31.2

8.64.617.12.013.42.6

20.7Ib84.22.4

79

SUPPLEMENT D Continued

Map index No.

121122123124125126127128129130

131132133134135136137138139140

141142143144145146147148149150

151152153154155156 *157158159160

Station No.

03565120035651600356525003565300035655000356612603566250035662600356632003566420

03566450035665430356750003570580035706000357083503571000035715000357183503578000

03579100035803000358120003582000035833000358336003583500035840000358450003585250

03585260035879000358840003588500035909000359330003593580035936000359370003593800

Drainage area (mi 2 )

37.832.711431.857.029.388.744.522.718.8

28.313.2

42823.786.2

27440211628.265.6

27555.949.4

82747.520.224.4

366178436.6

17.415.443.0

34842.549.426.966.714.9

104

Streamflow 7Q2 recession

index

1201201206514013095904880

676012072808085656550

90505011037501006075

140

1401401401386865130130130125

Observed (ftVs)

20.019.064.012.840.923.042.017.0

9.5

5.47.0

20712.545.014020960.013.033.7

14413.014.0

4166.07.49.7

12384327.0

10.017.032.6

21520.010.217.043.013.062.0

Regression (ftVs)

22.519.469.811.339.018.544.320.9

7.8

10.24.3

2719.1

37.312219142.59.919.0

13516.114.2

49610.65.712.3

12379324.7

11.510.229.2

24715.77.0

16.943.09.2

65.7

7Q10

Observed (ftVs)

9.59.2

30.06.1

21.712.521.07.62.95.7

5.62.1

1183.7

12.035.062.018.03.17.9

57.15.55.6

1873.63.45.9

54.537019.0

6.09.416.9

1288.23.811.028.06.2

37.1

Regression (ft'/s)

12.210.637.04.4

22.910.620.89.72.03.5

4.11.6

1393.8

15.950.781.016.03.96.3

59.95.44.7

2393.01.96.1

45.430314.7

7.06.217.3

1386.22.39.7

24.25.4

35.7

7Q20

Observed (ftVs)

7.88.5

24.05.0

20.011.518.05.91.55.0

3.51.7

1013.09.5

27.049.914.02.44.3

43.74.54.4

1513.22.55.3

43.628718.0

5.28.214.0

1126.42.99.5

25.05.6

32.2

Regression (ftVs)

10.69.2

31.83.4

20.59.417.07.91.52.8

3.11.2

1183.012.639.663.812.13.04.5

48.03.93.4

1972.01.45.1

33.222913.2

6.35.615.5

1204.81.88.6

21.24.831.0

80

SUPPLEMENT D Continued

Map indexNo.

161162 *163164165166167168 *169170

171172173174175176177178179180

181182183184185186187188189190

191192193194195 *196 *197 *198 *199 *200 *

StationNo.

03594040035941200359415003594160035941800359426003594400035944450359530003596000

03596500035970000359770003598000035995000360038003600500036016950360186003601950

03602235036025000360260003603000036035500360366003603720036037500360400003604060

03604180036045000360460003605555036062800360650003607000036072000702425007024300

Drainage area (mi 2 )

53.745.525.8

20150.724.716.8

11535.3

107

20866.3130481120837.517.58.4315.35.56

22.720274.7

255760.237.713.419.1

4477.34

15.270724.831.941.4

20537947.943.555.5

Streamflow 7Q2 recession

i ndex

66757766649560

20560100

105454490504510013013075

1201351359014014014014012095

140125135110230240200240200350

Observed (ftVs)

26.017.113.093.014.08.04.777.011.046.1

15118.030.0

19536315.08.06.515.02.8

7.299.259.0

100230.037.06.412.0

2822.5

10.544216.018.020.0

10611830.022.041.2

Regression (ft3/s)

19.57.610.575.717.911.95.5

47.711.756.1

11617.634.5

240378

9.88.75.19.52.1

13.313949.9

134041.225.58.812.7

2843.4

10.047016.117.518.796.115522.417.634.3

7Q10

Observed (ft'/s)

13.05.15.8

47.67.64.92.2

42.05.6

22.8

79.07.89.4

99.8144

5.84.54.010.01.0

3.861.336.0

55020.024.05.68.0

1841.6

6.8281

7.712.012.068.895.022.012.030.1

Regression (ftVs)

7.62.84.5

28.46.85.82.1

32.04.4

26.9

56.25.5

10.4105117

3.14.43.05.5.9

7.377.428.6

56024.215.15.47.7

1461.7

6.1244

9.59.113.270.210416.111.629.6

7Q20

Observed (ftVs)

10.93.04.6

40.76.64.31.9

35.04.618.7

64.06.36.0

84.3109

4.63.93.69.3.8

3.355.233.0

47418.022.04.07.0

1661.5

6.1253

7.010.311.061.290.020.010.027.4

Regression (ftVs)

5.82.23.6

21.45.24.81.6

28.63.3

22.3

46.63.97.2

83.581.12.23.72.74.9.7

6.467.725.2

43821.613.64.96.9

1231.4

5.5207

8.57.811.864.092.914.610.328.0

81

SUPPLEMENT D Continued

Map index No.

201 *202 *203 *204 *205 *206 *207 *208 *209 *210 *

211 *212 *213 *214 *215 *216 *217 *218 *219 *220 *

221 *222 *223 *224 *225 *226 *227 *228 *

Station No.

07024500070247200702500007025300070253500702550007026000070273000702750007027700

07028000070285000702890007029000070291000702938007029400070294100702944007029500

0702970007030000070300200703020907030280070304000703050007031700

Drainage area (mi 2 )

38313720383.736.7

480185216049525.0

100373.488.2

36986794.8

83747.640.4

1480

84.31940

92.076.950571.9503770

Streamflow 1(\2 recession

index

23530015030065

20517523023060

19514012019516014013025060

160

210175170165150170230210

Observed (ftVs)

17292.040.136.04.5

15365074.0

2181.4

32716.118.0

13731050.133826.06.8

752

32.093622.019.0

10121.0

243312

Regression (ftVs)

17775.865.646.35.2

20068372.5

2253.2

40222.323.514829728.8

24022.95.2

507

35.671532.826.816425.6

229327

7Q10

Observed (ftVs)

11671.024.331.51.2

12143153.0147

.5

21513.410.0

10616818.6

17319.52.0

361

22.050216.014.582.115.0

187225

Regression (ft'/s)

12961.437.737.31.7

13643551.8162

1.0

26912.211.897.717915.8

13016.81.6

307

24.145620.016.094.815.6

165226

7Q20

Observed (ftVs)

10566.021.530.5

.911638748.0132

.42

19212.99.0

99.814214.1

14517.01.5

292

18.043115.013.578.813.5

174200

Regression (ftVs)

11757.332.434.71.3

12238646.9148

.7

24110.49.8

87.215713.5

11015.31.2

270

21.540517.413.982.013.6150205

82

SUPPLEMENT D Continued

Map index No.

123456789

10

11121314151617181920

21222324252627282930

31323334353637383940

Station No.

03408500034095000341450003415000034155000341600003416100034178000341800003418020

03418050034193000341950003420000034201200342020003420500034208000342090003421000

03422800034246700342660003426800034268500342688003427500034279000342900003430100

03431600034317000343180003433500034337000343400003434500034346000343500703435400

Drainage area (mi 2 )

38227220211444510613815.178.722.5

50.316.7

15717578.8

174126132303642

16.813725.539.124.524.0

26265.1

571892

51.624.397.2

40859.6

11568156.211.298.0

Streamflow 300.2 recession

index

32374748536062656565

6575757667371406011085

603590

104506046344545

373510032130100569057

100

Observed (ftVs)

45023523673.0

443107120

6.253.916.0

51.016.0

21020041.0150109140350688

__-_25.039.218.024.0

20839.0380568

47.017.481.1

27530.073.0

47027.014

100

Regression (ftVs)

26919815788.2

36787.711612.266.318.4

41.914.2

14115867.0126136no310618

____23.137.518.519.2

20444.7450711

36.216.494.0

28761.811257751.98.6

94.8

30Qio

Observed (ftVs)

95.048.040.014.0

14025.047.02.3

16.55.2

16.04.6

84.052.015.069.056.742.0160254

____9.012.43.88.0

38.07.3

100140

11.05.4

31.969.418.041.015211.02.8

24.0

Regression (ftVs)

53.843.440.022.6

10125.834.93.7

20.55.6

12.94.7

47.653.921.127.468.032.4134229

-_

8.715.44.85.6

51.29.2

112177

7.83.4

38.057.629.345.216519.62.4

38.3

30Q2Q

Observed (ftVs)

48.033.025.09.0

90.015.033.01.7

11.23.6

11.03.7

59.041.511.024.047.226.0123183

____7.28.32.86.3

27.05.0

65.0100

6.53.7

23.643.515.034.0107

8.41.7

15.0

Regression (ftVs)

31.526.325.514.665.817.523.82.6

14.13.9

8.93.4

33.838.414.716.655.421.9103165

____6.511.93.23.8

32.55.5

70.3111

4.82.1

28.833.723.634.210814.61.7

29.1

83

SUPPLEMENT D Continued

Map index No.

41424344454647484950

51525354555657585960

61626364656667686970

71727374757677787980

StationNo.

03435500034357900343590003436000034361000343620003436430034367000343690003436970

03455000034612000346130003464815034650000346550003466200034663700346670003466840

03466885034670000346749003468250034691120346916003469238034695000347000003476980

03478602034816250348200003484420034849110348550003486500034875200348755003491000

Streamf lov Drainage recession

area index (mi 2 )

70675.132.0

18693518813012434.511.9

185810.255.381.015.9

80578.114.940.478.0

7.9922041.210.411.264.124.076.2

35318.4

12.912.6

10213.825.5

13710.344.536.347.3

75508055758080

120120120

140100941001001001201205098

5068655010072

111958050

968876

10070

110506510070

v 30Q2

Observed (ft'/s)

34344.015.0

108781no97.0

11132.012.0

211018.256.059.013.0

95274.024.02151.0

3.211221.05.2

1545.029.073.0

3437.6

8.07.6

64.01323.015211--28.936.9

Regression (ftVs)

65558.328.115287417211812834.411.6

21409.4

51.878.014.7

81979.514.630.974.6

5.919334.27.710.355.523.272.1

32913.8

11.711.290.712.721.4

1387.6

--34.340.3

30Q1Q

Observed (ftVs)

93.711.05.2

27.115530.022.029.010.04.2

119511.029.029.05.6

53333.08.67.4

25.0

1.439.67.51.67.4

20.01535.0164

1.9

4.53.8

35.06.08.1

85.84.4

--9.212.5

Regression (ftVs)

22415.39.8

42.530060.941.657.915.55.2

10903.7

20.131.55.9

33636.06.58.1

29.7

1.561.610.52.02.1

18.29.9

28.2117

3.6

4.64.1

30.95.16.9

59.22.0

--13.813.0

30Q20

Observed (ftVs)

63.67.24.017.688.022.015.026.18.82.7

10057.0

18.523.04.0

44425.06.23.6

20.0

1.027.85.0.75

4.6121022.0100

1.4

3.83.2

29.04.76.0

72.23.0

--6.87.8

Regression (ftVs)

15710.07.2

28.121043.830.045.612.34.2

8692.915.123.94.5

25128.45.25.3

22.5

1.042.67.31.33.212.97.8

21.283.42.4

3.53.1

22.13.94.9

45.71.3

--10.59.2

84

SUPPLEMENT D Continued

Map index No.

81828384858687888990

919293949596979899TOO

101102103104105106107108109110

111112113114115116117118119120

Station No.

03491300034945280349474003495000034973000349800003498500034992000349930003499620

03518410035185000351880003519640035197320352004303527600035280000352830003528400

03531815035319000353200003532100035322000353400003534980035350000353505003538180

03538225035396000353980003543200035435000354423503557148035615000356504003565080

Streamflow 300,2 Drainage recession

area index (mi 2 )

47.018.26.68

61.410619226913.211.29.62

67.111827.916.047.223.385.8

147419.02.68

19.962.5

68531.224.024.57.82

68.593.310.2

82.5139518.026.411722.279.4

44714.88.54

65120506514590100135120120

87112100120140120606590120

1157510090425382807570

653232538470115140120120

Observed (ftVs)

32.024.03.9

48.022123737617.016.012.0

86.019926.024.066.032.067.0

13078.01.79

18.056.071936.018.032.04.5

60.272.014.0

11211257222.010917.078.0

87214.08.0

Regression (ftVs)

39.117.94.951.411518326713.410.99.3

61.611926.215.749.823.070.7

133017.12.52

19.354.7

69428.417.218.86.7

61.382.58.4

69.695.436720.310818.679.8

49714.58.2

30Q1Q

Observed (ftVs)

9.58.5.60

16 096.01041758.67.44.2

35.01038.810.026.010.023.0

3803.3.78

8.016.0

1908.82.07.71.3

14.535.02.8

19.021.080.02.2

30.03.2

35.0340

6.64.4

Regression (ftVs)

12.08.01.3

15.858.869.5109

6.44.94.2

22.851.610.57.0

24.710.320.8

4196.41.1

8.418.4

28410.74.05.12.4

21.527.92.7

21.519.073.75.5

39.16.0

35.2251

6.53.7

30Q20

Observed (ftVs)

4.58.0.30

10.056.079.21008.24.73.9

26.083.38.28.0

24.09.514.0

2802.6.66

6.010.0

1506.81.24.51.19.0

21.01.7

12.08.5

43.01.8

27.92.9

27.0180

5.03.5

Regression (ft'/s)

8.36.4.80

11.048.351.281.75.33.93.3

16.840.08.05.6

20.38.214.1

2834.8.90

6.713.2

2138.02.53.41.7

15.619.81.9

14.811.243.03.7

28.54.2

27.5202

5.23.0

85

SUPPLEMENT D Continued

Map Index No.

121122123124125126127128129130

131132133134135136137138139140

141142143144145146147148149150

151152153154155156 *157158159160

Station No.

03565120035651600356525003565300035655000356612603566250035662600356632003566420

03566450035665430356750003570580035706000357083503571000035715000357183503578000

03579100035803000358120003582000035833000358336003583500035840000358450003585250

03585260035879000358840003588500035909000359330003593580035936000359370003593800

Drainage area (mi 2 )

37.832.711431.857.029.388.744.522.718.8

28.313.2

42823.786.2

27440211628.265.6

27555.949.4

82747.520.224.4

366178436.6

17.415.443.0

34842.549.426.966.714.9

104

Streamflow 30Q2 recession

index

1201201206514013095904880

676012072808085656550

905050no37501006075

140

1401401401386865130130130125

Observed (ftVs)

37.031.0in32.366.036.095.037.021.019.5

16.016.0

39528.010834047814033.087.3

284-43.041.0

83923.018.019.0

301173034.0

15.024.052.0

36648.022.323.057.016.090.2

Regression (ftVs)

37.832.611726.260.429.984.240.916.916.3

23.510.4

45420.077.6

25438398.623.251

26443.138.0

86733.215.222.8

312169038.4

17.915.845.2

38335.818.627.469.314.9

108

30Qio

Observed (ftVs)

17.014.050.010.830.817.036.011.07.08.7

4.85.2

1949.2

32.010015244.011.028.0

1057.48.4

3616.86.89.2

11476925.0

9.012.022.0

17613.07.2

14.035.016.049.2

Regression (ftVs)

17.014.753.18.0

30.014.133.015.44.35.7

7.33.0

2086.5

27.389.814130.57.113.3

10111.39.9

3777.23.99.1

92.658319.0

8.87.8

22.419111.34.712.932.97.0

50.2

30Q2Q

Observed (ftVs)

13.011.039.07.2

24.214.025.010.05.56.7

3.33.4

1556.2

20.063.010129.05.5

18.0

75.87.27.0

2745.15.07.5

85.859322.0

7.510.020.1144

9.05.212.031.06.5

42.0

Regression (ftVs)

13.511.741.95.6

24.611.424.711.52.84.2

5.12.1

1624.719.764.410221.05.08.7

74.07.46.5

2884.42.67.0

62.140615.6

7.36.518.4

1547.93.2

10.526.55.7

39.9

86

SUPPLEMENT D Continued

Map indexNo.

161162 *163164165166167168169170

171172173174175176177178179180

181182183184185186187188189190

19119?193194195196197198199200 *

StationNo.

03594040035941200359415003594160035941800359426003594400035944450359530003596000

03596500035970000359770003598000035995000360038003600500036016950360186003601950

03602235036025000360260003603000036035500360366003603720036037500360400003604060

03604180036045000360460003605555036062800360650003607000036072000702425007024300

Drainagearea (mi 2 )

53.745.525.8

20150.724.716.8

11535.3

107

20866.31304811208

37.517.58.4315.35.56

22.720274.7

255760.237.713.419.1

4477.34

15.270724.831.941.4

20537947.943.555.5

Streamf lov recession

index

66757766649560

20560100

105454490504510013013075

1201351359014014014014012095

140125135110230240200240200350

v 30

Observed (ftVs)

43.625.231.0

17824.013.09.4

11428.094.5

27441.011048499731.015.610.022.07.8

13.015490.0

215047.056.012.019.0

4344.1

16.069120.033.026.5

15817142.038.061.5

Q2

Regression (ft 3/s)

45.018.622.3

17442.122.813.373.928.5

104

20849.798.3

4681000

27.716.28.315.44.6

22.421878.8

259063.839.513.719.7

4746.6

15.676825.530.927.3

14124632.227.242.8

30

Observed (ftVs)

19.210.68.672.010.06.23.4

57.07.5

31.0

11717.014.0

17736412.06.64.811.01.5

4.874.144.0

92025.030.05.69.8

2291.9

8.5357

9.416.016.590.212727.017.036.5

QlO

Regression (ftVs)

14.05.37.6

54.512.88.83.9

41.18.3

42.0

87.112.223.8

179267

6.86.53.97.21.5

10.110738.3

100031.719.66.84.7

2172.5

7.736212.313.216.585.213319.915.232.6

30

Observed (ftVs)

15.28.46.2

56.08.25.22.4

46.06.5

27.0

89.013.011.0

128264

6.25.24.08.81.0

3.861.136.0

72320.025.04.78.2

1931.6

7.2298

7.713.014.077.8

12024.014.031.3

Q20

Regression (ftVs)

9.7'3.8

5.537.68.96.72.7

34.95.7

31.2

66.47.8

15.1131171

4.35.03.25.91.1

8.086.131.1

72426.016.15.68.0

1691.9

6.428410.110.314.274.1

11217.212.829.8

87

SUPPLEMENT D Continued

Map indexNo.

201 *202 *203 *204 *205 *206 *207 *208 *209 *210 *

211 *212 *213 *214 *215 *216 *217 *218 *219 *220 *

221 *222 *223 *224 *225 *226 *227 *228 *

Station No.

07024500070247200702500007025300070253500702550007026000070273000702750007027700

07028000070285000702890007029000070291000702938007029400070294100702944007029500

0702970007030000070300200703020907030280070304000703050007031700

Drainage area (mi 2 )

38313720383.736.7

480185216049525.0

100373.488.2

36986794.883747.640.4

1480

84.31940

92.076.950571.9503770

Streamflow 30Q2 recession

index

23530015030065

20517523023060

19514012019516014013025060

160

210175170165150170230210

Observed (ftVs)

28311871.645.016.0

2381160110354

5.0

58925.365.0

20659580.068836.018.0

1350

58.0154035.026.016b33.0334463

Regression (ftVs)

26410211761.513.8

3161170108340

8.9

65640.345.5

23752452.3

4b432.414.4

902

54.41230

54.845.129542.6346515

30Qio

Observed (ftVs)

14384.032.038.02.9

13254567.0195

.90

28414.616.0

12321628.2

30124.04.8

581

28.068619.017.586.519.0

225276

Regression (ftVs)

15670.053.242.73.5

17256963.9198

2.1

34317.918.2

12624323.118920.53.4

416

30.859727.422.213321.4

201283

30Q20

Observed (ftVs)

11976.026.331.01.8

11544558.0167

.60

23513.011.0

10816220.923921.53.2

458

23.055116.516.076.017.0

206248

Regression (ftVs)

13662.843.238.32.4

14647455.2171

1.4

28814.314.2

10620018.515017.92.3

341

26.349722.618.2

10817.6

174241

&U.S. GOVERNMENT PRINTING OFFICE 1986-631-262/40005